What is RevOps? Revenue Operations explained (7 strategies)

Before diving in, let’s take a step back and give a definition of Revenue Operations and a RevOps Manager.

Revenue Operations and respectively the RevOps Manager at a company is traditionally defined as the glue between strategic sales, marketing and (customer) service. The role became increasingly important and strategic in modern organizations, including SaaS businesses, over the course of the past years.

Popularity started increasing thanks to the rising need of companies to make their sales operations and growth levers more effective. In order to do so, they knew growing sales (and subsequently revenue) was important, but they also started focusing more on decreasing the cost of the sales process itself.

Where there is demand, there is supply. With this increased focus on making the sales process cheaper, new companies were founded to drive automation, elevate reporting, better lead quality, improve data hygiene, and overall, increase sales productivity.

It was in the early 2010’s that companies such as Outreach (2011), Zapier (2011), Clari (2013), Calendly (2013), Gong (2015) and Lusha (2016) found their way to the market. Back then, relatively small organizations, today all easily valued above $1 billion dollars.

Companies in the Bay Area (California) started to quickly adopt these new solutions and with a growing tech stack, the role for a Revenue Operations Manager was born: someone who could strategically define which sales processes, tools, motions, marketing and services were necessary in order to increase revenue and decrease the cost of revenue at scale.

While revenue operations can be focused on multiple aspects of an organization, this guide will help you find an answer on how Revenue Operations can decrease your sales cost and grow your business.

You will find 7 tips, strategies or projects you can start thinking about today to make your company more profitable.

The first strategy is a strategy related to lead scoring to make your organization better at predicting the potential value of business which will play a crucial role in your load balancing of resources.

Lead scoring is attributing a value between 0 – 100 to both inbound and outbound leads in order to estimate their likelihood to convert or do business with you.

The lead score attributed to a lead is always an estimate or prediction, based upon external and internal signals.

Companies taking their sales development reps seriously and aiming to do business at scale, will use lead scoring in order to guide prioritization (especially in businesses with high volumes of leads) and use lead scoring as a signal in order to estimate their potential sales pipeline.

Lead scoring can be set up directly in your CRM or using software such as LeanData. Nevertheless, the location of your lead scoring is inferior to the data it is based upon and how the data is used in order to attribute a score to a lead.

In complex lead scoring models, both internal and external scoring signals are used in combination with a machine learning model in order to estimate the value of the lead using up to date data to learn, in a live setting, the correlation between the data and the lifetime value of existing clients.

Decreasing your cost of sales, starts with allocating the right resources to value generating activities. Or simply put: decrease the time necessary to make more money.

In order to do so, organizations need to:

• Get rid of non-value generating activities
• Make revenue generating activities easier
• Understand and prioritize activities that generate more money

Lead scoring plays an important role in the ability of a company to do this. It impacts the quality and prioritization at the start of the sales funnel which will prevent waste of resources further down the sales process.

Lead scoring is like fueling your car with the most efficient resource. It decreases your cost (you pay less for the resource), increases the value generated (you can drive longer) and it limits your waste of resources (your environmental impact is lower).

The three most important benefits of lead scoring are:

• You will work on leads that generate more revenue (drive longer)
• You will invest less time of reps on low value opportunities (waste is lower)
• You will be able to use that time for other activities or remove headcount (pay less)

In short: you will be able to decrease the cost of sales without compromising on value.

It shouldn’t come as a surprise that the best signals for lead scoring are highly dependent on your business. Companies will generally categorize signals in three types:

• Internal future signals
• Internal current signals
• External signals

While the specific signals within these categories might be (and better be) different between organizations, the overall type is similar amongst all organizations. To future clarify, you will find a breakdown below with examples.

Internal future signals are attributes of existing good performing clients which we will look for in newly created leads.

They are basically an indication of ‘what success looks like today’ and for which we want to type cast when looking for new potential clients.

Examples are: industry, company size, software on client’s websites (which can be found using BuiltWith), annual revenue, headquarter location, presence of departments etc.

Important when looking at future signals is to keep two caveats in mind:

• When you score leads highly that have the same attributes, there is a risk your company will become overdependent on these type of clients (lack of diversification)
• You need to have access to live data as what is performing today might be bound to seasonality, macro economics, your current product features etc.

To prevent reading data wrong (e.g. reporting) and take decisions without deeper insights, your revenue operations, sales finance and sales strategy partners need to collaborate.

Example of signals: LinkedIn Advertising Solutions

LinkedIn Advertising Solution might use future signals such as: employee growth, the presence of a career page, rapidly growing industries, etc.

The company is prone to mistakes when it would take reporting for granted without looking behind the data.

Example of signals limitations: LinkedIn Advertising Solutions

One can expect that air travel companies had tons of jobs after covid (which made them in desperate need for advertising job postings), but once all routes are reestablished, their headcount and subsequent job posting advertising needs would tumble.

Internal current signals are signals we are getting either through a lead form, newsletter or event registration and from product usage.

The first category of internal current signals is simply a combination of all the parameters that a potential lead declares when signing up for your product or service.

In an outbound context, these parameters are the ones that are publicly available to us.

The goal is to match these signals with the ‘internal future signals’ in order to find out how well the parameters of your new lead are matching with your existing best performing clients. This match rate is what eventually defines our lead score or the prediction of the potential performance of this new lead.

The second category are signals we can obtain from interactions between the lead and our product or service. Let’s look at an example.

Example of internal current signals

Consider Cognism, a company founded in 2015 which provides software for contact enrichment either manually or directly in your CRM.

Based on the different product-led actions the user has taken, Cognism will be able to drive sales, marketing or growth (outside the scope of this e-book) but also determine the ‘willingness to work’ with their software of the lead.

This is an important indicator. The product-led signals give an indication of how advanced the lead is in the funnel which will have a positive impact on their likelihood to convert or buy the product.

Machine learning can give companies an additional competitive advantage. The algorithms will analyze the data, identify patterns, build models to predict lead conversion likelihood and eventually help attributing a lead score in real time.

The best lead scoring is not static and changes based on new interactions.

The last category is external signals: signals you are able to find online to enrich your internal signals at scale.

The important difference with the previous category of signals is:

• They are not directly provided by (an action of) your leads
• They are provided at scale (e.g. with minimal human intervention)

“Data is the new oil” — Clive Humby (2006), mathematician and entrepreneur

And your competitors know this too. Data is the new oil and data input from humans is often limited. To make better decisions about the likelihood of a lead to convert and give a lead a score in line with it, companies can choose to enrich their data with external data.

Through integrations with enrichment software, databases and libraries a company can collect more relevant and correct information about their leads. This will positively impact the prediction.

A couple of ideas here are:

• Connecting with Data.ai (formerly AppAnie) to get information about mobile apps
• Connecting with SimilarWeb to get competitive and market size data
• Connecting with Phantombuster to crawl social media data
• Connecting with Clay to get data from Google Maps, event attendance, etc.
• Connecting with Contact Enrichment tools to get up to data contact information

There is a tremendous amount of software available in order to accumulate useful data based on the unique parameters you mostly will collect through your lead form (first name, last name, email and website). The latter provides a unique combination which can give you access to the endless extra signals.

It’s important though to note that Clive was wrong (sorry, not sorry). Data is not the new oil.

“Data is merely the new crude oil. Insights are the new oil.” — Megan Foster (2023), no one significant

Ok, when I am honest with you, I suspect Clive knew this and I definitely cannot take credit for this reinvented quote. The point is also not who said what, the point is way more simple:

Accumulating data for the sake of accumulating data is useless and can be damaging to your business.

To make sense of data, you need to know which data to collect and how to find insights.

Enter the impact of Revenue Operations on lead scoring.

So what’s the role of Revenue Operations and your RevOps Manager in all of this?

As stated before your Revenue Operations is the strategic link between sales (processes), tools, motions, marketing and service. In the case of lead scoring this manifests itself in three key areas of responsibility:

• Logic to transform signals into lead scores
• Integrations to capture and receive signals
• Lead routing, constraints and load balancing

The first objective of a Revenue Operations Manager is to be able to transform raw signals into lead scores. This in the core means:

Working together with cross-functional (XFN) stakeholders in sales to understand the different parameters driving success for their business and determining ‘the weight on the likelihood to convert’ of these parameters itself.

The role encompasses a tremendous amount of cross-functional stakeholder management and the beauty is the zoomed-out, holistic view Revenue Operations need to obtain in order to understand the impact from start to end (and the other way around) on the sales funnel.

The most successful RevOps Managers you will encounter in a professional setting, are those that know a lot about the different stages in the business, but not too much to be inherently biased about any function in particular. They have Pareto efficient knowledge of every step in the funnel.

Once they determine (together with sales) the needs of the ‘last step’ in the sales funnel (existing business) they work their way back to the start of the funnel (new business) in order to determine which signals are available in new business and how these signals can be weighted to facilitate prioritization and value generating activities for the last step of the funnel.

This weight attribution to parameters requires in-depth data analysis and collaboration with Sales Strategy and reporting to see what are common threats between the most successful clients.

In the most simple terms: they make a list of all data points available for existing clients, that are captured for new potential clients, and put a weight to the correlation of that data point with the revenue and value generated by existing clients.

After this exercise has been done, RevOps will work together with CRM engineering or a software partner (lead routing) in order to implement the automatic attribution of the weighted scores when signals are present on newly created leads.

The sum of these weighted scores will determine the final lead score of the newly created lead and is the indicator helping Sales Development Representatives to prioritize their leads.

Additional note about hiring from the author:

The topic on how to compensate and set up a successful Revenue Operations Manager team is outside the scope of this article, but is covered on SlideFill. Most important to know is that tying variable compensation of RevOps to sales outcome (target attainment) will have a favorable effect on the alignment between personal and sales objectives.

Under the previous objective you looked at weighting data or signals in order to come up with the final score. And as we learned “data is the new oil”, Revenue Operations has a second objective: ensuring the right signals are available to attribute the right score.

The first step can be easily clarified by the ‘Cognism’ example you looked at before. If Cognism decides insights about their product usage could be a meaningful driver to make business decisions, but they do not have the data available on how their users interact with their product, they have a gap.

Analyzing gaps in data is the continuous process of making assumptions of ‘what could have impact on the business’ and finding the missing data points to validate the assumption.

Getting the missing pieces of the puzzle is more complex as signals are often omnipresent in other infrastructure but not in your CRM.

Data can come from:

• Manual data input from sales reps during the sales process
• Product usage signals captured by engineering in a database
• Event registrations input captured by marketing in event software
• Client engagement data captured in SEP* (Outreach) or SIP* (Gong)
• External data enrichment tools such as SimilarWeb, Lusha and Cognism
• Meeting scheduling signals captured in scheduling software (Calendly, Chili Piper)
• …

There are thousands of sources of data that can be captured (keeping in mind accumulating data for the sake of data is useless) that all require cross-functional or stakeholder management.

Revenue Operations will be tasked with setting up a Business Requirement Document in order to scope out the business impact, value, technical need, training need, reporting, timeline, change management, stakeholders and future state while driving the management of peers to drive the execution of that document.

They are capable of translating the business idea into tangible value and language understandable for technical, product and sales partners.

1. Revenue Operations Lead Scoring Model © SlideFill 2023

* SEP = Sales Execution Platform
* SIP = Sales Intelligence Platform

Future prediction: client engagement and CRM updates

The future is very exciting. In-call (meeting) client engagement has been a very tough nut to crack, especially linking back meeting conversations to your CRM. Sales people are in general not too keen on taking in-depth notes.

With Generative AI making its way to sales processes, there is a tremendous opportunity to summarize calls at scale (through for example Gong in combination with GenAI) and push that information to your CRM, using text mining to update opportunities, objection reasons and other dull administrative tasks.

What about constraints and action?

The last objective of Revenue Operations is to take constraints into account and make theoretical work actionable by sellers.

• Align headcount limitations with demand volumes
• Align headcount with the most revenue generating opportunities
• Provide clear actions to sellers in order to help prioritization decisions

Lead routing is the answer to the three necessities above. It’s an (automated) system to determine how to align your resources (headcount) to demand (leads) and defines prioritization (type and time to response).

Consider a medical emergency center with two ambulances available getting ten calls for help. The core task of the dispatch is to align their ambulances (resources) to people in need (demand) and decide who to help first (prioritization) as they are unable to help everyone all at once.

Similar logic applies for business – although the business is not saving lives. A company has x amount of Sales Development Reps (resources), y amount of leads (demand) and lead scoring to decide which leads will most likely generate the most revenue (prioritization).

This decision on how to align limitations with demand volumes is called load balancing and the process to allocate actions to sellers to help prioritize the most revenue generating opportunities is lead routing.

Revenue Operations plays a crucial role to lead the project of setting up, changing and working with L&D* to roll-out lead routing. Technical implementation is outside of the scope of this article, but this mostly can be done through queues in a CRM or external software such as LeanData.

Lead scoring using the right signals, based on the right data and insights, in combination with clear prioritization set by lead routing will be a powerful tool in order to allocate your resources to the most revenue generating activities and eventually decrease the cost of sales while increasing output (conversion and revenue).

2. Revenue Operations Lead Routing © SlideFill 2023

* L&D = Learning and Development

Before covering why insights are the new oil (and data merely the crude oil), we will need to get aligned on a couple of definitions. This second section of the guide to decrease sales costs through revenue operations will be a bit more emotionally driven based on my previous experience.

No worries, you will still learn and get facts.

Data is unanalyzed information about an object. Through looking for observations and patterns (‘analyzing’) one will find insights: actionable opportunities coming from transforming data and making connections between data.

If your business is a Lego house, the data bricks would be data points. The individual brick has a certain value, but by combining the bricks in a certain pattern they will have an impact on your house (e.g. your ability to construct the house). That combined value, the house, is more worth than the individual data, the bricks.

Reporting, is a more ambiguous term and is often (wrongly) used as synonym for getting ‘insights’ while in most cases it’s just showcasing or visualizing different data points.

If you would have 100 bricks in 5 colors (data), a report could showcase how many bricks you have of each color, but it wouldn’t tell you how to build a Lego house.

Too often business meetings (Quarterly Business Reviews, Team Meetings) focus on reporting, which lack the patterns impacting your business. They bucket data and provide some level of detail about the data you have available, while not providing the bigger picture of how this data impacts the business

A good business owner or leader will focus on insights and not on reporting. Most leaders know this, but do not manage to get their team aligned with this vision.

Over the course of the past years, I spent an immeasurable amount of time in meetings full of reporting and while reporting still provides important insight in your business, it doesn’t provide the actionable opportunities.

So why is so much time underutilized? The answer lies in different pitfalls but it’s mainly related to our most expensive resource: time.

Without the intention to offend anyone, one of the pitfalls around data, reporting and insights is the lack of education of people involved in the provision of them. The lack of education is mainly related to:

• Definitions
• Statistics

The first issue is related to definitions. Many of us don’t really know the true meaning of data, reporting, insights, analysis, observations etc. which leads to these terms being used interchangeably.

On top of that, we just like to use them to give (emotional) strength to the argument we are making. We are all victims (and offenders) of this. It just sounds so much more acceptable when you for example hear ‘data proves humans can’t fly’ while you don’t need data as proof but just simple physics.

Getting alignment in definitions and nomenclature is important in order to decrease time wasted.

The second gap we have is our limited education about statistics (and the wrong use of terms).

Take a 30 seconds break and do the following self-test:

Most likely one of the following words came to mind:

• Causation
• Correlation
• Sample Size
• Significance
• Distribution

A subsequent self-test would be to instantly give a definition of these terms and instantly check how accurate your definition was.

This guide is not meant as a basic course on statistics, but if you had any of the terms wrong and used it recently in a conversation, you actually told them a potential lie. Again, not here to offend anyone.

The problem is that we overuse these terms even when we do not know 100% what these terms mean. Too often, so-called ‘correlations’ and ‘causations’ are found without the necessary proof of it being a correlation.

If you have 100 employees leaving your company and you find all of them are leaving for a better paid job, it doesn’t instantly mean there is causation, correlation and significance present between ‘a better job offer’ and ‘them leaving’.

First of all, it depends on the size of your population if the sample size is even relevant. Secondly, it can be that they all left because you are just a bad employer and it’s just a coincidence they all left for a better paying job. One last time: no offense intended.

What’s the point?

The point is that you need to make the time to educate employees and especially leadership on definitions, models, analysis and coming up with relevant insights.

Most of your commercial leadership were individual contributors before: Sales Development Reps, Partner Managers, Accounts Managers, Marketeers…

For years these individuals got trained to ‘sell an idea’ and ‘drive sales at all cost’. Now they become leaders and they are asked to provide the most factual insights (and drop their sales and marketing packaging) while potentially the last time they used statistics before becoming a leader was in school. That ask is doomed without the right rewiring.

You need time to refresh their knowledge and educate them.

A second category of data, reporting and insight pitfalls are:

• Lack of hypothesis: we don’t have a critical assumption
• Overconfident assumptions: we want our assumption to be true
• Data bias: we choose data to make our insight true

All of these are again, heavily influenced by the time we have available.

The case of ‘lack of hypothesis’ is when we do not take the time to come up with a hypothesis.

Let’s go back to our Lego example: we have Lego bricks (data), we have a manual (patterns) and we know we are building a Lego house (business opportunities). In the case you miss one of these objects, you need the time to think and figure out what is missing.

The same goes for your business: if you have data and you want to find business opportunities, you need to find patterns between the data and business objectives. In order to do that, you need to make an hypothesis and test this hypothesis. This requires time.

The two shortcuts that are often observed are overconfident assumptions which are missing non-critical context or even worse the manipulation of data in order to prove outcome.

Extreme example of overconfident assumptions

We have a report of our existing business and we see that the more we meet with clients, the more our clients invest in our product. There is a causality between meeting clients and revenue. (See what I did here?)

What might be issues with this statement?

The first issue:

Saying there is a causation would mean that 1 extra customer engagement would lead to $x more in revenue. Now, what do you think would happen if I call my client every single hour of the day for a month? According to the statement above, that would positively impact my revenue, but I feel confident that data would show you otherwise.

The second issue:

What if we turn this report upside down, and we make the assumption: ‘clients spending more on our product, are more interested in talking to us’? This might be the case – which might imply that driving more customer engagement for low spending clients is actually a waste of resources.

Too often we are not critical about the assumptions we are making and excluding business and macro-economic context can be deadly for the investment decisions you make.

The other shortcut is data bias: we have an assumption and we want to prove the assumption is true. To do that, we tweak the data to be in our favor.

Extreme example of data bias

You believe ‘humanity is inherent evil’ and want to prove your insight by looking at the %-of people that committed a crime. A shortcut to prove your point is to send out a survey to ask inmates in a prison ‘if they ever committed a crime?’.

The problem here is that the sample (prisoners) is most likely not the right one for the insight related to your population (humanity).

In a business context the same mistake can be made and data bias is something that’s unfortunately omnipresent.

Once again, the resolution to many of these issues is time.

Time will allow individuals to be more critical about their assumption and to feel less inclined to alter data or omit crucial context.

If the lack of time is really the root of all evil, why don’t we solve it?

You should.

To solve the dilemma of time you need to move from reporting to revenue generating insights. The explicit blocker here is ‘reporting’.

The flow to revenue generating opportunities is traditionally:

Data < Reporting < Hypothesis < Analysis < Insights < Opportunities < Revenue

Most businesses are stuck or lose time in the second step of the process because:

• They accumulate too much useless data
• Data is dispersed across multiple platforms / software
• Most ‘analytical’ software focuses on reporting

3. From Collecting Data to Generating Revenue
Adapted from: © South Park S2E17
(Matt Stone & Trey Parker) 1998

Accumulating too much data is straightforward: gathering data for the sake of having data without a hypothesis that might use the data.

Dispersed data is an issue that arose with software springing up like mushrooms. When CRMs, SIPs, SEPs, Email Marketing, Enrichment and Scheduling software were created the founders realized they could make the cost of attrition higher by putting all of their customer data in a walled garden (which they observed worked amazingly for giants like Google, Apple, Meta, …).

The result is that all of your data is enclosed within the software you are using and data is not centralized. Your email engagement lives in Salesloft, your scheduling lives in Chili Piper, your meeting information lives in Gong, your email marketing lives in Klaviyo, your event registrations lives in Splash, your product data lives in your databases and your customer data is in your CRM.

This creates issues to understand the exact customer journey from start to finish and the process to integrate all of them (or even simply consolidate the data) is tedious. It’s one of the reasons big software companies decided to build all of this software in-house (which resulted in Google and Meta employees that never opened Salesforce or HubSpot before).

On top of that, most ‘analytical’ software (think Tableau, PowerBI, Salesforce reports) make it easier to get reporting but not extremely easy to get insights. And while the reporting is great for daily users, those who don’t open these tools often, don’t know how to get the information they need.

Because of this, teams decided to do business reviews, where weekly, monthly or quarterly defined metrics are presented in order to understand ‘how the business is doing’.

To create these reviews, time is a necessity – which is time that could be used to find insights.

The ‘insights’ team needs to copy/paste data points, tables and visualization from different software to consolidate in one snackable presentation to see the current state of business, which leads to mistakes, wrong decisions and the lack of time to provide expert advice around revenue generating opportunities.

As decreasing the cost of sales and increasing output is one of the core tasks of your (soon-to-be-hired) Revenue Operations Manager, the task of magically increasing the amount of time available fits their role and responsibilities.

Their expertise can help you to:

• Decrease the volume of unnecessary data
• Increase the availability of necessary data (covered before)
• Consolidate available data
• Facilitate faster and more accurate reporting

Difficulty: 1/5

A relatively easy responsibility of a Revenue Operations Manager is to work together with other departments (Sales, Sales Strategy and Operations) in order to define which data is useful to come up with insights around revenue generating opportunities and which data can be removed.

We all experienced annoyingly long sign ups forms wondering what the data is used for. If the answer is as easy as ‘it’s not used for anything’ there is no need to keep it.

If you don’t need to know the color of the eyes of your users, don’t ask for the information. Revenue Operations should define, in collaboration with other departments, which data is useless to gather and remove it from the sales process.

They should also safeguard the quality of necessary data in order to prevent the collection of garbage. If half of your leads are signing up with:

first name = ‘John’
last name = ‘Doe’
email = ‘email@gmail.com’

You might have work to do in order to build trust to receive real data and rethink the timing of asking your (potential) customer for their information.

Lastly, Revenue Operations should implement a systematic approach to maintaining data quality. Having a recurring plan to clean up stale data will prevent wasting time on making wrong decisions.

Difficulty: 4/5

Less easy is the task of consolidating available data. The consolidation of data requires:

• Removal of walled gardens
• Finding a unique identifier
• Transform data to be aligned

The removal of walled gardens is not something in control of your Revenue Operations Manager. Getting access to data that’s in a closed ecosystem, will heavily depend on the willingness of your software suppliers to make the data available and their ability to create a useful API* at scale.

Most of the RevOps software is still in a very infant state when it comes to data exchange. They built their product around the minimum of information they need to pull/push from/to your CRM, which makes their APIs still limited today to get all data useful for your business.

Even in a perfect world, where all APIs are mapped 100%, there would be limitations. It would require engineering resources to get all data into a central data lake, all records (mostly leads, contacts, accounts or opportunities) would need a unique identifier that is software agnostic (e.g. we need to be able to identify ‘Company X’ across all software) and all data would need to be transformed to be in the same format before it will become useful.

At this point in time, I don’t have the Holy Grail to solve this issue. The best advice is to keep data consolidation in mind when you procure new software. When you are still setting up your sales processes and the respective stack, you have the opportunity to choose software that’s aligned to your data needs.

* API = Application Programming Interface

Difficulty: 1/5

If your insights team needs to copy/paste data points, tables and visualizations in order to prepare for weekly business review presentations, you will be 100% rewarded for reading this article up until this point.

You can solve this waste of time instantly.

In order to stop this loss of time for your reporting team, we created SlideFill (which is 100% free). The software allows you and your sales, reporting, marketing and analytics teams to create presentations with parameters that will be automatically updated with your data from Google Sheets.

You will need to invest less than an hour in creating a template from an existing presentation, replacing data points with placeholders. Once this is done, you will be able to create presentations in seconds directly from your data without storing your data anywhere on our servers.

You can for example export Salesforce or Hubspot data as a Google Sheet and create a presentation from that data in 3 clicks.

This will save you hours to:

• Create data-driven presentations from scratch
• Automatically update recurring business reviews
• Customize presentations with audience specific data

No more copy/paste. No more mistakes. No more wasting time.

So… watch the catch?

There is none. As said at the beginning of this section, this part of the article is a bit more emotionally driven. Frustration drives opportunity. Over the course of the past years, I observed this was a common issue at multiple companies and we wanted to make this an issue of the past.

So… why is it free?

An ideological belief in serendipity. At this point in time, we don’t have bandwidth to commercialize, we want to create up-front value and we save hours ourselves. That’s a win.

Consider SlideFill a passionate gift and try the app here.

The topic that’s now top of mind in organizations, especially due to the economic downturn, is how you as a leader can do more with the same amount or potentially less resources. If this is today on your mind, automation is your answer.

In the previous section, you already got an understanding of how technology can help you to minimize your headcount investment on reporting and there is more good news. Automation can be deployed in most areas of your business.

To take a step back, let’s provide a definition of automation.

Automation is the ability to take an action (Y) without human intervention when a trigger or condition (X) is met.

To use the reporting as an example:

When weekly business data is available (trigger X), create a presentation using this new updated data (action Y).

With that definition set, we can look at the question: “How can automation benefit your business”.

There are multiple benefits of automation:

• Save time
• Increase productivity
• Grow performance
• Decrease operating cost
• Elevate operational excellence and visibility on required action
• Improve customer experience and differentiate from competition

These benefits can be categorized in three categories related to your metrics.

This first category has to solely do with the input of resources in your organization. These input resources often have a direct or indirect impact on the (‘client facing’) output but we leave the link between the two out of this category for now.

The main goal you have with input resources is to make the resource more productive. This means from the list above that we want to make sure the automation can save time in order to make the resource more productive, performant and eventually decrease its relative cost.

The decrease in operating cost (or cost of sales in our case) will be defined by either more output with the same resources (decreased marginal output cost) or the same output with less resources (decreased cost).

In a sales organization, this is often tied to headcount and the task – input – performed by the headcount such as sending emails, making presentations, creating reports, meetings, vetting leads etc.

The example above about automating reporting through SlideFill belongs to this category.

The first category made an abstraction of the impact of input on output and also (non-explicitly) didn’t talk about the potential ‘pull’ from output (clients and revenue) for which the input resources need to take action.

Given the line above is rather complex, I will give two examples:

A client (trigger X) is at risk of churn, how do we communicate to the salesperson to contact the client (action Y).

A seller sends an email to a client (trigger X), how do we make sure the seller follows up with the client (action Y).

The action here is slightly different compared to the first category: the action itself is passing information to our resources in order for them to know which task to perform.

This will improve operational excellence and increase visibility on required actions through the automated signal.

The last group of automations is related to automating the reaction to output (clients, revenue) without the intervention of input. It’s similar to the first category, but the trigger here is coming from outside the organization and the action is taken without the intervention of a human resource.

You experience this specific category every single day:

When you order a product online (trigger X) and get a confirmation email (action Y)
When you cancel a meeting (trigger X) and are asked to book a new one (action Y)

When you are late for dinner (trigger X) and get an angry text from your partner (action Y).

The key thing to remember here is that the trigger is mostly external (and not from within your business or organization) while the action is internally set up.

This action is often a ‘response’ or a form of acknowledgement which will improve the customer experience and can differentiate you from competitors at scale.

When you look at activities you can automate in your organization, you most likely will end up with an endless amount. To prevent that you need to scroll for hours, you will find a high level overview on a more conceptual level.

Things will get a bit more complex here, but you will find a step by step overview.

Step one is to understand the key criteria to keep in mind on a conceptual level. The three key criteria are:

This is related to the value of the external output (client) which is measured as the revenue coming from the client, the total contract value, the risk of losing the client and so forth.

This is related to the opportunity cost of the manual action required when the triggering conditions are met. Think about the cost of saving time, the cost in productivity and the cost in performance.

Through the automation of the activity, we gain efficiency (with a value calculated as):

(Cost of resources without automation) – (Cost of resources with automation)

This efficiency gain can either be invested in more resources (more resources for the same amount of investment) or in the reduction of resources (saving cost).

This is related to the potential damage the automation can do when timed or set up wrongly.

Going back to a previous example:

When you are late for dinner (trigger X) and get an angry text from your partner (action Y)

It would be most likely undesirable that you, on your end, have automation that is:

When you get an angry text from your partner (trigger Y), send an automated reply stating you don’t care about their complaint (action Z).

The automation here would do more bad than good. The same mistakes are made within businesses and you should prevent them from happening.

Think of a client sending an email that they are not satisfied with their subscription (trigger X) and your automated first reply being an email with the purpose to upsell them to a more expensive one (action Y).

Or try to think of the last time you urgently needed a person to assist you (trigger X), but you got caught in a loop and endless conversation with a chatbot (action Y).

These experiences can break the relationship between your business and your clients very abruptly. When you decide about which activities to automate, you need to take into account the risk associated with the automation.

The amount of risk you will have will often be influenced by the relationship with the client, the importance for the business and the accuracy of the trigger (data) and the alignment of the action to the situation.

If we would rewrite the above situations but did our job well, you feel we would be in a better position:

When a client sends an email that they are not satisfied with their subscription (trigger X), send an automatic reply acknowledging their feedback, offering a meeting and provide a temporary upgrade (action Y)

When a client needs urgent assistance from a person (trigger X), instantly connect them with a customer service representative (action Y).

You can see how these situations, still automated, most likely will increase relationships and value.

In short, whenever we make a decision to automate an activity, we need to think about the:

• Value of the output related to the automation (higher better than lower)
• Efficiency gain of automating the input such as saving time (higher is better than lower)
• Risk of automation (lower better than higher)

Given I didn’t figure out how to make the right decision matrix with more than 2 variables, we will need to go over a couple of steps to make the best decision about which activities to automate and how to decide what activities we automate first.

The first decision is between:

• Value of the output of the automation
• Efficiency gain of automating the input

Ideally, we want to prioritize activities that cost us a lot of time (e.g. efficiency gain is great) and have a big positive impact on our business (revenue, retention, churn prevention etc).

4. The Value-Efficiency Automation Matrix © SlideFill 2023

There are four outcomes when you do this exercise. We will need to calculate the ‘weighted’ value of these outcomes. When the parameter (value or efficiency gain) is high, attribute 10 points.

For example: automating a high value activity that would normally cost us a lot of time (high efficiency gain) will give us a score of 10 + 10 or 20 points. The weighted value of this combination is 10 points (20 points / 2 parameters).

A second example: automating a high value activity that would normally not cost us a lot of time (low efficiency gain) will give us a score of 10 + 0 or 10 points. The weighted value of this combination is 5 points (10 points / 2 parameters).

In an ideal world without risk, we would want to prioritize the 10 points value above the 5 points weighted value.

There are four outcomes when you do this exercise for your activities and the value:

• High Value + High Efficiency Gain: These are activities you want to prioritize when setting up automation, but due to the high value, it’s important to make sure to estimate the risk (step 3)
• Low Value + High Efficiency Gain: These are activities you want to prioritize when setting up automation, given the lower value there might be lower risk, but as per example above, the wrong automation might do damage.
• Low Value + Low Efficiency Gain: These are activities you want to deprioritize except when it’s extremely fast to automate them (think for example a confirmation email when someone signs up)
• High Value + Low Efficiency Gain: These are activities that are somewhere in the middle of prioritization, given they might impose high risk while not saving a lot of time, but when set up correctly, they do have a big positive impact.

The weighted value we will call the ‘input and output combined value based prioritization’ score which we will use in step 3 to make our final decision about which activities to automate first.

The second decision you will need to make is the trade-off between the combined input and output value and the related risk of the activity.

The risk of automation is linked to:

• The value of the output (revenue decrease, client attrition)
• The type of activity
• The quality of the data used as trigger

The value of the output is very straightforward: the more valuable the client is, the more we have to lose.

Example: Value of output

Making a mistake on a $10 million contract is going to impact your business more than making a mistake on a $5 dollar subscription.

Secondly, risk is linked to the type of the activity and what you are automating. As seen above, failing to show up with the right solution, at the right time (for example trying to upsell your client when they are thinking about moving to a competitor) can have a long lasting impact on your relationship and subsequently revenue and retention.

Example: Type of Activity

Sending a client proposal containing data that’s under NDA with BMW by accident to Mercedes through automation, will more negatively impact your business than addressing someone at BMW with the wrong name.

These risks are influenced by the quality and level of details of the data that was used to trigger the automation. Risk increases when the quality of data decreases, as the data will decide which automation to trigger.

Example: Quality of data used as trigger

When you aren’t certain about the quality of the language data about your clients in your CRM, it’s not a good idea to set up automated messaging in that specific language.

* NDA = Non-Disclosure Agreement

When mapping out the trade-off between the combined input/output value and the related risk of activities, you will have 4 possible (extreme) scenarios:

5. The Weighted Value-Risk Automation Matrix © SlideFill 2023

• High I/O Value + High Risk: These activities should be deprioritized in terms of automation.
• Low I/O Value + High Risk: These activities are somewhere in the middle in terms of prioritization, overall the damage you can do is low and you should focus on decreasing the risk.
• High I/O Value + Low Risk: These activities should be prioritized in terms of automation given low risk and high impact.
• Low I/O Value + Low Risk: These activities should be prioritized but a secondary to the ones above, given the impact is lower.

You can use a similar system in terms of ‘points’ compared to step 2.

Most cases will not be extreme and if the weighted value between combined input/output value and risk is favorable, you should move ahead with automation.

The above decisions are all to assess the value that can be generated and the trade-off with the risk involved to create that value.

As William Shakespeare would say when he was still around in 2023:

“To automate, or not to automate, that’s the question” — definitely not William Shakespeare (2023)

The final decision to automate or not will depend on other constraints related to setting up the automation itself. Factors involved are:

• Cost of automation
• Difficulty of automation
• Opportunity cost of automation

6. Factors to consider when automating sales processes © SlideFill 2023

The cost of automation is purely the financial cost (or cost of resources) in order to make the automation.

Example: Cost of automation

If you want to automate a low risk and low value activity saving your business $1,000 a month but the monthly development and maintenance cost is $2,000 , it makes no sense to decide to automate.

This cost is also impacted by the difficulty to automate. That difficulty is related to the data available, the software involved, the quality of APIs and the internal skill set in order to bring the automation to fruition.

Example: Difficulty to automate

Imagine you want to set up automatic pitch decks based on industry and location, that will send an automatic email to potential leads with a personalized presentation about the value your business can generate for them (based on their input in the lead form).

To realize this, you will need to:

• Set up the lead form to capture data in your CRM
• Send the data from your CRM to Google Slides
• Create presentations based on different conditions (industry, location)
• Draft an automated email in a SEP (Apollo, Outreach, …)
• Attach the presentation to the email
• Get the contact details from your CRM in the SEP
• Send the email

You can see this is a complex installation involving a lot of software flawlessly working together. Your organization might not have the resources to set this up, while the impact would be of great value: personalized proposals to new leads which will increase their likelihood to convert and increase your revenue.

P.s. As we need this ourselves, we will launch the ability to do all of this on SlideFill in 2023.

Lastly, your final decision will be based on the opportunity cost of setting up the automation. Automation will cost you money and time, which makes the same resources not available for another project.

From a business strategic prioritization point of view, it might make more sense to allocate these resources to a different pillar in your organization.

When making this decisions, it’s important to actualize the value of the automation as it often requires set up and a relatively low cost of maintenance

Example: Opportunity cost of automation

You need to decide between automating an activity or sending all your clients an end of year gift. The total cost of both is $25,000. The uplift in relationship with your clients through the end of year gift, will return you $100,000 in additional revenue in the upcoming year. The automation on the other hand will save you $10,000 per month.

On a first glance it might look like the end of year gift is the way to go. But if you would actualize everything to the beginning of the year:

Value of the end of year gift: $100,000 – $25,000 = $75,000
Value of the automation: $10,000 x 12 – $25,000 = $120,000 – $25,000 = $95,000

Most likely you will also be forced to do the same ‘end of year’ action the next year, while the value of the automation will run over in the new year without additional cost for your business (apart from maintenance).

You should be well equipped now to make the right high level decision about what you want to automate based on:

• The external value of the automation
• The internal value of the automation
• The risk related to the automation
• The cost of the automation
• The difficulty of the automation
• The opportunity cost of the automation

Your Revenue Operations Manager will play a vital role in the automation of your sales and potentially by extension marketing and customer services. The person you want to hire should be able to:

• Make decisions about prioritization
• Understand impact of automation across functions
• Scope business and technical requirements and feasibility
• Drive cross-functional stakeholders to execute set timelines

Knowledge often lives in silos. One of the most amazing things about being in Revenue Operations is the holistic organizational view: across departments, functions, business, marketing, technical etc.

This view is crucial to prioritize requests. Your Revenue Operations team will get most of their requests from revenue driving stakeholders (thanks Captain Obvious) and all of these stakeholders will have their own ideas and goals.

RevOps is in a great position to ‘centralize’ all of these ideas and goals and make a decision about the prioritization of the requests from the different teams.

Your Revenue Operations Manager will be able to provide strategic advice around which projects to pursue and which projects to kill based on the criteria outlined under the previous heading.

Once your Revenue Operations Manager has decided which automation projects to pursue, they are also in the right position to determine the impact of a project on other stakeholders, the similarities between projects and the potential spillover effects for other functions (economies of scale).

Similar to product managers they will be able to find ‘common themes’, think of solutions that are beneficial for every step of the sales process and find potential gaps that might break in between steps.

Example: Economies of scale

An automated lead scoring model to prioritize leads and find the most valuable ‘variables’, might be reusable with some modifications to find out which existing clients are the ones you should focus on for accelerated growth

Example: Gaps between steps

An automation solution that increases the conversion of leads to existing clients by 10%, will require more resources on the existing business side to serve this increased volume of customers.

It’s key that the person you hire is capable of ‘seeing scale’ (across regions and functions) while being critical about potential points of failure.

Now the decision has been made which automation projects will be pursued, the potential scope of the project and the potential impact on other stakeholders; Revenue Operations will play a crucial role in the high level planning and ensuring the execution of the plan to make it become reality.

To do that, Revenue Operations will start working on the business requirements and the translation of these business requirements in high level technical needs. This leads me to the question that I got the most while being in Revenue Operation is:

“How technical is a Revenue Operations job?”

The answer: It’s not a necessity to have in-depth technical knowledge.

Understanding technical concepts will help you as Revenue Operations Manager to translate business requirements into technical needs and it will also help you to guide technical teams. The core is into your ability to explain as clearly and structurally what needs to happen in an ideal state and what needs to change between the current and future state.

The format you use to explain this: logic, visualizations, text; doesn’t matter as long as the other party understands you. I personally never needed any in-depth coding skills in order to do my job and it would most likely mean you are too much in the weeds.

Now that is settled – we continue the revenue operations objective. After translating business needs in technical requirements (and checking feasibility), your Revenue Operations Manager will set the executional timeline and ensure cross-functional stakeholders move the execution forward.

In an ideal state, Revenue Operations role during execution is to ensure stakeholders adhere to timelines and meet the quality set.

Depending on the scope and stage of the automation projects, these stakeholders are:

• Sales
• Marketing
• Customer service
• Engineering
• Product
• Procurement
• Finance
• Learning and Development
• Reporting

And these stakeholders are tied to different roles:

• Scoping: sales, marketing, customer service
• Planning: revenue operations
• Technical solution (in-house): engineering, product
• Technical solution (external): procurement, finance
• Testing: revenue operations
• Roll-out: learning and development, revenue operations itself
• Measurement: reporting, sales, marketing, customer service
• Feedback / iterations: depending on which steps to iterate
• Documenting of learnings: revenue operations

Over the whole timeline and most stages, Revenue Operations within their RACI be: accountable and informed.

In some stages they will also be responsible or consulted (either directly or through their relationships).

* RACI = Responsible, Accountable, Consulted, and Informed

The beginning of this article gave a definition of Revenue Operations as the glue between strategic sales, marketing and (customer) service.

Up until now you have mostly learned about the first pillar: strategic sales which includes being strategic with resources, finding better revenue opportunities and driving efficiency through automation.

Outside of your sales pillar, there are two other departments that are heavily influencing your revenue:

• (Customer) service
• Marketing

In this section you will learn how a strategic approach to customer service can improve your revenue outcomes. Let’s first define some concepts:

The reason I put customer service between brackets is because it’s too often defined as customer support. Customer support and customer service are not the same.

Customer support is a part of the overall service delivered to the customer. It’s how you support the customer when they have a problem or provide feedback.

Purely looking at this from a two-way approach:

• Client asks a question or provides feedback
• Company provides an answer

Will make your company guaranteed to miss out on tons of opportunities. When considering customer feedback in this limited way, you will only increase retention.

Helping a customer through customer support or acknowledging feedback is going to generate a stronger understanding of your product or increase your relationship. This will subsequently prevent attrition. But there is way more – revenue focused – value that can be generated here.

Feedback and questions from clients is an important source of information to evaluate:

• Your product (and its roadmap)
• Your sales teams their skill set or quality
• Your documentation and client’s understanding
• Your overall customer experience and perception

All of these are not only prevention attrition, they can also generate additional value.

When the right process is in place, feedback from clients will become part of strategic planning in order to create more revenue generating opportunities.

These are the easiest to define through examples

Example: Product and it’s roadmap

If customer feedback showcases x% of your existing clients want a certain feature, incorporating the feature in your product can lead to higher product usage, upsell opportunities and eventually sales or revenue.

Example: Sales teams and their skill set of quality

If customer feedback is indicating they are not getting the right level of support it’s mostly related to a gap of knowledge on your sales team. Working with L&D you can improve your sales teams to close that gap and make them better at the positioning over your solutions, eventually leading to better customer experience, sales and revenue.

Example: Documentation and client’s understanding

If customer feedback is indicating client’s do not understand your product or service, it could drive the product roadmap but also the available ‘self-learning’ material for the clients increasing their understanding. The better they understand how your service is answering their needs, the more they use, the more you sell and make revenue.

Example: Customer experience and perception

If customer feedback showcases a bad customer experience, you can improve this experience, which will increase the satisfaction of your customers, make them advocates and eventually drive referrals, sales and revenue.

These examples all deliberately end with the words ‘sales and revenue’ as they all close a gap and lead to additional usage, upsell opportunities, referrals or simply put: revenue growth.

The most common, widely, adopted solution in order to collect customer feedback is called CSAT or Customer Satisfaction Score Calculation. CSAT will provide you with:

• A weighted percentage of satisfied customers
• The likelihood of customers recommending your service

In my non-requested opinion, CSAT made organizations lazy.

The reason I say this is because it allows companies that are not 100% bought in to listen to their customer feedback to use it as an excuse for caring.

A bit like stating: “You deeply care about the environment, because you don’t throw trash on the ground.” – you should see what’s wrong here.

The problem with CSAT is that it’s often not representative of your customers, unless you find a way to enforce it (which is difficult) and even then it might not be extremely reliable.

Don’t get me wrong. CSAT is still important and sending out a survey requesting feedback about an interaction or product is always good. Just keep in mind, CSAT is heavily impacted by self-selection bias: only people who want to fill it in, fill it in.

This often results in skewed results:

• Non-representative sample for all your customers filling in the survey
• Responses are overly skewed to extreme negative or positive

You can imagine the consequences of this when you use it to set your long term strategy to improve customer service.

Instead organizations need to set metrics to track customer satisfaction which are more product-led:

• Time spend in your product
• Number of times logged to your product
• Amount of output created with your product
• Completion of your self-study material and guides
• Amount of people who want to use your referral program
• Willingness to engage with your sales team and specialists
• Number of tickets created in order to get additional support
• …

The right metrics highly depend on the product or service you are offering and there is no one-size fits all. Once you have these metrics, you should find a balance between Product-Led Feedback (coining this term) and survey-driven Customer Satisfaction Scores.

How to do this? This is where your Revenue Operations can help: building out the right metrics to track, data capture, consolidation of the data, making data available cross-department and the decision making from the data itself.

* CSAT = Customer Satisfaction Score Calculation

The first role of Revenue Operations is to work out which feedback is relevant for the revenue side of the business. These are mostly data points, written feedback, scores or usage insights that give an insight about the perception of the total value created.

The key stakeholders in identification of these metrics are Sales Leadership, Sales Strategy and Revenue Operations itself. In order to capture the data points, Revenue Operations might rely on different other departments or systems in place.

We can visualize potential department using the metrics we defined under the previous header:

Revenue Operations will define these metrics and work with sales (or other departments) in order to get them. Organizations might be in a situation where no data is available and in this case it’s the task of RevOps to create a business requirement document and plan (stakeholders, resources, timeline, etc.) to get a system in place to get the data or consolidate this data.

Example: No system

As a small company you can provide support through an email alias (help@), but as you grow this will not be sufficient to route tickets and collect data around the categories of problems your clients encounter (feedback). In order to solve this, a system like Zendesk can help you in routing and categorizing data, providing insights into the most common issues.

Example: No data consolidation

Your product team can capture in a database how often your users generate output using your product. This can give a good indication of upsell opportunities. This doesn’t mean the data is easily available to sales. Revenue Operations can work with the product team to get the data from the database in your CRM and create notifications to sellers when certain upsell thresholds are met.

These examples (and in essence this whole article) are a good testament why the cliche ‘breaking down silos’ holds a lot of truth. When departments refuse to look beyond their borders, they will miss out on tons of opportunity.

Additional note about internal feedback from the author:

The same principles are true for internal feedback. It’s crucial to define metrics and a system to collect feedback from your revenue generating teams (sales, marketing, customer service) given they are the unsung heroes driving front-line sales. Failing to give them a secure and open platform to provide feedback, will hurt your organization.

After all relevant feedback can be captured, Revenue Operations is responsible for creating the feedback loop. This loop looks different based on the type of feedback:

• Explicit: for example a customer filling in a survey
• Implicit: for example a customer using your product less

In the case of implicit feedback a couple of steps can and should be omitted. Revenue Operations will be responsible for the strategic design and driving the implementation of the feedback loop, while other stakeholders are responsible for the final execution and taking the right actions.

The full feedback loop looks as follows:

7. Full feedback loop in Revenue Operations © SlideFill 2023

1. Receive feedback or data point
2. Acknowledge feedback (explicit only)
3. Consolidate / categorize the feedback
4. Transfer the insight to the relevant team
5. Make a decision (involved team) about a solution
6. Implement a solution
7. Communicate solution back to revenue-driving team
8. Package solution in order to:
   • Increase revenue
   • Increase retention
   • Decrease cost of revenue
9. Deliver solution to feedback provider
10. Scale solution to other customers
11. Document the solution for future deployments
12. Report on the impact of the solution (measurement)

The more of these steps can be automated, the better.

In this feedback loop there are three caveats most companies struggle with and most likely you do too:

Organizations often forget the power of acknowledgement. A simple authentic (‘non’ automated) message of acknowledgement can have a powerful influence on your relationship.

An even worse customer experience is when your feedback is acknowledged but no action is taken.

Over the years, I have worked with many suppliers (SEPs, Scheduling Tools, …) that acknowledge feedback, promise the feedback is included on the product roadmap but never deliver a solution.

It’s especially frustrating, when you are asking for ‘basic’ functionality that never comes to fruition while they are releasing new product updates that are shiny but not necessary. This definitely accelerated with the desperate *need* of companies to include GenAI in their products.

What’s the point of sales teams being able to write automatic emails through GenAI when they are unable to target the right audience because of a product limitation?

On the flip side of that coin, I have worked with suppliers (Enrichment Tools – Lusha, Cognism) that put me directly in contact with their product teams which allowed us to create amazing solutions together both helping our business and theirs.

This built trust and relationship and made me an advocate for their solutions (hence the mention).

Because of silo’s in your organization, there is a risk that feedback is being passed on to the relevant teams but the deployment of a solution is not reaching the revenue-driving team.

(Technical) teams often have a passion for solving hard problems but forget that finding a solution is only 90% of the work. When no one knows a solution is available, people will still have the same problems.

This is most likely the biggest learning I have about a role in Revenue Operations: invest as much time in letting people know you have the answer, as you invest in finding the answer.

It’s the same trap that makes tons of businesses fail: “If you build, they will come”

This is not the case and often glorified. There are tons of speeches to be found online of Steve Jobs explaining how Apple became so successful by answering customer needs through a user experience that was simple, appealing and working.

But don’t fool yourself: they invested a lot of money in letting people know this was the case (as 43 million viewers on YouTube confirm).

The same goes for your solutions, whether it’s internal or external, make sure your audience knows:

• There is a solution to their problem
• There is a solution to a problem they didn’t realize they had

In short: failing to communicate that you have a solution is as good as having no solution at all.

This one we will cover as the last standalone Revenue Operations objective as it combines two steps from our feedback loop: making a decision about the solution and packaging the solution to drive revenue.

Making a decision on strategic (revenue) opportunities is a shared responsibility between Revenue Operations and other departments. It’s definitely not only up to your Revenue Operations Manager.

To understand this better, you should go more in depth about two steps of the feedback loop:

• Make a decision (involved team) about a solution
• Packaging the solution for revenue

You should know that there is more at play than purely revenue when you make a strategic decision about a solution and every solution is a question of trade-offs.

The first trade-off someone needs to make is that a solution is in line with the vision and brand of a company, products or service.

While solving a problem can be beneficial, it can also go against your long term vision.

If this is the case, make sure to let your customers know and table the solution for now. Going back to what I said before, authenticity always wins in the long run. Instead of explaining to your customers that it’s on the roadmap and never deploying it, it’s better to let them know why the decision to not pursue this now has been made.
Things that can influence your strategic decision are:

• Vision
• Brand
• Policies
• Negative impact on others
• Deviating too much of your core business
• Etc.

It’s easier to explain this with an example:

Example: Vegetarian store

If you are running a vegetarian store with a brand built around animal welfare, promising a solution on customer feedback around the fact they can’t find a ‘real steak’ can kill your whole business.

As obvious as it is, starting to offer a cow steak will impact:

• Your brand: you are no longer a vegetarian store
• Your vision: you do not longer care about animal welfare
• Your other customers: negative perception from them
• Your core business: need for completely different supply lines

Whatever might seem like an additional revenue opportunity here, can have a negative impact on all of your other revenue and subsequently your complete business.

The second trade-off has to do with your most precious resource: time.

Companies often have a short-term strategy that’s aligned with a long-term strategy. Any decision that’s been made about providing a solution, will take time away in the short-term from another project that might influence both your short and long term strategy.

Companies, more specifically start-ups, often make mistakes here focusing too much on short-term (to survive) compromising on long-term vision. This is a risky trade-off.

Example: Uber’s price increase

To increase adoption of customers (problem), the company entered the market as a very cheap alternative to taxis (solution). Over time, this impacted profitability. Uber increased their prices by 82% between 2018 and 2022 leading to churn of their earlier customers.

Whenever a decision is made about a solution (which involves other teams than Revenue Operations), one needs to take into account long-term impact beyond revenue.

The moment that building a solution based on feedback makes sense from a timing and overall business perception, the decision on how to package the solution and use it as a revenue lever often comes back to Revenue Operations, Customer Service, Marketing and the Sales Teams.

RevOps will play its role in deciding how the solution can strategically drive:

• The growth of your sales organization: upsells, retention, cross-sells
• The decrease in cost of your sales: efficiency or productivity gains

They will need to help drive a motion either externally (growth of revenue) or internally (decrease of cost) to drive adoption of the solution.

This includes decisions around where to pilot the solution, how to go-to-market with the solution and how to scale the solution once insights showcase the solution is working. They should create a (global) vision that this solution can benefit different parties.

If Apple would have only offered the iPhone to a handful of customers complaining about a phone with a keyboard, they would have missed out on the $600 billion smartphone market.

Your Revenue Operations Manager and its stakeholders need to have a broad vision to see a link between the potential of local, limited, feedback and a broader audience of customers or internal stakeholders with a problem (they potentially do not know they have).

$600 billion dollars.

That’s the amount of money all companies combined are annually spending on digital advertising according to Statista.

With global marketing spending topping $1 trillion dollars, which is as much as the valuation of Google, we are in a pickle when we are unable to measure impact.

This guide will not weaponize you with the newest techniques to do measurement online, but it will definitely give you some new ideas to think about when you are in a position today where you feel you are not fully capitalizing on all marketing effort and spend in your company.

A good revenue operations requires the understanding of:

• Marketing initiatives
• Potential sales opportunities
• Touched and actioned revenue

When your organization has silos that are blocking the communication of upcoming marketing initiatives and subsequent sales opportunities, your marketing investment will be partly wasted as your sales and revenue generating employees will not know where to take action.

As important is the other direction of the data flow. Marketing needs to understand what has an impact, how much revenue is generated and where they should allocate resources in the future in order to drive additional sales.

In 2006, Philip Kotler already wrote about ‘ending the war between sales and marketing’ and now, more than 15 years later, we are no closer to an armistice.

So, what’s not working? The answer is simple, but the solution is less so:

• Externalization of failure, internalization of success
• Lack of communication to understand opportunities
• Lack of reporting to understand success

Reading these blockers, one might think the solution is straightforward: we need to break down silos and set up data streams between the two (sales and marketing) departments. It’s a correct conclusion, but legacy, incentivization and historical organizational structure is not creating the right environment to do so.

Here’s why in more detail:

Legacy

In-group cohesion has made the ‘war between sales and marketing’ inherently biased and we love to strengthen that bias. Think of all the times you heard ‘marketing is not supporting us’ or ‘sales trying to say what marketing needs to do’.

Incentivization

Sales is often not incentivized to drive marketing initiatives forward (inviting clients to events, getting new newsletter subscriptions etc.) and marketing often doesn’t receive sales-driven commission

Historical organizational structure

Marketing rolls up to the CMO and sales to the COO. Organizations often lack a senior leader, such a revenue operations manager, that can build a bridge between the two organizations aligning communications and plans.

These blockers are preventing your capability to increase the return on investment of the budget invested in marketing and define the right marketing initiatives to get the most revenue from its resources. Let’s see what you (theoretically) can do better.

Before you keep on reading and expect a cure to solve all of your sales and marketing problems, I want to come back to the last line of the paragraph above. Let’s see what you theoretically can do better. Theoretically.

The reason I emphasize theoretically (did it again), is because the below is not solving your legacy, incentivization and historical structure. Your organizational design is heavily dependent on your company and changing it can take multiple years.

When these issues are deeply embedded in your culture, your success following these practices ain’t written in the stars. Therefore, it’s theoretical: it’s assuming you have a blank sheet to start again.

The core to solving legacy, pointing fingers, the externalization of failure and the internalization of success, is data. Instead of having an emotional argument about what works and what doesn’t work, both departments need factual common metrics in order to make a point.

This can be solved by process design. Marketing should have the ability to create marketing driving opportunities for sales teams and sales teams should execute on these opportunities which should translate into results. These results should be passed back to marketing in a reporting and feedback loop.

If this is not happening in your organization, you have a problem. The reason you have this problem is process design or incentivization (but that’s the next topic).

To achieve this process design, marketing needs:

• A systematic approach to create opportunities
• Collaboration with sales to set input metrics
  • # of opportunities created
  • $ value of opportunities created
  • % of opportunities pitched
  • % of opportunities closed
• Reporting coming from sales on
• Touched revenue
• Actioned revenue
• Analysis of the data to decide future strategies

Most of these topics can be resolved through Revenue Operations and Sales Strategy & Operations in combination with Marketing.

By creating such a systematic approach, marketing will be forced to think about target setting (and accountability) outside of their department. Apart from their own metrics (attendees, subscribers, etc.) they will need to set metrics for stakeholders following up on their initiatives: sales input metrics.

Sales on their end have to accept to attribute value to marketing with the concepts of touched and actioned revenue.

Touched or assisted revenue is the concept in which value (mostly revenue) is attributed to marketing while keeping in mind there are other touch points (sales) that had an impact.

Example: Touched or assisted revenue

Sales is pitching a new feature while marketing on their end is later organizing a webinar about the feature. After the webinar, the customer adopts the feature leading to 20% increase in revenue.

This is where the conflict starts: sales claiming it’s because of their pitching the client adopted the feature while marketing claiming it was the webinar.

To solve this, marketing can classify the uplift in revenue as ‘touched revenue’ when a client attended the webinar and it can do so as long as a customer adopts the feature within x amount of days after the webinar.

Now sales on their end can calculate the total uplift revenue of all people that adopted the feature regardless of them attending the webinar. The difference between the two is touched revenue or the revenue that was assisted by marketing.

Actioned revenue is when there is only one channel involved for one specific action taken by the customer (although possibly assisted by another channel). An example here would be a person attending a webinar of your company and bought your product or service without speaking to sales.

Example

Consider a lead with a $10,000 budget. The lead fills in a lead form and talks with a Sales Development Representative. A couple of days after the conversation, the lead is invited to a webinar. The lead attends the webinar and decides to raise its budget to $12,000, makes the decision to go forward and buy your product.

TL;DR: the better your capability of attributing factual data to the channels (separately and combined), the easier it will be to avoid pointing fingers.

Truth be told, the above will never work without the right incentivization.

In most organizations:

• Marketing is not incentivized to keep sales responsible for execution
• Sales is not incentivized to execute on marketing asks

This drives frustration and you can’t blame anyone for it (except leadership).

Getting incentivization right is easier, but it requires the right reporting and metrics, as the only thing more frustrating than not getting a bonus is seeing someone else get a bonus for your work. This destroys both extrinsic and intrinsic motivation.

Once reporting is accurate, leadership needs to tie marketing compensation and target setting to sales outcomes. This can be done by going beyond clicks, attendees and subscriptions – and include activations, product adoptions and touched and actioned revenue.

Sales on their end need to get incentivized to action on marketing opportunities. This can be done by creating OKRs around following up on marketing opportunities (input metrics) or driving a competition or sales program incentive on top of normal compensation and revenue driven commission.

It’s important to note here that just simply throwing money at sales for doing the ‘basics’ of their job is risky. First of all, it can become an acquired right (which will dilute the incentive itself) and secondly you want to prevent people from cheating the system.

Being smart with incentives is key and so is a rigid quality assurance team or a controlling power. It’s similar to most democratic political systems:

• No one should take their power for granted
• No one should be able to push their bill without control
• No one should assume absence of corruption

In an organization the same holds and its success mostly boils down to your ability to report on operations. Sellers won’t take the risk to cheat on administration or input when it can influence their next promotion and they will never turn down the opportunity to earn more money.

* OKRs = Objectives and Key Results

Solving your organizational structure and the need for it, is your internal kitchen. But regardless of your willingness to solve it, having an individual (or team) that can bridge sales and marketing better is never a bad idea.

This team can be your Revenue Operations team, given the bridge will allow you to:

• Design a process accessible for both teams
• Align reporting between sales and marketing
• Facilitate the communication between stakeholders

And the fact that being this bridge will help them obtain their targets:

• Increasing revenue
• Increasing productivity
• Decreasing cost of revenue

If you want to succeed in burying the hatchet between sales and marketing, you will need to be able to empower both teams to work out of a shared source of truth. To do so, your Revenue Operations Manager needs to think out the requirements for a process allowing information to flow from and to marketing.

This means scoping out a process allowing to:

• Communicate between (a part of) MarTech and sales stack (mostly your CRM)
• Create, assign and showcase opportunities for sellers including next steps
• Send back reporting on input and output metrics to marketing

Your Revenue Operations team will drive the (technical) implementation of such a process involving their stakeholders.

This single source of truth, preferably your CRM and/or SEP given sales works out of here, will remove any emotional argument between the two parties. If it doesn’t exist in the system, it didn’t happen. It also allows for automation to remove human intervention, which is prone to errors, and save your organization time.

If you are now thinking: ‘all good and well, but this is a utopia, we will never be able to do this’ you either need to hire better people, facilitate collaborative communication between marketing and sales, or reconsider your own willingness to solve the issue.

This is, 100%, possible. The main reason it often doesn’t become realized is because of departmental ego and incentives (aka willingness to solve the issue).

Example: Not aligned process design

Marketing organizes an event about a new product feature X and collects registrations through Eventbrite. Sales will be tasked with pitching feature X after the event and needs to adapt its sales pitch based on warmth of the lead (e.g. attended vs. registered). Product marketing created these sales pitches.

What happens in most organizations, and potentially yours is:

• Marketing shares an Excel after the event with random attendance data
• Excel is shared with sales and they need to find their clients
• Sales has no idea when to use which pitch deck and copies of copies go around
• Opportunities are created in the CRM with ambiguous names
• Marketing has no insight on how much revenue was generated by the event
  • Marketing blames sales
• Sales disliked the extra time consuming task as it didn’t help achieving their bonus
  • Sales blames marketing

How many of these steps do you recognize?

The easiest way to solve this, which is not going to sound easy at all, requires two things:

• An API
• Willingness to talk

That’s maybe a bit over simplistic, but in general it does come down to that.

Sales and marketing could be aligned on a unique identifier (for example: email address) between the event registration platform (marketing) and the CRM (sales). They would collectively agree on the minimum data necessary (for example: attendance).

Next a well-designed process and API could generate opportunities linked to the unique identifier based on attendance data in the MarTech directly into the CRM. While populating these opportunities, the material to be used (pitch deck) and pitch tag (for measurement) is added to the opportunity. Sales works through the opportunities and marketing is able to report the metrics defined in the previous section.

Example: Aligned process design

Marketing organizes an event about a new product feature X and collects registrations through Eventbrite. Sales will be tasked with pitching feature X after the event and needs to adapt its sales pitch based on warmth of the lead (e.g. attended vs. registered). Product marketing created these sales pitches.

The situation changed now:

• Opportunities are automatically created with attendance data and pitch decks (API)
• Marketing can measure the success of the opportunities in a shared report (API)
• Sales will pitch opportunities with minimum wasted time (willingness)

Again, how many of these things do you recognize?
Or better, how many of these things would you love to recognize?

8. Marketing & Sales Process Design © SlideFill 2023

If you don’t – you know where to invest:

• An API
  Willingness
  Revenue Operations

Organizations that truly aim to achieve the best results, will need to set up the right communication and incentivization. That means, alignment to thrive, clear communication lines and rewards linked to achievement.

RevOps plays an important role here, as they have a common goal that’s overarching sales, marketing or customer service: they want to generate revenue at the lowest cost in order to drive profitability. Given their ‘target’ is not linked to a book of business or one specific function/scope, they can benefit from investing time and resources in building a bridge between sales and marketing.

The ability of an organization to communicate between marketing and sales often doesn’t fail at the highest level – most CMOs and COOs can be easily put in one room.

The struggle is coming from a power play happening on a lower leadership level, where the sales lead for a fraction (for example: Canada) is not interested in the marketing activities for the whole of the region (for example: North Americas) where Canada is not the highest priority.

This is the frontline of the battle: the perception of sales failing to see the value that can be created by marketing initiatives designed for a region, for their specific fraction, and the perception of marketing failing to invest relatively low resources in involving the fraction of the region.

As Revenue Operations is inherently interested in listening to any opportunity that can generate additional value, they can create a bridge between marketing and sales by identifying how the initiative can have an impact on the fraction and communicate that value to sales.

In more serious terms: your Revenue Operations Manager can create economies of scale from marketing initiatives by facilitating spillover effects to more stakeholders. In doing so, they should try to prevent putting additional short-term burdens on marketing itself.

Burdens should either have a long-term positive impact on marketing or they shouldn’t be asked. This showcases your true personal investment and not simply your involvement for personal gain (which will decrease willingness to collaborate over time).

Now Revenue Operations has defined these spillover effects, the second play is incentive. As everyone who ever read a page in a book about psychology knows, there are two types of motivation: intrinsic and extrinsic.

Influencing intrinsic motivation is always a difficult one in a corporation, as most people, myself included, work in order to afford a fulfilling life. This is in its core an extrinsic motivation.

That said, it doesn’t mean one cannot be passionate about what they are doing. The ability to create value is something that gives intrinsic motivation to a job.

So the first important communication and incentive that needs to be set up is motivation related to the fact that supporting this initiative will create value. This reflects on the individual involved: they will be able to create value. This value creation in itself is an incentive and likely one of the more powerful intrinsic incentives in your arsenal.

The second group of incentives to drive sales to execute on marketing incentives are extrinsic:

• Linking the marketing initiative to target achievement (commission)
• Linking the marketing initiative to a prize (award, recognition bonus etc.)
• Linking the marketing initiative to minimum requirement for performance (promotion)

To be able to do these incentives, you have different needs going back to two concepts you read about before:

• The ability to showcase value (spillover effects to a fraction)
• The ability to report on value (reporting) to have correct incentives

And that ability, to go full circle, goes back to: process design, reporting and communication which RevOps can facilitate from start to finish.

The next two chapters are less core strategies for Revenue Operations today, but they will become increasingly important over the course of the next year.

The first topic looks at customization of content at scale and why customization in the sales process is key.

The answer: content is a unique differentiator for your brand. Better alignment of your value proposition to your prospective and current customers leads to an increase in revenue.

Don’t take my word for it, smart people at McKinsey created the “The value of getting personalization right—or wrong—is multiplying” – study showing 71% of customers expect personalization and companies mastering customization realize 40% more revenue.

Tailoring your message to needs, giving relevant recommendations, offering targeted promotions, addressing people personally, celebrating milestones and sending your communications timely is more important than ever.

And still we are here:

9. Unpersonalized content examples © SlideFill 2023

This is ridiculous and we all recognize it. The irony of it all: organizations are being pushed by FOMO to adopt Generative AI which will lead to more of these – personality dead – messages.

I could have written this whole book in a matter of minutes using ChatGPT, but it would have sucked my soul out of it.

The future doesn’t look bright. Companies that see the change to even more plain, undistinctive and dull content coming, will be victorious in the long run.

You will need to proactively prevent that your messaging, pitch decks and one-sheeters will end up in the saturated pile of GenAI driven content.

Companies consolidating all their content creation through GenAI will win in the short run (saving cost) but will lose in the long term by lack of differentiation and personalization.

Why?

71% of your customers expect it, you will have 35% more conversion leading to 40% more revenue and you will differentiate your brand in the long run.

Before you go back to your leadership saying ‘Megan said Generative AI is just a fancy fad’’, you need to dig a bit deeper bringing multiple concepts together.

Consider Generative AI or tools like ChatGPT the “automation of content”.

Customization, which also can be automated, is your “ability to personalize”.

Based on this definition, the same principles covered in the chapter about automation are true. Depending on the use case of your content, automation (or GenAI) will be desired:

• Content of low value: can be automated through ChatGPT with a minimum of customization

When thinking about content of low value, you should think about sending a confirmation message, an out of office or similar low value activities.

Example: Low value content

A lead books a meeting to go over a demo, you send an automatic confirmation message of the meeting.

You can create this material using tools such as GenAI as the lack of customization will only impact customer experience minimally.

There are also plenty of tools, such as Outreach or Salesloft, allowing you to customize these sequences pretty easily.

But what happens when we change the example?

Imagine now that you want to share a presentation slide deck showing your product and how it can help for your leads’ specific industry attached to the confirmation.

Example: High value content

A lead books a meeting to go over a demo, you send an automatic confirmation message of the meeting with a link to a slide deck showing how your product can help for their specific industry (Customization).

The function of the personal slide deck tailored to the lead’s industry is to make the lead warmer and confirm you have a solution for their specific use case.

This is a high value activity, given it can have a direct impact on the likelihood of this lead to convert and purchase your business.

Customization should go further than just personalizing their first name in your messaging.

• Content of high value: should be less automated through ChatGPT with a maximum of customization

There are plenty of examples of ‘high value activities’ that require in-depth customization.

Imagine activities such as doing:

• Sales pitches
• Following up with leads
• Sending out marketing collateral
• Pitching a new product feature

All of these activities are asking the client or lead to do something:

• Purchase your product
• Adopt a new feature
• Attend a marketing event
• Increase their investment

It’s unbelievable most companies and individuals use a one size fits all approach with effort similar to a swipe on Tinder to ask their clients to commit to more resources (money or time).

It doesn’t work. And if it does for you, it’s still guaranteed you are losing a lot of revenue.

We need to customize to get our 40% increase in revenue.

Now the ‘why’ is established we can move to the ‘how’.

First of all, the use of generative AI and the ability to customize, are not mutually exclusive. The right customization requires creating templated data-driven content.

A template can consist of multiple modules, which in themselves can be either customized or generic. Your goal is to find the right balance between the two based on the value of the activity.

Let’s look at an example of a lead filling in a lead form, scheduling a call and our first sales call with this individual.

Example – Step 1 – Capturing data

The lead fills in a lead form including their first name, last name, website, country and industry and main reason for reaching out.

10. Customization of content example step 1 © SlideFill 2023

Example – Step 2 – Low value confirmation

We send them a confirmation mail that one of our sellers will reach out.

This is a low value activity (the confirmation email), given it’s most likely an automated process and the main function is to have a quick confirmation that we received their data.

That email in itself, based on the example above, will be a template containing different modules:

11. Customization of content example step 2 © SlideFill 2023

Example – Step 3 – Higher value book a meeting

The next step will be to have the lead book a meeting with us. This activity is more valuable, given we know that leads booking a meeting are x% likely to convert and generate value for our organization. As this is not a confirmation email, we can add more specific, personalized information that’s relevant for the lead in order to convince the lead to book a meeting:

12. Customization of content example step 3 © SlideFill 2023

Example – Step 4 – Highest value conversion focused pitch

Once the lead has booked a meeting, we will jump on a sales call in order to ‘convince’ the lead why our service or product is solving their issues based on their provisioned data. The presentation we prepare contains both modules with generic and customized information.

By doing so we increased the likelihood of conversion by ~35%, increased the revenue potential by 40% and made the best use of both our times (as 76% of customers get frustrated when being presented with only generic information).

Most of you will recognize all of this is best practice, but struggle with the execution of it. The reason I say this is because I struggled with the execution of this.

Different SEPs such as Outreach, Apollo, Salesloft allow you to customize your emails using parameters, but they are quite limited to email only. Sending a customized email with non-customized material in attachment is not going to do the complete trick.

That’s why SlideFill is here.

SlideFill is 100% free and will allow you to create data-driven sales pitches, case studies and marketing material at scale simply using data from a Google Sheet which can be created from your CRM.

It will give you the benefit of customization – and a 40% increase in revenue – while taking away the pain of spending hours to customize material. In 3 easy steps, you will be able to create hundreds of data-driven presentations filling in the customizable modules of your template using your customers’ data.

In our simple guide you can find out how it works and start saving hours, literally, today!

Similar to Revenue Operations objectives under automation, your Revenue Operations will be a key consult and decision maker when it comes down to deciding which process (prioritization) requires data-driven presentations.

Decision will be based on:

• Customization need of the activity
• Risk of customization and organizational readiness for it
• Efficiency gain in terms of output value from customization
• Data availability and quality of data in order guarantee success

These different factors are all intertwined and shouldn’t be considered as stand alone items. Whatever the factors for your decisions indicate, the need for customization is a question of ‘when’ and not ‘if’.

In the next couple of months and years, generic content and pitch material will be more saturated, given every company now has access to a semi-qualified copywriter, ChatGPT, that bases their generated copy on existing content.

There will be a fatigue amongst the receivers of such content, which will simply result in your emails and pitch material landing in your customer’s bin.

To prevent this, now is the time to take action. By creating personalized scaled content, you can influence the decision of readers today to open your emails, read your decks and jump on calls with you in the future. Building this trust should be a long term strategic priority before the window of opportunity closes and damage is done.

You’ve been warned.

Regardless of your decision when and if you will customize collateral for marketing, sales, customer service or all of them (best case), you will need to decide which input parameters will define the customization you want to provide.

The proximity of your Revenue Operations Managers to the data around these different teams, puts them in a good position to decide on demographics and client-specific information to be used to decide which variables to dynamically replace in your marketing one-sheeters or sales decks.

The earlier in the funnel, the less information you will have. For leads and new clients, demographic data will be typically used: industry, vertical, company size, location etc.

Further down the line, you can start incorporating data specifically to your clients such as their investment, their return on investment, their usage of your product and other sales or product usage led parameters.

Example: Generic pitch material

You are launching a new product feature called ‘Superboost’ that enhances the quality of product recommendations which will boost the return on investment of your clients by 20%.

In the old or current landscape, you will inform them using one deck that is positioning the new feature, most traditionally including:

• Generic why: return on investment up by 20%
• Generic case study: one client their story
• Generic how to implement: three steps to activate Superboost

This is how most sales organizations will position a new feature today. The problem: it doesn’t resonate. So what if we customize the presentation based on triggers?

• You will use the current ROI of a client and showcase the future ROI based on their own data (instead of a generic why)
• You will use a case study of a client in the same industry as the client we are pitching to (instead of a generic social proof)
• We keep the generic how as it’s not dependent on the client

Let’s go back to Jane who is running a Fashion & Retail company in Australia:

Example: Customized personal pitch material

By doing so our messaging related to the opportunity of implementing ‘Superboost’ will resonate much better with the client. The client will be able to see:

• Direct expected impact from implementing the solution for their business
• How implementing the solution helped a similar company (social proof)

Creating such data-driven presentations at scale is something you can do today using SlideFill.

You just need to upload your data using a Google Sheet, set a presentation with variables as template and you will get hundreds of presentations related to your specific client needs.

Given the endless opportunity here, your Revenue Operations Manager will play a key role in facilitating the availability of such customization to your sellers, marketing and customer service teams; guiding them which triggers and data points to use effectively.

RevOps will also steer your content teams, to create such templates allowing for customization as you want to decrease the amount of hours sellers need to spend on creating decks or customizing templates given this can be done as scale.

Additional note of self-reflection:

The last job of Revenue Operations related to content is making data-driven presentations and templates available to sellers. There are two options, depending on the size and structure of your company:

• Centralized content operational excellence
• Decentralized content operational excellence

Option 1 would require the set up of one team that is responsible to centrally create the templates (with variables) or to create the presentations themselves at scale.

This approach has benefits including time savings, global alignment and brand consistency but also comes at the cost of regional nuance, relevance and depth of customization.

Given regional sales, marketing or customer service teams have no ‘input’ in making the customized presents for different clients, they are ‘forced’ to use the ones provided by a centralized team. This will save time (you only have to create them once at scale) but the willingness to use them might be lower (no early buy-in from the teams).

Option 2 allows the sellers to create their own presentations from their own templates, which will still save time, increase regional relevance and elevate early buy-in. The cost is simply losing brand control and global scale.

The solution is somewhere in the middle. By providing global templates, one can control their brand and benefit from global scale. Allowing the sellers freedom within these templates to decide what variables to add, keep or remove will increase relevance.

Revenue Operations will lead the trade-off exercise based on the activity to decide the room for flexibility.

Example: Centralized global content creation

You want to invite all the clients globally to a global webinar that has one-size fits all content. The follow-up material will be solely customized on the industry of the attendants.

This is something that can be led from a global content center of excellence, given it doesn’t require high customization. There is additional importance for brand consistency given this is global marketing led. Option 1 would be sufficient.

Example: Decentralized relevant content creation

You want all sellers to talk to their clients about an upcoming product feature increasing ROI by x% based on industry, size, location etc.

This requires flexibility for sellers, given they can decide which variables and insights would best resonate with their local market, audience and the culture of that audience.

A template can still be provided by the global operational content center of excellence, given some slides in the presentation will be client agnostic (for example: how to implement the product feature).

“Sometimes I’ll start a sentence, and I don’t even know where it’s going. I just hope I find it along the way.” — Michael Scott (2009), world’s best boss at Dunder Mifflin Paper Company

While it’s just fun to start a chapter quoting The Office, it’s a surprisingly good analogy to introduce the need for data quality in order to make AI work. The ability of generative AI to finish or answer a sentence, will highly depend on the data you provide it along the way.

This is in general true for all artificial intelligence models. If you start typing a query on Google the ‘auto complete’ of your question suggested by the search engine will highly depend on a mix of signals related to you as a person both based on historical and present data.

This is the reason we get the live score of a soccer game when we search for ‘England vs France’ and not the history of the Hundred Year’s War when the game is on.

With the rise of artificial intelligence in revenue generating processes, companies will need to make significant efforts to increase the quality of the data they have available if they want to use AI in a meaningful and relevant way.

Having the right data will give companies a unique competitive advantage and should (at least in my humble opinion) be the number one priority of your company if you want to leverage AI in the long run.

The short-term pitfall to avoid (which is currently omnipresent) is jumping on the bandwagon of ChatGPT building processes that over time will become a commodity. Real innovation is not writing an email with ChatGPT, it’s creating content and insights based on your own data, tone of voice, strategy etc.

To avoid adopting artificial intelligence like a headless chicken, one should think about how they can combine this increasingly public available technology in combination with unique internal information. This is the true definition of prompt engineering and will require an engineer (and not a self-proclaimed guru on Twitter).

To make this work in the future, you need a plan allowing for specificity.

Simply using artificial intelligence without customization, will create dull generic output which will flood the business world. Only companies that understand specificity will be able to really capitalize on the trend.

Whether you are generating content or trying to get insights for your strategies, the quality of the output will highly depend on the prompt. That prompt should be extremely specific based upon variables (or data) you have available.

Similar to results on Google, only an abundance of contextual signals will allow you to create relevant output for your internal teams and customers.

To do so successfully, you should have three core assets:

• Multiple sources of data (see lead scoring)
• High data hygiene and quality (see reporting)
• The ability to customize/automate timely prompts

Data and its quality was extensively covered before, but this last asset needs further explanation.

Comparable to creating content, using parameters in order to make it relevant for your reader, there is value in using the same principles when creating output using AI. This will allow you to alternate the ‘input’ provided to the model in order to create the output.

I can see a future where companies have a set of static parameters related to their company (for example: tone of voice, brand, etc) in combination with customer data from their CRM that will be combined to create content or strategies.

Every time a result is generated it will be based on a slightly different prompt to make it more relevant for the audience using it (which I assume will be true prompt engineering).

Example: Generative AI ideal prompt engineering in sales and marketing

You run a company selling high end apparel. You just launched a new line of female white sneaker footwear and want to use AI to generate a picture for your upcoming newsletter given you only have product shots but not yet any with a real person wearing them.

Based upon this ‘data’ you can create a visual using a prompt “A lady wearing white sneakers”.

It’s not too bad but it’s quite dull. What would be possible if we had more data available?

Now imagine we add static information about our brand. Our products are known for being bold, playful but yet sophisticated. We also know all creative on the website is normally realistic and pictorial. We can add this to the prompt:

Prompt: “A lady wearing white sneakers, bold fashion photography, bold color-blocking, hyper realistic rendering, color-blocking, playful yet sophisticated, pictorial — ar 35:47”

This is some form of customization which is unique to your brand, which will make your result stand out compared to other brands on the market.

But what if we go one step further and create a prompt based on data in our CRM coming from our sellers or product?

Here is where magic starts to happen.

Imagine we have two customers in our database, one of the customers clearly has a favor for bold colors. The last products she bought on our website were a green dress and sunglasses. Another person is more simplistic in style, buying non-popping colors. We also know the ethnicity of both people.

With this information we can make way more targeted prompts and subsequently resonating visuals:

Based on the smart usage of qualitative data in combination with automation, you will be able to generate a unique newsletter based on your specific audience. The same magic can be used in order to come up with insights or create better customer experience.

Revenue Operations today is definitely not tied to in-depth usage of (generative) artificial intelligence, but AI will definitely impact how we work and it’s inevitably going to be a part of the revenue operations role itself.

Just like you, I am limited when it comes to predicting the future. Nevertheless, you can predict based on the observations above a couple of fields where RevOps will play a crucial role in the adoption of AI.

Revenue Operations will be a decision maker in the use cases of AI and will collaborate with others to provide prioritization of all the use cases proposed for different teams, including sales, marketing and customer service.

These use cases can be both internal and external (as the example above).

A couple of use cases you should start thinking off:

• AI to do effective forecasting
• AI to analyze and improve quality assurance
• AI to provide better tailored customer service
• AI to create customized scaled content for sales
• AI to analyze large data sets and come up with hypothesis or insights for
  • Productivity gains
  • Cost reduction opportunities
  • Revenue generating opportunities

All of these use cases can be a standalone chapter (and one day I might write them all).

The point, for now, is that AI will go further than writing some simple email. It will be embedded in all we do and its success for you will depend on your preparation today.

Finally, your Revenue Operations Manager will be unmissable in the integration of your current revenue generating tech stack and AI software. Different systems need to be able to talk to each other.

If we look at the example above, generating pictures for our newsletter, it’s clear you need a tremendous amount of integrations to make this automated.

Your eCommerce platform needs to send purchase data to your CRM. Your CRM should send data in a template to generate a prompt for your AI:

“A {{ethnicity}} lady with a {{previous purchased products}} wearing {{new product}} in the style of {{your fashion style}} photography, bold color-blocking, hyper realistic rendering, color-blocking, {{brand image}}”

The output of this prompt should be returned to your email marketing platform, being inserted in the newsletter together with the customer data and off we go.

This can sound overwhelming complex, but in reality it is again feasible using a data lake, APIs and willingness.

This is what true prompt engineering will be: integration tech stack to facilitate the best performing input for AI and return output systematically.

Your Revenue Operations Manager today should start breaking down barriers in order to enable systems to communicate – preventing blockers for when the day comes AI is not a nice to have, but a necessity to survive.

Before you head to the conclusion of this article, you can find answers on frequently asked questions related to Revenue Operations.

Depending on the maturity of your business and Revenue Operations organization you might feel overwhelmed with the information provided. The key to success is knowing what’s missing to get there – as this will create revenue generating opportunities.

If there is a key summary you want your organization to understand it’s:

1. Your understanding of future value and resource allocation is data-driven

Lead scoring, load balancing and lead routing is essential in deciding which opportunities have the greatest value and where to allocate resources to decrease cost while increasing revenue.

2. Your team should focus on insights instead of reporting

Identifying what works well and what can be improved requires time allocation to finding insights in data. Don’t accumulate data for the sake of it. Educate teams to create hypotheses and turn data into insights to identify your next area of revenue growth and investment savings.

3. Your desire to automate depends on value and risk based prioritization

Automation is crucial for doing business at scale. When making decisions about automation keep in mind efficiency gains, output value and the risk of the automation. Your revenue operations team can help prioritize and ensure cross-functional alignment of processes.

4. Your service starts and end with cross-departmental data

Setting up a service feedback loop involves more than CSAT. Through the right data flows, you will get additional signals around strategic growth opportunities and you will be able to package solutions with the goal to drive more profit.

5. Your marketing and sales need to bury the hatchet

Willingness to collaborate and well designed APIs will allow your sales and marketing teams to work in a unified process. Enable for new measurement solutions to prevent legacy friction, facilitate communication between departments and set up the right incentivization to motivate both teams.

6. Your content will lose in the future without customization

The value of customization is ~40% in terms of revenue. With increased access to content generating tools, the right scaled customization is key to prevent the disappearance of your team’s ability to engage with new and existing clients.

7. Your ability to leverage (generative) AI depends on data and integrations

Artificial Intelligence will become a commodity over time, taking away your differentiator. The right foundations in terms of data and integrations need to be created to leverage (generative) AI to generate value at scale.

Hiring the right Revenue Operations team will help you to:

• Increase revenue at scale
• Decrease cost at scale

Decide which of the 7 strategies defined in this article is the most urgent for your business and get working. Starting today is always better than tomorrow.

P.s. if it’s content customization at scale – SlideFill can help.

Keep in mind these strategies are no side projects, they require extensive cross-functional stakeholder manager, time, planning, strategic thinking and execution. It’s certain this investment will return itself over time.

Thank you for reading.

Let us know what you think in the comments!

This article does not contain any promotional or paid placements.
Views are personal and not affiliated to employers.
No generative AI was used to write the article.
All examples are illustrative and fictional.