The Metric that Links Martech to Business Value

We use the verb “feel” in the absence of an equation to prove the value of martech. Martech utilisation taps into the need to get an answer to “Are we getting value from our martech stack? There is a metric that correlates the company revenue-per-employee ratio and martech maturity…

“Are we getting value from our martech stack?” That is the million dollar question many CMOs, and CIOs ask. It’s the right question to ask but not easy to answer.

Marketing departments are getting better at demonstrating campaign ROI and attribution. But what about martech? ROI is well suited for calculating short-term results like campaigns, projects, or implementations. However, martech investments support long-term results like architecture and IT infrastructure. The martech business cases are often ROI calculations based on saving resources and costs, ie. efficiency. Efficiency is a good way, but not the best way to ‘sell’ martech internally.

Efficiency is about

• doing things right
• saving money
• focused on the company

Effectiveness is about 

• doing the right things
• making money
• focused on the customer

Don’t get me wrong, efficiency is great, but effectiveness is better. It is great we are saving resources, but to get the board room’s attention you’ll have to talk about company value. Many company boardrooms feel they do not get value from the martech stack. We use the verb “feel” in the absence of an equation to prove the value of martech. 

Some CIOs and CMOs look at the utilisation of martech, as a kind of proxy for martech value. A recent Gartner report reveals that companies only “utilise” 33% of their martech capabilities. Martech utilisation taps into the need to get an answer to “Are we getting value from our martech stack? However, defining what is ‘good or poor utilisation’ is hard, let alone calculating it.

For instance, is frequent use of a feature good or poor utilisation? 

Is a press release tool underutilised when only used for crisis management once in three years when glass particles are found in baby food? 

Is daily use of an email messaging tool a good thing, if conversion rates drop because of email fatigue by certain audiences?

Just like with ROI, utilisation focuses on the use of software, i.e. efficiency, instead of the value it creates for the company.

How Martech Relates to Company Value

For the past five years, we have investigated the interplay between many data points like vendor and stack size, revenue, headcount, industry, business model, and specific martech components. We found a metric that correlates the company revenue-per-employee ratio and martech maturity. It is only a start, but it is already very promising and insightful.

We have conducted hundreds of data experiments with a team of data scientists, utilising our martech data warehouse. The warehouse contains 14,106 customer technology tools, 1,133 global, real-life, cross-industry customer technology stacks, and 4,538 requirements. It is continuously curated by more than 467 experts across 30 countries.

The Performance-Maturity Equation

The State of Martech 2024 – Scott Brinker & Frans Riemersma., 7th May 2024, page 51

The metric is a correlation between internal and external company performance. 

• Internal company performance is measured by self-reported maturity for the different martech. The maturity model is a Likert scale based on the Capability Maturity Model from Carnegie Mellon University. 
• External company performance is measured by the revenue/employee ratio, sourced from annual reports. 

The correlation between the two indicates how the maturity and revenue/employee ratio change together in a particular pattern. It does not specify why this happens or if one causes the other. Correlation is not causation, as market conditions, industry trends, company acquisitions, or regulatory changes impact both metrics simultaneously. Therefore this metric should be regarded as a directional cue. It is useful to drive thoughtful conversations.

If we focus on outperformers in separate industries we can see what they do and learn what practices they follow. We can see where they invest and where they divest. This does not imply that you should blindly copy and paste their stacks. The outcomes should still be translated into your business context.

Outperformers are the top 30% ranking companies in one industry based on their revenue-per-employee ratio. It is remarkable to see that outperformers tend to suffer much less from cognitive bias concerning their maturity than the low 70% of performers (see The State of Martech 2024, pages 52-54). The Dunning-Kruger effect tells us that the lower 70% probably think they’re better at leveraging martech effectively and efficiently than they actually are. Whereas the top 30% have become more realistic in their ways as they have “learned their lessons’. 

#MartechDay 2024 Keynote, Scott Brinker & Frans Riemersma., 7th May 2024, slide 69

Comparing positive and negative correlations of out- and low performers in a certain industry translates into a simple matrix with four quadrants. One of the immediate insights is that increasing martech maturity does not drive business value positively in all cases. This explains the enormous differences in success cases of specific martech between industries. 

For instance, CRM works well in Consumer Goods; the correlations of out- and low performers are both positive for CRM. However, in Banking and Financial Services CRM out- and low performers have both negative correlations. In the Pharma industry, CRM outperformers show a positive correlation, but low performers do not.

The matrix for Banking and Financial Services stacks positions different martech in one of the four quadrants, each requiring a different approach to drive value.

Quadrant 1 – Both out- and low performers show a positive correlation between maturity and improved revenue/employee ratio. Martech in this quadrant can be called ‘High Flyers’, rolling solutions out and reaping the benefits is a relatively straightforward exercise. 

Quadrant 2 – Outperformers show a positive correlation, low performers do not. If they increase their maturity their revenue/employee ratio decreases. Martech in this quadrant requires some homework before rolling it out, e.g. aligning goals, defining KPIs, use cases and key requirements, and growing skills.

Quadrant 3 – Outperformers show a negative correlation, but low performers do not. If they increase their maturity they improve their revenue/employee ratio. This martech has a positive impact initially, but less so when the company revenue/employee ratio improves.

Quadrant 4 – Both out- and low performers show a negative correlation between maturity and improved revenue/employee ratio. This does not mean you should avoid this martech. Take CRM for instance in this industry. 73% of the outperformers have kept a CRM in place. They use it in a piecemeal fashion on purpose. In this case, CRM is a “Negative Satisfier”. It is required-martech but comes with an over-engineering hazard.

Also Read: The Subscription Model is A Game of Balance

These insights help to have focused conversations about specific martech and find answers not available before. With client projects, we learned it helps to reduce the noise in martech conversations, which is helpful as there is a lot of anecdotal evidence in martech. Without these insights, companies will continue to suffer from the HSW syndrome, the Highest Salary Wins. And that syndrome is a big problem in martech because ”The client is not the user.” The client is the budget holder (C-level) and is normally not the actual user. That is a recipe for disaster, which leads to poor adoption, orphan licenses, shadow IT, etc.