Measurable results for key roles is the foundation of customer-led growth. The focus on people, not just the company drives engagement. Measurement of impact on the metrics that matter for these people provides the rational basis for buying, renewing and expanding use of your product. It is staggering therefore how few companies reliably measure the results customer achieve.

I have long railed against how customer success is measured in B2B SaaS companies. Ask most CS leaders and CEOs how they measure customer success and they will typically reply with metrics like logo churn, gross and net revenue retention and NPS. I understand the importance of these but none are measures of customer success; they are all measures of the company’s success. None measure the improvement customers achieve. The measurement of the basis of successful acquisition and growth is lacking.

I have addressed this previously so in this blog, I want to explore different ways company’s can collect these key data using a maturity model. Remember, this is about collecting data on metrics that matter to each key role, so the data already exist. That said, customers don’t always know what they should be measuring: providing guidance on metrics and how they are collected is an important element of what you provide. It also provides greater control for the supplier, who should be the expert in the domain addressed by the product.

Customer Results Maturity Model

0 - Don’t measure customer result

Companies operating at Level 0 have no measures of how well they are meeting the expectations customer key roles have from their products. This lack of maturity often goes hand-in-hand with a lack of understanding of the metrics customer use in their jobs. Such companies have the greatest risk of unexpected churn.

1 - Internal assessment based on proxies

Level 1, companies collect a range of data points on usage, sentiment and engagement but do not directly track the results customers achieve in the metrics that matter to key roles. Some of these proxies correlate with retention but unexpected churn risk exists as there is no way of relating them with the improved performance expected from using your product. Level 1 companies measure what they can, not what they should.

2 - Customer assessment

Prompted requests ask a customer to rate the improvement they have seen in the metrics that matter to them. Level 2 companies allows suppliers to report perceived improvements but cannot quantify them. These are subjective data and subject to cognitive biases. There is therefore no real data to reliably justify renewal and growth. This approach is also subject to the willingness of customer key roles to complete the questionnaires. If coupled with goal setting, Level 2 helps suppliers to provide better guidance to support each key role to achieve goals that matter to them.

3 - Customer reported data

Level 3 gets customers to self report the actual values of the metrics that matter to them. This real data allows companies to track the performance of key roles and provide contextually rich guidance to improve. It also allows reporting of results and improvements and provides data to support a renewal or expansion business case. This data, subject to customer approval, is also invaluable support for marketing and sales in new customer acquisition. Like Level 2, it is reliant on the each key role providing the data and is subject to data entry errors.

4 - Integrated data feed

Level 4 sees the sources of data used to track key role metrics integrated into your product. This automation of data collection removes the effort, data entry and bias barriers that undermine lower levels of maturity. It also makes it easier to build effective in-product reporting and trigger contextually richer, timelier interventions using a Next Best Value (NBV) approach. Goal-setting is driven by actual performance, which in less mature approaches is more subjective. Automatically captured, actual data also improves the efficacy of measuring results and therefore the reliability of the whole process.

5 - Predictive

Level 5 predicts the results achievable. This is built on four pillars:

• Aggregate, anonymised data of results achieved by other, similar roles to guide goal-setting

• Maturity models that inform the achievement attainable.

• A Level 4 approach to gathering the data.

• Providing proscriptive NBV guidance to use the product effectively and enable ‘beyond product’ changes needed.

Barriers

Barriers to measuring results exist in two areas.

The first set of barriers are internal - what I call legacy mindsets.

Companies think success is all about building features customers request better than the competition. Product matters, really matters, but only if what you build improves the measurable results that matter to the key roles you sell to and serve. And even if a feature does add value, it is of little use if people struggle to make changes in their work that are often needed to exploit the capabilities your product provides. More on that, including an approach to thinking about roadmaps here.

The second is the lack of willingness to put in the hard work needed to build the deep understanding of customers that sets out what metrics matter, even when customers don’t know themselves. Add to this the challenge of developing the means to capture these data effortlessly and reliably and many companies put it in the ‘too difficult, therefore ignore’ bucket. As the saying goes, we have met the enemy - it is us!

Barriers are also presented by customers.

As mentioned above, many don’t know what they should be measuring and need educating on the metrics they should be tracking and how to do it. This should be tested during the sales process as it is a red flag to moving the customer to value quickly. So important is this, it should be a parameter of your ICP. It’s also an area that should be covered by top of funnel content: begin the education process early.

Perhaps the biggest barrier is trust. Trust that you can keep important operational and financial data secure. Trust that you will use the data to the company’s benefit. Trust that you will not share the data without explicit permission. These issues can be overcome. SOC2 and/or ISO27001 compliance are important. Clear explanations about what data is collected, how they are used and how they benefit will help to remove some concerns. Guarantees written into contracts will also help to reinforce your good intent. Carrots may also be needed - for example, making access to some advanced features and enablement subject to agreement to share the data behind measured results.

CLG is all about converting results for customers into revenue for your company. The central importance of measured results for key customer roles to profitably win, satisfy, retain and grow your chosen customers makes your approach to measurement critical. It’s an area where many B2B SaaS have to mature quickly or become part of the CFO’s dreaded ‘nice to have’ product list!