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Showcasing the positive effect of Enablement on Customer Success

Article audience: Education data analysts and reporting specialists

 

In the previous blog post, I shared the results of the recent SAP CX Enablement Study, where we aimed to establish the Effect of Enablement on Customer Success Metrics.

The main takeaways of the study are that investment in training helps to:

  • Reduce Time-to-go-Live of the implementation project (by 1 month).
  • Maximize Software Adoption. Companies that invest in training activate on average 9-10% more business rules and features and gain more value out of the implemented software.
  • Improve Customer Satisfaction. Customers that invest in training are in general happier with a purchased solution and the overall relationship with SAP.

In this article, I will explain how we approached the SAP CX study from a methodology perspective and how we arrived at these results.

 

“Customer First” philosophy and LACE model

Within SAP, we preach and practice the “Customer First” Philosophy. It means that customer interests always come first, before SAP or a Line of Business. It is reflected in the LACE operating model (Land – Adopt – Consume – Expand). LACE entails that all organizations: Sales, Services, Education, etc. should work in unison to support customers along all steps of the customer journey. This is done to achieve one ultimate goal – customer success.

In order to evaluate how our education offerings impact customer success along various stages of the customer journey, we picked metrics that reflected SAP performance along 3 phases of the LACE model: Adopt – Consume – Expand. See the image below.

  1. Stands for consumption-based compensation. See definition below
  2. See definition below

First phase of the LACE model is the Land phase – where initial contact with a customer is established. We left it out of the scope of our study on purpose, as we were primarily interested in the impact of training on Customer Success starting from the implementation phase.  

Second phase is Adoption. It encompasses such activities, as implementation & launch of the project as well as initial adoption of the software. Therefore, we picked metrics that reflected success of these activities:

For Implementation & Launch – Time-to-go-Live;

For Software adoption – cbc% – consumption based compensation – a metric that shows utilization of configured features & business rules indicating productive use of the solution.

The Consume phase includes a large number of customer engagement activities: e.g. support, customer feedback and references. For this reason, we picked a general metric that allowed us to evaluate the overall status of the relationship between a customer and SAP during that phase – Customer Success Sentiment. Input for this metric is normally provided by Customer Engagement Executives based on their overall experience with a customer account. The status is reflected as green, yellow and red. For the purpose of the study we quantified this metric: green status – 3 points, yellow – 2, red – 1.

In the next iteration of the study, we plan to assess the effect of enablement on a number of support tickets. This could be another extremely valuable insight to evaluate customer success.

And last, but not least, we evaluated success of the Expand phase based on software contract renewals and upsell. These are financial indicators that are more relevant for the vendor itself. However, they also evidently indicate the level of customer satisfaction with an offered solution.

 

How to assess Effect of Enablement on Customer Success

To evaluate the effect of Education & Enablement on the metrics described above, we established which customers participated in training and used free enablement offered by SAP CX.

To assess the effect, we split customers in 2 groups: those that participated in training and those that did not. Then, we compared averages of Customer Success metrics for these groups. We used t-tests to ensure statistical significance of the results. For nominal data, for instance renewal and upsell, we used Chi-Square tests.

These tests allowed us to conclude that differences in means between trained / not trained groups did not occur due to chance alone.

Additionally, we assessed participation of partners in training when they were in charge of implementation projects. We used similar methodology to evaluate the effect of partner enablement on customer success metrics, such as time-to-go-live, software adoption by the customer, customer success sentiment, etc.

 

Possible limitations of the study and how to avoid them

Of course, the tricky part of such research projects is isolating other factors, when making conclusions on causality.

Thus, in one of the previous studies, where we attempted to establish a correlation between enablement and customer success metrics, we found that relative investment into training strongly correlated with the size of the company. Indeed, larger companies might have more funds available to spend on training activities. For this reason, we additionally assessed differences between trained and not trained project teams within different customer segments: from larger customer accounts to smaller ones.

The methodology for this part of the analysis is exactly the same as described above: we repeated the same steps of the analysis as we did before, only splitting customers into customer segments beforehand. This allowed us to see if there are any differences in results for different types of customers and to strengthen the reliability of our findings. Regardless of the size of the company, we were able to establish similar results in terms of the effect of training on customer success metrics.

 

Bottom line

Enablement is an incredibly powerful tool for the success of an implementation project and software adoption. Numbers published in our SAP CX study strongly support this fact.

With the tips described above, I hope you can design such a study and show the value of enablement to your own ecosystem to help them get the best possible ROI in software. Best of luck!

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