Customer Success Leadership Community

Adoption Data; reducing churn, driving growth

  • 1.  Adoption Data; reducing churn, driving growth

    Posted 23 days ago
    I am writing an article on the importance of capturing and analysing adoption data in the B2B space. It's the leading indicator of customer health. Knowing:

    • if customers are using the products they are paying for
    • how much they are using those products (and functions/ features)
    • how easy they find it to use those products (eg online, integration)

    Is fundamental to being on the front foot and engaging customers in the proactive discussions that improve customer health, reduce churn and lead to upsell opportunities (amongst other benefits). 

    For those happy and able to share, I'm keen to have any market insights or intelligence. 

    • What does good look like? Who is best in class?
    • Quantifiable impact of adoption data on reducing churn and generating upsell
    • Adoption data white-space analysis driving new sales opportunities
    • Other costs/ benefits

    Many thanks – Richard


    #CustomerHealth
    #CustomerSuccess
    #IndustryData&Insights
    #Metrics
    #Outcomes
    #RevenueManagement

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    Richard Jeffreys
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  • 2.  RE: Adoption Data; reducing churn, driving growth

    Posted 23 days ago
    Sounds like a good piece to write, @Richard Jeffreys. Some thoughts:
    • Usage often predicts retention, but that's not always the case. In the old days when voice traffic dominated telecom networks, high usage actually predicted high churn. Remember the T-Mobile commercial "Can you hear me now?" Also, "good" and "best in class" depends on industry and application. Some subscription-based products and services are best not used at all (insurance, disaster recovery services, certain cybersecurity services, etc.). You may want to qualify your research to conditions where usage improves a process, which in turn improves personal and business results.  
    • Quantifying impact is properly done using statistics. In this case, exploratory or factor analysis can be used to screen factors (correlation, contingency tables, ANOVA, etc.) and then regression (multiple or logistic) or classification techniques to determine the sequence, significance and weightings for each of the factors. Customer churn reasons typically simplify into four categories: 1. Unmet expectations for quality and value, 2. Lack of attachment, 3. Ease of switching, and 4. Customer issues (change in needs, M&A, bankruptcy, etc.). This means when studying loyalty, it's best to understand usage in the context of other factors, and again things vary quite a bit. What's the "right" or "best" for one company may be entirely different for another. 
    • Adoption level and "white space" again depends on context. If assumes that the company offers multiple products, which is not always the case. If a simple add-on or upgrade is a possibility, and the CSM is capable of handling the transaction, then a track record of delivered value tends to earn the privilege of consideration. If a complex, global enterprise with multiple independent business units has common needs, then an Account Manager (as opposed to a CSM) may be a better choice. In that case, he/she/they would develop an account sales plan to leverage successes to trigger and pursue opportunities within the account. 
    • When it comes to other costs/benefits, I would recommend exploring the nature of value. It turns out to be a complex subject involving six (not two) different factors. It's subjective, context and role-dependent, and the business benefits we talk about all the time (usage, productivity, ROI, etc.) don't necessarily lead to retention and revenue growth. People make decisions for personal reasons, intuitively, not logically, so these numbers typically only serve to justify decisions that have already been made. 

    I hope that helps. I look forward to reading your article.

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    Ed Powers
    Consultant
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  • 3.  RE: Adoption Data; reducing churn, driving growth

    Posted 22 days ago
    Many thanks @Ed Powers for taking the time to reply. These are all great points. Regarding your point on 'value' this is something I am working on. I feel that adoption data (in its simplest form) is a benchmark or comparison. The base level, in a B2B context, should be a comparison of usage versus what's been sold/ licensed - being paid for. Then, to your point, it needs to be compared against 'value' as defined by/ agreed with the customer (which as you say will often be a combination of factors). Ideally, 'license' and 'value' should be the same - if not then that's a red flag. It's a pretty nuanced area but one that is extremely interesting and being able to obtain and analyse the data is the key to unlocking the science and the potential to reduce churn and generate growth.


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    Richard Jeffreys
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