Adoption and Indicators

By Russell Bourne

In today’s blog, I’d like to explore a bond between a couple of subjects I’ve noticed come up a lot lately in Customer Success communities: Adoption metrics, and Leading and Lagging Indicators.

Adoption

In many CSM organizations, Adoption is the most passive stage of the customer journey. It usually comes directly after onboarding, and often represents a time when customers are pushed out of the nest to use a product with minimal supervision. How do we know they followed through on all the great things we taught them, and to what degree? These are big questions considering the next journey stage is usually renewal.

Fortunately, there are solid clues all around, if you know where to look.

Before we go on, it’ll help to clarify terminology:

Consumption is a measurement of how much of a product is used. For example, you may be using 9GB of Google account storage. Often, vendors use consumption as the basis for billing.

Usage shows where a product is consumed. From the Google storage example, of the 9GB, 5GB is from Photos, 3GB is Drive, and 1GB is Gmail. Usage begins to show you what value a customer derives from a product.

Adoption is a state of being in which the customer has undergone change management and now uses a product as it was intended, as an ingrained habit or procedure. Keeping the same example scenario, you have high Google adoption if you migrate your files from your hard drive to Google Drive, and you create and edit content online in Drive instead of offline in Office.

As you can see, Adoption isn’t inherently measurable in the way Consumption and Usage are. Instead, you can use a number of leading indicators to predict that a customer has Adopted well, and a number of lagging indicators to prove it after the fact.

Lagging Indicators

I recently engaged with a SaaS vendor who had an unacceptably high rate of customer churn. It was a classic post-purchase scenario: executive management invested in a SaaS tool that would help their employees work more efficiently, but the end-users wanted nothing to do with it. Some end-users refused to use the product, while others logged in to “check the boxes” and then went about their work “the old way”.

This is where relying too heavily on lagging indicators can give you a false positive. If a CSM at this vendor ran a report showing license consumption, they might see that most seats were installed. If they ran a report showing end-user usage, they’d see logins and data inputs. The CSM might conclude good Adoption - and might initiate a renewal opportunity with the completely wrong playbook!

Leading Indicators

An executive with the vendor told me he was considering a CSM initiative that would boost the number of data inputs from the end-users. The problem was, that would only result in more false positives. I asked him why he thought the end-users weren’t simply using the product as intended. What was holding them back?

To my surprise, he already knew the answer: lack of onboarding. He had a technical team running implementation, but there was no training. No one from his company trained the customer end-users, nor did they even train a customer department head who could then train their end-users. There was no online training platform that would show each end-user’s progress. The training wouldn’t have only been on the interface; it could have been a true change-management exercise that showed these end-users the personal benefits to them if they could use this software to help them exceed their goals.

The executive had a leading indicator hidden in plain sight: the yes-or-no question of whether certain onboarding steps were taken. The vendor can create a short checklist of the onboarding steps they feel are important. The checklist can live in field form in their CRM or CSM platform, and can be filled out by the CSM or possibly even by the customer. Consensus is always great to have. Then, a CSM can run a report showing which customers had thorough onboarding.

Putting it all Together

Now, back to the lagging indicators. If a customer’s leading indicators show poor onboarding, but their lagging indicators show strong consumption, that’s a sign the lagging indicators may be unreliable. But, if the leading indicators show full change management took place, you’re in a better position to trust the lagging stats.

If the above sounds similar to compiling a Customer Health Score, it is. Overall Customer Health Scores take all the Adoption factors into account, plus non-Adoption factors like relationships, payments, geography, and so on. Is it overkill to create an Adoption score on top of already having a Health Score? Probably - for some products, Adoption isn’t an important part of a customer being healthy and renewing. Sometimes, one executive user is all that matters, even if none of the other end-users adopt!

However, if you’ve isolated Adoption as an area needing improvement, it may help to think about what leading indicators factor into good Adoption and whether they’re worth measuring.

The Success League is a customer success consulting firm that offers customer success evaluations that are a great way to see what is working well and what needs improvement. For more information on our consulting services and training classes, please see TheSuccessLeague.io

Russell Bourne - is a Customer Success Leader, Coach, Writer, and Consultant. In a Customer Success career spanning well over a decade, his human-first approaches to leadership and program management have consistently delivered overachievement on expansion sales and revenue goals, alongside much friendship and laughter. Russell serves on the Board of Gain Grow Retain as co-lead for Content Creation. He is passionate about equipping individual contributors and business leaders alike to lean on their Success practices to grow their careers and help their companies thrive. He holds a BA from UCLA, and in his free time plays guitar semi-professionally.

Scoring Health and Risk

By Kristen Hayer

Last week Jeremy Gillespie wrote about the Top 10 Health Metrics Customer Success Should Be Measuring, and I thought I’d jump in with some practical advice on how to turn those into a health score. Whether you’re thinking about ways to make your manual health score more quantitative, or building a health algorithm for your CS platform, you need to take a methodical, data-driven approach. Here’s the process we go through when we’re working on developing health scores with our clients.

List Your Hypotheses

Every company has ideas about why customers are healthy and why they churn. Your job is to separate fact from fiction, but before you can do that you need to understand the thinking that is out there. Meet with the leaders of customer-facing teams like sales, marketing and support, as well as your own CSMs and collect a list of all of theories people have on churn and health. As crazy as some of them might sound (“Calling our customers too often is making them churn.”) it is worth testing as many as you can and debunking any myths that might be floating around. Be sure to go beyond product usage and consider the items on Jeremy’s list as well as demographics (like industry or location) that may make specific groups of customers inherently riskier.

Test Your Theories

Go down the list of hypotheses and design tests to see if those items do in fact make customers healthier or riskier. A starting point is to look at the data you have on the customers you consider the healthiest and the customers that have churned over the past year. From those data sets, you can see if there are trends that support the theories you came up with. For example, to explore whether more calls to customers do drive churn up, you might measure the number of calls that each churned customer received and compare that to the number of calls to customers who stuck around. Note: Early stage companies often won’t have enough data for these tests to be statistically valid. You’re looking for solid trends, not perfection at this stage. Keep testing, and make changes as needed over time.

Determine Thresholds

Once you’ve figured out your key indicators of health or risk, think about them on a spectrum. For each measure that will be a part of your health score, you’ll need a point at which a customer is considered healthy, and a point at which they are considered at risk. Anything in the middle is shown on most models as yellow – OK, but not great. This is where you can go back to the tests you performed in the last step. Let’s say you found that customers who use your solution less than once a week are more likely to churn. That’s your risk threshold. Then you need to consider the healthy side of the spectrum. How often do your healthiest customers use your solution? Once you determine that, you’ll be able to set the health threshold. If you have a large customer base, keep in mind that you may find that different customer segments have different thresholds.
 

Test Your Algorithm

When you have all of your indicators and thresholds established, you have a health algorithm. Now you need to test it. This is definitely easier if you have a CS platform or CRM you can use to track a customer’s health score at any given point in time. However, you can get scrappy if you have to and manually review a customer’s score at the point of churn, expansion or renewal. On the churn side of things, you shouldn’t see any healthy (green) customers churning. Likewise, you shouldn’t see too many risky (red) customers expanding or renewing. If you do, something is off with your algorithm. Dig in on those accounts to see what happened, and make adjustments to your algorithm as needed. Ideally you should test over the course of a quarter, two quarters if your volume of customers is low or your business is highly seasonal.

Visualize Your Base

Once you have dialed in your health score, you can start to really see how the initiatives you’re tackling as a customer success team are playing out in terms of health. If you snapshot your entire customer base each month, you can really see the movement of customers. Most popular CS platforms include reports you can use to visualize the health and risk of your entire customer base, but even if you don’t have one of those tools, you can use a spreadsheet to accomplish the same thing. As you review these snapshots over time you should be able to see the impact that your efforts are having on your base. This can be a powerful demonstration of the value customer success is bringing to the organization. 

 As you go through the process of determining your health score, keep in mind that this should be unique to your organization and that it will shift over time. Developing a data-driven score takes a lot of effort, but is worth the investment. Accurate measures of health and risk are an excellent resource for your leadership team, and a great way to showcase your team’s work.

Need extra help developing a customer health score? The Success League is a customer success consulting firm that offers Leadership Coaching. For more information on our consulting services as well as our training classes and other engagements please visit our website at TheSuccessLeague.io

Kristen Hayer - Kristen believes that customer success is the key to driving revenue, client retention and exceptional customer experiences. Her areas of expertise include developing success goals and metrics, designing the optimal customer journey, selecting technology, training teams, and building playbooks. Prior to founding The Success League, Kristen built and led several award-winning customer success teams. Over the past 20 years she has been a success, sales, and marketing executive, primarily working with growth-stage tech companies. Kristen has her BA from Seattle Pacific University and her MBA from the University of Washington.