When technology buyers only had on-premise technology as an option, I would estimate that more than 50% of all technology purchases were shelfware, i.e., they bought it, they owned it, but it was never implemented, or if it was, it was never used. As one circa-1995 CEO told me, “They don’t like the software? Too bad, their check has cleared.” This sort of executive thinking trickled down. Development focused on bells and whistles that demoed well but didn’t solve real business problems. Buyers selected products based on which vendor could check the most boxes on a 50-page RFP…mostly features they would never use.
Moving from on-premise to technology subscriptions has had a more dramatic effect on how technology is developed, sold, and implemented than early cloud vendors ever anticipated. Some legacy vendors continue to struggle with the cultural change required to build technology focused on ease of use and delivering quantifiable business outcomes as quickly as possible. Product adoption has become table stakes. If customers don’t adopt, they don’t receive business value/ROI. If they don’t receive business value, they don’t renew the subscription. If they don’t renew, you will be out of business.
As critical as adoption is, unfortunately, many technology companies have very little insight into how their customers are consuming products. One TSIA survey of B2B firms found that only 30% of companies had data on which product features were being used by specific accounts, and only 14% knew which features were being used by particular users within an account.
While adoption may be table stakes, the sad truth is many companies are flying blind. This blog will discuss key adoption metrics technology providers should track, common challenges to overcome, and examples of how to leverage the adoption information you do have access to.
Why Adoption Data Matters: Quick Finds
Adoption data is critical for measuring the health of the account and developing the correct strategy for each account to boost renewal and expand selling efforts. Three of the most important reasons for having accurate and detailed adoption metrics are:
- Primary Charter. 84% of customer success organizations say their charter is customer adoption. Without detailed adoption data, you have no idea if customers are consuming the technology. And even more importantly, CS teams must act on the data, with defined outreach strategies in place to boost adoption when the data shows consumption is slower than anticipated.
- Customer Value. 85% of B2B technology buyers say that product usage data or utilization reports are the most valuable information in determining whether to renew. If you can’t provide data for each account demonstrating the level of consumption, you lower your chances of renewing the subscription.
- Inform & Drive. Of the companies that do collect adoption data, 85% say they use the information for strategic product planning and roadmap decision making. What are the features and process flows that are used the most, and can we create more? What do customers rarely use, and can we stop building those?
Challenges to Collecting Actionable Adoption Information: Quick Finds
There are often challenges to accessing accurate, detailed adoption data. Some challenges are technical, and some more political. The top challenges I’ve seen working with TSIA member companies include:
- Access to data. You may assume that with all adoption data stored on the servers owned by a cloud vendor, access would be straightforward, that isn’t always the case. In some organizations, you must negotiate with an operations group to get access to the information, requests can be backlogged, and ultimately the data may not be delivered in a useable format.
- Interpret clickstreams. Clickstream information, i.e., the raw data showing how users navigate through applications and what features and fields are used, may not have been stored in a way conducive to easily mining actionable insights. Analyzing millions of clicks to identify user flows, feature use, and abandoned processes is not a trivial task.
- Associate clickstreams. Once user flows are parsed, associating them to contacts and accounts, and making this data identifiable through CRM, requires another layer of integration and processing that may be on the roadmap for years before becoming reality.
Four Key Feature Adoption Metrics: Quick Finds
Though different companies and departments have various names for the adoption data they use, at a high level, success and product teams should be able to understand adoption patterns from these four perspectives:
- Breadth. How widely are features adopted by user segment? This helps build profiles of users for use in onboarding, and to gauge adoption by segment or title.
- Depth. How often do user segments touch the feature? While some features may be critical and used frequently, others may only be touched periodically. Depth of feature adoption may be because certain options are only used during month-end processes, or it could indicate a usability issue.
- Time. How long does it take for users to start using features? If some options are only ‘discovered’ after weeks or months, it could be that the feature is difficult to navigate to, not intuitive, or should be better highlighted in training and onboarding.
- Duration. How long do users continue to use a feature after trying it? This metric helps identify “must have” features to emphasize during onboarding, as well as options that users may not find valuable. For the later, the product team should be evaluating these features for redesign or even retirement.
Customer Success Adoption Frameworks: Quick Finds
Once you have access to customer clickstreams and can analyze the data to identify adoption by account and contact, you are still only part of the way there. Ideally, you should establish adoption frameworks so you can gauge if a particular customer is consuming technology at the expected rate, allowing you to identify adoption laggards, requiring additional coaching or onboarding, or adoption pacesetters, who may be good targets for case studies or reference programs.
Unfortunately, only 33%, of technology companies have an active and documented adoption framework that can be repeatedly used to assess how well specific customers are adopting technology. By analyzing adoption patterns for various customers over time, you should be able to identify:
- Adoption Curves by company size, industry, or other demographics. This information, noting where an account profile should be at one month, three months, six months, etc., is helpful to identifying slow adopters and can be factored into account health scores.
- Adoption Patterns by role or use case. This information will help you develop very tailored onboarding by role within the customer organization, focusing on the features or capabilities most used by other customers in similar use cases.
- Unique Patterns for customers with rapid outcome realization, high renewals and expand selling, or other business metrics. Alternatively, understanding adoption patterns common to customers who churn can also be used to identify at-risk accounts.
Adoption and Product-Led Growth
Product-led growth (PLG) is a go-to-market strategy that relies on the product as the primary vehicle for customer acquisition, conversion, retention, and expansion. Technology companies emphasizing product-led growth are much more responsive to the input of customers than in years past, when product marketing and sales drove product roadmaps based on competitive analysis and snazzy demos that didn’t necessarily equate to business value.
Product management teams in a PLG environment rely on adoption data, and the metrics listed above, to understand which users are leveraging what features, the most popular features, and those that are seldom used. This information helps them build a product roadmap that reflects the needs of customers and the features they need to be successful. There is ongoing ideation with customers to identify what is missing in the product and prioritization of these new capabilities on the roadmap. Granular adoption data can also help to understand which features customers say they need, and are widely adopting, which may indicate these features need to be easier to find or use within the platform, or should be emphasized more during customer onboarding.
Ideally, product management should be closely collaborating with customer success and the customer education group to create onboarding programs and content that best represents the intent of the technology capabilities, how these capabilities map to specific business challenges, and to constantly evolve onboarding as new features are introduced in each release.
Planned Spending for Adoption Monitoring Technology on The Rise
There are an increasing number of options available for tools to monitor, mine, and report on product adoption. Companies may build their own using an analytics platform or look to a specialist in digital adoption. Data from TSIA’s 2020 Technology Stack showing adoption and planned spending for adoption monitoring technology.
With multiple groups across the enterprise seeing product adoption as part of their charter, hopefully, there will be collaboration on identifying a platform that will fit the needs of all groups, and not create siloed implementations of multiple tools.
Final Recommendations
As we have seen, few companies have a truly robust adoption data program, and there are multiple barriers preventing easy access and analysis of the data. Here are four final recommendations to boost the success of your adoption metrics program:
- Inventory the adoption data available to you today. There may be data available to product management or development that the customer success group is not aware of. Be sure you know everything available today, where it is stored, and what format it is stored in.
- Understand the level of adoption information customers require to make renewal decisions. With 85% of companies saying adoption data is the single biggest driver for their renewal decisions, be sure you are talking with customers, and surveying them, to understand what data they expect.
- Create a roadmap for the additional information or level of detail you need. It is unlikely that you have 100% of the data and insights you would like today. Start by creating a prioritized list of additional information to help the product and development teams understand how to approach changes in the collection and analysis of clickstream data to provide what you need.
- Identify a cross-functional team to create a realistic timeframe to deliver on that roadmap. With adoption data critical to show value to customers, improve renewal rates, and build the case for expand selling, having a team involving product management, product marketing, professional services, customer education, and development, can help to build not only a complete vision for an adoption metrics program but will also help build consensus on the importance of the project.
Contact us to learn more about how we can help you supercharge your adoption metrics.