Measuring product adoption by users is critical for SaaS and Cloud companies as this is the most telling indicator of the value customers are getting from products and services. And when it comes to preventing churn and driving growth, it is necessary for companies to know which customers and users are using their products, how they are using them and to what extent.
In order to create this visibility, cloud and SaaS product teams need to instrument their applications (web, mobile, saas) to report on product usage. By “instrumenting a product,” I refer to the technical process of creating an event log of user activities, so this log can be analyzed to answer the usage questions mentioned above.
The technical process of instrumenting a web or mobile application is relatively straight forward. It involves adding a simple instrumentation code into the application that logs the user activity at various integration points. Totango provides such instrumentation technology out of the box for both web and mobile applications.
Once the product usage events are being reported, preferably in real-time, a usage analytics system is reading the instrumentation log and provides KPIs of the various dimensions of product usage and adoption. These KPIs can be used to predict and prevent churn, identify growth opportunities, and provide information to product managers and designers to improve product adoption and value.
Table Of Contents
Product Usage And Customer Success Management
Solutions for Measuring Product Usage And Adoption
Interactive Usage Metrics
| Timestamp | User ID | Account ID | Activity | Module |
| 1/1/19 8:00 | 1000 | ACME | log in | gsuite |
| 1/1/19 8:01 | 2000 | ACME | log in | gsuite |
| 1/1/19 8:05 | 1000 | ACME | new doc | slides |
| 1/1/19 8:07 | 1000 | ACME | update | slides |
| 1/1/19 8:07 | 2000 | ACME | share doc | sheets |
| 1/1/19 8:08 | 3000 | XYZ | new doc | slides |
A typical usage event record (SDR – Service Details Record) log contains the following information:
- Timestamp
- User ID
- Account ID *
- Activity ID
- Module ID
Please note that this record format applies for both B2B and B2C. In a B2B scenario, it is important to count both individual users and, at the same time, associate those users with their respective accounts. Products that are only designed for B2C use cases will fall short when it comes to mapping usage data into the customer success use cases which will be described below.
With this simple log record we can answer many usage questions:
- DAU, WAU, MAU – How many unique users have used the product (logged-in or other) in a single day (DAU), in a week (WAU), and in a month (MAU). In a B2B use-case, the same metrics at grouped to a single customer account provide insight into the usage pattern of users of the same customer, for instance; how many users of account ACME have used the product in the last day, week, month, and overall.
- Usage Frequency – What is the frequency of use – every day, a few times per week, a few times per month?
- Modules Used – Which modules have been used? What part of the application was used mostly and by inverse which modules have not been used?
- Time Spent – How many user sessions per day, week, month, what is the session duration, and what is overall time spent
As you can see, a service details record (SDR) log provides a very powerful way to present that usage pattern of every user, every customer (collection of users), and how they are using the product.
Usage Counters
In addition to interactive usage counters that track user interactions, it is also highly recommended to track non-interactive counters. I call those ‘inventory’ counters. These counters track resources created on behalf of users and accounts.
For example, in a photo sharing application it is common to track:
- How many photos are being stored
- New photos uploaded per day, week, month
- Overall storage being used
- Additional storage being added every day
Inventory counters measure the ‘investment’ of the user and customer in the system.
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In many cases, those counters can represent the actual value derived from the product and service, as they can measure results. In the CRM example – actual opportunities being closed in a period, the win rate, and the growth rate. Quite powerful, isn’t it?
Activation Metrics
Activation Metrics are used to measure activation or provisioning of capabilities. It is critical to measure activation and provisioning to ensure that capabilities are available for use.
Few common examples:
- In a seat based licensing model we may want to measure how many seats have been provisioned for use
- In a capacity-based licensing model (think dropbox) – how much storage is available for use
- Multi-Module packages products would want to measure which modules have been provisioned for use.
Usage Ratios
As you can see from above, by instrumenting product usage for interactive usage events, inventory counters, and activation flags provide complete visibility into how users and accounts use your products and services and the actual value they get (or not.)
In addition, there are a few common ratios that allow you to normalize and compare (benchmark) usage patterns.
Here are the most common ones
- DAU over MAU (DAU/MAU) – This ratio measures how many of the monthly active users are also daily active users. This measure represents user retention, how sticky is the product for daily/weekly use?
- MAU over Seats – This represents license utilization. Close to 100%, it reflects full adoption and upsell opportunity.
- MAU over Licensed Seats – represents usage against license
- MAU over Provisioned Seats – represents usage against activation
- Activated Seats over Licensed Seats – Represents the actual activation rate
You can generalize those rations into: Actual Use In Period / Capacity Provisioned or Sold
Time Windows and Change
Some products are designed for daily use while others are designed for different usage cycles. For that purpose you’ll need to adjust the time windows – day(s), week, month, quarter, year – to the right usage cycles.
I’d like to point out that, looking at trends and changes in usage metrics is critical to operationalizing. The changes and the trends are also very much telling and can provide guidance for what needs to be done to improve.
Product Usage And Customer Success Management
Creating visibility into how customers are using your product or service is the first step, but ultimately we’d like to use these metrics in day-to-day customer success operations to drive the business outcomes of retention and expansion.
In other words, we’d like to use product adoption(or lack of) to drive appropriate engagement along the customer lifecycle in order to lead towards customer success. If the customer does not use the product adequately, there are things the company can do in order to grow usage and value to customers. On the other hand, a positive usage trend leads to additional business opportunities with the customer.
In that context, product usage and adoption information can be used to determine how the company will engage with the customer and for what outcome.
The wide range of product usage and adoption metrics are crucial as they measure and represent different usage goals along the customer lifecycle. In the context of customer onboarding our goals are to ensure:
- Product Activation – we’ll monitoring product activation metrics
- Initial User Adoption – we’ll monitor using user retention and feature adoption metrics
Later on, in the customer lifecycle, we’d like to drive product adoption:
- Ensure that license utilization is getting close to 100%
- Key modules are being used
- Inventory metrics are trending up
We are also going to use these condition as part of true Customer Health Score, in conjunction with other dimensions of customer information.
Solutions for Measuring Product Usage And Adoption
You have several options to implement the above framework to instrument product usage and adoption, calculate usage KPIs, and operationalize this with Customer Health Score (see What Is Customer Health Score) and customer success operations.
- Custom Build Your Own – Companies can invest heavily in building and maintaining this framework. The collection of data initially seems trivial as it is merely log recording of events. However, maintaining it and streamlining operations may require heavy ongoing effort.
- Piece it Together – Build home-gown integrate solution from log reporting, analytics solution and integrate that into the customer success technology that your company use
Summary
I hope this article helped you organize your thoughts around product usage and adoption for SaaS and cloud products. Feel free to leave me a note at the comment box below with your thoughts.