Quantitative Adoption Funnels and Growth Loops are for Everyone

I have found that it is the belief of many executives that investing in product analytics and measuring product adoption (including identifying up-sell opportunities, or growth loops) is something exclusive to B2C, consumer, and/or product-led-growth (PLG) businesses only. I would argue the counterpoint that these are for everyone, regardless of business type – and will explain why as the methodology is explained.

The wonderful folks at Reforge have defined a fantastic, simple methodology to quantitatively measure product adoption.

• Signup Moment – The user has signed up or otherwise onboarded into the product and is capable of configuring it to receive the core value proposition.
• Setup Moment – The user has performed the necessary actions to setup the product for the core value proposition.
• Aha Moment – The user has experienced the core value proposition for the first time.
• Habit Moment – The user has established a recurring habit around the core value proposition.

For example, in a business intelligence product, this funnel might look like the following:

1. Signup – The user has signed up through self-serve or has had the customer success/onboarding team create their account.
2. Setup – The user has connected at least one external data source to their account.
3. Aha – The customer has viewed at least one report based upon their own data.
4. Habit – The customer is viewing reports based upon their own data at least twice a week.

A growth loop might be upgrading to the next higher tiered plan, whereupon custom reports are available. The up-sell would occur when viewing reports on a regular basis within the product user experience. In this case, the next user adoption funnel for the growth loop would look like:

1. Signup – The customer sees and clicks on the option to upgrade their plan within the reporting user experience.
2. Setup – The customer has created their first custom report.
3. Aha – The customer has viewed their custom report for the first time.
4. Habit – The customer is viewing custom reports at least twice a week and sharing the data at least once a week.  

This process would continue until the customer is on the highest tiered plan, is deriving value on a recurrent basis, and renews.

In this example, the upgrade occurs within the product experience. But it could just as easily have been an in-product call-to-action to contact sales or customer success. OR, it could have been an alert trigger based upon usage for sales or customer success to contact the customer.

Regardless of one’s business model, utilizing PLG-based principles such as Quantitative Adoption Funnels and Growth Loops truly are for everybody as it can be easily adapted to a sales-led business model. This is how you source and track Product Qualified Leads. And it is a table stake for anyone considering offering a self-serve plan option or for those who are true PLG businesses.

Assuming that your product has product-market fit, making this happen is relatively straightforward, assuming that one’s product is well instrumented (or can be easily made so) with an analytics tool. The process looks like the following:

1. (Highly Recommend Pre-Requisite) Start with your Jobs-to-be-Done (JTBD) implementation, as that will provide a baseline of the customer journey through your product experience based upon the value you are marketing to customers. Hypothesis formed using this insight will likely be far more accurate than those starting from a blank page.
2. Map out your expected customer journeys for each user persona throughout your product experience. If you have multiple levels of user maturity, make sure AfH has its own discrete persona and that there is a unique set of moments for each respectively. Formulate a hypothesis of your Setup, Signup, Aha, and Habit moments for each use case and persona. Formulate a hypothesis of where your growth loops are and where the next Setup-to-Habit journey should begin.
3. Instrument your product’s user experience end-to-end using your analytics platform of choice.
4. Start diving into and analyzing the data. Identify the actual moments versus the hypothetical moments, and validate or adjust the hypothesis. You will end up with a funnel that for each user journey might look something like:
   1. Signup: 95%
   1. Setup: 70%
   1. Aha: 60%
   1. Habit: 48%
5. In an ideal world you will get Signup and Setup at or near 100% and Aha and Habit in the 90%+ range. That will ensure that your customers are receiving recurring value such that they should hopefully renew with 90%+ gross retention, keeping your product within best in SaaS metric range.
6. Where numbers are not meeting the objectives, use the analytics data combined with qualitative customer research to dive into the why, identifying the points of friction and removing them from the product experience until the desired state is achieved.

Note – if your product does not have product market fit, this methodology will not produce valid data. Focus on obtaining product market fit and optimizing JTBD with actual customer research until over the line.

Regardless of one’s business model, utilizing PLG-based principles such as Quantitative Adoption Funnels and Growth Loops truly are for everybody as it can be easily adapted to a sales-led business model. This is how you source and track Product Qualified Leads. And it is a table stake for anyone considering offering a self-serve plan option or for those who are true PLG businesses. Going to this level of rigor and discipline is critical to maximize user adoption and ultimately retention. Besides, with the combination of JTBD and Quantitative Adoption Funnels, you can easily explain to executives or board members that all reasonable actions have been taken – both qualitatively and quantitatively – to optimize the customer’s product journey.