Why Time To Value Can Be a Deadly Onboarding Metric

The problem with using any simple measure of time to value, onboarding completion percentage or time to adoption is your onboarding might fail before customers reach the average for any of those metrics.

Stuart Balcombe

February 18, 2022

3 minutes

Most onboarding teams measure their success based on a the average time to value (TTV) of their customers.

Some use onboarding completions.

A handful explore the relationship between onboarding and specific product adoption metrics.

Few however take into account this uncomfortable reality.

Your onboarding might fail before customers reach the average for any of those metrics.

Here’s the problem with using any simple measure of time to value, onboarding completion percentage or time to adoption.

  1. Any individual customer is not the average - The average may be skewed by a few very “successful” or a few very “unsuccessful” onboarding journeys.
  2. The average does not tell you why - The average assumes that all moments and events inside the onboarding journey are both equal in time and equal for all customers.

You could very well be solving the wrong problems and spending your time in the wrong place by looking at the average time to value.

Time to value is like trying to improve your lap time on a racetrack without knowing if you need to go faster in the corners or get a whole new car entirely.

For TTV to be actionable, you need to know how quickly different customers are making progress towards your definition of value.

You can’t wait until months down the line — nor a tenth of that time. In onboarding, momentum is king.

Here’s the secret: Know the actual time it takes customers to complete each step on their journey through onboarding.

Only then can you identify the blockers and strategically intervene at the right moment to improve your metrics.

To do this you need a granular cohort based metric in place of TTV.

Why granular? Because understanding which specific steps in the journey are blocking and how blocking they are relative to others is the best way to prioritize effort.

Why cohort based? Because looking at onboarding performance by cohort allows us to establish a baseline and track our impact on that baseline over time. We can also create cohorts based on different parameters to deepen our understanding.

What cohort based measurement can do for your onboarding

On the surface your new metric might look similar to TTV when looking at the aggregate data. But unlike TTV you can tailor it to explore questions about onboarding performance specific to your business.

A granular cohort metric lets you ask (and answer!) thorny cause-and-effect questions, about your onboarding like:

Based on their team size and the plan a customer purchases, how quickly do we expect them to be activated?

Based on their technical expertise and solution they need to migrate from, which tasks in their onboarding plan should we pay most attention to?

How can we prioritize our team’s time on the highest impact moments in the onboarding journey by reducing our effort at others that are less important?

Next week we’ll breakdown how to calculate this new metric for your own onboarding and your own customers with templates and examples included.

This is the first in a 3-part series on onboarding metrics and optimization.

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