Product Management In 5 minutes (Part 7)

What gets measured gets managed.
— Peter Drucker

What are they!? | Why are they important? | How to choose them. | Real-life instances.

THE METRICS

As product managers, we have goals, which are essential components of product roadmaps and strategy. They serve as a guide for the product allowing us to remain on the target destination lane. But how do we as product managers get to measure the goals, performance of the product, and the success rate of the product strategy?

“Metrics”

These are measures of quantitative assessment that provide insight towards the progress of the product goal, commonly used for comparing and tracking performance or production. It is also referred to as Key Performance Indicators(KPIs). They differ depending on the type of product manager you are or the type of industry you are in.

They are the targets that the development and sales team aim for, and also provide hard facts about the products’ health.

And we have two base types of metrics namely Reporting and Exploratory Metrics.

Reporting metrics are things we track over a long period of time to ensure the product is doing well and is on the right track.

Exploratory metrics (NOT exploratory data analysis) are basically data points that we check just for a little bit of a clue to derive a solution from to potentially build a feature to hit the reporting metric target.

THE METRICS RELOADED

Metrics must be used to facilitate discovery and inform product strategy decisions, capable of changing the direction of the product strategy by extension, the entire organization.

It’s a common truism that if you don’t measure something, you can’t improve it, without data-driven metrics strategy becomes a guessing game, which implies that the industry’s decisions would become speculative.

Therefore, tying the product goals to proper metrics enables us as product managers to make informed decisions.

THE METRICS REVOLUTIONS

Metrics provide real-world data, as well as Frameworks for analyzing the provided data, today’s business world is awash in a sea of data if your metrics are based on data, whereby when we collect too much data we will be drowning in irrelevant information, collect too little and we could miss something crucial. Hence the question, what’s the right data to measure?

The option seems endless right, well don’t fret here are a few guidelines on how to pick good metrics:

• Understandable: your metric needs to be relatively simple when telling people about it.
• Changeable: Ensure to position your metrics in a way that it can be changed with relative ease when need be.
• Rate and ratio based: Metrics should be rated and ratioed rather than being measured percentage-based for instance number of returning customers VS new customers
• Correlation: Avoid taking readings or assumptions from correlated metrics that are erroneous in nature for instance the rate at which people like ice cream and the rate of drowning deaths.

Now, here is a framework that would make the process of choosing your metrics easier.

The HEART Metrics Framework:

This framework is a methodology that helps think through the process of selecting the right metrics for every aspect of the customer/user journey, it is an acronym that stands for Happiness, Engagement, Adoption, Retention, and Task Success. And it is illustrated on a table with a Goals, Signals, and Metrics column on the right section see Image demonstration below.

First, always put the customers/users' Happiness first when deriving your metrics.
Then Engagement always takes note of how engaged your users/customers are in short-term spans.
Next is Adoption, at this point, you measure the rate of interested customers/users who have actually tried out the product.
Retention is basically the rate of returning customers/users over a long period of time, and it is most commonly measured monthly.
Task Success, this concept helps decide how successful we are as product managers at allowing users/customers to perform the most valuable task as regards the product.

Goals Column — are the target of what we want to actually happen.
Signals Column — are what we measure on each phase in order to know if we are getting close to our goal.
Metrics Column — are basically expressions of the goals and signals over time, they are what we would actually monitor.

As the image illustrates the proper lineup of this framework is ATERH because first your users/customers have to first adopt the product, then they perform the most valuable as regards the product, after they show other signs of engagement. Finally, they are either being retained over a long or short period of time, and happiness is at the bottom because it can be gauged at every point of the products’ customers/users' journey

THE METRICS RESURRECTIONS

The more frequently you’re getting accurate feedback, the more effectively you manage the product, this is known as the Feedback loop process, and it's the actual core of agile development, and using the guidelines and HEART framework from the previous section I would give an instance of deriving metrics.

Deriving metrics for a Hosting platform.

Above is a metric board for a hosting platform using the HEART framework.

Conclusion

Note: Metrics come in a wide range of varieties with industry standards and proprietary models often governing their use.

The entire product management role revolves around Metrics/KPIs, and with the proper metrics, PMs can establish what's working and what’s underperforming. And by analyzing certain data they can find creative solutions to then improve the performance of the product.

There are sometimes things that we know we can track on our individual team that makes the overall metric for the company increase which brings about high-level and low-level metrics and how low-level metrics roll up to the high level. This means we as product managers might have to track minute metrics first.

Examples of metrics are Monthly active users, Returning customers, and Reviews.

The HEART Framework was introduced and populated by Kerry Rodden.

Use the HEART framework for reporting, not exploring. It’s not strict and you don’t have to use them all — try to pick one that matters most. You can as well use the signals column to inform engineers of tracking requirements.

There are more frameworks that can be used to draft out an efficient metrics board aside from the HEART framework, we have frameworks like the AARR(Acquisition, Activation, Retention, Referral) Framework by Dave McClure

Retention can sometimes be considered as an engagement metric, depending on the nature of the product.

I expect questions for clarification. In the next part, we would learn about People Interactions as PMs.