Product Metrics

Key Product Metrics that every Product Manager should be aware of


  • What are KPIs and metrics (the nuances)
  • Choosing the right metrics
  • Driving business decisions using these metrics

There is no one way to go about being a Product Manager. Some have UX background, economics, business grad, etc. They all have their own strengths and niche based on their role and the company and industry they work in.

  • Ideate: What you are building and why you are building it.
  • Prioritization: Knowing how important a product or a feature is important for your customer and business stakeholders.
  • Persuasion: Communication is the biggest skills
  • Execution: Get the ball rolling.

Biggest goldmine: DATA (use it to make decisions)

Measure: Metric or KPI?

Measure is basically a measurement; think of it in like numbers or pounds.

how many times do I breath?: this is a measure.

Number of breaths per minute : metric (is more quantitative)

Measurable of a value that demonstrates how effectively the company reaches its objective

KPI: # breaths this minute vs # breaths I took in the last minute and doing a cause analysis on that.

Who cares about this? Who would love to know more about the metrics and KPIs insights?

One word: Stakeholders. Keeping them in the loop is v important.

Business stakeholders care about: Revenue, gross margin

Sales team: Funnels and churn

You focus on what YOU control.

As a PM you will be solving the problem for your customers and how you measure it; the metrics would be;

A) Are you solving that problem?

B) Are your customers satisfied with it?

Framework 1: OKRs

Objectives and key results

O: what needs to be achieved ; set of metrics: KPIs: more qualitative or strategic; focus more on action oriented steps that company can take

Key result: they measure the how and numeric quantitative data behind it.; should be succinct , measurable, susceptor

Frameworks: SMART

Goals and objectives are SMART; cuz they are not metrics.

Specific: What particular pain point is this addressing?

Measurable: Do you have a basis on which you can measure it?

Attainable: Is it viable?

Relevant: Does it go with the company objective?

Time based: You cant have goals which have infinite timeline. You should have a timeline when you are expecting the product to be done based on prioritization.

Lets talk about Data for a bit.

With Big Data comes big responsibility.

How does one avoid falling into the analysis paralysis of data?

One word, 10 letters: Frameworks.

PIRATE metric and heart metric

Pirate Metric: AARRR

Acquisition, Activation, Retention, Revenue, Referral.

Lets take the example of tinder.

How did you get into tinder? Search google? LinkedIn? Social media?

Measure this: how many downloaded, from where, who dropped off, why?

Activation: After registering, we want them to feel happy.

Main goal: TO find a partner;

First thing you do is text: activation metric is text

Measure that metric: Suggest to send first message, how many take first step?

Retention: How do you make sure people share?

Make it super easy and keep using it; how many have subscribed? How many clicking through push notifications? Month later, week later how many come back? Stickiness measure? How many using 5 days a week? 10 days a week?

Revenue: How do we monetize it? Freemium model: Hiding age, swiping left by mistake: Average revenue per user; ARPPU: Average revenue per paying user.

ARPU= lifetime revenue of your application/ no. of users you have.

ARPU Helps you see where you are and where you want it be.

Referral: Word of mouth; Virality; Net promoter school. Marketer and campaigners are crucial here.

Framework: HEART; (developed by google)

Measure happiness of metrics

Goal: Making customers happier;

See how your customer feel abut it.

Adoption: When you adopt some features, are using downloading it? What are key issues? Are customers using them? Because of you gotta scroll down enough?

Task success: users ability to use this to find what customers feel.

Metrics summary:

Quantify what you’ve learned so far

Have right level of depth to figure out best solution.

Think about this:

Are you using your data to support what you want to do?
Or what you’re doing, is that supported by the data you have?

Sounds like the same thing but its not.

How to tackle this?

Does my action change depending on the data? if not, continue iterating and improving on what you have.

But if your data actually changes the actions you going to take, go through another analysis. Is it going to cost a lot of money? Is it easy to rollback or reverse?

Is it a one way door or a two way door?

1 way: once you made decision, you cant come back.

2 way: allows you the flexibility to make those changes, view what the results are, analyze if they align with where you want it to be, and if that's not the case, you should be able to rollback and reiterate. and implement new solutions.

The scientific way of going about Product Metrics:

Setting the goals
Setting the metrics
Measuring the metrics

Although, you do need to keep in mind some points.

Are you measuring the right things?

Sure, data is crucial but you should not focus too much on just our KPIs or metrics unless you know what matters and why.

The metrics you are focusing on should tie directly to the company’s objectives, either for the product, company or you.

Metrics should be simple and measurable and they should hope to solve the customer problem.

Lastly, these are the common metrics which PM uses to measure the metrics.

General Product Metrics:

  1. NPS
  2. Revenue
  3. Action
  4. MRR (monthly recurring revenue)
  5. Churn (Customers who didn't like and stopped using your product)
  6. Cost per acquisition (Lower the better)
  7. Referrals: How viral is your product?
  8. Lifetime Value (Value of a customer over the lifetime using your product)

There's so much more to discuss in the domain of product metrics. Countless frameworks, Objective fulfillment, etc.

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