Instrumentation is the backbone of data-driven product management, and yet it’s still a mystery for many PMs.
Product instrumentation involves adding tracking and analytics tools into your product to measure user interaction and gain valuable insights into overall performance.
Although it’s a technical concept, it’s so impactful on a day-to-day basis that every PM should at least grasp the basics.
In this article, you will learn what instrumentation is, why you should care about it, and how to implement it within your team.
Table of contents
- What is product instrumentation?
- Product instrumentation process
- Benefits of instrumentation for product managers
What is product instrumentation?
Instrumentation is the process of defining data events and setting up tools to collect and process these events. Data events are snippets of information that are sent from your product to your analytics tool of choice, such as Google Analytics or LogRocket.
As an example, let’s see how you would answer the question of how many users visited a specific page of your app. Because LogRocket’s autocapture starts capturing all user actions once it’s installed, it captures navigation events every time a user visits that page. To understand the total number of users who visited that page, you’d simply create a chart of users and add a “visited URL” filter for the page you want to track.
The total number displayed on the chart is the sum of all navigation events collected in a specific time period. These events can be later processed within LogRocket to develop meaningful segmentation, cohort analysis, correlation analysis, etc.
Analytics tools with autocapture capabilities, such as LogRocket, Heap, and the like, enable you to capture every event automatically, so you can answer any analytics question without needing extra instrumentation. However, tools like Google Analytics, Mixpanel, and Amplitude, require you to manually tag every event you want to track — which means range and variety of data you can analyze is limited to what you’ve already thought to track.
Product instrumentation process
The challenge with instrumentation is that only so much can be provided out of the box. Each product is different, with a unique user flow and needs. So while you get the basics out of the door, you’ll get a very limited picture without some custom work.
Now let’s walk through the steps you should take to implement product instrumentation:
- Choose a user type
- Define the journey
- Map events
- Combine events by adding properties
- Add user properties
- Implement events in the code
1. Choose a user type
There’s a chance you have more than one user type on your platform.
For example, you can have:
- Buyers and sellers
- Students and teachers
- Creators and lurkers
Choose your most important user type. We’ll revisit other types later.
2. Define the journey
Here, specificity is the key. Go with as many details as you can. For example, you could define a journey with the following:
- Sees the list of categories
- Clicks on “expand categories”
- Clicks on a specific category
- Visits the list of offers
- Clicks on the “filter by” button
- Applies a specific filter
- Scrolls down the page
- Changes the page
Consider alternative journeys and failure journeys as well.
Learn more →Alternative journeys
There’s probably more than one path a user can take. You can finalize your purchase by browsing the platform, by finding a link in Google, or by receiving a private message from the seller. Capture all of them.
Negative journey
Not every journey results in success. There might be a scenario where, after applying filters, the results page is blank. Capture these situations as well.
3. Map events
Turn the user journeys into a sequential list of events. For example, your buyer’s journey could be defined as the following events:
- Category page visited
- Expand category clicked
- Category flowers clicked
- Offers page visited
- Filters option clicked
- Filter X selected
- Filter Y selected
- Filters applied
- Offers page visited
There are various taxonomies on how to name the events, but there’s no one right way. The most important part is to keep event names consistent and maintain the same structure. Otherwise, it might be hard to figure out what event does what.
4. Combine events by adding properties
Events can come with various properties. Properties are additional, dynamic data points that are transmitted with events. These can help us avoid needless event repetition and overcomplication.
For example, let’s say you mapped all potential user journeys for your subscription products, and at some stage, you might have the following events:
- Purchased subscription X for 1 million
- Purchased subscription Y for 1 million
- Purchased subscription Z for 1 million
- Purchased subscription X for 12 million
- Purchased subscription Y for 12 million
- Purchased subscription Z for 12 million
Keeping six separate events for that would be messy, but with the use of properties, you can combine these events into a single event with a few dynamic properties:
As a result, instead of having six separate events, you have only one with two dynamic properties. Based on these properties, you can later filter and process these events in your analytical tools of choice.
A proper use of properties reduces the number of needed events.
5. Add user properties
You can also attach a user property to an event.
It’s similar to event properties, but instead of asking, “What exactly happened?,” they ask, “Who made the action?”
Define the optimal way to differentiate your users and build user properties around that. For example, you might find it interesting if it’s a new user or returning user, or if it’s an individual or an enterprise individual:
You’ll also notice that many events repeat as you repeat the instrumentation exercise for your other user types.
Then, instead of adding brand new events, you can specify additional user properties to differentiate the users.
6. Implement events in the code
The last step is to actually implement the defined events in the code.
Robust instrumentation is time-consuming. As a PM, you might need to decide what information you need right now and what you can save for the future, as well as how to balance the need to get the right data with the need to deliver new functionalities for the users.
Benefits of instrumentation for product managers
From a high-level perspective, it might seem like instrumentation is a niche and technical aspect of building software. That might be true, but I believe product managers should be interested in the instrumentation process and contribute to it.
A product manager’s input during the process of implementing instrumentation can:
- Improve the quality of data collected
- Gain a deeper understanding of the product
- Source of inspiration
Improve the quality of data collected
It might be tempting to leave all instrumentation to the dev team, but the truth is, developers aren’t the people responsible for the iterability of the next sprint.
It’s your job to understand what type of data you might need to analyze to assess the performance of a given solution and decide on the next steps.
Way too often, the PM wants to get specific information about the feature usage just to learn that the team doesn’t collect that type of data.
That’s an instrumentation failure.
Gain a deeper understanding of the product
There’s no better way to understand the nitty-gritty of the product you are working on than through learning instrumentation.
If the instrumentation was done correctly, you’ll get to know all possible user flows, failure scenarios, and much more.
You’ll also be able to look at data in a more specific and isolated manner, instead of just relying on high-level aggregated dashboards.
Source of inspiration
It’s easier to look for insights if you know what you can see. Sometimes, simply knowing what type of events and data you collect can help you guide your thinking on what to analyze next and where to seek potential correlations.
For example, you might learn that you collect information on which entry point users used to purchase a premium subscription. This might motivate you to segment users based on that to define which entry points perform best and which ones need further improvement.
Summary
Instrumentation is a powerful tool that product managers often neglect.
Although it’s a technical topic, PMs can benefit from understanding instrumentation. It helps them by:
- Ensuring they gather all relevant data
- Helping them understand the product better
- Serving as a source of inspiration when looking for new opportunities
Learning instrumentation improves the way you think as a product manager and is also one of the most efficient ways to improve your data skills.
Featured image source: IconScout
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With LogRocket, you can understand the scope of the issues affecting your product and prioritize the changes that need to be made. LogRocket simplifies workflows by allowing Engineering, Product, UX, and Design teams to work from the same data as you, eliminating any confusion about what needs to be done.
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