Product Analytics 101
For Sales or Marketing, analytics is part of their day-to-day and critical to their success. For product teams, this needs to be the norm too. Product analytics is no longer an auxiliary part of product management, it’s a necessity.
We live in an age of “more” and today’s product teams are evolving to keep up. A study by New Voice Media
found that after only one negative experience, 51% of customers will never do business with that company again. The sheer amount of options out there have put us all in a tough position.
- More experiences happen within the product
- More products to choose from at the customer’s disposal
- More opportunities for users to have a bad experience and leave for another product
To keep users coming back to your product, businesses need to be hyper-aware of the experiences we provide.
A benefit of living in an age of “more” (or as we’ve referred to it in the past, the Age of the Customer
) is that we have more data. To stay competitive, we need to utilize this data to create experiences that will make your product an irreplaceable part of your user’s daily workflow.
Being data-driven requires a new mindset that puts the customer over the company. Most users interact with your company through your product, making it the first line of defense against churn
It’s up to your entire business
to cultivate an experience that keeps users coming back. This doesn’t mean listening to the largest account’s needs, or your executive’s needs, or even the needs of one team over another. It means breaking down silos, having a standardized understanding of the metrics that correlate to company success, and using data to create a product that is held to the standard your customers expect. Companies that understand this will outpace their competitors exponentially—customer-centric companies are 60% more profitable
than those who aren’t.
What is Product Analytics?
Product Analytics is the collection, and interpretation of usage data within your product and the application of usage data into more effective decision making. Product Analytics is often used to illustrate how users utilize your product features, predict areas of product friction, and improve the product experience.
Product, Engineering, and Development utilize product analytics to better understand who is using their product and how they are using it. Executives and stakeholders can use product analytics
to get real-time insight into how the product is contributing to overall business goals.
Why is Product Analytics Useful?
There are lots of products out there—we all have competitors, no matter what market we sell in. Because of this surplus of solutions, it’s vital that your product meets the needs of your users.
You might be surprised to hear that many companies evolve their product based on internal needs, guesswork, and gut instincts. If you’re not surprised, then this probably sounds all too familiar.
"Market problems should be defined based on multiple sources of data, not just anecdotes from visiting customer offices."
If you’re not using product analytics to make data-driven decisions, you’re never going to create a better product because you will have no idea what “better” means for your users or your business.
While feature delivery is a huge use case of product analytics, there is an often overlooked, yet hugely important, purpose product analytics can play. It provides a way to justify the business impact your product has made.
You can show your direct effect on revenue, expansion, churn, and other growth measures.
Product Analytics vs. Product Metrics
There are distinct differences between product analytics and your product metrics—but they go hand-in-hand.
finds patterns in your usage data so you can understand it and use it to answer business questions.
measure your progress towards achieving your set goals and provide accountability. They’re indicators of success or areas of improvement.
Product metrics vary depending on your goals
. For example, if you’re focused on growing your user base, you’ll track metrics like Monthly Active Users (MAU) and Customer Acquisition Cost (CAC). If you’re focused on retention, you’ll focus on metrics like churn and expansion rates.