Product analytics for a changing media and entertainment landscape
Why media & entertainment needs product analytics
It’s no secret that COVID-19 has upended how the world works, forcing many industries to transform and become increasingly focused on digital-first experiences. However, it’s difficult to argue against the claim that the media and entertainment industry has adapted the most. Consumption of online content has more than doubled over the last year, and adoption of digital entertainment has continued accelerating across all age groups. We’ve also seen a drastic increase in the number of online services made available to consumers, with HBO Max, Disney+, and NBC’s Peacock all being launched during COVID lockdowns and many highly anticipated movies getting released straight to streaming platforms. And to top it all off, we’ve witnessed user-generated content platforms like TikTok, Houseparty, and Clubhouse become global phenomenons.
Though many argue that COVID didn’t disrupt media and entertainment but only hastened it’s digital transformation through necessity, one thing is undeniable — consumers will continue (and prefer) digital content consumption once the world recovers from the pandemic. This only makes a stronger case for media and entertainment companies to deliver better experiences to their users with better digital products, especially as consumers will face an unending barrage of options to choose from.
The only way for media and entertainment businesses to grow their user base, retain users, and increase brand and product loyalty in this new digital era is to leverage data to inform their product and content strategy.
“Media & entertainment products occupy an incredibly competitive landscape. The quality bar is really high, and our users are demanding and don’t have a lot of brand loyalty. But it’s also where creativity and data come together to make magical experiences!”
Chief Product Officer, KidsKnowBest
Using data in the world of media and entertainment
So, how can media and entertainment companies turn data into products that their end-users love? To start, they need to capture essential product data to understand how their products get used, and then analyse this data to inform their product and content strategy. That’s where product analytics comes in.
“Product analytics is a must for today’s digital world,” says Filip Nedelkovski, Digital Marketing Manager at Alite International, a digital innovation and strategy agency. “It helps us capture all the essential data from customers across all our platforms and assess the performance of the digital experiences we build. Product analytics provide us with critical information needed to optimise performance, diagnose problems, and correlate customer activity with long-term value. By using Mixpanel, we have been able to increase the conversions, retention rates and decrease the churn rate for our customers.”
“Media & entertainment products need product analytics to understand both the preferences of the audience and their behaviour, to adapt their content production strategy, use different channels effectively or improve any proprietary channel.”
SVP of Product, Orfium
But, capturing the right data is only the first step. To convert this data into actionable insights you need to know which metrics to track and which questions to ask of your data. We asked our media and entertainment customers how they’re doing it, and this is what we heard:
Activation metrics track when a user gets activated (i.e., set up for success) in your product. Usually this means being able to realise value, like watching a video or creating a playlist for the first time, which can be a precursor to user engagement and long-term retention.
Activation metrics are usually tracked with questions like:
- How many users read 2+ articles in their first session?
- How many users share their uploads on a social platform within the first week?
- How many users watch 5 videos in their first 15 days?
Analysing conversion can help you understand performance of key funnels, both inside and outside the product, and how that performance varies across user segments. Tracking user conversion allows you to answer questions about user acquisition, completion of key in-product actions, subscription upgrades and much more, so you can be more effective at making the most of your resources.
Conversion analysis can help you answer questions like:
- Do users actively engage with a video before they subscribe to a channel?
- What percentage of signed up users upgrade after creating a song playlist?
- Did users that got served an ad while watching a video eventually make a purchase?
Product engagement is a measure of how your users are interacting with your product. Analysing engagement helps you identify trends in product usage and content consumption, so you can see what features are used the most and what your users are most likely to consume. This helps optimise not just content, but also product strategy (like which features to dedicate more time to), so you can deliver more of what your users want, and understand how usage varies across different user segments.
“I work with kids apps, and the way kids use features never ceases to amaze me. They can be shockingly quick to dismiss or discard an activity that doesn’t immediately appeal; in other words, they are brutally honest! But if they find a connection, kids can also obsess over a feature for incredibly long periods of time. So dwell time and interactions data is a real treasure trove.”
Chief Product Officer, KidsKnowBest
Sample data questions:
- How many unique videos do users watch every day?
- How many games does an average player complete in a week?
- How often is the playlist feature used every day, and how does that vary by user segment?
Retention measures how many of your users find enough value in your product to come back and use it again. Retention analytics helps you understand how long your users stick around and which users are most likely to return to use your product or a specific feature. As consumer choices increase, retention becomes increasingly important for effective product growth, especially because acquiring new users is much more expensive than retaining existing ones.
- How many users return to view a video in the first 30 days post sign-up?
- How many players complete a game level every week?
- What percent of video watchers create playlists on a weekly basis, and how does that vary by app version?
Turning metrics into actionable insights
No one metric is enough though. The most successful digital products are made by teams that look at many different metrics, break them down for each user segment, and combine the insights to identify underlying patterns in end-user behaviour that they can act upon. Digital-first media and entertainment products are no exception.
“The key metrics we track are around addressable consumption hours and monthly active users — these are what drive our profits. These are lagging metrics however,” says Katie Phillips, a Sr. Product Manager for Content Discovery & BritBox Optimisation at ITV. “So we need to look for signals within the data to act as warning indicators for improvement. To help us understand the journeys that users take, we’ll look at metrics such as where that consumption is coming from (i.e., did the user find the content from a content rail or from search, the number of video views per user, what content was being viewed, conversion to view and plays per user). Being able to follow the user’s journey is imperative to our decision making and helps us to further understand what improvements we can make for our users.”
Creating a clear framework for your analytics strategy can help ensure all metrics work in concert while also keeping all teams focused on moving the metrics that truly matter.
Advancing your product analytics maturity
Although identifying and measuring the right metrics is a critical step in data-driven product development, creating or sustaining a digital transformation involves so much more. As you grow your product and user base, you’ll begin to ask even deeper questions of your data that then influence product development, and the depth of the questions you answer is highly tied to your overarching data and product analytics strategy. Simply put, the more advanced your product analytics maturity, the stronger your ability to understand user behaviour and improve user experiences.
What’s more? As your product analytics gets more mature, so does your tech stack. This means you can connect your product data with A/B testing tools, attribution tools, messaging tools, and so much more, thus enabling a data-driven approach to everything from experimentation to messaging and engagement.
Ultimately, the user insights that enable you to build better products—and the degree to which you can improve user experiences across the entire user journey—are tied to your product analytics maturity. Whether you’re already measuring advanced product metrics or just getting started with a product analytics tool, you should aim to iterate on your product analytics strategy the same way you do on your product.