Product analytics is every Product Marketing Manager’s secret weapon.
The data gathered helps you understand which parts of your product users are engaging with, and leads to informed decisions that drive growth.
In this article, we’ll cover a few ways you can use product analytics to:
- Activate more users during primary onboarding
- Improve product adoption and engagement
- Drive more upsells
- And promote new product and feature launches
What is product analytics?
Product analytics refers to data about who your users are and how they interact with your product.
You can collect two types of product data:
- User identification data — data collected from the users directly
- Product usage and user behavior — data collected using tools that incorporate analytics
- Account logins
- Web pages visited
- Feature usage
- User sentiment
You can then put these two data sets together to derive insights that benefit both your product and marketing teams.
Benefits of product analytics for Product Marketing
The role of Product Marketing is to position the product in order to drive product adoption and retention.
No product marketer could achieve the above without data. Product analytics data is essential in understanding your user needs and adjusting your communication and actions accordingly.
But not just any data.
There are quite a few marketing analytics tools out there and with the abundance of data you collect, it’s easy to get lost and track everything due to FOMO. If you can collect it, you must use it, right?
The true benefits of product analytics come when you start looking at what matters to your users. That’s what creates value for users and makes them stick around.
More precisely, reflect on what creates value for them QUICKLY and how your product can make their life easier.
By “life,” I mean job-to-be-done since every user has at least one task they need your product to perform. Otherwise, they wouldn’t use it.
By understanding what makes users stick, product marketers can achieve higher activation, engagement, and retention — and ultimately close the gap between what users are getting from the product and what they could be getting.
You start by analyzing data at each touchpoint in the customer journey then use those insights to guide your actions.
Now onto the specifics about how exactly you can achieve that.
How to use product analytics to activate more users
Identify activation points for each use case
In a user journey, “activation points” are the key steps that a user must go through in order to experience the value of the product. Since the number of active users is an important marketing KPI for a SaaS company, it’s important to understand what the activation points are for each type of user persona.
Product usage data and product research help product marketers identify the activation points in the user journey.
It’s all about repeated patterns. First, segment users based on their use case. Then look at the ones that convert compared to the ones that didn’t, and identify patterns in their journey.
Which features did they interact with? Which did they have problems with? It’s all in the data — you just need to look at it and segment it.
Even when you’re just starting out, you’ll probably have some educated guesses about what those activation points are.
Using data will help you validate them and, more importantly, will help you identify different activation points depending on each use case your product caters to.
Find the shortest path to activation and replicate
Once you’ve identified your activation touchpoints, you’ll need to guide your user to take the necessary steps to complete each one.
But it shouldn’t stop there.
As a product marketer armed with analytics data, looking into what works is a continuous process. To activate more users, you need to guide users towards the shortest path that will give them value.
Does a user have to invite a team member as part of the activation process? Depending on your product and use case, that might be a secondary feature you should highlight only after the user has reached the activation point.
Choose the right channel at the right time
Is the user logged into the app? Should you send them an email explaining the benefits of your product, or should you prompt a pop-up once he clicks on a feature inside the product?
You should only communicate with the user outside the app for general announcements, or to bring them back into the app.
This is why product analytics is important. It lets you track user behavior and tell you the right time to send a message, what that message should be, and where to send it (in-app vs external).
What if the user hasn’t completed all the steps in the activation process and not logged in to the app for several days? In this case, you should reach out using external channels, like email, and give them the reasons they need to take action.
You can have the greatest in-app onboarding experience ready to go, but it won’t help improve your activation rate if users drop off in the middle of it and you aren’t reaching out to bring them back.
How to use product analytics to promote feature usage
Know which features are important to whom
Product data will help product marketing managers to identify two or more features that users leverage together in order to be successful with your product.
A Business Intelligence tool such as ClicData will help you identify these features. BI tools work by amassing huge amounts of data from all your business tools and databases both internal and external systems and then rendering any insights from that data as visualizations that are easy to interpret.
Once you know which features are most beneficial to your users, identify users who are only using one and not the other, and position the missing feature as important to their use case.
In doing so, you increase the chances of your users getting value from your product and will reduce churn.
Proactively direct users’ attention towards relevant features
As mentioned above, continually directing users towards what’s relevant for their use case will help you improve feature adoption and engagement.
Kommunicate, a tool that helps companies combine chatbots with human customer support, looked at their product analytics, and discovered a problem. 60-70% of their users were engaging with only 3-4 major features of their product and never made it to the adoption phase in the user journey.
Using product analytics, they identified which touchpoints in the user journey they needed to optimize through secondary onboarding, and A/B tested different in-app messaging and experiences to help users get more value by adopting additional features.
A/B test to determine which tactic drives the best results
There’s no one-size-fits-all when it comes to marketing tactics aimed at driving feature adoption and engagement.
Product analytics help you determine which features are underutilized and by which user segment. Once identified, in-app experiments will help you drive engagement.
Instead of making assumptions, A/B test different product experiences and let data show you which product iteration has the highest impact on adoption and engagement goals.
Most in-app product experience tools let you run A/B tests automatically. Start by setting a specific goal that you can track and measure. Then you’re ready to test.
Examples of in-app experiences for feature adoption you can test:
- Add a hotspot to highlight a specific feature and test if it helps increase engagement.
- Users are having trouble figuring out how to use a feature? Add a series of tooltips to guide them through the steps.
How to use product analytics to push for upsells
Determine the right moment to ask for upgrades
Timing is everything when it comes to asking the user to upgrade their account. The best way to do this is by triggering an in-app pop-up when the user reaches a milestone where they might benefit from an upgrade.
You should track feature usage using product analytics and ask for upgrades when it makes sense for your users.
Look at how Mailchimp does it. Once you’ve reached your Audience limit, you automatically can’t send any more emails, and an “Upgrade now” pop-up shows:
Position upgrades as increased value, not just an upgrade
Your mission is to help users get the best results using your product. Is there a better way to use your product? Let them know and drive upsells in a way that brings value not only for your company but also for the user.
Product analytics help you identify users that could benefit from a specific feature they are not currently using.
Hubspot nails this.
They highlight the benefit of a PRO feature right when you are experiencing the pain an upgrade can solve. Using a modal, they let the user know there’s a better way to write emails instead of copy-pasting.
How to use product analytics to promote new product launches
Gather qualitative and quantitative feedback from a soft launch
The success of a new product launch is not equal to how many users your launch announcement reached. Your goal as a product marketer is to make sure users adopt the product and find value in using it.
One way to improve your product launches is to release the update to a small segment of your users first, and collect qualitative and quantitative data to drive your main launch.
Track how users interact with the new product and its features, see where they stumble and need help, and use those insights to improve the experience when the launch is made available to everyone.
Quantitative data will tell you how many people engage with your product and which features are relevant for their use case, while qualitative data tells you why.
NPS surveys are a great way to collect both qualitative and quantitative data.
A standard NPS survey asks users a simple question: On a scale of 0 to 10 ”How likely are you to recommend [product] to a friend?”.
The net promoter score gathers user sentiment, but you can go one step further and ask a follow-up question: ”Why did you choose this score?”. Here’s where you’re actually collecting insights on what exactly your product does that makes users stick or not.
Direct new feature launch communication to specific segments
Launching a new feature?
Not all new features are relevant to all users. Product analytics is vital in order to understand which users will benefit most from a new feature and which will not.
Before sending an email campaign and setting up in-app pop-ups to announce the shiny new feature, take a moment and analyze your data. Will this feature add more value to the users and improve their workflow, or is it just another feature that they need to learn how to use in order to get the same result as before?
Leverage data and direct new feature announcements to a specific group of users who would benefit most from that feature.
Plus: your ”What’s new” pop-up doesn’t have to say the same thing to everyone.
The benefit of using data to segment users is that you can tailor your message to highlight specific benefits the feature brings to each segment, which will ultimately drive an increased adoption rate of your newly released feature.
To not get lost in data and leverage only what matters for your product marketing efforts, it’s important to first understand what you are trying to achieve.
Product analytics tools will help you identify what’s stopping you from achieving those goals and where you should focus your attention.
Each tool out there has its own analytics you can track and act upon. But if you need a 360° view of all your data, you can try using a tool like ClicData and connect all your data sources in one dashboard, making it easier to drive decisions based on product insights rather than guesses.
Sign up for a free ClicData 15 days free trial and start acting on product analytics insights right away!