Product signals are a powerful tool for understanding the intent of both prospects and customers in your SaaS business.
You and your CS and product teams can apply this vital data to free users and customers with the potential for upselling. In fact, 75% of companies undergoing a product-led growth (PLG) makeover adopt free trial or freemium models to gather this data.
Product analytics tools and the signals they provide are the bread and butter of SaaS businesses, and PLG helps you develop a deeper understanding of this data to make your products more actionable and profitable.
By leveraging user behavior, you can gain a deeper understanding of the customer experience and develop more actionable and profitable product decisions.
Whether you go for a free trial or freemium model, product data and its signals are the foundation of a successful PLG motion.
Product data management gives you insights into customer behavior, preferences, and pain points when appreciated properly. All these juicy details will inform your product development, marketing, and inbound sales strategies.
Wielding product-related data sounds like a lot of work, and it can be. But any process is more easily digestible when you break down its importance and requirements, which is what we’re doing here.
Being data-driven is vital for any SaaS sales business looking to grow and scale.
Let’s start with a couple of examples
Let’s say you log into your product analytics platform to see how your customers behave.
Looking at your product usage stats, you notice that many free trial users cancel their subscriptions before they expire. This poor product metrics rate may indicate a problem with your onboarding process or the value your product provides.
What went wrong?
Let’s start at the beginning of the user journey with your onboarding process. There’s plenty of foundational data to appreciate here to understand a user’s behavior from day one.
Look at which steps a user took during this process and isolate the points where they drop off.
Or, you could ask folks who canceled their subscriptions why they did so through surveys.
Both approaches will yield enough evidence to enhance your onboarding process and improve your free trial to paid conversion rates.
Or, if a high percentage of your customers upgrade to a higher-tier subscription over a short period, you can bet your product provides much value and has plenty of upsell opportunities.
Understanding this data and its actionable insights allows us to create targeted marketing campaigns or sales strategies to capitalize on this opportunity.
How Zoom developed its customer-first approach
Former Webex VP of Engineering Eric Yuan was an invaluable member of his previous company.
As a foundational engineer, Yuan developed Webex’s 10-strong engineering squad to an international 800 team throughout the late 90s.
By 2007, when Cisco acquired Webex for a cool $3.2 billion, Eric switched to the new owner’s VP of Engineering position.
The creative spark that had driven Yuan dimmed, as is often the case with new management. He became disillusioned with the now-defunct product he’d strived to build and its mounting dissatisfaction.
Despite his best efforts, Cisco’s C-suite ignored Yuan’s requests, and he decided to grab about 40 of his best engineers and get out.
Together, the elite startup crew founded Zoom, with a hereditary focus on customer needs and high-touch sales.
The Zoom squad initially discovered that their user demographics consisted of small and medium-sized businesses.
Yuan and co then zoomed in on their customers and did their business intelligence homework.
The scrutinizing team nailed the usage patterns with product analytics software, and their celebrated freemium model earned them enough product data to build The Matrix.
So, here you have a bunch of customer-focused engineers - technical brilliance coupled with actionable empathy. You can bet Zoom’s product people used human needs for their product roadmaps.
Yuan expanded his product over time, pumping out Zoom Rooms, Zoom Phone, and Zoom Video Webinars, upselling throughout the entire customer journey.
Finally, the Zoom crew had the upsell and cross-sell goldmine that earned them billions and placed the communications platform firmly on many companies’ tech stacks.
Zoom’s customer-centric, product-data-obsessed discipline continues today, and Yuan constantly oversees his product’s improvement based on user feedback and needs.
By the end of 2022, Zoom had maximized its customer lifetime value (CLV) to the point it had around 850,000 customers and almost $160M in revenue.
What it means to be genuinely data-driven: user optimization
Now, let’s talk about a topic near and dear to our hearts: user optimization.
You might think, "But wait, isn't it good to cater to everyone's user journey?"
Well, not exactly. When tweaking your product for user interactions and demands, it's important to remember that not all are created equal.
You might have a wide range of users, but you can generally divide them into four broad categories:
- Low-Level Engagers
- Power Users
- Super High LTVs
Let's start with the Churners
Some folks will quickly disappear after a signup. Don’t feel too bad, as churning users were never not potential customers, they’re probable churners.
Churn is unavoidable in meeting your business goals, but certain users simply aren’t a good fit for your product. Instead of spending time and money trying to keep them around, focus on the users who will stick around.
Remember that focusing too strongly on user retention without accommodating your larger business objectives can be one of the greatest money holes in Saas sales.
However, it’s not all doom and gloom with your least committed users.
Churn and its granular user analysis is a superb way to cut out experiences users generally dislike or don’t need and enhance irresistible features that keep users around.
Next up, we have the Low-Level Engagers
Said users might keep their subscriptions going, but they hardly ever log in to your product, let alone work with it.
Low-Level Engagers are not as bad as the Churners, but they're not exactly assets for your product performance. Consider them the Seinfelds of your digital product experience.
Think of that tool hanging in your browser extensions bar that you never use and want to uninstall but are somehow confident you’ll need one day.
Enough with the spoilsports.
Now, let's talk about your Power Users
Power Users are the subscribers who know their stuff. They're the most skilled members of an account, often responsible for onboarding their colleagues.
These champions understand your product's value and deserve your focus and care.
Last but not least, we have the Super High LTVs
Users with unusually profitable LTV are the cream of the crop of your user base and should be the focus of your product strategy.
They’re your potential product leaders and have met most of your customer milestones. Users with unusually high LTV need the most attention from CS, and you can presume their subscriptions are indefinite.
Said high rollers are getting the most value out of your product, and you want to keep them as happy as possible with a borderline obsession with their customer analytics.
It's important to focus on the ones who will stick around and get the most value out of your product. Happy optimizing!
Segmentation is the best user filter
Are you ready to take your product analytics instrumentation to the next level?
Let's talk about the magic of product data and how it can help you segment your users, focusing on the ones with the juiciest lifetime value (LTV).
Think of product data like a secret key that unlocks the gate to your product's inner circle and the secret sauce of successful companies.
It's like a VIP list for your product, where only the best and most valuable customers get in. Not only will this help you keep the bad-fit customers out, but it will also help you refine and perfect your Ideal Customer Profile (ICP).
Best of all, you’ll enjoy optimal conversion rates.
Now, I know what you're thinking. "But wait, if I'm being more selective with my users, won't that lower my signup-to-activation rate?"
This is a valid concern, but hear me out.
Your free-to-paid conversion metric will soar by being more selective and focusing on the users with the highest LTV. It's like trading quantity for quality, letting your entire team work on high-value customers.
But before you wave goodbye to those bad-fit users, find out what tanked their customer loyalty in the first place. They may have valuable feedback that can help you improve your product and attract better-fit customers in the future.
Remember that whatever you feed your chosen tool for product analytics makes it smarter. Every little detail helps piece together a predictive and complete customer journey model.
It’s about removing any blocks and enabling the flow that makes your product scalable.
How product data patterns weave into your business
We all love finding trends in our customer base and identifying product-qualified leads (PQLs). But what should we be looking for?
Ask yourself a few questions about your top active users, based on the entire customer lifecycle, like:
- What are their most common behaviors?
- Which qualities do my leading customers share?
- Which product features are they missing out on?
- Which features appealed to them most throughout onboarding?
Let’s also show your worst types of customers some attention and ask a few churn-related questions, like:
- How do my churning customer journeys differ from my leading ones?
- Were any of the churning customers part of my ICP?
- Which of their goals that may have led to their churn weren't achieved?
- What were the other reasons for their churn?
You can use your product data as a reference for each question. These answers serve as invaluable customer signals.
Focus on product usage
As far as your front-line reps go, we’d argue product usage is the most insightful resource for buying signals.
Workbase was one company that ushered its AEs into product data Valhalla, and they soon became experts at picking out the hottest prompts.
Said AEs knew they had power users kicking around their product; they just needed to get serious about usage metrics to know who to talk to.
They focused on scenarios like:
- Analyzing 1,000 freemium accounts to isolate the 50 worth upselling to.
- Boosting proof of concept conversion by confirming the recently logged-in users that enjoyed the most benefits from their product.
- Securing expansion signals by knowing which feature usage indicates a user has warmed up to the possibility of purchasing a similar product.
You’ll need about $10K (or over) in ACV to enjoy the same actionable perspective Workbase has. Focusing on the fresher enterprise logos might not yield enough usage data to make sense of.
But once you reach that stage, and product signals like Workbase’s examples are guiding you, you’ll be selling and upselling at an incredible rate.
Using Segment or Amplitude to gather that data is a good start, but it’s not enough to nail and act on the most rewarding user behaviors.
How to make the most out of product signals
Sure, product signals are potential revenue gems. But you’ll be dumping these opportunities if you don’t have a proper ordering system.
A PLG CRM is a good starting point.
Breyta integrates with Segment to review your user and customer data across a single source.
Now you’re ready to list your customer segments under signal lists.
Start by setting the conditions needed for each major user or customer type, and we’ll automatically add them once they meet your criteria.
Here are a few examples of our signal lists:
- Product-qualified leads (PQLs): The members of your ICP who have met your engagement milestones.
- Churn risk: Good fit users whose engagement scores have dropped worryingly low.
- Upsell: Any account on this list is a superb customer fit, and their user engagement is close to 100%, meaning CS should open up a conversation.
- Cross-selling: Notify your most profitable users about any new product release.
- Land and expand: Identify and track your product champions silently asking for a full company onboarding.
You can zoom in on any account in these lists and review their recent activity and appreciate the average time users take to convert. You’ll also have access to any notes other teammates left, and the VIPs like champions and decision-makers.
Enjoy full-circle tracking and never miss any analytics events again.
Use Breyta as a real-time customer health tool, with product data as the symptoms.
The resource SaaS companies simply can’t sell without
Product data is your competitive advantage, secret weapon, and conversion analysis crystal ball. It lets you understand exactly what your users and customers need and how to deliver value to your PQLs.
The product-led growth era and its high-tech product managers depend on product signals, tracking, and acting on customer behavior, needs, and problems.
Become a fan of detailed reports, meaningful insights, and catering to custom audiences.
Just don’t get too cold and mechanical with your digital product and its usage. Remember to have customer interviews and craft personalized experiences based on your valuable insights.
You’ll be amazed at how useful a good old-fashioned conversation is, and said exchanges can always be recorded and uploaded to your product analytics solutions.
To summarize, you can weave product data into patterns to segment your customers, and Breyta lets you list and monitor your most valuable and at-risk users.
You can also develop your product according to your wins and identify areas for improvement based on what works for customers, and what doesn’t, for maximum product retention.