Learn / Blog / Article
Data-driven vs. data-informed decision-making: which should your product team use?
Data is a crucial part of building a product your customers love. But just how much should you rely on data, and how do you ensure it works in the best interests of your team—and end-users?
You may have heard the term ‘data-driven’ to describe teams guided by data. But being data-driven doesn’t always lead you down the path that’s best for your customers—or business.
Many customer-centric teams (like ours!) prefer to take a data-informed approach to making decisions and building products, allowing you to zoom out and focus on the needs of the customer from multiple angles to create a better user experience.
Read on to learn what it means to be data-informed, how it’s different from being data-driven (and why that matters), and our top tips for pivoting to a data-informed approach that puts your customers first.
What's the difference between data-driven and data-informed? Data-driven decision-making is based solely on data, while data-informed decision-making uses data among other inputs.
Powerful ways to become more data-informed include investing in data infrastructure, democratizing data access, and combining data with context
How Hotjar used data-informed decision-making to go from seven core products to four
What’s the difference between being data-driven and data-informed (and why does it matter)?
The difference between being data-driven and data-informed is a subtle but important one:
Data-driven means making decisions based solely on data
Data-informed means using data as one of several inputs, alongside factors like your company’s objectives and key results (OKRs) and employee expertise, in decision-making
“There’s often the misconception that the two are the same and many people incorrectly use them interchangeably,” says Andrei Beno, Director of Product at Hotjar.
So which is better? In a customer-centric culture, teams should strive to be data-informed, not data-driven. Here’s why.
1. The types of data you have matter
For many, the term ‘data’ implies quantitative data (i.e. numbers). But customer-focused teams know that qualitative data (i.e. non-numerical data that captures how users experience and feel about your site or product) is equally as important.
Being data-driven often means focusing on hard numbers at the expense of other types of insights, but being data-informed means knowing that it isn’t a case of qualitative vs quantitative data—it’s both, working together to create the best product for your customers.
💡 Pro tip: data ≠ just numbers. Customer-centric product teams need to combine quantitative, numerical data with qualitative data analysis to reveal real user behavior—and needs.
Some of our favorite ways to get deeper insights, stay close to the voice of your customer, and make data-informed product decisions include
Heatmaps: visual aggregates that show you where users clicked, tapped, scrolled, and moved on a web page
Recordings: video-like playbacks that let you watch real people navigate your site, revealing moments of user frustration or delight
User interviews: in-depth research sessions with a diverse pool of global participants who meet your ideal customer profile (ICP)
All of these tools give you valuable quantitative and qualitative data that helps you understand—and empathize with—your users, so you can create better experiences for them.
Use heatmaps to see the most and least popular elements on your web pages
2. You’re only as strong as the quality of your data
More data isn’t always better. You can have all the data in the world—but if it’s not accurate or doesn’t address the right questions, it’s not going to help you make the types of decisions you need to get meaningful results.
Being data-informed means you understand which data is the most important, and that you prioritize quality data to underpin your business decisions.
People may assume that having lots of data automatically leads to better decisions, but data quality and relevance are crucial.
3. Human judgment and context are—and always will be—essential
A key principle of being data-informed is that data should inform decisions, not dictate them. This is where things like alignment with strategic goals—and your company values—come into play.
For example, your raw data could indicate that a group of users really want a specific new feature, but when you look into the user behavior behind it, you might realize that
This feature doesn’t align with company goals or the overall roadmap for your product
These users aren’t part of your ideal customer profile so it doesn’t make strategic sense to prioritize a feature for this audience above others
Customers could get the results they want from an existing feature if they had better training and content to help with product adoption
This additional context is crucial for product prioritization, ensuring your development resources are spent most efficiently for your team, business, and customers. In this case, the knowledge, context, and expertise your team brings to the table are all just as crucial as your hard data.
4. Data has limitations
As Andrei reminds us:
By definition, data can only tell us what has happened or is happening right now. It can’t predict the future and it’s not great at predicting large shifts in trends.
For example, think about BlackBerry. “If we were in 2007–2008 and were looking at the data in terms of consumer trends regarding mobile phones, we would have concluded that BlackBerry devices and physical keyboards were the future of mobile,” Andrei says.
Spoiler alert: they weren’t. Innovative touchscreen devices quickly took over. The large blind spot in data is what consumers actually wanted—which data alone wouldn’t have predicted. This kind of innovation can only come from going beyond the data and understanding your customers so deeply that you know what they want before they do.
6 ways to use data for more impactful, customer-centric decision-making
So how can teams take a data-informed approach? Here are six powerful ways to maximize your data’s impact.
1. Invest in data infrastructure and empower everyone to use it
One of the biggest challenges of a data-informed approach is data quality and availability —that is, ensuring your data is accurate, up to date, and accessible.
Investing in the necessary tools and processes to effectively collect, store, and analyze data pays dividends. Having this infrastructure in place means you can rely on your data and use it confidently.
But this isn’t just about using the right technology: you also need to democratize access to your data and promote data literacy throughout your company. To do this, you should
Give everyone access to data so they can easily find relevant insights
Provide training or resources to help people interpret it
Encourage people to use self-serve analyses to answer their questions themselves using data
💡 Pro tip: give every team access to crucial user behavior data and bring insights into their daily workflow using integrations.
Use Hotjar to send high-value data—like recordings from your target audience or feedback responses from frustrated users—to a dedicated channel in your team’s central workspace (like Slack or Microsoft Teams), so it’s even easier for everyone to make data-informed decisions.
Forward selected data to your team’s shared workspace to bring key insights into their everyday workflow
2. Combine data with context
“Striking the right balance between data-driven decisions and the expertise and intuition of employees is hard, but it’s where the magic happens and how the best product teams stay ahead,” says Andrei.
This doesn’t mean giving in to biases. But to remain innovative, teams need to be able to rely on data and follow their conviction. Encourage employees to consider data alongside their domain expertise and the broader context of the business, by asking questions like
Do product managers or team members have personal experiences they can share from a similar project?
What learnings from previous product launches should be taken into consideration?
What game-changing industry trends (like AI) do teams need to be aware of when building their roadmap?
How Hotjar used data-informed decision-making to reduce its number of core products
When deciding to go from seven core products to four, the Hotjar team considered a number of different inputs to ensure they had all the context they needed. Andrei shares the factors that led to their (data-informed) decision.
Usage data and customer value: we noticed that some features had a low adoption rate and usage level, signaling they didn’t provide our users with enough value
Strategic direction: we wanted to shift our focus from being a one-size-fits-all product to having a smaller set of features but investing more into building them out and making them truly valuable for our users
Team capacity: to execute on that new strategic direction, we needed to prioritize our team resources to avoid spreading ourselves too thin and diluting our focus
Competitor landscape: Hotjar doesn’t operate in a vacuum. We wanted to make sure our product offering remained competitive in light of a growing ecosystem of industry peers.
📖 Learn more about these changes here.
3. Use segmentation and personalization
Once you have your data, make the most of it. Use segmentation to understand your audience more effectively, then leverage these insights to create personalized experiences and marketing campaigns.
For example, a B2C ecommerce company could analyze customer purchase history to recommend products tailored to individual preferences.
Or a B2B software company that discovers buyers who use a certain feature are stickier (i.e. less likely to churn) could create more tailored onboarding journeys and help content to increase adoption.
By using your data in targeted, strategic ways, you uncover more opportunities to connect with your customers and build long-term relationships.
🔥 If you’re using Hotjar: use filters to get even more granular insights.
Filter recordings or feedback responses by specific user attributes such as role or geographic location to understand how different cohorts behave and feel.
Then combine Hotjar with your customer relationship management tool (like HubSpot) to trigger more personalized marketing flows based on this data—and boost conversions.
Integrate Hotjar with HubSpot to create a personalized product experience for your users
4. Implement A/B testing
A/B testing (also known as split testing) is a research method used to test two versions of a page to see which one performs better. It’s an easy way to put your hypotheses into action and validate them with real users before rolling out major changes.
Use A/B testing to make data-informed decisions about web pages, new features, products, or designs. Then, analyze user behavior and conversion rates from your tests to optimize your strategies even further.
💡 Pro tip: A/B tests show you which version wins, but they can’t tell you why. Combine your A/B testing software of choice—like AB Tasty, Unbounce, Omniconvert, or Optimizely—with Hotjar to watch session recordings from both variants and identify which elements users liked (or disliked).
Watch recordings to discover how users behave on each variant in your A/B test
5. Encourage cross-functional collaboration
Different teams engage with your customers at different points in their journey, meaning they all have unique insights. But those insights are no good if they’re siloed.
Instead, encourage customer-facing departments like marketing, sales, and customer support to share their unique findings. This leads to a more holistic view of your customers and their needs throughout the entire journey, instead of just focusing on one small step.
💡 Pro tip: get everyone on the same page—or should we say screen?—by hosting a Hotjar Watch Party. These are cross-functional sessions where stakeholders from different teams watch a selection of recordings together on a specific topic (like ‘user frustrations’ or ‘checkout journeys’). They’re a great way to foster alignment, empathize with your customers, get new perspectives, and collectively prioritize improvements.
6. Create a feedback loop for continuous improvement
Being data-informed is an ongoing process. As you make these data-informed decisions, you generate new data points about what works and what doesn’t.
Take time to evaluate your decisions based on the outcomes and adjust your approach accordingly. This empowers you to continuously refine your strategy based on data-driven insights and feedback, and course-correct when needed as new data or learnings surface.
💡 Pro tip: use Hotjar Surveys and Feedback to understand where to improve.
Capture feedback about changes you’ve made by sending surveys to targeted groups of users. Use concept testing surveys to get feedback on different designs, choose from our library of survey templates, or let AI quickly whip up a survey based on your specific goals.
Want to create an open line of communication with your users and gather always-on feedback as users browse your site? Use a Feedback widget to let people leave comments or emoji ratings to get in-the-moment insights about their experience.
Let Hotjar AI for Surveys auto-generate questions tailored to your goals to get actionable feedback for continuous improvement
Adopt a data-informed approach to make better business decisions and improve the customer experience
Being data-informed—not data-driven—enables you to make more customer-focused decisions and stay innovative.
The good news is you don’t need to be a data scientist to start taking a data-informed approach. By considering your data alongside other key factors, like your company strategy, metrics, and your team’s unique strengths, you ensure you always make the best choices for your business and customers—and retain your competitive advantage.
FAQs about being data-driven vs. data-informed
5 tips to recruit user research participants that represent the real world
Whether you’re running focus groups for your pricing strategy or conducting usability testing for a new product, user interviews are one of the most effective research methods to get the needle-moving insights you need. But to discover meaningful data that helps you reach your goals, you need to connect with high-quality participants. This article shares five tips to help you optimize your recruiting efforts and find the right people for any type of research study.
How to instantly transcribe user interviews—and swiftly unlock actionable insights
After the thrill of a successful user interview, the chore of transcribing dialogue can feel like the ultimate anticlimax. Putting spoken words in writing takes several precious hours—time better invested in sharing your findings with your team or boss.
But the fact remains: you need a clear and accurate user interview transcript to analyze and report data effectively. Enter automatic transcription. This process instantly transcribes recorded dialogue in real time without human help. It ensures data integrity (and preserves your sanity), enabling you to unlock valuable insights in your research.
An 8-step guide to conducting empathetic (and insightful) customer interviews
Customer interviews uncover your ideal users’ challenges and needs in their own words, providing in-depth customer experience insights that inform product development, new features, and decision-making. But to get the most out of your interviews, you need to approach them with empathy. This article explains how to conduct accessible, inclusive, and—above all—insightful interviews to create a smooth (and enjoyable!) process for you and your participants.