How Data Led Approach Can Help You Drive SaaS Business Growth

A data-led approach in SaaS is the key to unlocking innovative ideas, more revenue, and faster product growth.

In this article, we cover the following:

• What it means to be data-led and why it helps SaaS companies grow fast.
• How to make data-led decisions.
• How to improve user experience by becoming data-led.

TL;DR

• A data-led approach involves using a combination of data, context, research, and human expertise to make business decisions.
• On the other hand, businesses that use a data-driven approach see data as the be-all and end-all of decision-making. A data-led decision can limit growth since data doesn’t always explain the whole picture – it can lack context and be outdated.
• A data-led approach helps you analyze user behavior and build experiences powered by the right data.
• It also saves you money and time since you’re more likely to make decisions that move the needle.
• To start being data-led, collect data from multiple sources. Do feature tagging and run heatmaps, record user sessions, and gather feedback with surveys.
• Go beyond standard analytics reports and choose a tool that customizes and manipulates your data. It’s essential to get a complete picture.
• Prioritize your decisions based on the data. Remember to review the data again after making any changes to see if you should pivot your strategy.
• Personalize the user experience based on data. You can segment customers and send personalized, helpful content.
• Product usage data can help you automate in-app help by telling you what features have been used, but not adopted. Product guidance improves retention and customer success.
• Trigger interactive walkthroughs to help users adopt high-value features.
• Optimize in-app experiences based on data. Find out what users want to see. For example, do they prefer video or written guides? This process of analyzing customer data helps you build a better product.
• Userpilot is a product adoption tool that helps businesses become data-led. You can collect behavioral analytics without the need for a developer and fully customize your data to focus your attention on the highest priorities. Create a better product experience based on your data and customer feedback. Book a demo to learn more!

What does it mean to be data-led?

Data-led businesses collect and analyze data to improve decision-making. They don’t just blindly rely on data – they pair it with context, in-house research, and human expertise to make the most informed decisions.

Data-led vs. data-driven

A data-driven strategy places data at the center of all decisions. When a business needs to make a decision, they look at the data and accept it as the single source of truth for what it should do. They constantly collect and analyze data, often with the help of artificial intelligence and automation. Usually, this means they’re overwhelmed with a mountain of raw data to sift through.

On the other hand, businesses that use a data-led approach are pulled by data. They see it as a vital tool for decision-making, but they don’t let their business metrics decide for them. They combine data with context and human expertise. This helps drive growth because you can better spot emerging trends, meet customer expectations, and recognize innovative ideas.

Why?

Because sometimes data misses out on context or hasn’t caught up to new trends. For example, let’s say you’re deciding which new feature you should launch next. With a data-driven approach, you would look at product usage analytics to see current popular features, and then build something similar or complementary.

With a data-led approach, you would still look at the product usage analytics to gain insights, but you could also survey customers to ask them what they need from your product. Or you could browse conversations online to see what people in your target market are looking for. With this added context, you’ll make product improvements that meet customer needs and drive growth.

The growth benefits of becoming data-led

Becoming a data-led business helps you promote sustainable growth in three ways:

• It enables you to analyze user behavior and build customer experiences powered by data, context, and research – not intuition.
• It’s cost-saving – creating the right products and services saves money and time. Don’t waste money building something customers don’t want.
• You can get excellent insights into the user experience so you can make better decisions to improve UX.

How to make data-led decisions and build better products

There are three main ways to make data-led decisions – collect data from multiple sources, use analytics tools that let you manipulate the data, and prioritize decisions based on data.

Let’s explore them in detail:

Collect data using multiple sources

Data assets are essential, but you need to have a plan. Know what data you need and where you’ll get it from.

When it comes to what data you need, think of it as this: Does it provide business value? Can it help make data-led decisions?

For example, let’s say your team is wondering if you should build a new feature. You will need data on product usage to analyze before and after. You’ll also need to conduct user interviews to get an insight into customer needs. You should also pair this with some user testing and screen recordings of beta testers using the prototype.

This is the true meaning of data-led – going beyond standard analytics. Raw data is full of metrics and numbers. No one understands what they mean until some context supports them.

There are three methods you can use to collect customer feedback:

Collect data with feature tags and heat maps

Feature tags and heat maps should be part of your data strategy. They give you accurate insights into how users interact with the product. What features are they loving? Which ones are going unnoticed? What steps do they take to go from A to B?

You can tag different UI elements and see how your users interact with them.

Couple it with feature heat maps to get more precise data. Heatmaps show you the areas that users engage with the most using a color-coded system. Red shows high activity where users spend the most time hovering or clicking.

Usage data like this is vital to help you make better business decisions since you know what resonates with your customers.

Collect customer feedback with in-app surveys

To collect qualitative data, ask customers for their direct feedback.

Use in-app surveys to ask for different types of feedback depending on your goal. For example, create an NPS survey to measure customer loyalty. NPS surveys ask customers to rate on a scale how likely they are to recommend your product to their network.

On top of the scoring system, you can create NPS surveys with follow-up questions. Then, tag and categorize the qualitative responses to find patterns amongst the detractors (low-scorers), passives (mid-scorers), and promoters (high-scorers).

Collect data with session recordings

Collect more precise user data with session recordings.

Notice areas of friction where users experience issues. See what features they turn to again and again. Take action on these insights by improving your product based on what you learned.

Go beyond standard data analytics reports

Look at more than just a bunch of raw reports in standard analytics tools. Instead, ask questions and dig deeper.

Some analytics platforms will limit this ability by only providing standard reports that can’t be truly customized. Look for a tool that lets you manipulate and work with the data to find trends and new opportunities.

Userpilot’s analytics features let you track usage trends by customer segments. That way, you can optimize the product experience depending on what a segment needs at the time.

Prioritize decisions based on the relevant data

Look at what the data is saying before and after making business decisions. A data-driven culture is about confirming your intuition with data (e.g., the numbers show this, so we should do this).

That being said, it doesn’t prioritize tracking the data after you’ve made a change to analyze the impact.

Also, it’s important to ensure you’re looking at the correct user data – don’t analyze your entire user base in one go. Use segmentation to get the data you need. Otherwise, your results might be skewed.

How can you improve the user experience by becoming data-led

The whole point of a data-led transformation is to improve user experience to drive growth. A data-led approach makes it possible to not only personalize the in-app experience but also automate in-app help and optimize UX.

Here’s how:

Personalize user in-app experience based on data

Use intelligent data to segment customers with similar characteristics and reach out to them with personalized messaging.

For example, you can use the data to find out which customers are having trouble using one of your features; then, you can segment them and reach out to them contextually to provide educational resources.

Segmentation helps you focus on customer needs. You can deliver personalized content that lets you meet those needs.

Automate in-app help based on product usage data

Your data can tell you what features are being used but have yet to be adopted. High-value features should be an integral part of your customer’s workflow. This improves customer satisfaction, loyalty, and retention.

To boost product adoption, you can create interactive walkthroughs and trigger them automatically when users engage with the feature. Remind users of the benefits of that feature, then show them how to use it.

Optimize in-app user experience using data

Good data helps you see what works best for each user type. For example, beginners might need more help. Some users might prefer video, while others want written guides. It’s all about testing and seeing what works.

A data-led transformation is about going at a granular or micro level to understand user behavior and needs. Using that data, you gather insights to optimize the user experience.

How Userpilot can help product growth managers become data-led

Userpilot is a growth platform that helps product growth managers make data-led improvements.

Here are the top three ways Userpilot can help you become data-led:

Collect user behavior data without the need for a developer

You don’t need developers, data engineers, or data scientists to collect user behavior data.

Userpilot makes data collection easy with its behavioral analytics features.

For example, you can tag UI elements, like features, in a few clicks to learn how users interact with them.

Analyze customer data your own way

Customization is essential to fully capitalize on your data. You need to be able to slice and dice your data to notice trends. Fortunately, Userpilot provides different data reports that you can customize.

Hardly any analytics tools give you this level of in-depth data. They all provide standard reports with little room for customization. It’s easier to do extensive research if you can work with your data.

You can also set custom goals to track how often people reach certain milestones in your product.

Build contextual in-app experiences based on data, not intuition

In-app guidance improves product adoption and customer success. But you should first look at the data to build in-app experiences. Identify what your customers need to learn most (and what will drive business value for you).

Then, create in-app elements that help you achieve those goals. You can build modals, slideouts, tooltips, and hotspots that guide users on what to do next.

Conclusion

Becoming data-led helps you make better business decisions. When you collect data and get additional context, you gain insights into what customers need and want. Then, you can build better product experiences, create new revenue streams, and improve operations.

Want to get started with a data-led strategy? Get a Userpilot Demo and see how you can track user behavior, customize your analytics, and build in-app experiences code-free.