How to Use Data Segmentation in SaaS to Boost Conversions

Companies looking to improve their marketing and sales efforts should perform data segmentation in order to improve customer retention and gain additional insights into existing customers.

In this article, we’ll discuss:

• What data segmentation is and why it’s important.
• Types of data segmentation techniques.
• Practical use cases of segmented and processed data in SaaS.

What is data segmentation?

Data segmentation is the division and organization of similar customer data into categories based on your chosen parameters. It makes sorting through data easier while also making the data more actionable for sales and marketing teams when implementing different strategies.

Why is data segmentation important in SaaS?

Segmenting and processing data is crucial to the success of many SaaS businesses. Its benefits include:

• Helping you personalize the customer journey by making it possible to deliver relevant messaging to each user, improving overall customer satisfaction.
• Accessing insights that refine your decision-making process.
• Identifying trends among existing customers, including their pain points, usage patterns, etc.
• Assisting in better understanding your clients and tailoring your marketing to customer needs, leading to better engagement and higher conversion rates.

Types of customer data segmentation techniques for B2B

Your choice of data segmentation technique as a B2B business will depend on your goals and what you expect to achieve with your segmentation. Consider some segmentation techniques and possible questions you can ask when using them:

Account data segmentation: This involves segmenting users based on their account-related data. What’s their geographic or technographic background? How big is their company?

Product usage segmentation: Group users according to their product usage data. How many features have they adopted? Which features are they struggling with?

Behavior segmentation: Your goal here is to group users according to their behavioral patterns. How often do they log in? What’s their frequency of usage?

JTBD segmentation: Segmentation by jobs-to-be-done (JTBD) groups customers based on the job they’re trying to accomplish with your product.

Time-based and occasion-based segmentation: This segmentation technique groups users according to when they purchase your product. It divides customers into seasonal, promotional, and occasion-based buyers.

Customer loyalty segmentation: Segmenting customers based on brand loyalty (most loyal, medium, churners). Segmentation by customer loyalty helps you determine what drives loyalty in your brand and how to create more loyal users.

Customer satisfaction segmentation: Determine how satisfied your customers are and group them accordingly – happy, neutral, and unhappy. Determine what drives satisfaction and work to improve your product’s customer engagement and satisfaction levels.

Challenges when collecting customer data

The task of segmenting your data is crucial, but many organizations struggle to do it effectively.

The top struggles that companies have with data segmentation are:

1. Not gaining insight quickly enough.

2. Unable to gain insights from data.

3. Inaccurate data.

4. Missing the right tools to segment data.

Now let’s take a look at those challenges and see how you can overcome them.

Not gaining insight quickly enough

You must collect and understand your data before creating any viable data segments. But data segmentation can be time-consuming, leading many to abandon the process.

To make the process easier and quicker, you must understand why you’re segmenting your data. What outcome do you expect? What key insights do you hope to gain from the data?

Knowing your target outcome will help you gather enough data and correctly organize it for your data segmentation efforts.

Unable to gain insights from data

Although we have more data today than ever, most businesses still struggle to derive useful insights from it.

This is often due to the disorganization in the data collection or analysis process. Thankfully, there are an increasing array of tools to assist professionals in the data analysis process.

So to get insights from your data, you need to create a plan before jumping into the data and set the criteria for successfully dealing with data. Then search out the best tools that suit your needs to ensure success.

Inaccurate data

Accurate data is key to successful data segmentation. Without it, your segmentation foundation will be faulty, and so will every result from your analysis.

By reducing data inaccuracy, you can save your team time and effort. To begin with, you can follow best practices for data validation. Clean, accurate data will be available to your team after data validation.

You can also collect data in-app from real customers to ensure you have real feedback from active users of your product.

Missing the right tools to segment data

Many companies still rely on human labor or archaic tools to segment their data. Although these can be helpful, there is a wide range of data segmentation tools that exist today to help you effectively collect and segment data.

For instance, the right customer segmentation tools enable you to create customer segments based on shared characteristics like a user’s JTBD, in-app behavioral patterns, NPS scores, or other such criteria.

Segmented data use cases for SaaS

So, how can you create effective data segments for your use case? In this section, we’ll examine specific data segmentation use cases and the practical steps or examples that can help you put them in place.

Segmentation by customer profiles

Your first step when segmenting by customer profiles is to define your buyer persona(s). The buyer persona identifies your ideal customers who you believe will get the most value from your product.

Next, collect customer data using a welcome survey. The survey could include questions about the users’ background, their role in the company, and the job to be done with your product.

Afterward, segment customers with similar characteristics and JTBDs.

Segmented email marketing campaigns

Segmented email marketing helps ensure email marketing effectiveness through contextual emailing. Rather than sending the same mail to every user, contextual email marketing ensures users only receive an email that matches their needs and helps them get the most out of your product/service.

For example, you can send onboarding emails to new users to help them get started with the product, and “re-engagement emails” to inactive users to keep them from churning.

Email segmentation, like any other segmentation, depends on your goal, and can be modified accordingly.

Predictive modeling

Data segmentation makes it easy to model user behavior and predict their actions. Once you’ve gathered enough data, you can connect different data points that show a behavioral pattern and analyze the possible decisions the user will make in different scenarios.

For instance, you may notice that a particular customer segment is prone to churning after using a specific feature. Based on this observed behavior, you can predict churn among users in the segment who are yet to use the feature.

Next, you can take steps to prevent churn among these users. For instance, you may create an interactive walkthrough to help them understand the feature and drive adoption, to prevent frustration.

Improve event-driven marketing efforts

Event-driven marketing is the process of triggering marketing messages or contextual flows based on in-app events and customer interactions.

Also known as contextual onboarding, it involves introducing new features to a user only after they trigger an event or interact with a specific feature.

When properly used, contextual marketing helps you provide excellent user experiences through personalization. It eliminates generic messaging and ensures users only receive the help/marketing information they need.

For instance, you can trigger an interactive walkthrough when users interact with a feature for the first time.

Apply data segmentation to your existing customers to improve loyalty

One way to improve customer loyalty is by examining your NPS scores. A simple NPS survey asks your customers how likely they are to recommend your product to their friends or network, on a scale of 1 (lowest) to 10 (highest).

Users with NPS responses of 6 and lower are recognized as detractors who are unlikely to recommend your product. Customer segmentation helps you identify these detractors by grouping users according to their responses.

Proactively reach out to these users to determine how you can improve their experience. Addressing their concerns will help you reduce negative word of mouth and churn, turning detractors into loyal customers.

Use data segmentation process to enhance customer education

Customer data segmentation helps you provide effective customer education driving users to quickly gain the value they need from your product.

By segmenting customers in advance, you’ll be able to understand your users’ pain points, motivations, and jobs to be done. Then, you can provide each user group with only the information they need to achieve their business goals and solve their challenges.

For instance, you can trigger webinar invites for a segment of users that tried using a feature but ultimately failed to adopt it. This webinar should teach the users how to get the most from the feature and encourage them to fully adopt it.

Increase WoM with a segmentation strategy

Power users are the lifeblood of your product. In addition to being active product users, power users are often keen to provide feedback and speak to other potential product users.

Data segmentation helps you identify and engage your power users. One way to do this is by examining your NPS scores and identifying your promoters (users with NPS scores of 9 or 10). You can also determine your power users by examining other engagement data.

Note that these users are happy customers who are delighted with the product. They thus present a wonderful opportunity for word-of-mouth marketing. Once identified, reach out to them and ask them for a review on your platform of choice.

How Userpilot helps you collect and act on customer data using segmentation

Userpilot is a powerful product growth tool that helps you boost engagement and drive adoption. It provides an array of tools for collecting and segmenting user data. Its features help you…

Collect accurate data

There are many different ways of collecting user data with Userpilot. In addition to integrating data from other analytics platforms (Mixpanel, Amplitude, etc.) and tracking users’ in-app behavior, you can also collect reliable data using different in-app surveys.

You can create surveys for different purposes, from NPS surveys to customer satisfaction, customer experience, welcome surveys, and more!

Customize these surveys to suit your needs: Surveys may have single or multiple questions, follow-up questions dependent on users’ responses, images, colors, or other personal branding elements.

Create well-defined data segments

Userpilot’s advanced data segmentation features help you select the right data segmentation technique and create different user segments.

Amongst other things, it helps you:

• Identify heavy, medium, and low product users through user analytics.
• Spot common usage trends and patterns in product usage data and act on that data to improve your product development and roadmap decisions.
• Create segments around customer engagement data and use this information to identify areas of friction or confusion in your product.
• Build customer groups based on the customer’s location in the customer lifecycle.
• Group customers according to their demographic, geographic, or other personal or sensitive data.
• Segment customers based on their feedback or responses to other surveys.
• Track how customers interact with specific features (or the product as a whole) using the custom event tracking feature.

Trigger contextual flows

Userpilot takes advantage of data segmentation to help you trigger contextual flows in your app. You can trigger flows based on pre-set criteria to provide users with targeted support.

Your onboarding flows don’t have to be monotonous and boring, either. Userpilot provides a variety of UI onboarding elements to enable you to deliver effective visual storytelling, from modals to tooltips, slideouts, banners, etc.

Curate the right onboarding experience for your users with a combination of UI patterns that help you reach users more effectively with your onboarding message.

Conclusion

There’s no such thing as too much data. With the right data segmentation techniques, you can personalize the user journey, curate contextual experiences, and boost conversion rates.

Tools like Userpilot enable you to collect user data and segment users accordingly. Book a demo to learn how Userpilot makes your sales team more effective with its data segmentation and collection features.