5 SaaS Analytics You Can Gather Through Surveys

Surveys are one of the most effective ways to collect user feedback and actionable product analytics. In this guide, we’re going to go through:

• The SaaS analytics you can gather through surveys.
• Which survey delivery method is best?
• How to find the right software for your needs.

Let’s get into it!

TL;DR

• Analyzing survey data can help you identify patterns, get ahead of issues, and make data-driven decisions moving forward to reduce churn while improving customer satisfaction.
• Collecting a combination of quantitative and qualitative data is the best way to avoid survey bias.
• Surveys can be used to gather customer satisfaction metrics such as NPS, CSAT, and CES, along with insights into the job-to-be-done of your users or reasons behind why they’re churning.
• Selecting which analytics to survey for will depend on your business goals, what to achieve through surveying, and which OKRs/KPIs you’re aiming to improve.
• In-app surveys are better than email surveys in most cases due to their higher response rates and ability to collect more recent data.
• Userpilot lets you create in-app surveys using templates, monitor responses through advanced analytics dashboards, and integrate with third-party analytics tools so you can sync data across your tech stack.

Why should you analyze SaaS survey data?

Survey data analysis is important because it can help you gather insights that highlight issues, measure satisfaction, and guide your product development or marketing efforts moving forward.

Survey data can also help you address detractor concerns early to avoid negative word-of-mouth, use CES data to minimize friction, and CSAT patterns to reduce customer churn.

On the other hand, JTBD insights and churn analysis can help you address problems more proactively. Whether it’s identifying (then fixing) the most pressing issues or increasing overall satisfaction, surveys are a great way to collect user feedback.

Types of SaaS analytics surveys

Survey analytics is the process of extracting insights through the interpretation of survey responses. That said, there are two different types of survey analytics that you’ll likely end up with: quantitative data and qualitative data.

Here are the differences between them:

Quantitative Data

Quantitative data is information that can be quantified (measured or counted) into product metrics.

Looking at quantitative data helps you analyze customer feedback from a more objective point of view and avoid various types of survey bias.

Qualitative Data

Qualitative data consists of non-numerical feedback formats such as text, audio, or video.

The unstructured nature of qualitative data makes it harder to objectively measure and leaves it more vulnerable to interpretation bias.

Which type of SaaS analytics surveys should you gather?

The best approach is to gather both quantitative and qualitative data to get the full picture during the customer feedback collection process. If ambiguous metrics lead you to a false conclusion, then a more detailed qualitative response could help clarify things.

Conversely, any misinterpreted qualitative feedback can be debunked by looking at the objective data from quantitative responses.

Think of these two types of survey analytics as counterweights that balance each other out.

Which analytics can you gather through surveys?

While not every key performance indicator (KPI), there are plenty of metrics that you can gather through surveys such as NPS, CSAT, CES, and more.

Let’s take a closer look at each of these metrics, what they measure, why they’re important, and how to gather them through surveys!

Net Promoter Score (NPS) SaaS analytics surveys

The Net Promoter Score (NPS) is a metric used to measure customer loyalty, satisfaction, and advocacy towards a SaaS product or business.

NPS data is a crucial indicator of how likely customers are to promote your product and whether or not they might switch to competitors.

Net Promoter Scores are measured by asking customers a single question:

“How likely are you to recommend this product to a friend or colleague?”

Respondents are able to rate their likelihood of recommending the product to others on a scale of 1-10. Depending on what rating they give, respondents are grouped into one of three categories:

• Promoters. Those who respond with a nine or higher.
• Passives. Those responding with a seven or eight.
• Detractors. Anyone who responds with a rating of six or lower.

To calculate the NPS score, you need to subtract the percentage of detractors from the percentage of promoters:

NPS formula: % of Promoters – % of Detractors

When running NPS surveys, it’s best to include a follow-up question that’s open-ended enough for respondents to explain their choice.

Finding out why a user is likely or unlikely to recommend your products to others is just as important as finding out how likely they are to do so.

Customer Satisfaction Score (CSAT) SaaS analytics surveys

CSAT surveys can give you a clearer idea of how customers feel about your product and the changes you could make to improve customer satisfaction.

Calculating CSAT scores comes down to dividing the number of happy customers by the total number of survey respondents. To get started, simply send out a CSAT survey that asks customers to rate their satisfaction on a scale of 1-10.

Anyone who responds to the CSAT survey with a score of eight or higher can be considered a satisfied customer.

The average CSAT score for SaaS companies is 78%, according to the 2023 CSAT Benchmark by Fullview.

CSAT surveys are best deployed after major changes to your product or business. This could include the addition of new features, tweaking existing functionality, or adjustments made to the pricing model.

Customer Effort Score (CES) SaaS analytics surveys

The Customer Effort Score (CES) is a metric used to measure the amount of effort needed for customers to interact with your product. Measuring CES helps you identify product problems, friction points, and other roadblocks that could lead to a poor customer experience.

Customer Effort Scores are calculated by measuring the portion of customers who found product interaction easy.

CES surveys are most often formatted in a seven-point Likert scale with an ease-of-use threshold set at ratings of five or higher.

Customer Effort Scores range between 0-100. If you survey 200 customers and 160 respond with a rating of five or higher, then divide 160/200 and multiply by a hundred. In this case, your Customer Effort Score would be 80.

In addition to collecting data on the percentage of customers who are able to easily use your product, CES surveys can also make users feel like their concerns are being heard.

Listening to the Voice of the Customer (VoC) can reduce negative word-of-mouth and customer churn rates.

Job-to-be-done (JTBD) SaaS analytics surveys

The first three metrics we’ve covered (NPS, CSAT, and CES) all center around customer satisfaction benchmarking — but they’re lagging indicators that leave you no choice beyond reacting to the feedback and curbing it in the right direction moving forward.

On the other hand, understanding the job-to-be-done (JTBD) of a user is a proactive way to maximize customer satisfaction from the get-go. The entire framework is built upon the idea that customers “hire” SaaS products to get specific “jobs” done for them.

These jobs could be any task, goal, or objective that makes the user’s life easier and generates value in some way. The job-to-be-done could also consist of a specific problem or challenge that the product must help the user overcome.

Building a product that is both attractive and sticky is only possible when you understand what users are trying to achieve with it. The most reliable way to identify a user’s job-to-be-done is through a welcome survey.

Here’s an example of how Asana uses welcome surveys to identify the JTBDs of new users:

Because these welcome surveys provide JTBD data early in the customer journey, you’ll be able to create a more contextual onboarding process and reduce the time-to-value (TTV) for new users.

Churn data SaaS analytics surveys

Churn surveys give you one final opportunity to speak to customers before they leave and uncover the reasons for their cancellation. This could provide unique insights that you wouldn’t be able to get from power users who are in love with your product.

Instead, this type of data helps you drill down on the underlying reasons why users are churning so you can prevent further losses. Lastly, knowing whether customers are leaving due to pricing, competitors, or a lack of features will also clue you in on which direction to take.

Here’s a look at a churn survey created with Userpilot:

While the primary objective of churn surveys should be to gather insights that can inform your next steps, you can also use them as an opportunity to change a user’s mind before they finalize their decision.

Depending on how a user responds to your churn survey, you could offer a discount, let them pause their subscription, or recommend an upgrade/downgrade to a plan that’s a better fit for their needs/budget.

Remember, there’s nothing wrong with collecting customer churn data that tells you how many users have stopped using your product as long as you couple that with churn analysis to investigate the root issues and figure out how to increase retention rates.

How to choose which SaaS analytics to survey for

Which analytics you should survey for will depend on your business goals and what you’re trying to achieve through surveying your customers. If you’re trying to reduce churn then all five of the metrics we’ve covered can be informative — albeit with varying degrees of actionability.

If your retention rates are good but you’re trying to improve customer satisfaction, then insights from the three lagging indicators above combined with JTBD information from microsurveys on your welcome screens could do the trick.

It all comes down to identifying which OKRs matter most and then working backward from there.

Email surveys vs. in-app surveys for SaaS analytics data collection

In-app surveys have higher response rates and provide more accurate data, which is why they’re usually the best choice.

In comparison, email surveys run the risk of getting lost in cluttered inboxes or being dragged into the spam folder. This could lead to nonresponse bias and skew your data towards false conclusions.

Even if you do get a response eventually, it may come too late to be accurate or actionable.

If someone responds to a churn survey two weeks after they’ve canceled their subscription, then you won’t get the opportunity to change their mind through a cancellation flow. Similarly, by the time you receive email responses to CES surveys, it may already be too late to prevent churn.

Of course, there are certain exceptions to be considered. If you’re trying to survey inactive users, then trying to reach them through email makes a lot more sense than sending them notifications through a product they no longer use.

In-app survey best practices

Seeing as in-app surveys are the best choice in most scenarios, familiarizing yourself with a few in-app survey best practices will yield plenty of benefits in the long run. Here are a few in-app survey best practices to keep in mind:

• Questions. Avoiding bad survey questions like double-barreled questions and sticking to good survey questions that result in unbiased answers is the best way to gather accurate data from users.
• Timing. Survey timing is just as important as the questions you ask. The best time to survey your user base is right after changes have been implemented, such as the introduction of new features or adjustments in product pricing.
• Delivery. Identifying the most effective delivery method for your users is key. In-app surveys will be the superior choice in most cases, but you could conduct A/B tests if you suspect that your user base may respond better to email surveys.

If you optimize your questions, timing, and delivery method, then you’ll be on track for success!

How Userpilot can help you collect SaaS analytics using in-app surveys

Userpilot is a full-suite product growth platform with built-in feedback collection tools. These include templates that will help you create surveys faster, advanced analytics for extracting insights, and a dedicated NPS dashboard to get a holistic view of your Net Promoter Score.

Here are Userpilot’s in-app surveying features:

• Survey Templates. There are 14 templates for you to choose from when creating a survey with Userpilot. These include templates for quantitative metrics like NPS, CSAT, and CES or qualitative open-ended feedback on specific product features.

• Advanced Analytics. Userpilot has native survey analytics, which lets you view the most popular choices, see what percentage of respondents chose each option, and read text responses from your users.

• NPS Dashboard. Userpilot’s NPS dashboard unifies the response data from all your NPS surveys. You’ll be able to see key metrics like the view count, total number of responses, response rate, score over time, and percentage of promoters/detractors.

• Integrations. Userpilot has native integrations for tools like Amplitude, Mixpanel, Segment, Kissmetrics, Heap, HubSpot, Intercom, and Google Analytics to ensure that data is synced across every platform you use.

Conclusion

Whether it’s satisfaction metrics, churn analysis, or JTBD insights that you can use to segment new users, there’s no shortage of analytics you can gather through surveys.

Userpilot’s native analytics capabilities, coupled with its dedicated survey features, make it a one-stop shop for your feedback collection needs.

If you’re ready to start tracking analytics and gathering insights through in-app surveys, then it’s time to get your free Userpilot demo today!