Whether you realize it or not, asking your users to complete a survey is a BIG ask. It may seem like a selfless request — the point after all is to collect data and feedback, apply those learnings back into your product, and improve the experience of the very same users you’re surveying — but your users don’t see it that way.
They view your survey as “work.” It’s your job, not theirs, to figure what they want. And if you can’t, then off to the next product or service that can. What’s worse is that not only are you asking your users to do work, but you’re also not getting the value you need from their responses. Most surveys today are conducted out of context, leaving you without clear, actionable insights.
The thing is, no product is perfect. Your users will find flaws in the next product just like they did with yours. And that’s why product leaders need to understand the needs of their users if they aim to get as close to perfect as possible when designing user experiences.
So then, how can we make surveys less like “work” and more of a native experience, so that your users don’t even realize they’re providing feedback? And perhaps more importantly, how do we ensure that we’re collecting the right feedback at the right time, and be able to quickly apply those learnings to our product before your customer drops-off, churns, or never even finds their way into your product in the first place.
That’s where contextual in-product surveys come into the picture. But before I explain what an in-product survey is, let me start by telling you what it isn’t. It doesn’t and shouldn’t feel like you’re taking a standardized test, where you’re stressing to recall what you read the night before as you stare at the endless questions.
The fact that product teams still send surveys at inopportune times (ie. weeks after the user has taken action in the product) is bewildering. Not only will their response rate be low, but their results will be unable to capture what the user was actually feeling at that precise moment in time while they were in the product.
That’s why contextual in-product surveys have become the ultimate tool to generate fast and accurate insights needed to build better product experiences.
So then, what exactly is an in-product survey and why are they important?
What is an in-product survey?
In-product surveys are targeted and timely questions that surface during a user's experience in your product. Because they are targeted, you only need to ask a few well-placed questions to get the insights you need. And because they appear during the product experience and not afterwards, respondents are more likely to participate and can easily take them on the go — important in an age where we spend more time on our phones than our computers. And you don’t have to wait weeks for results, you can get them in real-time, allowing you to quickly take action from the insights you derive.
In fact, in-product surveys are best used when they become an iterative part of the product development process. Since they’re easy to launch with Sprig, and you’re able to quickly get feedback, you can increase the speed at which you’re improving the user experience. This can be a huge competitive advantage in the race to iterate and optimize faster than your peers.
Here are some more reasons why contextual in-product surveys should be the only types of surveys your team is running.
You can target the right users, at the right time
Let's turn our attention to the “contextual” aspect of in-product surveys. In-product surveys are more effective than traditional surveys because you can target them at precise moments during the customer journey.
Research platforms like Sprig allow you to surface in-product surveys in your product at any time — before signup when visitors are browsing your website, during active use of the product, such as when they engaged with a particular feature or click a certain button, and even when your customers have churned.
And if you’re leveraging your unified user data, or integrated with popular tools like Segment, you can feel confident in your ability to target the right audiences.
By asking the right users at the right time, you’re not only increasing your response rates but also driving more relevant insights. Compare this to if you were to send an email to your users weeks later when they have likely forgotten about their experience or interaction with your product. What’s worse in this scenario is not even a lack of response, but inaccurate OR vague feedback that you can't easily act on since they can't remember the details at that point.
The Secret Sauce: Text Analysis
The last piece of the puzzle, and the secret ingredient to making in-product surveys work as quickly and effectively as possible, is being able to figure out how you can avoid spending hours sifting through open-ended responses to extract overarching themes and insights that are common amongst your users.
So why ask open-ended questions in the first place? Wouldn’t it just be easier to give answer choices in your surveys? Yes, but it wouldn’t give you the information that you didn’t realize you needed.
Open-ended questions are valuable in surveys because you’re going to surface insights you did not even know were issues and wouldn’t be able to ask in a close-ended format. In-product surveys benefit from open-ended questions because you can understand what your users are experiencing, in their own words.
Unique in a world of surveys, Sprig's text analysis does in-depth analysis of responses through unsupervised AI and expert human review — pulling out real, concrete insights that you can use right away. No word clouds or keywords, instead, specific improvements or actions you can take to design a better experience.
To summarize, in-product surveys allow you to understand what customers are experiencing in real-time, as it happens.
The key benefits include:
Fast: Surveys are launched in minutes and insights emerge in hours.
Timely: Use continuous surveys to measure progress and surface new insights the moment they emerge.
Effective: Target the right users at the right times and rely on text analysis to take care of the heavy-lifting by categorizing messy, open-ended responses.
Contextual in-product surveys should be the main types of surveys your team is running because at the end of the day, they allow you to focus on what’s most important — improving the customer journey and building delightful user experiences.