You could be a 5-person startup creating an app to locate ice cream trucks or a 500-person organization with a fitness tracking platform. You could be a scrappy product manager trying to incorporate research on your own or part of a dedicated research team focused solely on one feature of the business. No matter what your team looks like, you have one goal in common: You need to understand who your users are, what they want, and whether they'll use your product. Translation: you need to invest in user research from day one (seriously, day one!) to power user-centric decisions and successful products.
Here's how this often plays out.
Early stage teams may be aware of user research, but might not know where to start. Companies already starting to scale up may start to wonder about best practices for integrating research into a growing organization, or how to retrofit a research function into a product and design team that’s been conducting some form of research on their own already.
At this stage, companies don’t usually have bandwidth for a user research-specific hire, so they need to embrace tools and technology that allow small teams to conduct meaningful research on their own. The goal is to make decisions that use capital wisely, and only prioritize those decisions that users actually want — both pre- and post-launch.
Teams might be surprised at how much clarity a short survey can provide into the ever-elusive product-market fit question. A simple 4–question survey can help indicate product-market fit, even with just 100 beta users. As a rule of thumb, if 40% of users or more say they would be very disappointed if your product did not exist, then there is some level of product-market fit. And if the survey indicates that there is no fit, the open-ended responses to questions like “How could we improve the product?” and “What are the primary benefits you receive from the product?” will help guide your next iterations and ensure the product does not drift away from what users like best.
Research at this stage doesn’t need to be perfect, but it needs to provide a general signal on which direction to go. And at this size, most companies are still small enough to have individual conversations with users that lead to targeted, productive, and beneficial insights. Tooling at this stage should enable fast, unmoderated testing, and provide templates driven by best practices.
As an organization grows, so does its research needs. Founders will feel the pull to create a dedicated user research team to address a growing number of questions regarding product decisions, the customer journey, and more — all critical in driving growth. While a company is growing, the research team may grow into its own entity and, eventually, add a dozen or so researchers to the organization. At this point, a small research team can begin answering more strategic questions and enabling product owners and decision-makers to tackle some tactical research on their own.
This is the stage where a company needs to put into place more rigorous research practices, enabling teams to ask the right questions of the right users at the right time. That’s because during periods of high growth, small changes in flows like acquisition and onboarding can make a huge impact. And making the wrong decision can cause massive declines in new user growth and contribute to millions in lost revenue.
By simply learning from users in-product, teams can obtain a clear and reliable signal about what’s working, what’s not, and why. For example, you could launch a well timed survey after users drop out of the onboarding flow or don’t convert from a trial to paid subscription. When asked at the right moment, users are eager to provide their thoughts — but it needs to be in the moment. The results can be analyzed using tools like Sprig’s AI analysis and, with that feedback, your users can provide clear guidance on how to optimize those flows within hours and iterate quickly, without waiting for the results of multiple A/B tests.
In my experience, these are some of the most common and widely used surveys because they generate real results, fast, and give you the ability to de-risk decision making.
Once a company reaches significant scale, usually post-IPO, user research can become a key competitive advantage. Whereas in earlier stages of company growth, speed to market and product-market fit will likely be the biggest drivers of success, companies operating at scale must optimize around the edges, and small changes matter much more (though it is important to continuously revisit PMF as you grow!).
At this point in a company’s journey, research is conducted systematically across the entire product lifecycle, and large teams of researchers work in lockstep with product teams to drive the right decision-making. At scale, it’s essential to continuously measure the user experience by capturing a variety of metrics and insights. These can range from simple surveys like Customer Satisfaction Score (CSAT) to customized measures that measure the product’s impact on business-specific KPIs or OKRs.
In companies like Meta and Google, this type of research enables teams to juxtapose user experience data alongside product analytics and financial data to ensure the company is making decisions that are in the best interests of both the company and customer. While this is not nearly the case at all at-scale companies, it’s the ideal state for organizations or companies aspiring to be customer-centric.
One way this is done is by conducting research as part of A/B tests. For example, let’s say you launched an A/B test measuring conversion on a subscription cancellation page. Looking at these results, there’s a clear winner in getting users from point A to point B, or deterring them from canceling.
But does this test give you the full picture? Maybe B made it so difficult to cancel that users gave up. Maybe they aren’t converting because of a positive experience, and, instead, they’re becoming increasingly frustrated that they weren’t able to complete an action. Asking for user feedback can help further validate the test and add a qualitative angle to the quantitative data.
When looking at qual and quant data side by side, as seen in the chart below, the results from the cancelation example look much different. You can now address the issue holistically and solve the root problem while thinking about both user experience and business metrics together.
Research won’t look exactly the same at every stage. It could evolve from a solo founder or a product team tackling research to a small team of talented researchers, eager to make an impact. And you’ll need to approach it differently depending on your size, goals, and resources. You might be able to have individual conversations in those early days, or you might be focused on figuring out a path to get qualitative insights at scale as you grow.
Daunting? Not with the right tools. We have the roadmap to help you evolve while you grow, invest in the right tools at every stage, and stay user-driven, even when those users hit the millions.
Additionally, the larger a company gets, the more it must invest in tools that help it scale and disseminate research across the organization, in order to keep all teams aware of and aligned around the customer experience. The best organizations use tools that enable continuous user-experience measurement and benchmarking as they seek to understand the impact of new product development and prioritize across projects.
How You Can Implement Research Today
Regardless of your company’s scale and budget, understanding your users is critical. As you can see, research doesn't always need to be perfect, but it does need to get done. And Sprig can help organizations of all sizes launch a research program (bonus: it doesn't even need to require engineering resources!). Create your free account today to get started.
This blog post is adapted from an excerpt from Sprig CEO Ryan Glasgow's article, Research Twice, Build Once: How to Know Your Users as You Grow, that originally appeared on a16z's Future blog.