Driving new user adoption with customer insights

Driving new user adoption with insights

There are many definitions of product/market fit but one thing is for sure, if you don’t have it, your growth will slow. SaaS companies are desperate to create products that end users love and VoC insights are a great way to realize that long term vision.

Here are two ways your software company can approach insights to find that elusive product market fit:

  • Qualitative research - Ask users directly in focus groups, panels, mobile qualitative research etc.

  • Feedback analysis - Survey your customers (at-scale) and analyze their feedback

There's also this wisdom from Sean Ellis:

“Survey your users and ask them ‘How would you feel if you could no longer use the product?’ and measure the percent who answer ‘very disappointed.’ If that percentage is over 40%, you have PMF (Product/market fit).”

Structured data is important, but there's value in giving users license to tell you in their own words what they love and don't love about your product.

According to Forbes, in the 80s and 90s software was sold to IT leaders. Between 2000-2015 a new era began where selling to department leaders was the norm. This strategy was pioneered by companies like Salesforce and others. Since 2015 we’ve been in an end-user era where the employees that have to use software are the ones recommending software based on what they prefer to use everyday. In this new world, product-led growth (PLG) as a strategy has grown in popularity.

In a nutshell, product-led growth boils down to weaponizing your own product to delight existing users so they recommend it to their friends, family and/or co-workers. This is important because investors value the growth of new users just as much as they value traditional metrics (such as revenue, margin and market share). As an insights team, should be wise to the long term objectives of your company.

These are some questions you should be answering when supporting your organization's product led growth strategy with insights:

  • What are the behavior drivers influencing word of mouth?

  • Which demographics are more likely to drive word of mouth? Why?

  • Which demographics are less likely to drive word of mouth? What can we can we do to change this?

  • What drives whether or not your software is adopted in the workplace in industry X vs. industry Y?

  • Which industries are more likely to give your product 5 star reviews on app stores?

  • What are the main drivers of 1 and 2 star reviews on app-stores? When you understand this you'll figure out how to turn low star ratings into 4 and 5 star ratings.

Answering these questions helps raise your team's credibility because they directly help your company drive new users into the product.

What is the end-user era?

The end-user era refers to the shift in buying patterns when it comes to B2B SaaS software. Instead of executives making the software decisions from an ivory tower or CIOs making six-figure purchases, the end-users of the software are making the choices for their departments and spreading adoption across the team.

It’s almost like the software is entering the company from the back door. Imagine Jane from Support using Zoom to talk to her sister and introducing it to the office because she prefers it to Skype. The rest of the team like the software and they upgrade to the paid plan. Zoom has a new customer without lifting a finger for marketing and sales. The product is the key selling point due to its ease of use and delightful customer experience. Software has become simpler and easier to use, and the move to subscription pricing has increased the ease of adoption.

The game has changed. Decision making is now bottom up rather than top down with end-users saying yay or nay to your software. This is actually a positive for the Insights industry because there's an opportunity to conduct deeper feedback analysis, more often and to share those insights widely across the organization.

Why is understanding user feedback so important for SaaS companies?

Product/market fit isn’t achieved if users have a poor overall experience.

GetFeedback has this to say about customer retention,

Only 1 out of 26 unhappy customers complain; the rest simply churn. Can you imagine the revenue growth if you had a plan in place to capture that missing feedback?

Listening to your customers starts with collecting their feedback across all channels. Mature CX programs collect both structured and unstructured feedback from all touchpoints across the customer journey. In doing so, one can get the real-time feedback they need to actually optimize the customer experience.

Collecting user feedback will help you identify friction in their user journey. The best advice that can be offered here is to focus on the entire journey, not just the acquisition end. While new user adoption is important, word of mouth play a big role in that adoption. Consider analyzing all types of users, both free trial users through to paid accounts. You can use these user insights to improve your overall product user experience. This also has the added benefit of making it easier to weaponize that product to power a PLG strategy!

According to Lisa Abbott from OpenView Partners, “By analyzing the open-ended comments that accompany the rating-scale questions, you can identify positive and negative themes in what customers are saying.” She also says, “Based on what you learn, you can confidently prioritize improvements to your product that will remove bottlenecks, which are the enemy of PLG success.”

And that’s the overall goal – remove bottlenecks from the experience and pave the way for scalable, sustainable new user growth.

In-house vs. external customer feedback data

There are two types of customer data open to insights and research teams at software companies. The first is data you already have in-house such as customer surveys, chatlogs, user research, sales data, demographic data and support tickets logged via platforms such as ZenDesk and others. This is where a data warehouse can help.

External data can be widely available if you know where to look for it. This data is publicly available through social media and product review websites and can be great for expanding your field of view. The only note worth mentioning is you'll need to have a process for scraping, storing and managing this data. Competitor feedback analysis, particularly looking at user reviews on app stores can give considerable insight into how you're positioned relative to the competition, whether your competitors are meeting customer expectations and delivering a superior experience and if you're able to capitalize on whatever is driving their 1 and 2 star reviews.

Use insights to find friction points in the full user journey

The best SaaS companies are customer-centric. They recognize growth comes from fixing the customer journey and that is done by gathering product feedback.

It’s critical to gather data from your customers to find out how they’re actually using your product and to understand their pain points. PLG obsessed companies should make it a habit to survey their customers and find out as much as possible about their experience. When customers onboard with your product it should be as smooth a journey as possible, encouraging them to keep using the software and spread the word to the rest of their teams. Did you know for example that 80% of customers have deleted an app because they didn’t know how to use it?

As previously mentioned, you need to consider the entire journey. Below you can see reviews for the app store for a major US bank’s mobile app. There’s clear frustration with active users preventing them from even using the product. It’s not a question of making the experience seamless, they just want to access their account. Ouch! The risk here isn’t whether or not those dissatisfied users will delete or uninstall the app, but whether they'll pack up their bags and switch to another bank.

Customers are the experts when it comes to deciding what benefits them. In the absence of feedback, SaaS product teams can only make assumptions about what changes to make in the product. Assumptions are dangerous because you’re gambling the future success of your company on the movement of high level scores (such as NPS or CES) rather than a deep understanding of how users actually use your product.

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