Thriday uses Refiner to improve their platform during beta and gets a whopping 57.7% response rate

Justin had experience using surveys to fuel growth at his previous job. He used Delighted in the past, but there were some requirements it didn’t meet for Thriday. Thriday is not only a web application, but also a mobile app on iOS and Android. Plus, their MarTech stack includes Segment and Amplitude which makes an integration with Segment a requirement.

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So there were a few boxes we needed to check. It needed to be integrated easily with Segment because we needed to be able to push the data into Amplitude, analyze it and have dashboards to display data and show it to everybody. And that needed to be self-serve and easy.

Customization and flexibility were also very important criteria.

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We also needed it to look and function nicely on app and web. And we needed different survey options like CES, PMF, NPS, etc. A real key part of what we do is the follow-up question. After people give us a score, we ask “Why did you choose that option?” And the verbatim response that we get needed to flow through that customer data platform and give us the information that we needed to improve.

In the end, Refiner was the only solution that met all the requirements.

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There was another one, Satismeter, which is integrated with Segment, but it was missing a part of that functionality. Refiner was new to me, but you just seemed to have more features built out, a better roadmap, super responsive support, which was good. And you understood quickly what we were trying to do.

Because Thriday is an all-in-one platform, the onboarding experience needs to be taken seriously or customers won’t know how to get the most out of it.

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People are joining Thriday without even really understanding how powerful it is. Some people are signing up, not realizing that they get access to a full business transaction account, so there’s all these things that the feedback loop can help us improve.

To make the best experience possible, Justin decided to measure effort. First, once after the registration. Then, after each key feature was experienced for the first time including: invoicing, bookkeeping, etc.

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With invoicing, for example, a survey is triggered after the first time they’ve used that feature. And then if they’ve used invoicing again, the next time they use it after 30 days is up, they’ll get that survey again.

The goal of the recurrence? Being able to track improvements over time.

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Hopefully a person that gave us a four will give us a five next time, because we’ve improved that part, or they’ve figured out how to use it properly. We ask the same people with the same surveys multiple times, but obviously with delays in between so we don’t annoy them.

With all these surveys, they get to pinpoint exactly what needs to be improved instead of relying on vague feedback.

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Our initial benchmark across the line for the customer effort score is to have a score above four for each of the features. But at a high level, I can look at that each day or each month as an aggregate right across all of the features and know that we’re above that benchmark. And we are also able to look at month over month. We can also do that at a feature level, because some features are more used than others, which skews the overall score.

When a score gets lower than it should, they see it very quickly and can take corrective action right away.

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If we see something that needs some work, then we’ll go on and do a couple of sprints on adding some more functionality or ironing out some little bugs or whatever it is we discover from customer feedback. And then once we’ve implemented those changes, we can then go and see how it changed the customer effort score to know we improved the feature in a measurable way.

While the current focus is on feedback, they already know what they will do for follow-ups.

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We have a plan in place as well for the people that give us really good feedback. We’re going to automate a follow-up to ask them if they can introduce us to any other small business owners as a referral play. But at this stage, it’s just collecting that feedback, improving the product based on the feedback, letting people know that we are working on the things that they need improving.

The data Justin has gotten so far has been pretty positive, with a score above 4 on average.

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Currently, our customer effort score is 4.43 on average, which is great. And the completion rate is 57.7% for customers who got the surveys.

With such a high completion rate, Thriday gets a lot of data even though it’s a beta with a limited number of users. And it already paid off.

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We know there’s a particular feature that we need to work on more than other features, just based on the feedback that we’ve received. So it’s already helping us prioritize, three weeks in, what we are going to be working on next.

• Justin needed a way to measure the ease of each feature during onboarding and over time.
• Each feature has its own CES survey triggered after the first use and after 30 days.
• After just 3 weeks, Thriday already had enough data to prioritize a particular feature over the others.

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The feedback loop you get from your customers is probably one of the most important things you’re going to do in your business. So the sooner you set that up, the better, and obviously Refiner has been a really great way for us to do that.