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How Castos uses Refiner to inform their product roadmap and optimize onboarding.

Product Research

About Castos

Castos is a podcast hosting platform with the goal of making podcasting easy and accessible to all. In addition to hosting, customers get a free website, automatic podcast transcripts, analytics, as well as tools to easily monetize podcasts. We talked with Craig Hewitt, the CEO of Castos. Castos has thousands of customers and hundreds of new trials every month. They needed to find ways to understand their customers better, and optimize onboarding to improve the activation rate. That’s why they started to use Refiner.

Key takeaways

  • They had some preconceived ideas of how their customers wanted to monetize podcasts but had no way to quickly gather insights.
  • They had one big onboarding form and wanted to improve it, but needed to measure the impact of the changes.
  • With Refiner, they were able to have hard facts on how their customers were monetizing podcasts which helped inform their product roadmap.
  • They improved the onboarding and put a survey if the customer skipped the wizard to know why and see how successful these customers were compared to the customers who completed the wizard.
  • They are sending out a product-market fit survey and are waiting to get enough results.

Why Castos chose Refiner: in-app surveys, flexibility, and user identification.

The first thing Craig wanted was to have surveys inside the application.

We could have used something like Typeform externally, but we wanted to have something inside our application.

Flexibility was also one of the criteria. Why? First, because they needed to be able to adapt onboarding quickly.

We wanted something flexible because our onboarding is meant to change quickly. And we wanted something that’s able to be changed as quickly as we get feedback.

The other reason for this need for flexibility was to not have to rely on developers.

We wanted a solution where we could extract data easily. As a marketer, I can just extract the data without having to contact the developer to query the database. And then if we want to change the behavior, we would be able to do it in an external tool instead of having developers write code.

Finally, it was important to Craig and his team to tie a user to surveys easily.

Being able to identify users is really important. Because you segment users and then end up making business decisions or customer interaction decisions later with that information.

In the end, Refiner met all the conditions and it’s why Craig decided to go for it.

So yeah, those were our criteria and Refiner checked all the boxes.

How their first survey informed the product roadmap.

The first thing they used Refiner for was to understand how their customers wanted to monetize their podcast.

When they sign up with an interest about monetization, we have a survey to know how they want to monetize their podcast. We did this at the beginning just to try and understand our customers better. And now, it’s an ongoing survey to continuously get data to make sure that our new customers still want what we’re building.

Craig and his team made assumptions about monetization. But they realized it was different from what customers wanted.

The results had a real influence on the product.

The survey has informed our product decisions quite a bit, because we thought we knew how people currently monetize or want to monetize, but the results were quite different. And that was surprising to us. I think mostly because I had a bias. The results have affected our product roadmap.

How they are measuring the success of onboarding.

The activation in Castos consists of customers creating a podcast and publishing at least one episode.

And the onboarding wasn’t getting customers there as soon as possible.

We had a really big step in our onboarding where we asked the customers to fill in a whole bunch of information all at once.

They broke it down to multiple steps instead, and made it easier to fill in some information.

We basically removed some fields entirely by making some more assumptions, and just made it more kind of visually step-wise. So customers knew that they were making progress along the way.

Those steps are skipped by customers, so they added a survey to know why and measure the impact.

If customers choose to exit the wizard, a survey pops up to ask why they are exiting it. And we’re going to be using that data to correlate people who exit the onboarding wizard and the trial to paid conversion ratio.

In summary:

  • A survey during signup enabled Castos to understand customers better and align the product roadmap with customers’ desired outcomes.
  • They improved onboarding and added a survey if customers exited the wizard to understand why and see if the onboarding has any impact on the success of new customers.
  • They are thinking of adding a survey when a customer wants to cancel their account.

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