Articulating the AI startup added value

When Valossa asked us to improve their onboarding, we didn't think of redesigning the whole platform along with the pricing plan. But that's exactly what we did. So let's dive in.

Some of the sign-up screens

Introduction

Before we started cooperating with Valossa, they had already been a well-known player in their field (Recognized as Gartner Cool Vendor 2018)— an audiovisual recognition platform for video content. An interesting part of their service goes beyond the video recognition, offering:

  • Speech to text analysis
  • Metatagging
  • Video recognition — e.g. people, brands, even what's happening in the video

The list above isn't complete. The application has a lot of features. The first question which came up was:

What were the reasons for the people to hire Valossa's services?

Product video of Valossa's services

Challenge

From the beginning, the challenge has been to factor out the onboarding process. The user journey was unclear and affected the portal usage rates. Part of the challenge we were facing was discovering what the tipping point for their customers was, and how we could enable them to reach this as soon as possible after the users' registration. Apart from this, we faced more questions:

  • Why are people hiring Valossa?
  • What's the tipping point?
  • When can people see the value?
  • How much are people willing to pay for Valossa's services?
  • How can we design the application so that users discover the new features easily?
Sketches 👩‍🎨

Process

We started with the stakeholders' interviews. We interviewed Karita, advocate for the users. Formulated hypotheses. Then we moved on to a quantitative part of the analysis to verify the hypotheses:

  • We watched some video recordings in Hotjar 🍿,
  • We checked GA 👨‍🔬,
  • We got inspiration from competitors and elsewhere 🎮.

The customer segments weren't easy to obtain due to the target audience being the broadcasting industry. We decided to take a risk preparing the final designs and testing them. After about a month we received the first results which proved our assumptions — the number of users from registration to video uploading (the tipping point) improved by 40%. This allowed us to focus on the whole platform.

After discussions, we changed the pricing page, which slightly affected the business model as well. The reasons for changing the pricing were

  • to address the needs of customers better,
  • to show them explicitly the benefits they could expect,
  • to explain to the customers the monthly fee.

There was a discussion about packages vs slider, because the price was determined by the number of minutes the user would spend analyzing their video contents. In the end, we decided on the packages, because they reflected the added value better for the customer. We also added a slider so that the user could choose which package they wanted, and they also saw the respective monthly fee.

ideation on the left and almost final design on the right side 🚀
The more we dug in, the more we felt like onboarding wasn't the only problem. So we decided to deliver a full package.

When we finished designing the platform we moved on to testing it with a small group of people in the Valossa lab. Big thanks to Teemu for helping us with the testing preparation, and all the best to his thesis about qualitative testing 👊. During the testing, we discovered a new customer segment, and a lot of opportunities for improvement. There is still plenty of work to do. The attribution funnel is working well, so from now on, the improvements will concern the platform adjustments, using the analytical tools of GA, Hotjar, and Intercom.

Case in numbers

  • 1 new customer segment discovered during the testing
  • 28 % improvement in onboarding (an increase in the number of paying customers)
  • 1 trip to 🇫🇮
  • Many improvements in online communication
Sneak peek to one of the screens, where users can search in their video content

Findings

The testing showed us that people still don't understand what AI stands for, more precisely users had trouble grasping what are all the benefits that they can receive by using the video AI service. With Valossa, we were lucky to have a possibility of deep understanding what they were doing and what business they were running. Therefore, we helped articulate and design a user experience that supports the communication about the added value towards users.

If you want to learn more about onboarding, there is a good guide. What we have learned:

  • You focus on how you can empower your users, not on the features, and you use this communication throughout the whole experience you are delivering to them
  • Allow them to see the added value of the design as early as possible.
  • Users vary, some need to be guided and some don't. Design the application not to bother the users with explanations or guidelines. Show them instead of where to find help.
  • Don't be afraid to try doing what your gut feeling tells you

We design to scale

We take an utmost care to understand broad environments. We don't deliver what we are asked for but we make sure we fly together with clients 🚀.

Valossa has been in an R&D mode for a long time, and now it’s ramping up the service side of things. We helped them to scale up the service growth — Valossa was nominated as one of the outstanding 25 deep tech scaleups.

Would you like to hire us for improving your onboarding? Or anything else? Hit me up.

At Status Quack we are currently focusing on conversational UIs so stay tuned about updates from our side.


Thanks to Vladimir Mokry for his UI mastery and for your attention. If you have questions, let me know. Don’t forget, sharing is caring.