3 things we learned embedding Yellowfin software

When you're building a product for other software developers and vendors, at some point you want to build an environment that mimics their experience.

One of the key pieces of work that we've done this past year is to actually build a completely bespoke application, so that we could properly look at the different ways that we could embed Yellowfin. This has helped us create a really unique customer experience within a third-party application.

Like all great stories, our vision fundamentally changed on that journey, and we learned three valuable lessons as we built this application we want to share with you.

#1 - We weren't asking the right questions

You only ever get to see your customers do easy things with your software because no one prioritizes time to do the difficult things. So in this process, we decided to do the difficult things that a customer would want and this influenced our product development.

We went to a lot of effort to change our product so that we could, hand on our hearts, say to our customers ‘if you can think of it you'll be able to do it’.  To do this, we had to look beyond enterprise use cases and think about how to embed Yellowfin into another application. Product managers aren’t thinking about data and decision making, they’re thinking about how they make their product better through analytics. So we had to think about our software application and determine what analytics we wanted in it.

This was a really eye opening process and taught us that we had been asking our customer the wrong questions. This meant we weren’t necessarily enabling them to achieve the best possible outcomes with their data.

We had to understand the experience that our customers go through when thinking about how they embed analytics into their application. What outcomes do they want, where do they want to go and how do they want to expose data to their end users.

Rather than thinking about how you embed software from a technical perspective, we had to think about what the end users want from that customer experience, and we learned an incredible amount from that.

#2 - We'd been doing operational analytics all wrong

By putting ourselves in the mind of our customers, we realized that the way we’d been thinking about operational analytics had been fundamentally wrong.

We had to completely rethink how people engage with and act on data, and we ended up with a whole new concept of contextual analytics. This involves embedding analytics so tightly into workflows that the user doesn't really understand when they're dealing with analytics and when they’re dealing with the actual product.

Offering a customer a workflow with embedded analytics is like Nirvana; they become sticky because they’re so reliant on the workflow. We can still give their CEO a dashboard so they have a high level picture of the world, but we also make the operational flows within their application so much more efficient. This approach to analytics really changes people’s minds and perceptions immediately about the many possibilities it can bring.

#3 - An MVP isn't good enough

When we started, we wanted to deliver an exceptional customer experience. What we realized was that an MVP is simply not good enough to achieve that.

You need to enable everything that a customer wants to do and you can’t take any shortcuts. We pushed our development team much harder - close enough wasn’t good enough. This means we’ve been able to do something that delivers on our promise.

When we demonstrate our product to prospective and even existing customers, the feedback we get now is exceptional. People are completely blown away by how they can take Yellowfin and do extraordinary things with it.

We can now do things that we never anticipated before we started this journey and that's what has made this process so valuable to us. What began as a way for us to highlight our capability to customers became something that pushed the boundaries of what embedded analytics could be and took it to a whole new level.

You may also like: