Seriously– data on the web is a solved problem, right? So why is it still so hard for SaaS companies to give their customers fast, interactive dashboards that prove value, answer questions, and win renewals?”

That’s not how it is. 

How it is: Six months and still "awful."

To get data to your customers takes a tremendous amount of developer time, which takes companies away from their core focus. And after all that time and expense, the dashboards tend to be slow, poorly visualized, and wholly inadequate to purpose. 

Case in point: one company we talked with had 10 people out of a dev team of about 150 on reporting, had been working on it for six months, and still thought their reporting “awful” (in the words of the CEO). 

Ten developers. Six months. And it’s still “awful.” 

It's not great for the people using the data, either. It’s not unusual to see tables of data that you have to page through… and I guarantee (because I’ve seen it) that some people submit support tickets because they can only find the records that start with the letter “A.”

Why is it like this? 

There's a reason data on the web is hard, and therefore generally bad. To build a great data experience, you need four specific skill sets: 

1. Domain expertise (marketing, inventory, ad sales) – business people 
2. Data engineering (joins, schemas, row-level access) – data engineers
3. Dashboard tools (front-end or BI tools) – developers and analysts
4. Data visualization best practices – analysts, designers, and data geeks (I say that with love as a lifelong data geek.) 

Very few people, or even teams, have all of this expertise, and so shipping data includes multiple learning curves— or results in bad dashboards. 

Just a checkbox? Or a competitive advantage? 

Every Saas company provides reporting. I’ve heard people say, “It’s a checkbox feature.” 

But the best companies know that great data can show your customers the value of the system they’re using. Analytics capabilities show up in G2 product comparisons, analyst reports, and other reviews. They becomes a differentiator and a reason for customer loyalty. 

I’ve lived this problem from two different angles: at Tableau, we enabled embedding dashboards with the best technology available at the time-- which was still too slow. Then, at Salesloft, I saw how-- even with a modern data stack-- developers, designers and data engineers had to spend far too much time to create dashboards.

Almost every C-level leader I talk with has struggled with this problem. It’s the problem we’re addressing at Ridge AI, using a new browser-based tech stack and AI to reduce the time to develop. If you’re one of those people, reach out– I’d love to show you what we’re building. 

‍

‍

‍

‍

We're starting Ridge because data on the web should be better – faster, more interactive, and in a tighter loop with action.

Understanding, sharing, and acting on data is essential to realizing its value. Innovations at the data and semantic layer have helped organize and scale data on servers, but a chain is only as strong as its weakest link. It’s time to elevate the last mile: the presentation layer.

That's especially true on the web, the universal communication platform. There, data still lives in images (!) or in dashboards and charts that are slow, poorly designed, and insufficiently interactive.  

This problem affects revenue for SaaS companies and other application providers. Providing data to customers is an essential part of these businesses. Done well, that reporting demonstrates the richness of the application to the customers and helps them see the value in the underlying application, so they feel great about renewing. Done poorly, customers complain and deals are lost.

And it's hard to do well. Many SaaS providers not only devote several teams to reporting, they have people creating custom reports by hand to bridge reporting gaps for customers.

Why is this still a problem?

We are decades into the data revolution, and entering an age of AI. While new technologies abound – LLMs, scalable in-browser analytics, and interactive data platforms like Mosaic, to name a few – these need to be carefully integrated to craft a new breed of data experiences.

We’ve worked in data for decades. We believe there's a better way, empowering easy authoring, effective presentation, rich interaction, and dynamic assistance for the “long tail” of analysis questions.

We're launching Ridge AI to scale this mountain. We'd love to tell you more and partner in the journey. Reach out to us at info@ridgedata.ai, or sign up below to stay up to date with product announcements.