Data is the new oil.
We have heard this phrase being bandied around since the dawn of the information age. Some companies learned to actually leverage data. And they became juggernauts. There is a reason why Facebook and Gmail are free offerings...
Simply put, when companies take the time to understand their customers well, they can more easily provide value. And this is true regardless of shifts in the market. Companies who have figured this out have been rewarded with greater expansion and minimal churn.
Unfortunately, most companies still haven't figured out how to make data a superpower. One way to quickly measure whether this might be true is to analyze a company’s Net Revenue Retention (NRR) rate. This is because NRR is a great measure of a company’s ability to effectively unlock its customer data and use it to add tangible value.
Regrettably, companies with high NRR are still the exception, not the rule. For example, last year private companies with revenue of $50M-$100M had a median retention rate of only 60%.
Of course, the median NRR was much higher for companies who IPO (114%), but that could very well be self-selection bias. Meaning, only companies with sufficiently high NRR go public lest they be punished in the public markets.
Basically, even with seemingly all the data in the world, companies are struggling to answer questions like:
Why are these questions still so difficult to answer?
If you asked companies 10 years ago—or even 5—they’d have mentioned the lack of systems to collect and analyze data (i.e. paucity of the data). However, over the last few years, most companies have adopted systems that collect data across the entire revenue chain (aka the customer journey).
The mental model I use to help understand the evolution of the data space consists of 3 distinct but overlapping generations.
Gen 1 included GTM Apps like Salesforce and Amplitude. These answer questions like:
These are interesting questions that provide answers that are typically useful to specific teams or functions in the company. But because they are used by teams in silos their utility for the company to drive insights across the revenue chain is incredibly limited.
Gen 2 involved CDPs and Data Warehouse like Segment and Snowflake. These solutions were built specifically to solve for the problems caused by siloed team views of Gen 1.
To do this, they consumed data from Gen 1 systems and were able to a provide a single view of the customer. They answer questions like:
Gen 2 is clearly a step in the right direction. They enable us to ask more complex questions and tease apart some of the inherent murkiness that exists in complex systems like business environments.
Yet, in my opinion, Gen 2 solutions are still limited. They rely entirely too much on human input, understanding, and experience. As Sami recently pointed out, our human minds were not built to compute multi-variate correlations.
This is where Gen 3 comes in. At Tingono, we believe we’re still in the early days of Gen 3. We’re building a future where organizations will have intelligence on top of consolidated data to drive automated activities. We’re answering questions like:
I have personally felt this pain both at my last startup and when I was running FeedbackNow at Forrester. My team was not only swimming in data but also flying blind and operating mostly on gut!
This paradox is unfortunately too common for most SaaS businesses. And it’s even more critical in the age of PLG. We now have an overwhelming volume of signals that simply cannot be analyzed using traditional means.
As a result, we see companies with a growing set of tools who are still not equipped to bridge the gap between Data and Actions.
There are, generally speaking, three ways you can go about solving this challenge. From least to most effective:
This likely won’t come as a surprise to you, but I think our approach is superior. Essentially, we’re building the solution I wish I had when running my last two businesses. And I’m super excited about it.
Our approach enables you to:
In short, our solution allows every company to expand revenue using their most valuable asset—their data.
If you have been searching for a solution that easily adds an intelligence layer on top of your current data systems, please reach out. We’d love to work with you!