The age of action-based business intelligence

If you’ve spent enough time looking at no-code analytics/enablement/revenue intelligence tools for whatever reason, you’ll realize that they all have very similar positioning — data-driven, activation, democratize data, self-serve, growing siloes, revenue-generating insights, etc. While these are all great words (and fair, because there’s only so many of them in the English language), they end up leaving you as a buyer confused and surrounded by products with seemingly the exact same pitch.

After all, who’s going to say no to a more empowered business team, a less stressed data team if you have one, and endless golden insights that could change the trajectory of your business without any lift on your end? No one, that’s who (caveat: at a reasonable contract size, maybe with a free trial thrown in and the CEO’s personal phone number as a customer service hotline if you’re early-stage — this can be arranged if you email us).

“Internal tooling” has the same building blocks 🤔

The building blocks are also very similar, usually some combination of these things: graphs, tables, alerting, automations, playbooks (really just another font of automations), reporting, and project management features. So why is there still such a potent need for figuring out what’s going on and what to do about it? And why does this need never seem to be satiated no matter how fast the tech stack grows?

While engineers are blessed with the option to either buy or build, for business users the set of options look a little different: buy purpose-built software, stitch a bunch of Notion docs and Excel sheets together, or harass in-house engineers to work on (and maintain for the next x years) an internal tool rather than the product they got hired to (and want to) build.

But lets face it — the last thing anyone wants to do is Slack Sean the senior SWE for the fourth time this week to fix some small bug in your internal tool — so once your Notion-Excel combo is falling apart, you’re back to option one.

Growth, operations, and revenue teams turn to purpose-built tools for specific use cases because BI is inherently usually not action-oriented or opinionated (latter isn’t as true when it’s purpose built to a specific industry like e-commerce), collaboration tools don’t have all the data the teams need, and you can do much more advanced automation in specific products.

It’s easy to end up in a place where you have all of these sort of overlapping tools, and different automations and dashboards and notes absolutely everywhere. It’s also easy (and very reasonable) to be absolutely terrified of this end state and run as lean as possible with spreadsheets instead.

In any of these scenarios the biggest risk here probably isn’t your burn rate, but a lack of visibility and focus. It’s hard to actually get to the real work if you’re constantly patching DIY solutions together for critical initiatives, learning new tools to add to an already robust stack, or waiting on data/engineering to build out systems they’ll have to maintain until the end of time.

It’s hard to get to strategic thinking without strong foundations 💪

The real work is arguably more difficult (yay). Figuring out what channels work best for each persona and pulling the information needed to report to customers how much value they got out of a product takes a lot of time and manpower — and this strategic work often comes second to putting out fires.

If the difference between success and a flame-out is being able to allocate capital correctly to teams that make smart decisions, a clouded view of that over a long period of time is a fast track to layoffs, teetering team morale, and/or weakening product market fit — a fantastically stressful trifecta. This is the real fire most founders are willing to put out with anything at hand.

Today, the tools we mentioned before serve as the real internal tooling — the complex automations, wordy documents, live dashboards, and long comment threads of those documents that notify you one too many times — that make up the plumbing keeping companies running smoothly.

But if the building blocks are all the same, and the metrics are also somewhat predictable (no one come for me I swear I know you define SQL or MRR a little differently from other companies), why hasn’t anyone turned this into a bunch of templates to put the power of building custom internal applications with real power into business teams’ hands yet?

Why business bliss is possible 👼

We think there’s a few trends that make what was impossible (or very hard) five years ago simple today:

• Months for onboarding and setup — Setting up the SQL for hundreds of metric definitions would have taken forever - with LLMs hundreds of tables can be processed, interpreted, and analyzed in minutes.

• Lots of maintenance overhead — Semantic metric layers combined with LLMs make adding, editing, deleting metrics faster than ever before, even for non-technical users

• Systems were immature — the data space has evolved meaning warehouses, lakes, and cloud-based tools are more commonplace and well understood by most people in the organization.

• Lack of literacy — Most operators today are more data-driven than ever before and interested in trying tools that make them more efficient and amplify their impact.

If you thought you’d get through this article without a pitch, unfortunately you’re mistaken 🙂 

Work at a startup that wants to spend less time managing your data warehouse and more time putting it to use or just like thinking about data? Definitely drop us a note - we love chatting with other like-minded nerds who think too deeply about the meaning of the word “insight”.