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Data-FIRST Manifesto: Why We Started scaleMatters

Data-FIRST Manifesto: Why We Started scaleMatters

Spewing, hand-waving and back-pedaling.

I can’t even count how many times across so many companies as CEO or Board member that I’ve asked questions looking for specific information to help guide important Go-to-Market decisions only to have someone respond with a substance-free answer where useful information is indiscernible (all the while gesturing to add emphasis).

This combination is what I refer to as spewing and hand-waving. When I press a bit deeper the story changes, twisting and turning until it has no resemblance to what was originally proffered…back-pedaling if you will. If you're a top executive or investor you've most certainly experienced those painful moments yourself!

The Damage Done by Spewing, Hand-waving and Back-pedaling

While we could certainly create a pretty comical series of memes from those cringe-worthy scenes, the fact is that this is symptomatic of a foundational problem for tech companies that at best stymies growth and depresses economic returns but at worst is a driving cause of so much infant mortality in the tech world.

I’m talking about the time and capital wasted by tech companies as they attempt to get their sales & marketing engines humming in a vacuum of dependable data and insights. They wing it. It’s gut, intuition, instinct…whatever you want to call it. And while that may make sense when you have an inkling of an idea, and decide to throw yourself into the wonderful world of tech start-ups, it doesn’t make sense once you have real expenses and cash burn. A short runway to speak of...

History is littered with countless examples of companies that winged it, actually acting upon spewing, hand-waving and back-pedaling.  Dig deeper and you see energy spent on dead-end initiatives or worse, initiatives that make the situation dire. At these companies, you commonly see energy spent on things that just don’t matter. Their leadership teams have an inability to separate the wheat from the chaff and really understand what to focus on.  So many fail to live up to their expectations resulting in highly dilutive financing rounds or the ultimate peril…closing the doors.

 

The Genesis of Spewing, Hand-waving and Back-pedaling

In the earliest stages of a company, you operate on gut because there is no data. As your idea starts to morph into a fledgling business and there is too much to keep track of in your head, you start to rely on data…but the data is garbage and you make bad decisions. And wow do they hurt!

The data is garbage because of the way sales & marketing tech stacks evolve.  Remember, this is legitimate technology. But, unlike the technology underlying production IT systems, in this case the technology users (sales people and marketers) also double as the architects, implementers and admins.  Now, where else would you expect the business users to play the role of expert IT folks? In HR? In Accounting? Hell, no! It’s ludicrous. And the result? You ask your staff questions and they say things like: “It’s too hard to tell because Pardot isn’t talking to Salesforce and they have contradictory data.” 

So you hire a Salesforce Admin and you think everything will get better, but the underlying data is still garbage!

Sorry to be a Debbie Downer...

For whatever reason, we expect our sales and marketing staff to be these great analytical minds. 

Salespeople have probably the hardest job in all of business…filled with constant rejection. Great salespeople are awe-inspiring in their persistence, empathetically connecting customer pain points to legitimate solutions, their ability to build genuine rapport, their work ethic and their ability to construct creative answers where none seem possible.

But they are not data analysts.

Phenomenal marketing people are awe-inspiring at communicating in ways that connect deeply, drawing on the emotions of the buyer to accelerate engagement. But they are not data analysts.

Yet, we expect them to be. And the result? They proudly show a beautiful slide to answer your questions, but rarely does their data accurately support their argument...or worse, the information is just wrong.

As you’re working to rapidly iterate to a more optimized state on product/market/message fit, and repeatability, predictability, scalability and efficiency of your Go-to-Market model, you are continuously undermined by a lack of dependable information to guide your moves.

 

Our Antidote to Spewing, Hand-waving and Back-pedaling

Early in my career, I was no doubt a contributor to perpetuating this goofy paradigm.  But at our previous SaaS company, because of the low-pay high-touch nature of our customers, the status quo wasn’t good enough…we had to do better.  And we did.

We methodically deconstructed our Go-to-Market processes into a granular model. This helped us quickly identify and remove process friction points. We built a new bookings plan at a level of detail that mirrored the sales & marketing model. Then, we tore down and rebuilt our tech stack to make sure that it not only made the jobs of our sales and marketing teams easier, but it also manifested the sales & marketing model from a data/KPI perspective so we could begin to measure performance with context.

We leveraged the skills of our super-star RevOps admin along with data ops analysts and business analysts to develop a "data-FIRST" approach to managing the company.

The results which were nothing short of amazing.

In 18 months’ time, we lowered the cost of acquiring new customers by nearly 80% and the time to acquire them by almost 50%!

 

From Concept to Company

At that point, we realized we could replicate and productize our approach and provide this "data-FIRST" environment for all B2B startups…dramatically improving the odds of success for early and growth stage B2B startups.

And that's how scaleMatters was born...

So leave the spewing and hand-waving to politicians, and the back-pedaling to Michael Jackson.

scaleMatters is here to deploy the data analytics & insights you need to grow revenue faster, scale more efficiently, and get higher valuations.

 

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