It's common to think of data as just an operational component for sales and marketing teams.
But did you know that the quality of your data can actually inhibit company growth?
How? The efficiency with which growth-stage tech companies acquire and retain customers has an enormous impact on the company’s growth and scalability.
Here are a few reasons why data is so closely linked:
#1: Data Reveals Efficiency of Customer Acquisition
Many investors understand that growth-stage companies are inefficient at customer acquisition. GTM teams willingly admit they waste up to 21 percent of marketing budgets because they don’t have accurate data about their customers.
These teams face a number of obstacles in capturing data. Imagine improving that efficiency by a small margin by having a better idea of who to target, or having the right messaging.
Just a 25 percent gain in efficiency would drive an even larger output efficiency. It could mean the difference between spending the same amount of money and bringing in $13 million instead of $10 million.
#2: Data Helps Identify Friction Points in Your Go-to-Market Process
The reason there's so much inefficiency or non-productivity in these growth-stage customer acquisition engines is because of friction points throughout the process.
What that means: Revenue leaders aren’t able to manage their teams or strategies with enough precision to identify what their friction points are.
Some friction points that quality data can uncover:
- Suboptimal strategies for sourcing leads or prospects
- Opportunities for performance improvement for individual sales team members
- Improper targeting of prospects
- Misalignment of messaging with prospect pain points
You can also uncover friction points not only internally, but externally with your customers, too.
#3: Data Can Help Refine and Dial In Your GTM Strategies
The more granular or detailed you’re able to measure your go-to-market process, the more precisely you will be able to optimize and manage for success.
Think about your home thermostat. What if it could only be adjusted in increments of 10 degrees? It’d be difficult to adjust the room temperature to get it right where you want it. Now think about that same thermostat with the ability to adjust it within one degree; it's a lot easier to adjust.
Similarly, think about your lead-to-deal process. It’s common to measure the top-of-funnel conversion (leads that turn into opportunities) and the bottom-of-funnel conversion (opportunities that turn into Closed Won deals). But that data doesn't help the revenue leader understand the reasons why leads failed to convert to opportunities.
There could be a number of reasons, from lead quality, to effectiveness of marketing-to-sales handoff, to the sales conversations themselves. These activities are known as middle-of-funnel, and they’re often forgotten in the measurement process.
By adding middle-of-funnel measurements to the data model, a company is more precisely able to understand the primary reason for leakage in the funnel.
And by having that more precise understanding, they're actually better informed to take action. Without that understanding, you’re just speculating on the actions you need to take to improve your growth.
How to Improve Your Go-to-Market Data Capture and Measurement
But what is the best way to capture and measure go-to-market data so that you can improve your acquisition efficiency?
A layered data infrastructure is the way to go, which offers:
- A conscious data model that determines what needs to be measured, and how to measure it
- A go-to-market tech stack that can capture the data
- Data integrity mechanisms that either fully automate or confine data capture methods to keep the data accurate
Implementing a layered data infrastructure takes time and planning among your go-to-market team. But it’s vitally important to start as early as you can.
Why? GTM data predominantly resides in the CRM and is notoriously plagued with data integrity or hygiene issues. Many people interact with the CRM and document data in their own ways. Having a data infrastructure helps alleviate the burden on sales and marketing teams to accurately track and keep data in the CRM.
Once you have the infrastructure in place, you will be able to continuously monitor your CRM for any data anomalies and expose those in real time. That way you can capture issues before they sit quietly and fester into something significant.