3 Ways B2B Startups Can Solve Their Biggest Go-to-Market Data Integrity Issues

How healthy is your data integrity? According to many B2B revenue leaders, their data and methods of measuring key performance indicators could use a checkup:

• 44 percent of companies cite CRM data quality as one of the top contributors that leads to forecast inaccuracy.
• On key sales metrics, 75 percent of companies lack company-wide definitions. 
• Only 9 percent of marketers are “mostly” or “completely” confident that their data meets their standards.

There are a couple of common problems that revenue leaders face when it comes to their sales and marketing data quality. 

B2B Companies Often Lack a Strategic Data Model

A data model is an undervalued component to an organization’s foundational go-to-market (GTM) tech stack. 

Every marketing and sales software (such as the CRM, marketing automation platform, or sales enablement software) has their own natively, built-in data model (AKA way capturing, storing, and categorizing data).

But those tools were built first and foremost to make the jobs of sellers and marketers easier. They weren't built with the goal of giving great data to revenue leadership teams.

It's on the revenue leaders, RevOps team, and analysts at your organization to determine what data you need to capture to manage the business, and then modify those software tools so they capture all of that data.

What is a go-to-market data model? Think of a data model as the underlying blueprint and source of truth to your GTM strategy: What data points need to be captured and measured through your tech stack so your revenue leaders can make informed business decisions? Do you have a singular definition of the data points that need to be tracked? Are your teams aware of how that data flows into your systems? 

Revenue leaders often purchase tech stack tools before defining their data model. It results in poor standardization of data, confusion around data input, and overall frustration with reporting. 

Other times, when the sales and marketing teams have thought about the go-to-market data model—it was thought about separately. The sales team handles its own data model in their tools, and the marketing team manages their data in separate tools. The result? Siloed data that makes alignment and reporting difficult. 

Poor Data Hygiene and Data Integrity in the CRM

As B2B companies scale, the desire to fit a square peg into the circle hole also grows. The systems and processes that worked at an earlier stage are often not sustainable as the number of customers serviced and prospects reached increases. 

What does poor data integrity look like in a growth-stage company? 

• Overly customized fields with lack of standardization
• New changes to the CRM with new sales and/or marketing leaders
• A heavy reliance on sales and marketing teams to input data correctly and upkeep data quality  
• Lack of parameters or change control so the CRM is exposed to changes, rendering historical data obsolete

Steps to Elevate Your Go-to-Market Data Integrity

What are the steps that you can take to elevate your go-to-market data integrity so that your revenue engine is fully aligned?

Treat customer acquisition/new revenue acquisition holistically

Having your sales, marketing and customer success teams work together creates transparency and streamlined movement toward the strategies that each team is responsible for.

Many companies are now appointing revenue operations teams that oversee the alignment between all parts of the organization’s revenue acquisition, including sales, marketing, product, and customer success. 

Hire a business analyst early

In the early stages of a company’s growth, the person who often handles the CRM technical implementation is usually head of marketing or sales. As the company grows, the leadership team usually hires a CRM administrator who has the junior technical skills to manage the CRM but may not have the analyst skills to provide in-depth analysis into that data.

A business analyst—especially if they report to a revenue or go-to-market team—can take responsibility for reporting insights into the data that’s captured in the tech stack, so that the sales and marketing leaders can make efficient business decisions.

Ensure cultural sanctity of data

There is a culture component to elevating your data integrity that requires the entire company to place importance on data management and integrity. Holistically, everyone has to believe in it and be advocates for treating the go-to-market data model as the source of truth. Once the company is aligned on making a strategic definition of the data model, all decisions can flow from there.

The importance of a go-to-market data model can not be overstated; being intentional and strategic about the way data is captured in your go-to-market tech stack can directly impact the strategies your team chooses to invest in.