Article
Why Keeping B2B Profiles Up-to-Date Boosts Sales & Marketing Success
Best Practices: Data Quality
Keeping B2B buyer profiles up-to-date is essential for maintaining effective sales and marketing strategies. Unfortunately, keeping profiles up-to-date is tedious and often neglected. Failing to update our customer or buyer profiles does your sales and marketing teams a tremendous disservice. Your teams could spend thousands of dollars and weeks of focus trying to get in touch with a great lead from last year, completely unaware that the person changed jobs three months ago – all because their profile within your CRM and marketing automation systems wasn’t up-to-date. People change jobs and companies go throughM&A all the time – and your sales and marketing teams need to stay informed. That’s just one of the many ways your teams will lose with outdated buyer profiles. Having accurate, up-to-date data seems like a no-brainer, right? Let’s consider why many sales and marketing teams don’t always have the data they need.
It takes a lot of buying signals to build the buyer profiles that our sales and marketing teams need to win business. Firmographics, demographics, technographics, intent, 1st-party data, predictive and engagement. Generally speaking, we can’t get all of those signals from one place. Instead, we’re forced to buy numerous sets of static data from several vendors, then blend it all together. Buying multiple sets of data from multiple sources is inherently expensive, and manually combining that data with our first-party data is time-consuming, cumbersome and error-prone. We might jump through those hurdles at first, but the problem arises when we need to update it.
A static data set is just a snapshot in time, and there’s no way to tell when data has changed to the point where you need a new snapshot. This means that in order to ensure our buyer profiles are up-to-date, we need to regularly buy all of our data over and over again, continuously blending it all together with the old data. That’s going to be very expensive, and it’s going to require a lot of time and effort dedicated to data unification. In many cases, by the time you’ve enriched your new data with the old data, that new data has already become old data. Naturally, many companies will decide that their slightly old data is good enough because they can’t justify the cost of constant data purchases or the time spent unifying it.
Not updating your buyer profiles is a huge mistake in a world of data-driven decision making, where all of the decisions you make depend on having accurate, complete and up-to-date data. Even the best predictive AI models will point you in the wrong direction if the data being analyzed isn’t correct. Simply put, if you want your sales and marketing teams to have the tools they need to reach out and close business, you need to give them buyer profiles that are dynamically updated.
Let’s look at 10 common strategies for ensuring that your buyer profiles are current and accurate, then consider a more realistic solution for automating the entire process.
Automated Data Enrichment
Latest Articles
Article
How Do You Calculate Match Rate on B2B Data?
Your CRM has thousands of records. Your marketing automation platform is loaded with contacts. Your outbound sequences are running. But when you try to enrich those records, route leads to sales, or fire a signal-based workflow, a large portion of your data simply does not match.
Match rate is the metric that tells you how much of your data is actually usable. For revenue teams running enrichment programs, account-based campaigns, or automated scoring, this number carries real operational weight. A low match rate means your workflows are running on incomplete information, your segments are thin, and your automation is making decisions with missing context.
Understanding how to calculate b2b data match rate, and what actually drives it, is one of the most practical things a RevOps or marketing ops leader can do to improve GTM performance.
Article
What Is Signal-Based Selling?
Your CRM is full of contacts. Your marketing automation platform fires campaigns on schedule. Your sales team works the list. And yet, deals stall, outreach lands flat, and pipeline forecasts drift further from reality every quarter.
The problem is not effort. The problem is timing.
B2B sales teams have spent years optimizing how they reach buyers. Very few have focused on when buyers are actually ready to engage. Signal-based selling changes that equation entirely. It shifts your go-to-market execution from a calendar-driven model to a behavior-driven one, so your team shows up when intent is live, not when the cadence says it is time.
This post breaks down what signal-based selling is, why it matters now, and what your revenue infrastructure needs to support it at scale.
Article
Aligning marketing and sales on inbound SLAs that work
Your inbound engine breaks when marketing and sales work from different clocks, different definitions, and different routing rules. That gap shows up fast in missed follow-up, weak conversion, and low trust across teams.
If you want inbound SLAs that hold up under volume, you need more than a handoff document. You need aData Management System that keeps records clean, routes leads with context, and gives both teams the same operating view.
That is the GTM alignment moment most teams miss. Marketing says the lead hit the threshold. Sales says the lead lacked context, landed late, or reached the wrong rep. Both teams look at the same funnel and see different stories.
A working SLA removes that ambiguity. It ties response time, routing logic, ownership, and enrichment to a shared data foundation.
