Product sheet
Building B2B Buyer Profiles
The goal? To deliver effective campaigns targeted at the best opportunities within our Total Addressable Market (TAM) – at the lowest cost.
Doing this successfully starts with creating complete, accurate, dynamic and unified buyer profiles of people, accounts and buying centers so we can properly prioritize and target opportunities with data-driven assurance that we’re delivering the right message to the right people at the right time. Unfortunately, building robust buyer profiles is a complex, cumbersome process – and it usually isn’t cheap.
Meanwhile, your data is decaying. Data decay is an issue that every company faces – especially after the pandemic. As the business environment restructures itself in the post-pandemic era, a new symptom is spreading among companies: millions of workers are quitting their jobs. People and companies change constantly. Companies make acquisitions, people change jobs, and intentions are dynamic. This means your buyer’s data changes every day – but does your database reflect that? Is the data you use to drive your business as accurate as the day you procured it? Historically, achieving that high-quality, up-to-date B2B buyer data has been much easier said than done.
Latest Articles
Article
The Hidden Revenue Tax: 10 Ways Enterprise GTM Teams Lose with Disconnected Data
Enterprise B2B go-to-market (GTM) teams don’t struggle because they lack tools. They struggle because their customer data lives everywhere, but doesn’t work correctly anywhere.
CRM. Marketing automation. Enrichment vendors. Intent platforms. Sales engagement. Data warehouses. Acquired company databases. Regional instances.
Each system holds a piece of the puzzle but none of them independently point towards the same truth. When customer data is fragmented, siloed, and static, the consequences surface exponentially.
Here’s what that really looks like inside an enterprise GTM organization.
eBook
How GTM Teams Can Future-Proof Their Data Architecture for 2026 – 2030
B2B go-to-market teams are entering a new era defined by AI-driven execution, buying group complexity, and real-time buyer signals. Yet most GTM data architectures still rely on fragmented systems, static enrichment, and lead-centric models that cannot support modern revenue operations.
How GTM Teams Can Future-Proof Their Data Architecture for 2026–2030 explores the structural shift reshaping B2B GTM and outlines the data architecture required to support identity resolution, buying group intelligence, AI-ready workflows, and real-time signal activation.
This eBook provides a practical roadmap for building a resilient, enterprise-grade GTM data foundation without disrupting your existing CRM, MAP, ABM, or analytics stack.
Article
Why Data Governance Is Now a Revenue Function
For a long time, data governance lived in the background of the business.
It sat inside IT. Sometimes legal. Occasionally security... It was something you needed for compliance audits, privacy policies, and system hygiene, but it rarely gets associated with pipeline creation or revenue performance. If anything, governance was seen as something that slowed go-to-market teams down. It was an approval layer or process hurdle that prevented a campaign from launching this week.
But that mental model was built for a very different GTM environment than the one enterprise revenue teams are operating in right now.
