Article
Top 10 Questions About Intent Data From B2B Sales, Marketing and GTM

Understanding buyer intent is critical for B2B sales and marketing teams looking to engage prospects at the right time. Intent data provides real-time insights into which companies are actively researching solutions, allowing teams to prioritize high-value accounts, personalize outreach, and accelerate deal cycles.
However, many businesses still have questions about how intent data works, the insights it provides, the limitations it has, how it’s integrated into GTM strategies, and how to measure its impact. In this blog, we’ll answer the top 10 most common questions about intent data, covering everything from its potential and limitations to lead scoring and integration. Whether you’re new to intent data or looking to refine your strategy, this guide will help you make the most out of your intent data.
Here are 10 frequently asked questions surrounding intent data that reflect the core interests of sales and marketing professionals who are looking to harness intent data for more targeted, efficient, and impactful outreach. Let’s dive into them from a B2B sales, marketing, and GTM perspective:
2. How accurate and reliable is intent data? What methods are used to ensure the data reflects genuine buying intent?
Latest Articles

Article
You're Prospecting Blind: How B2B Intent Data Fixes the Timing Problem Every SDR Has
The timing problem nobody accounts for
Your SDR sends 500 cold emails on Monday morning. By Friday: 12 have replied, 3 have booked meetings, 2 will become real opportunities. The other 488? Many were not in-market at all. Some had just renewed with a competitor. Some had no active budget cycle. A few — and this is the part that stings — were actively evaluating solutions exactly like yours. You just had no way of knowing.
That is not a volume problem. That is a timing problem. And B2B intent data is how you fix it.
Intent data identifies the small, time-sensitive subset of accounts in your total addressable market that are actively researching solutions like yours right now — before they fill out a demo form, before they appear as an inbound lead, before your competitors know they are evaluating. Signal-qualified leads — accounts flagged by buying intent before outreach — drive 47% better conversion rates, 43% larger deal sizes, and 38% more closed deals. Not because of better copy or a stronger email sequence. Because they were genuinely ready to buy when you reached them.

Article
Why Your Cold Emails Aren't Getting Replies (It's Not Your Copy)
The number that exposes the real problem
Generic B2B cold email achieves a 3.4% reply rate on average. Signal-personalised outreach — where the message references a specific buying trigger — achieves 18%. Same SDR. Same inbox. Same writing quality. The difference is entirely in who you are targeting and why you are reaching out at this particular moment.
Most SDRs and sales managers look at low cold email reply rates and immediately reach for copy solutions: better subject lines, shorter emails, new opening lines, different calls to action. Sometimes it helps. Usually it moves the number by fractions of a percent. Because the problem is not the copy. It is the targeting and the timing.

Article
Why Your SDR Stack Is Slowing Your Reps Down (And the 7 AI Sales Tools That Actually Help)
The productivity trap disguised as a tech stack
The average SDR in 2026 switches between 8–12 tools every single day. CRM, sequencer, enrichment platform, LinkedIn Sales Navigator, intent data dashboard, email validator, dialer, calendar tool, Slack, Chrome extension for this, browser plugin for that. Each context switch, according to UC Irvine research, costs 23 minutes of refocus time. Over a full working day, that is hours lost — not to bad prospecting, but to the tools that were supposed to fix it.
Most SDR tech stacks were not designed to make reps faster. They were built to give managers visibility, give RevOps control, and give procurement something to sign. The individual rep using them every day is an afterthought.
The result: 81% of sales teams claim to have implemented AI in their sales motion. But only 19% of reps actually use the AI features built into their tools. The rest are copy-pasting into ChatGPT and calling it signal-based selling. The gap between what companies claim to deploy and what reps actually use defines the SDR productivity crisis in 2026 more than any single tool choice.
The AI sales tools that actually move pipeline are not the ones with the most integrations. They are the ones that get out of the rep's way.
This is the honest ranking. Seven tools, each evaluated by one question: does this reduce the time between a buying signal appearing and your SDR's first touch?


