Article
Taking the Guesswork Out of Sales & Marketing
Best Practices: GTM Targeting

Table of Content
It’s always that time of year – in sales and marketing we’re always starting a new quarter, ending a new quarter, trying to create demand for the following year or just planning. We always want to start strong and grow better. Let’s assume you start strong. But how do you grow better? How do you outsmart the competition? How do you create sales and marketing systems that help identify the leads that matter? We need to create a system to identify these closeable leads so that sales teams can understand which deals that they can count on for revenue going forward.
I hosted a webinar where we explored how to up the odds of your marketing and sales campaigns’ success. Closeable revenue is all about the math. Whether that revenue is from demand generation, new opportunities, leads, etc. These days it’s easy (or should be easy) to use systems to determine those opportunities and leads that will convert into closeable business.
We dove into the 6 steps to increase the odds of building closeable demand and closeable business. It boils down to creating the right profile so you can target the right audience and then building models to understand and categorize which are the right accounts/people to go after. Figuring out which are the best models to identify and categorize leads. Building campaigns using AI to optimize and go after the right kinds of companies and people. Testing the models to identify and evaluate the right results. And finally, do this across both sales and marketing to ensure both teams are fully aligned. So what are the right questions to ask as you go through these steps?
Step #1: Build Better Buyer Profiles – How do you build Buyer Profiles? Do you have a customer data project? Customer Data Platform? How often is it updated? Is it shared across GTM? What’s the breadth of data sources?
Step #2: Target Your Ideal Buyer & TAM – Targeting is easy once you have models. Have you created a model, or is it at least in your head? What are the buying signals that matter? How many lookalikes in the world? Which territory is your next best place?
Step #3: Create Your Buyer Model – Better campaigns are all about “lift” – propensity, persona and intent. How does industry, persona, tech install, engagement or company specialty fit in?
Step #4: Optimize Your Campaigns – Campaign to Buyers and Buying Team combinations by propensity, persona and intent. Do you understand which regions convert with which products or personas?
Step #5: Put Your Buyer Model to the Test – Increase lead flow by removing friction. Are you using A/B testing to formulate GTM campaigns and how much engagement is needed? Are you doing territory and ABM investment tiering based on GTM science?
Step #6: Align Marketing & Sales with Your Buyer Data Platform – Are both sales and marketing aligned together on the same customers and prospects to deliver the outcomes? Are both teams together leveraging the profiles and funnel optimization techniques to deliver better growth? Is there an aligned measurement system to track what you manage?
These are the six steps that I use in building scalable and closeable demand. Explore what we found really works and what is delivering today with results for sales and marketing professionals worldwide with respect to each of these 6 steps by watching last month’s webinar, Taking the Guesswork out of Sales & Marketing.
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?


