Article
New Logo Land: Aligning Intent and Tech Install for New Business
Best Practices: Intent & Technographic Data
In B2B sales and marketing, timing is everything – and relevance is your secret weapon. The best Go-to-Market (GTM) teams know that simply identifying companies in your Total Addressable Market (TAM) isn’t enough. To win new business, you need to know who’s in-market and why they’re a good fit. That’s where both intent data and technographic data come into play.
Individually, each signal offers deep insights into buying behavior and customer fit. However, using them together unlocks an unfair advantage: the ability to engage the right accounts at the right time with the right message.
What Is Intent Data?
Intent data reveals which companies are actively researching topics relevant to your product or solution. Intent data is collected through:
Web content consumption across publisher networks
Search behavior
First-party engagement (e.g., email clicks, site visits)
Third-party behavioral signals (e.g., Leadspace)
Intent data tells you which companies are showing signs that they might be in-market this week.
What Is Technographic Data?
Technographic data tells you what tools, platforms, and technologies a company is currently using – or used in the past. This includes:
CRM, marketing automation, cloud providers, security tools, hardware, some services, etc.
Recently adopted or dropped technologies
Tech maturity and compatibility with your offering
Technographic data tells you if an account is a good fit for your product based on their technology stack.
More Powerful Together
Intent and technographic signals are useful by themselves, but they become much more powerful when used in combination. By aligning on both signals, sales and marketing teams are able to:
Pinpoint High-Fit, High-Intent accounts. When a company is actively researching a problem you solve and has the right tech stack to support your solution, they jump to the top of the priority list.
Accelerate pipeline with precision outreach. Technographics inform how your solution fits, while intent shows why the timing is right. This enables reps to craft personalized, relevant outreach that resonates immediately.
Customize messaging by tech environment. Your messaging should adapt based on what tools the prospect already uses. If someone is using your competitor, you can highlight migration advantages. If they lack a key dependency, you can qualify them out early – or position an add-on strategy.
Fuel Account-Based Marketing (ABM) campaigns. Layering intent and technographics lets marketing launch highly targeted ABM campaigns based on real signals – not guesswork. Target only those showing buying intent and product compatibility, increasing conversion rates and reducing ad waste.
Improve AI scoring models. Technographic and intent data are both strong predictors of purchase behavior. Feeding these into your AI scoring engine enhances accuracy – helping your GTM teams prioritize the right accounts across your TAM.
Basic Steps to Aligning on Intent and Technographic Data
Step 1: Define your Ideal Customer Profile (ICP).
Start with clarity. What tech stack characteristics define a good-fit customer? What intent topics map to buying triggers?
Step 2: Integrate data sources.
Connect your intent provider with your technographic data source. Feed both into your CRM or CDP to build unified account views.
Step 3: Build precision segments.
Use filters to create dynamic segments like:
Companies using X + researching topic Y in the past 2 weeks
Accounts showing intent that also use your competitor’s product
Prospects with complementary stack but not yet in-market (for nurture)
Step 4: Segment Fit Scores.
Filter segments for High-Fit scores (e.g., Leadspace) to ensure the company is a firmographic match to your Ideal Customer Profile (ICP).
Step 5: Activate sales and marketing plays.
Turn data into action:
ABM ad campaigns targeting top matched accounts
Sales sequences personalized to current tech and pain points
Content offers aligned with intent topics and stack maturity
Step 6: Measure and optimize.
Track pipeline velocity, win rates, and engagement for accounts surfaced by this combined approach – and refine your ICP, scoring models, and outreach accordingly.
Conclusion
In the noisy B2B landscape, relevance is what cuts through. By aligning Intent data with Technographic data, sales and marketing teams can stop chasing every lead – and start focusing on the right opportunities at the right time. This isn’t just smarter marketing. It’s a competitive edge that helps you move faster, convert better, and land more new business – especially in a world where precision is everything!
For more information about Leadspace’s Intent offering, get the product sheet here. Stay tuned for our next blog series, where we will explore the importance of maintaining accurate customer data with a strong Identity Resolution framework when implementing AI scoring models.
Latest Articles
Article
How to audit and fix duplicate CRM records in 2026
Your CRM is supposed to be the system of record for your entire go-to-market operation. In practice, it often becomes a graveyard of duplicate contacts, mismatched accounts, and stale fields that no one trusts. When that happens, every downstream system that depends on CRM data starts making bad decisions.
Scoring models weight the wrong signals. Routing sends leads to the wrong reps. Segmentation breaks. Campaigns reach the same buyer five times across three different records. The problem is not that your team is careless. The problem is that CRM data quality issues compound fast, especially when you are pulling data from multiple sources and running enrichment at scale.
This guide walks through how to find the root causes of duplicate records, build governance rules that hold, and maintain data validation and cleansing as an ongoing operation rather than a quarterly fire drill.
Article
Measuring TAM coverage, not just TAM size
You already know your TAM number. That number looks useful in planning decks and board slides. It tells you how many accounts fit your ICP and how much revenue sits in the market.
It does not tell you whether your team has enough territory coverage to work that market well.
That gap matters. In outbound TAM development, territory performance depends on coverage over volume. If you assign a large market without measuring who you can reach, who you can route, and who you can engage across the buying group, you create blind spots inside your territory model.
This is whereEnterprise Data Management becomes operational. It gives you a way to measure TAM coverage at the account, contact, and buying group level. You stop asking how big the market is. You start asking how much of it your team is equipped to work right now.
Article
Turning account engagement into buying momentum with Custom Audiences
Account engagement rarely fails from lack of activity. It fails when you see activity at the account level but miss who is driving it, how interest is spreading, and when to act. That gap slows follow-up, weakens targeting, and leaves pipeline exposed.
If you want stronger account engagement, you need more than account coverage. You need Custom Audiences built from buying-team signals. That gives you a way to move from broad account reach to coordinated influence across the people who shape a deal.
That shift matters because B2B buying is already group-driven. According to 6sense research, 92% of B2B purchases involve groups of three or more people. A lead-centric model misses that reality. Your targeting should reflect the full buying team.
