If you’ve got a pile of leads but keep hearing “not a fit” or “not interested,” it might be time to look closer at your data. It’s not always about getting more leads—you want better ones. That’s where technographics come in: data about the tech your leads actually use. If you’re tired of guessing which companies use Salesforce, AWS, or your competitor’s product, this guide will show you how to add that missing context with Hginsights.
This is for anyone who’s stuck with a spreadsheet or CRM full of basic info—company name, maybe an industry guess, and not much else. If you’re in sales, marketing, or operations and need to cut through the noise, keep reading.
Why bother with technographics?
Let’s be real: contact info and company size aren’t enough. You want to know:
- Do they use software you integrate with?
- Are they already using (or spending big on) your competitor?
- Is your product even relevant for their tech stack?
Technographics help you avoid pointless outreach and target the right prospects. They can also help you personalize your pitch (“We see you’re on Marketo, so here’s how we help…”). But don’t expect them to solve everything—bad fit leads are still going to slip through, and no database is perfect.
What you need before you start
- A list of leads. At the very least, company names and domains. The more accurate, the better.
- Access to Hginsights. You’ll need an account or a data subscription. (Sorry, there’s no magic free version.)
- A way to match data. Excel, Google Sheets, or a CRM—doesn’t matter, as long as you can import/export data and do some basic matching.
That’s pretty much it. If you’re hoping for a one-click “make my leads better” button, you’ll be disappointed. There’s a bit of manual work, but it’s not rocket science.
Step 1: Get your lead list in shape
Before pulling in any technographics, make sure your lead data isn’t a mess. Here’s what actually matters:
- Company name: Try to use the “official” name. “IBM” vs. “International Business Machines” can trip things up.
- Website domain: This is the gold standard for matching. If you don’t have it, scrape it or use a service to look it up.
- Other IDs: If you already have LinkedIn Company IDs or something similar, great—but not required.
Pro tip: If you’re working from a CRM export, double-check for duplicates and weird formatting. Clean data now saves headaches later.
Step 2: Get technographics from Hginsights
This is the part that trips people up. Hginsights offers different ways to pull technographic data. Which you pick depends on your setup (and budget):
- CSV Export: The most straightforward. Log in, pull the tech data you need, and download as CSV.
- API Integration: If you want to get fancy and automate updates, Hginsights has an API. Just be ready to wrangle some code or ask Ops for help.
- CRM Integration: Some versions support direct integration into Salesforce or others. It’s slick, but setup can be a pain and depends on your plan.
What data should you get? - List the specific technologies you care about (e.g., “Salesforce,” “AWS,” “ZoomInfo”). - Look for install dates, spend estimates, and other signals—not just “yes/no” if possible. - Don’t download everything “just in case.” More columns = more chaos.
What doesn’t work: - Relying on vague categories (“uses CRM software”). Get specific. - Expecting real-time data. All these databases lag behind reality. - Downloading the entire technographic universe. You’ll just slow yourself down.
Step 3: Match technographics to your leads
Now comes the grunt work: joining your lead list with the Hginsights file.
- Use the domain: This is usually the most reliable match key.
- If you have to use company name: Clean and normalize both lists first (remove “Inc.”, “Ltd.”, etc.).
- Fuzzy matching tools: If you’re dealing with “Acme Corp” vs. “Acme, Inc.”, try Excel’s Fuzzy Lookup Add-in, Google Sheets’ MATCH functions, or more advanced tools like OpenRefine.
How to actually do it:
- Pull both your lead list and the Hginsights export into Excel or Sheets.
- Use VLOOKUP, INDEX/MATCH, or similar functions to pull tech fields into your lead list.
- Spot-check a few matches before moving on. Don’t trust automation blindly.
Pro tip: Don’t get lost trying to match every single lead. Some companies just won’t have technographic data. That’s normal.
Step 4: Decide how to use the new fields
This is where people overcomplicate things. You don’t need to build a machine learning model. Start simple:
- Segment your list: Filter out companies that don’t use key technologies, or highlight those that do.
- Personalize outreach: Add a field to your email template—“We see you use X, here’s how we help.”
- Score leads: Give a bump to those with the tech you want, or downgrade the ones who already use a competitor.
What matters: - Focus on 1–3 key techs. Don’t try to use 50 columns. - Test on a small batch first. See if you actually get better replies or conversions.
What to ignore: - Don’t expect miracles. Some companies look great on paper and still ghost you. - Don’t get hung up on missing data. It’s just one signal, not gospel truth.
Step 5: Keep your data fresh (or at least not stale)
Technographics aren’t static. Companies add and drop tools all the time. Here’s what’s worth doing:
- Refresh quarterly if you can. Annually at minimum. Set a calendar reminder.
- Spot-check big deals before you reach out. If you’re chasing a whale, double-check their stack manually.
- Don’t obsess over perfection. 80% up-to-date is better than 100% out-of-date.
What works, what doesn’t, and what’s just hype
What works: - Using specific tech data to qualify or prioritize leads. - Personalizing outreach with a nod to their tech stack. - Quickly disqualifying leads that are a dead end for your product.
What doesn’t: - Blindly trusting every data point. There’s always some lag or error. - Assuming technographics will solve your pipeline problems alone. - Downloading every possible field and drowning in details.
Ignore the hype: - No, “AI-powered intent signals” and similar buzzwords don’t magically find you perfect leads. Start with the basics and work up from there.
Keep it simple (and keep improving)
The real value of technographic enrichment is focus. You’ll waste less time, have slightly smarter conversations, and maybe close a few more deals. Start small: pull in two or three data points, test your new process, and fix what’s broken before scaling up.
Don’t wait for perfect data or fancy tools. Do the basics well, and iterate as you go. If you get stuck, ask yourself: “Is this actually making my list better, or just making it bigger and messier?” You’ll know the answer.