Technographics
Verified technology installations at the product and location level
What is it
Technographics reveal which technology products a company has deployed — not at the vendor level, but at the specific product level. HG tracks over 26,000 products with verified install data across categories like CRM, ERP, cloud infrastructure, cybersecurity, marketing automation, and more.
Every install record includes the product name, vendor, category, the date HG first detected it, the locations where the product was detected, the date it was last verified, and an Intensity score. Intensity reflects the number of unique dates HG has detected that technology at that company. Higher intensity means higher confidence in the install and a more entrenched footprint. Lower intensity means less confirmed adoption.
What problem it solves
Technology stack is one of the strongest predictors of fit, intent, and timing in B2B. Most teams either don't have that data, or they're working from data that's inferred, outdated, or too broad to act on.
HG's technographics are verified at the product level and continuously refreshed. That means you're not guessing on fit, guessing on competitive exposure, or guessing on timing. You know which accounts run your competitor, which ones are architecturally ready for your product, and which ones are likely in a buying window.
What you can do with it
- Competitive displacement: Find companies using a competitor and target them for switch campaigns
- Complementary selling: Target companies using products you integrate with
- Whitespace analysis: Identify accounts without any solution in your category
- Account scoring: Score accounts by the presence of competitor, partner, or complementary technology installs
- Personalized outreach: Reference specific products in prospecting
- Market Analysis: Track technology adoption trends by industry, company size, or region
Real-world example
Competitive Displacement Campaign
A cybersecurity vendor wants to identify enterprise accounts using an older endpoint protection product. Using Technographics, it builds a segment of 2,000 companies with verified McAfee ePO installs, then filters that list for companies with $1M+ in security spend and active lower-funnel research intent for security products on TrustRadius.
The result is a high-confidence target list of accounts running a competitor, with the budget capacity to switch and signals that they are actively evaluating alternatives. Conversion rate: 3x higher than generic outreach.
Example Data
Walmart Inc. — Top 5 Database Management System Installs
| Rank | Product | Vendor | Intensity | Locations | Last Verified |
|---|---|---|---|---|---|
| 1 | MySQL | Oracle Corporation | 4,576 | 121 | Jul 2026 |
| 2 | Microsoft SQL Server | Microsoft Corporation | 4,538 | 124 | Jul 2026 |
| 3 | Apache Cassandra | Apache Software Foundation | 4,263 | 101 | Jul 2026 |
| 4 | IBM Db2 | IBM Corporation | 4,219 | 45 | Jul 2026 |
| 5 | Oracle Database | Oracle Corporation | 4,194 | 93 | Jul 2026 |
- Intensity = count of detections; higher means deeper deployment.
- Locations = distinct sites where the product was detected.
How to read it
Open source is king
MySQL and Cassandra — both open source — rank #1 and #3. Walmart values cost efficiency and engineering control over vendor lock-in, and isn't afraid to run OSS at scale.
NoSQL has a seat at the table
Cassandra's presence indicates distributed, high-write workloads — likely real-time inventory, e-commerce transactions, or IoT from stores and warehouses.
The legacy footprint is real
IBM Db2 and Oracle Database are still in play, verified as recently as July 2026. These are probably core financials, supply chain, or SAP integrations that are expensive and risky to migrate.
Microsoft is strong but not dominant
SQL Server shows solid intensity but doesn't dwarf the others. Walmart isn't a “Microsoft shop” for databases.
So what? The sales angle
If you're the incumbent
Oracle, Microsoft, IBM — you're in, but you're not safe.
- Embedded, not irreplaceable. Walmart clearly shops around. Five platforms at comparable intensity means every workload was a decision, and can be re-decided.
- Expansion is real but contested. Growth opportunities exist — you're competing for that budget against OSS alternatives that cost nothing in license.
- Watch the modernization risk. Any modernization initiative could prioritize cloud-native or OSS replacements over renewing you.
If you're the challenger
Snowflake, Databricks, MongoDB, CockroachDB — this data is your opening.
- Target the legacy systems. Db2 and Oracle are verified but likely technical debt. Lead with a migration story: move off legacy RDBMS to cloud-native without rewriting apps.
- Complement, don't replace — yet. They already run Cassandra, so they're OSS-friendly. Pitch “add this for this specific workload” rather than rip-and-replace.
- Follow the Cassandra signal. Cassandra means teams comfortable with distributed systems. That's the entry point for NoSQL and NewSQL plays.
- Use the fragmentation. Five database platforms across 100+ locations is operational overhead. Consolidation is a CFO-friendly story.
Business impact
Increases: Higher conversion on displacement campaigns vs. generic outreach
Decreases: Shorter sales cycles when reps already know the stack
Increases: More relevant marketing campaigns
Decreases: Less rep time spent on discovery
Directional outcomes HG customers commonly report. Actual results vary by program and data application.
Under the hood
How it's unique to the market
HG Insights Technographics delivers verified, product-level install intelligence with the organizational context GTM teams need to act on it. Rather than stopping at a vendor-level view, HG identifies the specific products a company uses and resolves those deployments to the relevant company, subsidiary, and location.
Each install record brings together multiple signals to show not only what technology is in use, but where it is deployed, the strength of the observed signal, and when it was last verified. This gives sales, marketing, and strategy teams a more precise view of an account’s technology environment—supporting competitive displacement, complementary selling, account prioritization, and market analysis.
How it's derived
HG's tech detection engine processes billions of documents from job postings, resumes, web crawling, and third-party feeds. A token matching system (positive and negative tokens) identifies product mentions. Each mention is resolved to a company location via CID matching. Intensity = the count of positive detections for a product at a company, giving a signal of deployment depth.