If you've ever tried to figure out which technology stacks companies are actually using, you know it's messier than it looks. Maybe you're in sales, doing market research, or just plain nosy. Whatever your reason, building accurate technology adoption reports is tricky — and if you use Similartech, you’ve got a powerful tool, but not a magic wand. Here’s how to squeeze the most truth out of your adoption reports, avoid the common traps, and skip the fluff.
1. Know What Similartech Can (and Can't) Do
Before you even hit “export,” get real about what Similartech is tracking. It’s not reading minds. It crawls the public web, scanning sites for evidence of technologies in use. That means:
- It sees what’s public. Anything server-side (like a database or custom backend logic) is mostly invisible unless the site leaves clues.
- It’s strongest with front-end tools. Think analytics scripts, CMSs, e-commerce platforms, chat widgets, and so on.
- Coverage isn’t perfect. Not every site is crawled equally often. Some may be missed or outdated in the index.
Don’t: Assume the data is gospel.
Do: Treat the report as a very strong hint, not a sworn affidavit.
2. Define Your Scope (and Don’t Get Greedy)
The biggest mess-ups happen when you try to cover too much at once. Get specific:
- Are you looking at a single vertical? E.g., only SaaS companies, or just retailers?
- What regions matter? US, global, Europe only?
- Which technologies do you actually care about? Hundreds will show up. Don’t report on everything “just in case.”
Pro tip: Make a shortlist of the tech you actually care about before you start. Otherwise, you’ll drown in noise.
3. Get Your Target List Right
Accuracy starts with the sites you’re analyzing.
A. Use a Clean and Relevant Domain List
- Start with a verified list. Don’t just grab “top 1M” domains — a lot are dead, spammy, or irrelevant.
- Scrub duplicates and oddballs. Watch out for subdomains, testing environments, or typo domains.
- If you’re analyzing your own accounts, double-check for errors or outdated entries.
B. Don’t Rely on Built-In Filters Alone
Similartech has some filtering (like by country, traffic, or category), but it isn’t perfect. Manual spot checks never hurt.
4. Pick the Right Technologies to Track
Not every technology is detectable, and not every detection means “this company is all-in.”
- Stick to technologies with solid detection rates. Google Analytics, Shopify, WordPress — these are easy. Niche or custom tech? Much harder.
- Be skeptical of generic results. “jQuery” shows up everywhere, and doesn’t tell you much.
- For SaaS or APIs: If it’s not visible in public-facing code, Similartech probably won’t catch it.
Ignore: Overly broad categories or vague “widgets” — they don’t give you much actionable data.
5. Set Up Your Report Thoughtfully
The way you slice the data matters as much as the data itself.
A. Use Consistent Date Ranges
- Stick to a clear time frame. Data can change week-to-week — don’t mix apples and oranges by comparing different periods.
B. Export Raw Data Where Possible
- The UI is fine for a glance, but exports (CSV/Excel) let you dig deeper, filter, and catch errors.
- Save a copy of your exports (with timestamps) so you can compare changes over time.
C. Document Your Methodology
- Note down exactly what filters, lists, and parameters you used.
- This makes it easier to repeat the process, or explain your numbers later if someone asks.
6. Sanity-Check the Output
Don’t trust, verify. Even the best crawler has gaps.
- Spot-check a random sample. Pick 10–20 sites at random, visit them, and see if the tech detections match reality.
- Check for false positives/negatives. Sometimes Similartech thinks it found Shopify because of a stray script, but the site is custom-built.
- Be alert for outdated data. A tech may have been removed, but the crawler hasn’t caught up yet.
What to ignore: Don’t waste energy trying to catch every single error. Focus on patterns, not perfection.
7. Interpret Results Realistically
Numbers out of context can be misleading.
- A “detected” tag isn’t a guarantee. It just means the tool saw evidence. It might be a test install, a leftover script, or a partial migration.
- Tech counts are not “market share.” They’re only as good as the sample list and detection accuracy.
- If you see a sudden spike, check if it’s a real trend or just a batch of new crawls coming in.
Pro tip: If the report is for decision-making, always caveat the uncertainty. Nobody likes surprises from overconfident data.
8. Present Your Findings Without Hype
Your audience (your boss, clients, or just yourself) deserves honesty.
- Highlight what’s solid. “Among the top 500 US retailers, 35% use Shopify, as detected on their public website.”
- Flag what’s uncertain. “This may undercount companies using headless setups or hiding their tech stack.”
- Use visuals, but don’t overstate. Pie charts and bar graphs are great, but don’t make them look more precise than they are.
What to ignore: Wild extrapolations like “Shopify owns 80% of the internet!” Keep it grounded.
9. Update and Iterate
Tech adoption changes. So does Similartech’s crawling.
- Set a schedule for regular updates. Quarterly is usually enough.
- Compare new results with previous runs. Look for real trends, not just noise.
- Note any changes in your process. If you tweak your domain list or filters, document it. Otherwise, you’ll never know if a change is due to tech adoption or your own setup.
10. Know When to Look Beyond Similartech
For some questions, Similartech’s as good as it gets. For others, it’s just a piece of the puzzle.
- If you need server-side tech adoption: You’ll need surveys, job postings, or direct customer interviews.
- If you’re tracking smaller vendors: Detection rates can be very patchy. Consider using multiple tools for cross-checking.
- If accuracy is mission-critical: Budget time for manual checks, or combine Similartech data with other sources.
Keep It Simple and Keep Improving
You don’t need the fanciest report — you need one you can trust and explain. Start with a clear scope, sanity-check as you go, and don’t get lost in the weeds. The best way to get accurate insights out of Similartech is to stay skeptical, document your process, and tweak as you learn. Build, test, repeat. That’s how you get to “accurate enough,” and that’s usually all you need.