If you’re responsible for marketing or sales reporting, you know the real headache isn’t generating leads—it’s getting data out of the tools and into a format that actually makes sense. If you use Visualvisitor to surface leads from website traffic, this guide is for you. We’ll walk through exporting your lead data, the quirks to watch for, and how to slice it up into reports that actually help you make decisions (instead of just ticking a box for your boss).
Why bother exporting Visualvisitor data?
Visualvisitor does a decent job surfacing companies visiting your website, but its built-in reporting features are pretty limited. If you want to:
- Combine lead data with other sources (like CRM or ad data)
- Do custom analysis (think: segment by industry, location, or campaign)
- Actually visualize trends and share with your team
You’ll need to get your data out. Spoiler: it won’t be perfect, but it’s doable.
Step 1: Figure out what you really need
Before you export anything, get clear on what you want. Visualvisitor collects a lot—company, location, visit details, sometimes guessed contact info. But more isn’t always better. Ask yourself:
- What questions am I trying to answer? (e.g., “Which industries visit us most?”)
- Who’s the report for? (Sales? Execs? Yourself?)
- What data do I actually need to answer those questions?
Pro tip: Don’t export everything “just in case.” It’ll slow you down later. Start lean; you can always re-export.
Step 2: Export your lead data from Visualvisitor
The actual export is straightforward, but getting the data you want takes a few clicks.
A. Log in and head to the Leads section
- Log in to your Visualvisitor dashboard.
- Find the Leads or Company Identification section—naming can shift, but it’s usually in the main nav.
B. Filter your leads
- Use filters to narrow to the time period or lead type you care about. (E.g., “Last month,” “Only US companies,” etc.)
- Filters can be clunky—sometimes you have to apply them, then hit “Export.” Make sure your filters are set before you export.
C. Export to CSV
- Look for an Export button. Usually it’s at the top right or bottom of the leads table.
- Choose CSV (Excel format works too, but CSV is more portable).
- Download the file to your computer.
Heads up: Visualvisitor’s export sometimes splits contact info or visit details across columns in weird ways. Open it up and scan for anything odd—missing fields, merged cells, or gibberish.
Step 3: Clean up your exported data
This is the part nobody advertises, but it matters. Most exports are messy. If you just import them as-is into Excel or Google Sheets, you’ll get junky reports.
What to look for:
- Empty columns: Visualvisitor often exports empty or mostly-empty columns. Delete these.
- Merged cells or multi-line entries: Sometimes addresses or notes get crammed into one cell. Split these up if you need the details.
- Date formats: Dates might export in US, UK, or ISO formats. Standardize them to avoid headaches.
- Duplicate leads: It’s not uncommon to see the same company show up multiple times (especially if they visited more than once). Decide if you want all visits or just unique companies.
Quick cleanup tips:
- Open in Excel or Google Sheets. Use “Remove duplicates” on company name or domain.
- Use “Text to Columns” in Excel if you see weirdly merged data.
- Rename columns to something readable (e.g., “Company Industry” instead of “IND”).
Pro tip: Save your cleaned version as a new file. Never edit your raw export directly—you’ll thank yourself later.
Step 4: Analyze the data—what’s worth the effort?
Now you’ve got a clean spreadsheet. Here’s where most people overcomplicate things. Skip the dashboards unless you really need them. Start with core questions:
Useful things to analyze
- Top visiting companies: Sort by number of visits, or by company size.
- Industries: Pivot by industry to see who’s interested in your site.
- Location: Are you getting traffic from the regions you care about?
- Repeat visits: Who keeps coming back (and might be warming up to buy)?
- Entry pages: What content or landing pages bring in the best leads?
How to do it (without fancy BI tools):
- Use pivot tables in Excel/Sheets for groupings (industry, location, etc.).
- Simple charts (bar, pie) are usually enough for most reports.
- For more context, you can match company domains against your CRM to see if any leads are already in your pipeline.
What not to bother with
- Contact info guessing: Visualvisitor sometimes tries to guess contacts at companies. These are hit-or-miss and can be outdated; don’t rely on them for outreach without verification.
- Session-level data: Unless you’re a web analytics pro, most of the visit details (like time on site, exact click paths) add noise, not insight.
- Exporting every field: Again, don’t make work for yourself.
Step 5: Build your report
Keep it simple, especially if you’re sharing with others. Here’s a basic structure:
A. Executive summary
- One slide or section: “Here’s what we learned.”
- Key numbers: “100 companies visited, 60% from target industries, 10 repeat visits.”
B. Charts/tables
- Top 10 companies by visit count
- Industry breakdown (pie/bar chart)
- Location map or table (if relevant)
C. Action items
- “These companies are worth outreach.”
- “We should focus more on X industry.”
- “Our blog drives more qualified leads than our homepage.”
Pro tip: Don’t flood the report with screenshots from Visualvisitor. Raw data is better when it’s cleaned and visualized.
Step 6: (Optional) Automate exports and analysis
If you’ve got to do this monthly (or more), consider automating:
- Zapier or Make: Visualvisitor doesn’t have a great API, but you might be able to set up a scheduled export via email, then use Zapier to move the file to Google Drive or Dropbox.
- Custom scripts: If you have dev resources, you could write a script to clean and reformat the CSVs as soon as they arrive.
- Templates: At minimum, save your cleaned spreadsheet as a template so you can copy-paste in new data each time.
But honestly? If your volume is low, manual cleanup is usually faster and less error-prone than a half-baked automation.
Pitfalls and honest truths
- False positives: Visualvisitor “identifies” companies based on IP. It’s not exact. Sometimes you’ll see ISPs, coffee shops, or random businesses. Ignore these.
- Contact data is shaky: Don’t expect golden leads with direct emails. Treat contact info as a starting point, not gospel.
- Privacy: Be careful with how you use the data. Just because you know a company visited doesn’t mean you should cold-email everyone you can find.
- Not all leads are equal: Some companies are just browsing, some are bots. Use common sense before handing off leads to sales.
Keep it simple, iterate as you go
Exporting and analyzing lead data from Visualvisitor isn’t rocket science, but it does take a little effort to get clean, usable reports. Don’t worry about perfection—focus on the questions that actually matter to your team. Start small, tweak your process, and build up from there. The more you do it, the faster (and more useful) your reports will get.