Are There Visitors I Should Exclude From Analysis?
Quick Summary
Yes. Not all traffic represents real potential customers. Including certain visitors—particularly bots, internal traffic, test sessions, and spam referrals—will skew your metrics and lead to wrong conclusions.
Core Insight
Types of Traffic to Exclude
1. Bots and Crawlers (Most Important)
What they are: Automated programs that visit your site.
Common bots:
- Search engine crawlers (Google, Bing)
- SEO tools (Ahrefs, Semrush, Moz)
- Security scanners
- Spam bots
- AI scrapers
Why exclude: Bots inflate visitor counts, have zero conversion potential, and create misleading engagement patterns.
How ObserviX handles this: We automatically detect bots using browser fingerprinting. Use the "Hide Bots" filter to exclude them.
2. Internal Traffic (Your Team)
What it is: Visits from you and your colleagues.
Why exclude:
- Your team visits pages differently than real users
- Testing activities create false engagement signals
- Checking "did my changes work?" isn't real user behavior
How to identify: Look for:
- Repeated visits from the same location as your office
- Patterns that match your team's working hours
- Visitors who only view admin/backend pages
3. Test and Development Traffic
What it is: Traffic generated during testing, QA, or development.
Why exclude:
- Test conversions inflate conversion counts
- QA sessions don't represent real user journeys
- Development traffic often has unrealistic patterns
How to identify: Look for:
- Unusual session patterns (very short or very long)
- Conversions with test values ($0.01, $999999)
- Traffic from staging/development URLs
4. Spam Referral Traffic
What it is: Fake traffic from spam sources trying to appear in your analytics.
Why exclude: It's not real traffic—just noise in your data.
How to identify: Check the Channel column for:
- Strange, unfamiliar referral domains
- High volume from a single unknown source
- Zero engagement (immediate bounce)
How to Use the Bot Filter
ObserviX provides a built-in filter to exclude detected bots:
| Step | Action |
|---|---|
| 1 | Look for the filter icon near the date picker |
| 2 | Find the "Hide Bots" option |
| 3 | Enable it to exclude detected bot traffic |
| 4 | Your metrics will recalculate without bots |
Recommendation: Keep "Hide Bots" enabled for most analyses. Only disable it if you specifically want to see bot traffic patterns.
Impact of Not Filtering
| Metric | With Bots Included | Problem |
|---|---|---|
| Total Visitors | Inflated | False sense of traffic volume |
| Avg. Session Duration | Lower | Bots have 0-second sessions |
| Bounce Rate | Higher | Bots often view one page |
| Conversion Rate | Lower | More visitors, same conversions |
| Engagement Distribution | Skewed | Many "Unknown" status visitors |
When to Include All Traffic
There are some cases where you might want to see unfiltered data:
| Scenario | Why |
|---|---|
| Security analysis | Detect bot attacks or scraping |
| SEO monitoring | See which crawlers visit your site |
| Full traffic audit | Understand all sources before filtering |
| Debugging tracking | Verify your pixel captures everything |
For regular business analysis, always filter bots out.
Checklist: Clean Data Setup
| Action | Impact | |
|---|---|---|
| Enable "Hide Bots" filter | Removes automated traffic | |
| Note your office IP/location | Mentally exclude when analyzing | |
| Avoid testing on production | Keeps test data separate | |
| Review unusual traffic spikes | May indicate spam or bots |
Why It Matters
Clean data = Better decisions
Your analytics are only as good as the data quality. Bots and internal traffic create noise that hides real patterns.
Rule of thumb: If a visitor could never become a customer, they shouldn't be in your analysis.
Always ask: "Is this traffic I could actually sell to?"
Practical Value
Failing to exclude non-customer traffic leads to systematically flawed analysis: inflated visitor counts create unrealistic conversion rate expectations, bot-driven session data distorts engagement benchmarks, and spam referrals obscure genuine channel performance. The "Hide Bots" filter is not optional for accurate business analysis—it's essential for seeing true user behavior patterns. Teams that analyze unfiltered data make decisions based on fiction rather than customer reality, leading to misallocated budgets and incorrect optimization priorities. Clean data enables confident decision-making by ensuring every metric reflects actual human prospects who could realistically convert.