Why Data Counts Differ Across Platforms

If you’ve compared a number in Bear IQ to what your registration platform, AMS, or exhibit sales system shows and noticed a difference — you’re not alone. This is expected, and it doesn’t mean something is wrong.

Here are the six most common reasons counts differ, and what Bear IQ is doing about each one.

1. Record Status Filtering

This is the single biggest driver of count differences.

Your source system stores every record it ever touched — cancelled registrations, refunded transactions, incomplete form submissions, and internal test records all sit alongside your real active registrations.

Bear IQ applies deliberate filtering rules so your counts reflect reality:

• Cancelled and refunded registrations are excluded from active counts

• Test and QA records created during setup are removed

• Incomplete or abandoned form submissions are filtered out

• Transfers are handled correctly so a transferred registration counts once, not twice

2. Timing and Sync Frequency

Bear IQ refreshes on a defined schedule. Your source system may update in real time. So at any given moment, the source system might be a few hours ahead of Bear IQ — this is normal, especially during busy pre-event periods.

Common examples:

• A registration comes in at 2:00 PM. Bear IQ’s last refresh was at 10:00 AM. It will appear at the next scheduled refresh.

• A batch of exhibit sales is posted end-of-day. Bear IQ picks these up on its next daily refresh.

• A name or category is updated in your AMS but Bear IQ hasn’t synced yet — the old value shows until the next refresh.

3. Deduplication

Some source systems create a new record every time a form is submitted, even if the person already exists. Bear IQ applies deduplication logic to ensure you’re counting unique individuals or unique transactions.

Example: A registrant submits a form twice due to a browser timeout. The source system stores two records. Bear IQ identifies the duplicate and counts it once — which is the accurate number.

4. Scope and Data Boundaries

Not everything in your source system is relevant to your event analytics. Bear IQ scopes data to what matters:

• Member records in your AMS that aren’t tied to the event are excluded

• Non-event product sales in your exhibit platform are filtered out

• Records from prior event years in a shared dataset are segmented so current-year numbers stay clean

5. Field Mapping and Categorization

The same record may be categorized differently in Bear IQ vs. your source system. For example, a source system might label someone “Exhibitor” while Bear IQ maps them to “Exhibitor — Full Conference” based on additional context from the registration type.

These differences won’t change your total counts, but they can affect counts within specific segments. Bear Analytics reviews field mappings with your team during setup and updates them as needed.

6. API Data Availability

Not every field or record in a source system is accessible through that system’s API. In some cases, platform limitations mean certain data simply isn’t available for integration — even if you can see it when logged into the source system directly.

When this happens, Bear Analytics works with the integration partner to expand access where possible. See Article 3 for more on how partner API quality affects data alignment.

If You Spot a Difference

Run through this quick checklist:

1. Check the time — when was Bear IQ’s last refresh?

2. Check record statuses — does the source count include cancelled or test records?

3. Check scope — are you comparing the same event year and registration types?

4. Check for duplicates — does the source count include duplicate records?

5. Reach out — your Bear Analytics team can walk through any discrepancy and explain exactly what’s driving it.