Bloomreach reports offer powerful capabilities but can also present challenges. This article highlights common reporting mistakes and how to avoid them, helping you improve analytics, boost efficiency, and drive better business outcomes.
Conflicting date filters
When a complex report doesn't return the desired results, it's important to understand that date filters can be set at multiple levels, and an incorrect configuration can affect the entire report.
Be sure to review all date filters across these key areas:
- Metric definitions – such as in aggregates, expressions, or other components
- Within each metric:
- Customer filters and their events
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Date filter - applied to all events within the metric
- Within report filters:
- Customer filters and their events
- Event filter
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Report filter - applied to the entire report output
Careful setup of date filters leads to reliable results—taking a moment to confirm there are no conflicts makes a big difference.
Reporting on customers with timestamp crilldown
When reporting on customers with timestamp drilldown, it is important to understand that the customer or customer attribute doesn't have a timestamp. Therefore, when you use the "Count of customers" in one of your metrics or formulas, the results may not be meaningful.
Consider using:
- Count of event metrics (First/Last) that ensures one counted event per customer.
- Running aggregates or expressions to define uniqueness (for example, the first/last/unique event per customer within a given timeframe)
Report limit reached
When you receive a report limit reached error, it is important to review our Limitations documentation, which explains all limits and their potential solutions.
Event attribute drilldown with two event types in the report
It isn't possible to drill down two distinct event types using a shared event attribute.
For example, if we're reporting on two different events that both have the attribute location, we would not be able to drill down by location across both events simultaneously.
There are 3 solutions, you can:
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Drill it down using a running aggregate that takes the Last page_visit or session_start location, but these results won't be entirely reliable, as a single location can count toward both metrics.
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Use parameters and report on specific locations one by one:
- Export the report for each event separately and then connect them in your analysis tool.
Using expired data
Another reason for the inaccuracies in your report could be that not all the data is included in your project. Make sure all attributes and events are up to date and haven't expired.
For more information about this feature, refer to the Data Expiration documentation.
Unexpected grouping and display formatting
If a metric or drill-down appears to be missing, or if you notice unexpected grouping or formatting, check the Grouping, Format, and Show N/A settings. The data may still be present but hidden due to how these settings are configured.
You can find more information about these three features in our report documentation.
Unexpected report totals
This is often caused by filter configuration rather than a problem with the report itself.
Common filter configuration issues include:
Selecting Equals instead of Contains. Equals returns only records where the field value is an exact match. If event names, campaign names, or other values include additional text or slight variations, those records are excluded from the results, which can make the total unexpectedly low. Contains includes records where the specified value appears as part of a longer value and is therefore more appropriate when values aren't identical.
Placing a segmentation in Metric filters instead of Report filters. Report filters apply the segmentation to the report's events, while Metric filters identify customers with at least one event that matches the segmentation.
These differences can significantly change the results. If a value appears too low or differs from another report, first compare the filter operator and placement.
Bonus tip: How to get rid of 'other'
When your report has more rows than are included in the grouped data, the extras may appear under (Other). To avoid this, apply aggregation, use "Show Values As," or choose a visualization - (Other) will then disappear automatically.