Explainability

The Explainability page lets you trace exactly why an item appeared (or did not appear) in a user’s recommendations. It shows the raw similarity score, which rules matched, and how each pipeline stage affected the result.

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Running an explanation

1. Navigate to Console > Ranking > Explainability.
2. Enter a User ID and Item ID.
3. Click Explain.

The system queries real data and returns a breakdown of the recommendation decision.

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What you see

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Similarity score

The raw cosine similarity between the user’s embedding and the item’s embedding, converted to a 0-1 score. This is the base relevance signal before any rules or pipeline adjustments.

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Applied rules

Each active rule is listed with:

• Rule name and type (boost, pin, filter, etc.)
• Match status — a green matched badge if the rule’s conditions were satisfied for this user-item pair, or a grey no match badge if conditions did not match.
• Conditions — what the rule checks (item metadata fields, segment membership, etc.)

This tells you immediately which rules are affecting this specific recommendation and which are not.

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Pipeline stages

Each pipeline stage is shown with a status badge:

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Feature contributions

A breakdown of what signals contributed to the final score — the embedding similarity, any metadata features, and rule adjustments.

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Common debugging scenarios

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”Why is this item ranked so low?”

1. Check the similarity score. If it is low, the user’s behaviour does not strongly align with this item’s embedding.
2. Check for bury or filter rules that matched. A bury rule reduces the score; a filter rule removes the item entirely.
3. Check if a higher-priority pin rule placed another item in the position you expected this one to occupy.

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”Why is this item appearing when it shouldn’t?”

1. Look for boost or pin rules that matched unexpectedly. The rule’s conditions may be broader than intended.
2. Check whether the user belongs to a segment that triggers a promotional rule.
3. Verify the item’s metadata — the rule may be matching on stale or incorrect data.

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”Why are rules not applying?”

1. Check the rule’s Active toggle — it may be inactive.
2. Check the schedule — the rule may have a start date in the future or an end date in the past.
3. Check the segment condition — the user may not belong to the target segment. Create a segment with broader conditions to verify.
4. Check the pipeline config — if the rules stage is disabled, no rules will apply regardless of their configuration.

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Tips

• Use Explainability before launching a campaign. Test your rules against real user-item pairs to verify they behave as expected.
• Combine with Analytics. If engagement drops after deploying a new rule, use Explainability to check whether the rule is matching more broadly than intended.
• Test edge cases. Try explaining items for users who are in multiple segments, or items that match conditions for multiple rules, to understand priority interactions.