Every priority score in Pilea is transparent. You can see exactly which customer signals are driving each backlog item's score and how much each signal contributes. This helps you understand why an item ranks where it does and whether the data matches your intuition.
You can view the breakdown in two ways: a quick tooltip by hovering, or a full breakdown in the item's detail panel.
Viewing the breakdown tooltip
The fastest way to check what's driving a score is to hover over it.
Open your Backlog in list, table, or kanban view.
Hover over the priority score bar next to any item.
The breakdown tooltip appears, showing a histogram of signal contributions.
SCREENSHOT: Backlog list view with the hover tooltip visible on a priority score bar, showing signal histogram.
Each bar in the histogram represents one of the six input signals. Taller bars mean a higher contribution to the total score. The bars are sorted by impact, so the signal driving the score most appears first.
Viewing the full breakdown in the detail panel
For a more detailed view with percentages and the option to override the score:
Click any backlog item to open its detail panel.
Scroll to the Priority section.
The full breakdown shows each signal with its bar, percentage contribution, and current value.
SCREENSHOT: Backlog item detail panel showing the Priority section with full signal breakdown, percentages, and override option.
The detail panel breakdown includes the same information as the tooltip, plus the exact percentage each signal contributes and the option to manually override the score.
💡 Tip: Use the detail panel breakdown when you're triaging items or preparing for a prioritization meeting. The percentages make it easier to explain to your team why an item ranks where it does.
What each signal means
The breakdown shows six signals. Here's a quick reference for what each one measures:
Signal | What it measures |
Revenue Impact (Deals) | Total MRR of existing customers who mentioned this item |
Customer Breadth | How many distinct customers mentioned this item |
Mention Volume | Total number of mentions, scaled so repeat complaints from one customer don't overwhelm the score (one customer filing 50 tickets won't outweigh three independent reports) |
Recency | How recently customers mentioned this item (exponential decay, 90-day half-life) |
Revenue Impact (Leads) | Deal size of prospects who mentioned this item |
Sentiment | Average sentiment of mentions - negative sentiment scores higher because frustrated customers are at higher churn risk |
An item doesn't compete against a global benchmark - it's ranked against other backlog items in your workspace.
ℹ️ Note: The signals shown depend on if/how you have adjusted the signal weights. See the article Setting up your prioritization framework for details.
Understanding zero-value signals
A signal showing zero doesn't mean something is broken - it means there's no data for that signal on this item yet.
Signal shows zero | What it means | What to do |
Revenue Impact (Deals) | No customers with known MRR have mentioned this item | Connect your CRM in Integrations (under Data Sources in the sidebar) to populate revenue data |
Revenue Impact (Leads) | No prospects with known deal size have mentioned this item | Connect your CRM to import prospect deal values |
Customer Breadth | Only one customer (or none) has mentioned this item | As more feedback comes in, breadth increases naturally |
Mention Volume | Very few mentions exist for this item | Import more feedback or wait for integrations to sync new data |
Recency | All mentions are older than the decay window | Fresh mentions will increase this signal. The 90-day half-life means older signals naturally fade |
Sentiment | The mentions didn't have clear positive or negative sentiment | This is normal for neutral or factual feedback |
Zero-value signals are common for new items or items with limited feedback. Priority scores improve as you connect more data sources and collect more feedback.
Recognizing a pinned (overridden) score
When someone on your team has manually overridden a backlog item's priority score, you'll see a pinned badge next to the score.
A pinned score means:
The number you see is a manual override, not the computed score.
The original computed score is preserved and shown as "Computed: X - manually overridden" in the detail panel.
The override was set by a team member with Editor or Admin access.
SCREENSHOT: Backlog item showing a pinned score badge with the "Computed: X - manually overridden" label visible in the detail panel.
To see who set the override or to remove it, open the item's detail panel and look in the Priority section. Only users with Editor or Admin access can set or remove overrides.
⚠️ Important: When scores are recalculated (after new feedback, CRM syncs, or a batch recalculation), pinned scores stay. The computed score updates silently in the background, but the pinned value remains until someone removes it.
Using the breakdown in practice
The breakdown is most useful when you need to answer questions like:
"Why does this item rank so high?" - Check which signals are driving the score. If Revenue Impact dominates, it means high-value customers are raising this issue.
"Why does this item rank so low?" - Look for zero-value signals. An item with no revenue data and only one customer mention will score low even if the feedback is urgent.
"Should I override this score?" - If the breakdown shows the data is accurate but you have context the AI doesn't (an executive commitment, a contractual deadline), an override makes sense. If the breakdown shows missing data, consider connecting more sources first.
"How do I explain this to my team?" - The percentage breakdown in the detail panel gives you a clear, data-backed explanation for any prioritization decision.