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The scenario: It’s planning time. You have a backlog of Features in Lane, each backed by varying levels of customer demand and strategic alignment. You need to get the right people in a room — or on a call — work through the backlog together, and leave with clear decisions on what’s going in, what’s out, and what’s waiting. By the end of this guide you’ll have a repeatable process for running a prioritization session using Lane as the single source of truth — so decisions are grounded in data, not dominated by whoever argues loudest.

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Before the session — prepare your backlog

A prioritization session is only as good as the data going into it. Set aside 20–30 minutes before the session to make sure your Features are ready to be compared. Make sure each Feature has:
  • Linked Insights from real customer feedback
  • Customers attached to those Insights with ARR, tier, and status filled in
  • An Objective linked — or a clear reason why one isn’t needed
  • A Value / Effort score set so the team can see relative return at a glance
Features missing this context are hard to evaluate fairly. A quick prep pass means the session stays focused on decisions rather than filling in gaps. Create a View for the session In Features, create a saved View that surfaces what you’ll be reviewing together. A useful starting configuration:
  • Filter to Features not yet started or in backlog status
  • Sort by total ARR or insight score to surface the highest-signal items first
  • Display fields that matter for the conversation — customer count, ARR, Objective link, effort, value score
Save this View to your Space before the session so you can pull it up immediately when the meeting starts.

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In the session — how to run it

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Set the frame first

Before diving into the backlog, spend five minutes aligning the room on one question: what are we optimizing for this cycle? The answer changes the weight of every signal. A team focused on retaining at-risk Enterprise customers will weight customer status and ARR heavily. A team expanding into a new segment will lead with strategic alignment. A team trying to ship fast will lead with effort scores. Making this explicit at the start prevents the session from turning into a debate where different people are unconsciously using different criteria.

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Walk the backlog together

Open your prepared View in Lane and walk through each Feature as a group. For each one, the conversation should move quickly — the data does most of the talking. Lane gives you several signals to draw on. Use the ones that fit what you’re optimizing for: Customer signals — who’s asking, how many, and what’s the revenue at stake?
  • Total ARR of requesting customers
  • Customer tier (Enterprise, Mid-market, SMB)
  • Customer status (Active, At Risk, Churned)
Demand signals — how much real pull is behind this Feature?
  • Number of requesting customers
  • Feedback count — how many Insights sit behind it
Strategic signals — does this connect to what the business cares about right now?
  • Objective link — is it tied to an active goal?
  • Strategic score — how aligned is it with your current focus areas?
Effort and value signals — what’s the return relative to the investment?
  • Value / Effort score
  • Insight score — a combined signal of demand and importance
You don’t need to review every signal for every Feature. For Features with obvious answers — very high ARR, strong strategic alignment, low effort — the decision is fast. Spend more time on the ones where signals are mixed or competing.

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Make a call on each Feature

For each Feature in the backlog, the output is one of three decisions: In — this goes into the current planning cycle. Assign it to a timeframe (Now) or release. Later — valuable but not this cycle. Leave it in the backlog with a comment on why — so the context isn’t lost when you revisit it next quarter. Out — deprioritized. Update the status and leave a comment so the team understands the reasoning. Customers who asked for it can still be notified if it ever gets picked up in future. Make the call in Lane during the session — don’t leave it to someone to update afterwards. Decisions that don’t get recorded in the moment tend to drift.

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When signals conflict

Sometimes the data doesn’t point clearly in one direction. High ARR but low strategic alignment. Strong customer demand but very high effort. This is where judgment comes in — and where having the explicit frame from the start of the session pays off. A few useful questions when signals conflict:
  • Which customer is behind the high ARR number? One large at-risk account is different from eight healthy accounts spread across segments.
  • Is the Objective this connects to still active and important? If the Objective has shifted, the strategic alignment score may be misleading.
  • Is this genuinely high effort, or has the estimate not been updated recently? Stale effort scores are common in backlog items that have been sitting for a while.
Use Lane to drill into the Feature detail during the session — linked Insights, customer names, and the feature brief are all there. You don’t need to rely on anyone’s memory.

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After the session — record and communicate

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Update statuses

Before closing the session, make sure every Feature discussed has an updated status reflecting the decision made. Features marked In should have a timeframe or release assigned. Features marked Later or Out should have a note. This takes five minutes and means the session produces a durable record, not just a shared memory. Any Feature going into the planning cycle that isn’t yet linked to an Objective should be linked now. This ensures your Roadmap is connected to your strategy from day one — not retroactively.

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Push to your delivery tools

For Features moving into active development, push them to Linear or Jira directly from Lane. Each Feature carries its linked Insights as customer requests — so engineering has the full context of who asked for what without needing a separate handoff document. Go to the Feature detail view, find the integrations section, and push to your connected tool.

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What a good prioritization session produces

When this is working well, you leave the session with:
  • A clear list of Features going into the cycle, with timeframes assigned
  • Every in-scope Feature linked to an active Objective
  • Deprioritized Features updated with notes on why
  • Features pushed to engineering tools ready for implementation
  • A Roadmap that reflects the decisions made — ready to share
The goal isn’t consensus on everything. It’s decisions grounded in data, made quickly, with the reasoning captured so the team can move.

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What’s next

Ready to move on to How to close the feedback loop?