The feature prioritization tool that ranks what to build next
Score every request with RICE, ICE, MoSCoW, or Impact/Effort against customer votes, voter segments, product strategy, and engineering effort from Jira or Azure DevOps.
SSO for enterprise plans
42 votes · 71% enterprise · Jira 3wk
Bulk CSV import for feedback
28 votes · 46% enterprise · Jira 1wk
Slack notifications on status change
36 votes · 22% enterprise · Jira 4d
The inputs
Prioritize with real customer demand, not gut feel
A feature prioritization tool is only as strong as its inputs. ProductLift feeds five real signals into every score, so the ranking you show the sprint review is defensible.
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1
Customer votes
Real users who asked for it, not a PM's estimate. Duplicate requests are surfaced and merged in one click, so the vote count on the winning card is the true demand, not three low-scoring copies.
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2
Customer segments
Define segments (Enterprise, SMB, Trial, or your own). Every card shows the mix, for example 71% enterprise voters. Percentages recompute automatically as new votes land. Filter the backlog by minimum segment percentage.
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3
Product vision & business goals
A defined product vision (target group, needs, business goals) is fed into every AI scoring call, so requests aligned with your strategy score higher and drift shows up before you commit sprint capacity.
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4
Engineering effort from Jira / Azure DevOps
Two-way sync means engineering-owned estimates flow into the Effort field. RICE and Impact/Effort scores update as estimates change, without a separate spreadsheet to reconcile.
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5
Manual judgment & override
Every score is editable inline, and a manual drag-drop rank is preserved alongside the numeric score. When an exec says "put SSO first," you keep the override without losing the calculation.
SSO for enterprise plans
Add SAML/OIDC so IT admins can manage seats via Okta and Azure AD.
AI-assisted prioritization
AI makes the first pass.
You make the final call.
Define your product vision once, and AI weighs feature requests against your target group, customer needs, and business goals, with a written explanation for every recommendation.
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✦
AI Suggest drafts scores for individual requests using your existing scoring patterns.
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✦
AI Prioritize reviews up to 50 requests and recommends the five strongest priorities.
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✦
Strategy changed? Update your product vision and reprioritize the backlog in one pass.
AI features consume credits included on paid plans. Jobs skip cleanly when credits are exhausted, no overage charges.
Target group
B2B SaaS product managers at 20-200 employee companies.
Needs
Close the loop between customer feedback and shipped features without leaving the tool.
Business goals
Expand to enterprise plans. Reduce time-to-first-vote from days to hours.
Frameworks built in
Runs the framework you already use
Four industry-standard frameworks are pre-wired into the scoring UI. Set a default per portal. Read the guide, or try the math in a free calculator first.
WSJF is available as a free calculator, separate from the in-app scoring UI. Not sure which framework fits? Compare frameworks side by side
One request, whole loop
The prioritized request is the same request customers voted on
No CSV export back to a separate roadmap tool. The card you score is the card you move to Planned, the card voters see on the public roadmap, and the card the changelog picks up when you tag it as Shipped. One object, four surfaces.
Feedback
Voters submit requests through the portal or widget. Duplicates get merged.
Prioritize
Score inline or with AI Suggest. Sort by score, votes, or segment mix.
Roadmap
Drag winners onto Planned. Same card appears on the public roadmap.
Notify
Voters get emailed on status change. Tag a comment for release, changelog picks it up.
The alternatives
Why teams pick ProductLift over a spreadsheet or standalone scorer
Option A
Spreadsheet
- Customer votes
- Manual entry, quickly stale
- Voter segment mix
- Not possible
- Engineering effort
- Copy-paste from Jira
- AI-assisted scoring
- None
- Public roadmap + notifications
- Separate tool
- Changelog
- Third tool
Option B
Standalone scoring tool
- Customer votes
- Rarely built in
- Voter segment mix
- Not supported
- Engineering effort
- Manual re-entry
- AI-assisted scoring
- Basic, no vision context
- Public roadmap + notifications
- Export required
- Changelog
- Not included
Option C · Recommended
ProductLift
- Customer votes
- Live from the public portal
- Voter segment mix
- Auto-computed per request
- Engineering effort
- Two-way Jira / Azure DevOps sync
- AI-assisted scoring
- Calibrated against your product vision
- Public roadmap + notifications
- Same card, same click
- Changelog
- Included, picks up tagged status comments
Engineering integrations
Fits the tools engineering already uses
Jira · two-way sync
Link a post to a Jira issue. Effort estimates and status updates flow both ways, so RICE Effort stays current as engineering revises the estimate.
Jira for PMsAzure DevOps · two-way sync
Same pattern for teams on Azure Boards. Work items sync with prioritized posts and effort estimates flow into the scoring UI.
Azure DevOps syncBuilding agents? The ProductLift MCP server lets Claude or Cursor score and rank requests through natural language over OAuth 2.1.
FAQ
Common questions
What is a feature prioritization tool? +
A feature prioritization tool is software that helps product managers score and rank feature requests so the highest-value items get built next. It combines a scoring model (like RICE, ICE, MoSCoW, or Impact/Effort), the inputs behind each request (customer votes, voter segments, engineering effort, strategic fit), and a way to move the winners onto a public roadmap.
Which prioritization frameworks does ProductLift support? +
Four are built into the scoring UI: RICE, ICE, MoSCoW, and Impact/Effort. WSJF is available as a standalone free calculator. You can override any score manually, and a manual drag-drop rank is preserved alongside the numeric score.
Can AI score my backlog for me? +
Yes. AI Suggest drafts Impact, Confidence, Ease, and Reach for individual posts, calibrated against your existing scoring patterns. AI Prioritize reviews up to 50 requests and recommends the five strongest priorities against your product vision, with a written explanation for each pick. Every AI score is a draft you accept, edit, or reject.
How does the tool use my product vision? +
You define product vision (target group, needs, product, business goals) once. The AI feeds it into every scoring call, so requests aligned with your strategy score higher, and drift shows up before you commit sprint capacity. When strategy changes, update the vision and reprioritize in one pass.
Can I see which enterprise customers voted? +
Yes. Define voter segments (Enterprise, SMB, Trial, whatever you use). Every request card shows the segment mix, for example "58% enterprise voters". Segment percentages recompute automatically as new votes land. Filter or sort the backlog by minimum segment percentage.
Do effort estimates come from Jira? +
Yes. Two-way Jira and Azure DevOps sync means engineering-owned estimates flow into ProductLift's Effort field. RICE and Impact/Effort scores update as estimates change. Manual override still works if a request has no linked issue.
Does the prioritization tool connect to a roadmap? +
Yes. Every prioritized item is a feedback post, so the moment you move it to Planned or In Progress it appears on the public roadmap and voters get notified. When you flip to Shipped and tag the status comment for release, the changelog picks it up.
Is there a free version? +
Prioritization is included on every plan, including the free tier. AI Suggest and AI Prioritize consume AI credits included on paid plans.
Rank what to build next.
Prioritize with customer demand, product strategy, and engineering effort in one shared workspace.