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The 6 best tools to prioritize customer feedback by revenue in 2026

Pixel art of a gold coin stack beside a glowing teal chat bubble
Talton Figgins•••7 min read

Your feedback board has forty votes on a dark mode request and three votes on an SSO request. The SSO request came from the two accounts that make up a third of your revenue. Vote count and revenue don't move together, and most feedback tools only ever show you the first number.

The tools below pull in billing or CRM data so a request shows what it's worth, not just how loud it is. Modem is entry one, and we're the team that built it, so take that ranking with the bias it deserves. The other five made this list without any relationship to us.

“we need SSO before rollout”
Slack logo“any update on single sign-on?”
Zendesk logo“SSO came up twice on this call”
↓ classified + deduped into
SSO requests
8 accounts asking · quotes kept
filesLinear logoLinear issue, quotes attached
writesNotion logoinsight report in Notion
answersyour agents
Stripe billing events flow into a context graph the agent can query, so the people and companies behind a topic carry plan and revenue context.

The short version

ToolRevenue sourceHow it weightsBest for
ModemStripe (or Salesforce)Plan and revenue on the companies behind each topic, joined to topics by the agent on requestDevtools teams billed through Stripe
ProductboardSalesforceOpportunity value rolls up per featureProduct orgs tracking deals in Salesforce
CannyHubSpot or Salesforce spend fieldsMRR/ARR attached to posts, factored into a custom scorePublic boards that also need a private revenue lens
EnterpretSalesforce or HubSpotThemes ranked by ARR and open pipeline touchedLarge support orgs with high ticket volume
VitallyCRM and billing syncMRR column on a feature request tableCS teams already running Vitally
DIY spreadsheetStripe exportManual join, sorted by handPre-revenue or single-operator teams

1. Modem

Modem's Stripe integration matches Stripe customers to the people and companies already in your feedback, so the companies behind a topic show their plans and accounts. Ask which paying customers asked for this, and the agent answers next to what those customers said, quotes attached. Billing events, new subscriptions, cancellations, trials ending, failed payments, can also trigger automations, so an account that cancels or has a failed payment gets noticed along with its open requests.

Each topic gets an AI-assigned priority that weighs how many companies raised it, along with severity, across every connected source, all sitting in one context graph that agents reach over MCP rather than digging back through every Slack thread and support ticket by hand. Stripe adds the revenue layer on top; Salesforce is a read-only sync the agent can query for pipeline data, for teams whose revenue truth lives there instead.

Where it fits: teams billed through Stripe that want revenue context sitting next to the feedback itself, answerable in plain language. Where it doesn't: there's no dedicated "sort by ARR" score or slider. You ask the agent or read the plan on the company page; you don't get an automatic revenue-first ranking the way Productboard's opportunity column or Canny's MRR sort does.

2. Productboard

Productboard's Salesforce integration links an opportunity field, deal amount for example, to features. Every feature request gets an opportunity value column showing the total deal revenue riding on it, so a roadmap review can weigh a request against pipeline instead of vote count. Teams can also build segments from synced account attributes, enterprise accounts above an ARR threshold for example, and see each segment's average MRR.

It only surfaces what Salesforce already tracks. If your revenue truth lives in Stripe subscriptions rather than Salesforce opportunities, this integration has nothing to attach.

Where it fits: product orgs already running deals through Salesforce that want pipeline value visible on the roadmap.

3. Canny

Canny's revenue tracking attaches MRR or ARR to each post, synced in from HubSpot or Salesforce spend fields. From there, Canny lets you build a custom prioritization score using Impact Factors, so revenue is one input you define, alongside votes.

Canny is still a public board first. Revenue data stays admin-only, since spend fields aren't shown to voters, layered on top of the same voting workflow.

Where it fits: teams that want a public voting board with a private revenue lens for their own prioritization calls.

4. Enterpret

Enterpret ties every piece of feedback to the account, segment, ARR, and lifecycle stage pulled from Salesforce or HubSpot. A theme then ranks by the open pipeline or renewal revenue it touches, not by mention count, across support tickets, reviews, surveys, and calls.

It's built for volume: large support and CX orgs feeding it thousands of unstructured tickets a month. A five-person devtools team won't generate enough ticket volume to need it.

Where it fits: large support organizations with enough ticket volume to need automated theme extraction instead of manual tagging.

5. Vitally

Vitally's Feature Request Hub is a table and dashboard inside its customer success platform. Columns can show MRR, health score, and NPS next to each request, and a summary dashboard groups requests by category, urgency, and revenue.

Vitally is a CS platform first, not a dedicated product prioritization tool. If your CS team already lives there, the revenue view is free to use; if not, it's a heavy tool to adopt for one feature.

Where it fits: teams whose customer success org already runs on Vitally and wants feature requests sitting next to health scores.

6. DIY spreadsheet joins

Export Stripe subscriptions, either through a Stripe-to-Sheets pipeline or a manual CSV pull, join it against your feedback log by customer email or account name, and sort by MRR.

It costs nothing beyond the time to build and maintain it. The join breaks the moment feedback lives in more than one place, a Slack channel and a spreadsheet and a support inbox, because nothing is doing the matching for you.

Where it fits: pre-revenue or single-operator teams with a short feedback list and no budget for a tool.

The decision rubric

Three questions settle most shortlists. What system holds your revenue data, where does feedback arrive, and who runs prioritization day to day?

Revenue lives inFeedback arrives viaWho prioritizesPick
StripeSlack, Discord, support, scatteredEngineers or foundersModem
Salesforce opportunitiesPM intake and integrationsA product orgProductboard
CRM spend fieldsA public voting boardPMs with a communityCanny
Salesforce or HubSpotThousands of support ticketsA CX or research teamEnterpret
AnywhereIssues already in Linear or JiraWhoever grooms the backlogTracker-native AI, but note it has no revenue view

That last row matters. Linear's Triage Intelligence, Jira's Rovo, and GitHub Copilot sort and route what is already filed. None of them read billing or CRM data, so if the question is "what is this request worth," a tracker-native tool cannot answer it.

ModemProductboardCannyTracker-native AI
Revenue sourceStripe or SalesforceSalesforceHubSpot or Salesforce spend fieldsNone
How revenue shows upPlan and revenue on the companies behind each topic, queryable in plain languageOpportunity value column per featureMRR/ARR on posts, one input in a custom scoreDoes not appear
Feedback capturePassive, across chat, support, email, callsThrough PM workflowsUsers post and voteWhatever gets filed as an issue
Weak spotNo automatic revenue-first sortBlind to Stripe-only revenueBoard-first, revenue is a private overlayBlind to revenue entirely

How to choose

What matters is where your revenue truth already lives. If it's Salesforce opportunities, Productboard or Enterpret read that natively. If it's Stripe subscriptions, Modem or a spreadsheet join do. If you need the revenue view to change how a public board scores requests, Canny is built for exactly that. Match the tool to where the number already sits, not the other way around. For the wider picture of where revenue-based prioritization fits against capture and analysis, see our stage-by-stage breakdown.