What is feedback vote velocity?
Definition
Feedback vote velocity is the number of new votes a feature request gathers per recent period — typically the trailing 30 days — rather than its lifetime total. It surfaces what customers want now: an old request with 400 dormant votes ranks below a month-old request gaining ten votes a week.
Formula: Vote velocity = new votes on a request in the trailing window (e.g., 30 days)
What data do you need?
- Votes at vote grain with timestamps (not just a count column)
- Request status, so shipped and closed items drop out
- Voter account or company for segment weighting
- Product area fields for roll-ups
- Optionally, account revenue for value-weighted velocity
SQL pattern
Vote velocity on open requests, trailing 30 daysPostgreSQL
SELECT
f.title,
f.product_area,
COUNT(*) AS votes_last_30_days,
COUNT(DISTINCT v.company_id) AS companies_voting
FROM votes v
JOIN feedback_items f ON f.id = v.feedback_item_id
WHERE v.created_at >= CURRENT_DATE - INTERVAL '30 days'
AND f.status NOT IN ('shipped', 'closed')
GROUP BY f.title, f.product_area
ORDER BY votes_last_30_days DESC
LIMIT 20;Common pitfalls
Ranking by lifetime vote totals.→ Totals only ever grow, so old requests dominate forever. Use a trailing window, and show the total as secondary context.
Only storing the current vote count.→ A count column can't compute velocity. Sync votes at vote grain with timestamps, or snapshot counts on a schedule.
Counting ten votes from one company as ten signals.→ Track distinct companies alongside raw votes — breadth of demand and depth of demand are different prioritization inputs.
Where does this metric apply?
This metric commonly uses data from Canny, Aha!, Featurebase, Productboard, plus any warehouse models that provide the same grain.
Related
Dashboards
Integrations
Metrics
Analytics
FAQ
What window should velocity use?
Trailing 30 days suits most B2B feedback volumes; high-volume consumer boards can use 7 days. Keep one window across the board so rankings stay comparable, and state it on the card.
Should velocity alone drive prioritization?
No — it's one input next to revenue-weighted demand, strategic fit, and effort. Its job is to stop lifetime totals from silently making those decisions for you.