Calculate cases sold per store per week across your entire retail distribution — see your weighted average velocity, your best and worst accounts, and the velocity range at a glance.
A buyer pulls up your line on their screen, glances at one number, and decides in about four seconds whether you stay on shelf or get cut at the next reset. That number is velocity — cases sold per store per week — and walking into the meeting not knowing yours is like showing up to a deposition without reading the file. This calculator makes your velocity concrete and defensible. Enter your Product or SKU Name, the Time Period in weeks, and for each store: the Store Name and Cases Shipped over that period. The tool computes each store's individual velocity, your Weighted Average Velocity across all accounts, and your Velocity Range from the highest-performing store to the lowest.
It is built for two moments: the buyer meeting where you need to walk in with a real number rather than a vague positive story, and the internal distribution review where you decide which accounts to nurture, which to visit, and which to flag for a potential pull before the buyer flags them for you.
What the 1.0 velocity threshold actually means for your brand
The tool flags whether your Weighted Average Velocity is above or below 1.0 cases per store per week — the threshold most retail buyers use as a rough keep-or-cut indicator. A velocity of 1.2 is star-performer territory in most categories; a velocity of 0.6 is in the danger zone where buyers start questioning whether the shelf space is earning its keep.
Below 0.5 is the red zone. At that level, a typical store is selling less than two cases per month — often not enough to maintain a reasonable in-stock rate, justify a dedicated shelf position, or survive a reset. If your Weighted Average Velocity comes back below 0.5, the tool surfaces that explicitly and the recommendation section tells you what that means for your next buyer conversation.
Velocity at or above 1.5 gives you pricing power. It signals demand that exceeds average category performance, which is the foundation for expanding distribution, negotiating better placement, or justifying a price increase. Use the tool to know where you sit before the conversation, not during it.
Why Highest Velocity Store and Lowest Velocity Store matter as much as the average
Weighted Average Velocity tells you where the brand stands. Highest Velocity Store and Lowest Velocity Store tell you why. A highest-velocity store that is running at 3.2 cases per week is worth studying: what is its demographic, its placement, its facings, its proximity to complementary products? Whatever is working there is a blueprint for improving lower-performing accounts.
The Lowest Velocity Store is where the proactive work happens. Before a buyer flags a low performer, visit it yourself. Check shelf placement and facings. Check whether the product is fronted. Check the expiration dates — old inventory is a velocity killer. Sometimes the fix is simple; sometimes the account is genuinely the wrong fit and pulling early saves a longer-term placement problem.
Velocity Range — the gap between highest and lowest — tells you how consistent the brand performs across different retail environments. A narrow range means the product works reliably. A wide range means performance is highly dependent on store characteristics, which is useful data for targeting new distribution strategically.
How to use velocity data in a buyer meeting
Buyers have access to POS data you do not always see. Walking in with your own velocity calculation — especially one that shows improvement over time — tells them two things: you track the business at a granular level, and you come prepared. Both signal that you are a low-risk vendor to work with.
If your weighted average velocity is above the category average, say that explicitly — but back it up with the number. 'Our velocity across eight accounts over the past eight weeks was 1.4 cases per store per week' is a statement that invites expansion conversation. 'Our product is performing really well' is not.
If velocity is below 1.0, get ahead of it rather than hoping the buyer does not notice. Come with a specific plan: a promotion window, a display unit request, a price reduction for a defined period, or data showing which store types perform best with your product. A specific plan at a below-threshold velocity is far better than a passive update.
Tracking velocity trends across buyer meetings
A single velocity number is a snapshot. The pattern across multiple periods is the story. Once you have calculated velocity for one time window, save the number and the store-level breakdown. Next quarter, run it again. Velocity moving from 0.8 to 1.1 over two quarters is a compelling growth narrative. Velocity moving from 1.2 to 0.9 is a warning that needs explanation before the next review.
Total Stores is an output field in the tool because distribution breadth matters alongside velocity. A brand with high velocity across 12 stores is different from one with lower velocity across 40. Both have their place in a growth story, but they represent different stages of the distribution funnel. Know your number in both dimensions.
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When to add or remove stores from the model
Add a new store to the model as soon as it has at least four weeks of sales data. Early velocity numbers are noisy — a new placement often runs hot for two to three weeks as consumers discover it, then settles to a sustainable rate. Four to eight weeks of data gives you a meaningful early read.
Consider removing a store from the weighted average if it is a clear outlier — an unusually large format store or a store with a major promotional event during your tracking window — that would distort your average in either direction. Note the exclusion when presenting to buyers rather than silently adjusting the number, which preserves your credibility.
How to use it
- Enter your Product or SKU Name and the Time Period in weeks you are tracking.
- Add each Store Name and the Cases Shipped to that store over the tracking period.
- Read Weighted Average Velocity — the mean cases per store per week across all accounts.
- Check Highest Velocity Store and Lowest Velocity Store to identify your best and most vulnerable accounts.
- Review Velocity Range to understand how consistently the product performs across different retail environments.
- Track the Total Cases (All Stores) figure as a distribution-wide volume benchmark for comparing future periods.
Who it's for
- CPG brand preparing for a regional buyer review — Enters 12 stores over 10 weeks, gets a 1.3 weighted average velocity, and walks into the buyer meeting with a specific number instead of anecdotal performance updates.
- Distributor evaluating underperforming accounts — Identifies three stores below 0.5 velocity, schedules shelf checks at all three, and discovers that two have facing issues a store visit resolves.
- Brand tracking velocity improvement after a promotional period — Compares pre-promo velocity (0.8) against in-promo (1.6) and post-promo (1.1) to demonstrate lasting velocity lift to the buyer as justification for expanding facings.
- Startup brand reporting first-distribution velocity to investors — Runs five stores at eight weeks of data, produces a 0.9 weighted average, and presents it as a credible early benchmark with a named plan to reach 1.2 in the next quarter.
Key terms
- Velocity
- Cases sold per store per week — the standard retail metric for measuring product performance across a distribution network. The single number buyers use to decide whether a product stays on shelf.
- Weighted average velocity
- Total cases shipped divided by total stores divided by total weeks. Accounts for variation in store count and time period across accounts.
- Velocity range
- The gap between your highest-performing store's velocity and your lowest-performing store's velocity. A wide range signals inconsistent performance across retail environments.
- Distribution breadth
- The total number of retail locations carrying the product. Grows independently of velocity — a brand can have strong velocity in few stores or weak velocity across many.
- Sell-through
- The rate at which product sells from a retail shelf to a consumer — as distinct from sell-in (units shipped to the retailer). Velocity is ideally calculated from sell-through data.
Frequently asked questions
What counts as one case in the velocity calculation?
One shipping case as defined by your UPC case pack configuration — typically 12 or 24 units depending on your product format. Be consistent: either track sell-through (what rang at the register) or ship-in (what you delivered to the store). Mixing the two in the same model produces misleading velocity numbers.
Should I use sell-through data or ship-in data for this calculation?
Sell-through data is more accurate because it reflects actual consumer demand rather than store ordering patterns. If a store ordered heavily when you launched but is selling slowly, ship-in data flatters your velocity. Use POS data from the retailer when available; use ship-in data only when POS is unavailable, and note which you are using in your buyer presentation.
What is a good velocity for a natural grocery product?
Natural grocery velocities vary significantly by category and price point. Condiments and sauces often run 0.5–1.2; beverages can run 1.5–3.0 in strong placements. The most useful benchmark is the category average at your key accounts — buyers will compare you against that rather than a generic number.
How many stores do I need to get a meaningful weighted average?
Five or more stores over at least six weeks gives you a statistically reasonable number to present with confidence. Below five stores, the average is highly sensitive to individual account performance and should be presented with that caveat. More stores and longer time windows make the number more defensible.
Can I use this tool for tracking multiple SKUs in the same distribution set?
Run separate calculations per SKU — the model is designed for one product or SKU per session. If you have three SKUs in the same stores, calculate each separately and compare the results. A store that shows high velocity on one SKU and low on another is a useful data point for planogram conversations.