Every product launch I worked on in a previous role ended up in roughly the same conversation a few weeks later. Someone would point out that the new product had already sold more than expected, someone else would argue it was clearly underperforming, and both of them would be holding up numbers that were technically correct. The problem was that they were answering different questions. Total sales in the first couple of months of a launch mostly tells you how quickly the product got onto shelves, not whether anyone actually wants it once it's there.
What eventually settled those conversations wasn't a better argument. It was agreeing on one measure, two comparisons and a handful of checkpoints before the product launched rather than after, and the measure at the centre of it was rate of sale.
What rate of sale actually measures
Rate of sale is sales per store per week. Instead of asking how much a product sold in total, it asks how much it sold in an average store that stocks it, which strips out the effect of distribution building over time. A product that goes from 200 stores to 900 over its first two months will show total sales climbing almost regardless of how it's performing, while its rate of sale might be flat or falling the whole time.
I tracked it in both dollars and units, because each one can flatter a product in a different way. Dollars per store per week picks up price and mix, so a premium product can look healthy in dollars while selling relatively few units. Units per store per week is closer to a read on how many people are actually picking it up, and when the two told different stories, the gap was usually the most interesting part of the review.
Rate of sale vs sell-through
Sell-through comes up in the same conversations and often gets treated as the same thing, but it answers a different question. It compares what sold with what was shipped or stocked, which makes it useful for working out whether a retailer will reorder or is sitting on too much stock. It says a lot about the supply side of a launch and very little about demand relative to anything else in the category.
A product can have excellent sell-through simply because the initial order was small, or poor sell-through because a retailer overbought for a launch display. Rate of sale doesn't care how much stock went in, which made it the better measure for the question we actually needed answered: is this product earning its place on the shelf?
What is a good rate of sale?
On its own, a rate of sale is just a number. Forty dollars per store per week might be excellent in one category and a reason to delist in another, so the figure only becomes useful once you decide what to compare it with. We used two comparison sets: similar products in the range, and the equivalent period in the previous year.
The similar-products comparison shows whether the new product is pulling its weight next to the things it sits beside on shelf. The previous-year comparison helps separate the product from the conditions it launched into, because a growing or shrinking category can make an average launch look brilliant or a decent one look weak. Choosing those comparisons before the launch matters more than which ones you choose, because once the results are in, everyone can find a comparison that supports what they already believed.
Agreeing the checkpoints before launch
The report template read each launch at four, eight, 13 and 26 weeks. Four weeks was an early warning rather than a verdict, because the first month is noisy with launch activity, uneven distribution and people trying something once out of curiosity. By eight weeks the distribution picture is usually clearer, and 13 weeks gives you a full quarter to judge against the comparison sets. Twenty-six weeks was the point where repeat purchase had time to show up, and where a product still behind its comparisons had mostly run out of excuses.
Fixing those points in advance changed the tone of the reviews more than I expected. Instead of someone declaring a launch a failure after three weeks, or someone else asking for "a bit more time" indefinitely, everyone knew when the read was coming and what it would be measured against. Because the template was the same every time, a launch could also be compared with the ones that came before it rather than being judged in isolation.
The licensed product that sold the same and earned less
The clearest example was a launch sponsored by a famous chocolate brand. The assumption internally was that a name that recognisable would lift sales, and on total sales alone the early numbers looked respectable enough to support that story. Against the comparison set, though, its rate of sale wasn't meaningfully different from similar products without the famous name on the pack. The sponsorship simply wasn't changing what people bought.
What it did change was the margin. The licensing costs came straight out of the product's profitability, so we had something that sold about the same as its peers while earning less on every unit. Without a rate of sale read against a fixed comparison set, it would have been easy to keep treating the partnership as a success because the brand was popular and the totals were growing as distribution built. With it, the conversation moved quickly from whether shoppers liked the product to whether the licence was worth paying for, and once the numbers were laid out that way, the product was dropped.
Where rate of sale can still fool you
Rate of sale is a better measure than total sales, but it isn't immune to the usual problems. Promotions can inflate it for weeks at a time, so it's worth knowing which weeks were on deal before reading too much into a spike. It also depends on where the product landed, because a launch that only reached a retailer's strongest stores will show a rate of sale that won't hold once it reaches the rest of the network.
The early weeks deserve the most caution. A strong first month can be trial rather than demand, and a slow one can be stock that hasn't reached shelves properly yet. The later checkpoints exist to show which of those stories is true before anyone commits to pushing, fixing or delisting the product.
Most of the value ended up coming from the agreement rather than the metric. Rate of sale is a simple calculation, and none of the checkpoints were especially clever, but deciding the measure, the comparisons and the timing upfront turned a launch review into a reading of the evidence instead of a debate about which number to look at. It's the same idea behind a useful dashboard starting with a decision: the report worked because everyone already knew which decision it was there to inform.