Setting a price
With complete marketplace information, pricing is simple: evaluate every possible price, calculate the revenue outcomes, and pick the point that maximizes profit. But most firms lack perfect information — they estimate outcomes and hope their projections match real consumer behavior. Models range from a small owner’s mental math to systems with thousands of lines of code, and all of them need data to work.
Updating the price
Once an initial price is set, you collect data on how it performs, look for factors you missed, and as more data arrives, expand collection and add model complexity. New data or model changes mean recalculating — which usually produces price updates that better reflect changing conditions.
When pricing becomes dynamic
“Dynamic” is about the frequency of updates, often bounded by technical or business constraints. Monthly supermarket shelf prices can count as dynamic; rideshare apps update per minute. Physical shelf tags constrain retailers, while rideshare platforms get continuous data streams. Quibble streams data into the pricing model in real time, and estimates that real-time versus interval-based updates could yield a 0.5–1% total revenue increase.
Who needs dynamic pricing
Large corporations run dedicated teams and software for data, modeling, and distribution — capabilities largely out of reach for small and mid-size operators. Quibble closes that gap, giving operators without the resources or expertise a way to price dynamically.