ASK any regular traveller who pays for his own tickets about fare pricing and you are likely to hear a string of obscenities. The variability from week to week—sometimes minute to minute—in the cost of a flight from point A to B can be maddening. Airlines use all the computational power at their disposal to maximise their returns by setting fares based on current and predicted demand. As a result, just poking around on airline and aggregator sites may alter the price.

Naturally, it did not take long for a response to emerge. Sites like Farecast, Kayak and others use historical pricing information, among other things, to predict, with varying degrees of confidence, whether a rate currently on offer was likely to rise or fall. These data boost the buyer's confidence that he is not a sucker if he clicks the "pay" button now.

Far less understood is how rapidly prices for consumer good change over both short and long periods, says Oren Etzioni, the co-founder of Farecast (since sold to Microsoft, and called Bing Travel). Eyeing an opportunity, Mr Etzioni launched Decide. The company, which is based in Seattle, estimates when a successor to a specific gadget will be rolled out and the odds that the lowest purchase price anywhere online will go up or down in the near future.

Dr Etzioni, a computer scientist at the University of Washington in Seattle who has founded four firms in all, says Decide relies on three main data sources: pricing data, news and rumours, and technical specifications. Pricing data comes from a variety of sources. Most are the company's trade secret, though they always include current prices of goods and sales data. The model also uses feedback about how its predictions fare over time to fine-tune their probability estimates. With news and chatter, Decide scores sites by how accurate their scoops are for particular categories of goods. The algorithm discounts rumour-mongers and gives a greater weight to reliable sources. So far, the firm has amassed a year's worth of data, many thousands of gigabytes in total.

These reveal unexpected consumer behaviour. For example, when a new model of a well-reviewed product is released, the older model's price paradoxically tends to go up and people continue to purchase it. Dr Etzioni explains that this may be because a new model has fewer reviews, which can make the older model seem better, and newer models often have a cheaper list price than an older one. This leads buyers to suspect the newer item is of lower quality (which can be true, but does not have to be). At the same time stocks of older products dwindle putting upward pressure on the price.

The Decide model differs substantially from simple price comparison services. Such sites, which date back to the 1990s, aggregate prices from many online retailers. Decide presents a similar list to show current prices, but also attempts to advise consumers on the most opportune moment to make the purchase. In time this might force sellers to slash their margins and discount obsolete products languishing in inventories as buyers await the arrival of new versions. That said, retailers' prices are already at or near equilibrium. At least half the time, Dr Etzioni says, Decide tells consumers that it is a good time to buy, as prices are stable and there is no replacement in the offing. (The exact numbers depend on product category and time of year.)

Your correspondent's grandfather taught him always to haggle. Haggling empowers the buyer, affording a sense that he holds some direct sway over the price of a desired good. Modern consumer societies tend to rely on mechanisms of price discovery which, though economically efficient, are less emotionally gratifying. Auctions offer a degree of explicit control but are often impractical. By giving advice on not just where, but when to buy, Decide helps make negotiating the online bazaar a slightly less passive experience.