As we speak about pricing policy, we should remember that trading businesses fall into two major groups: traditional and modern online retail. We have already discussed this division in the previous case study of our Purchases series.

Everyhing we said there about the complexity of forming an assortment matrix applies even more to pricing policy.

Traditional retailers" pricing is so simple that it we can add nothing new.

A spiteful comment
So simple that their useless Marketing Specialists have to concoct price disturbances, as absurd as they harmful, simply to prove their own utility — and to bullshit both their bosses (we do not know if they are successful — but they seem to, as those known saboteur positions are still present in their staffing plans) and consumers who have long since lost all interest in those red/yellow/green price tags, posters screaming "SuperPrice!" and other half-arsed efforts of the marketological saboteurs.
 

In the case of Internet retail, pricing policy is a more complicated affair, but luckily, simpler than filling the assortment matrix.

The pricing policy as such stems from the company’s clearly worded market positioning. And never vice versa.

If we exclude pseudoscientific locutions a pricing policy is formed in two stages:

• firstly, we determine the list of Benchmark Competitors (BCs), the market’s key companies;
• secondly, we formulate the rules for establishing our own price via mathematical ratios into which we read the BCs" prices.

It is clear that the BC list and, consequently, our pricing policy will be formulated separately for each goods category. And for each region, if the company operates in regions where the market situation differs widely.

The description of a correct approach to identifying BCs goes well beyond the scope of this text. We shall simply state that (a) in most cases, no BCs are singled out at all — so a meaningful pricing policy is out of question here, and the result is quite predictable; and (b) even in the infrequent case of a systematic approach to BC identification it is plagued by mistakes. We can’t expect a perfect result in this case, either.

A correctly defined list of your BCs (e.g. Company A is an example from the premium network segment, and Company B is a cash-and-carry store offering the whole market’s lowest prices, while we position ourselves as a company in the medium price segment, a chain of "next door" shops) will help you formulate clear mathematical ratios such as:

Our Price = The middle between the A and B prices. If B doesn’t have the goods, and A has, then Our Price = A price minus 3%

If A doesn’t have the goods, and B has, then Our Price = B price plus 5%

If neither company has the goods, then we double our mark-up.

If the goods left will last less than three days of sales, we double our mark-up.

If the goods left will last less than two days of sales, we treble our mark-up.

… and so on. The complexity and volume of the pricing logic are unlimited.

Most importantly, the logic must be formalizable. And you shouldn’t try to blow up your brain and produce a brilliant set of rules out of nothing. Because:

• To do it well will take time anyway, and the wasted time can be put to better use;
• The pricing logic must be constantly improved (that proverbial kaizen concept) — as a result of both growing internal competences and changing external conditions. It is quite impossible to establish it once and for all.

If you are the indisputable market leader, then you may need no list of BCs (possibly, but we haven’t heard of such). But even in this case, pricing rules will be extremely helpful — even if not based on BC prices.

With a subtle motion of the hand, correctly (i.e. mathematically) described pricing logic is offloaded to IEM System — where all the tools are ready for this; the rules are formulated by the system’s functionality, competitors" prices are downloaded at the required frequency in the background, and sales/reservation statistics is available online.

Voilà ! Previously we showed how to define the assortment matrix and to measure PCMs" (Purchaser and Category Managers") success in executing it; here we have described how to relieve them of immense routine (and, as such,always poorly done) price updating work.

We recommend that after the algorithm is debugged, access to manual price change should be restricted as much as possible, and certainly taken away from line PCMs.

If manual price changing remains available to them, you will never obtain normal pricing rules and, consequently, your prices will never be fully up-to-date.

As your PCMs object to your prohibition to adjust prices manually, they may argue something like, "we feel the market, when something is going up or down, and we can correct things on time — and you are going to drive life into those silly rules, how that foolish computer will price it, and all".

The truth is as follows:

1.  In the previous episode we have already discussed the true utility of speculations like "we know what is going up or down".

2.  In fact, no one can keep the prices of hundreds of goods items that vary constantly and accidentally updated at all times. At best, the most important ones are updated, while the price will change by the time of the next purchase. As for the slow-moving merchandise the price will never change.

3.  Those rarest individuals who really try to adjust their prices actually follow the algorithm that is a simpler version of the BC-based pricing rules. Meaning that they watch and ape their closest competitors. But they do so only when the goods sell no longer, or when they have nothing else to do.

4.  The above scheme by no means excludes the PCM from the pricing work. On the contrary, it leads him to switch from the chaos of accidental "gnarled hand" adjustments to systematic actions. What shall we do about scarce goods? We check the "scarce" box that multiplies the mark-up by five and automatically clears after the goods arrive next time. If we need to dump any goods, the procedure is similar but reversed in sign.
 

A spiteful comment
As you listen to your PCM’s objections, remember you should believe nothing of what you hear and only half of what you see. However much they may emblazon their great talents as connoisseurs of the market and virtuosi at pricing abundant or scarce goods, they will somehow be unable to deliver a measurable result (e.g. a marginality percentage of their goods category that is much higher as compared to competition over a year’s period).

Now you can use the analysis and control features of IEM System to focus your PCMs on the really needed and extremely important thing that no computer can do yet: to physically pack your warehouse with those very goods that will attract margin-bearing herds of consumers longing to give you their money, so that you can milk them.

See in the next episodes.

Optimal allocation of goods within the retail chain