THE PRICE IS NEVER RIGHT
We have examined the issue of retail pricing strategy extensively in one of our chapters in the text. I was drawn back to this topic recently when I read an article recently (True cost of Amazon pricing revealed: The Times; 9th September 2017, p7, Andrew Ellson).
This article addressed the general issue of dynamic pricing, something which I hasten to add is not new. Service sectors such as airlines and hotels have used the practice for a number of years in an attempt to get the balance between supply and demand more in their favour. Where a company is selling a perishable product (i.e. it cannot be stored or inventoried), such a strategy, based around changing the price of the service constantly – sometimes upwards, sometimes downwards, can help to optimise sales and the margins.
Amazon, our old friend, which is usually in the forefront of pioneering endeavours, has arguably taken the practice of dynamic pricing to another level. This is reflected in the practice of changing the price of items much more frequently than is the case with hotels and airlines. The author of the article mentioned above cited a study which suggested that the price of an item could change very dramatically over a period as short as a week or a day. In the case of one item the price varied by as much as forty-five per cent over the course of a week.
Further details of this study revealed that over the course of a one-year period and based on a random selection of one hundred items including books, DVD’s and so on, prices fluctuated by up to as much as two hundred and sixty per cent between the highest and lowest price points.
As we might expect prices changes tended to be linked to certain events that related to the items. For example if a film was a success then the price reflected that level and degree of popularity. Seasonal events such as the onset of summer, Halloween and Christmas also played a significant part in the re-formulation of prices.
In essence it is the disparity in the price changes, the frequency of such changes and the scale of the change (on a wide range of items) that has taken dynamic pricing to a new level. You might say that such bewildering change only serves to confuse and potentially annoy shoppers. Ellson quoted the example of a Waeco fridge that featured on the Amazon website. On August 3rd 2017 it was priced as £400. On August 6th it was advertised at the price of £580. A week on from that date it had dropped back to a price of £398.
On average the one hundred products that featured in the study changes price every five days and in the case of one item the price changed by as much as 300 times during the year.
What are we to make of this from the perspective of retail marketers and as shoppers?
From the perspective of businesses in general and retailers in particular the ultimate challenge is the charge the maximum that people or companies are willing to pay for the product or service. Reality intrudes and suggests that this is not always possible or indeed desirable at certain times.
For instance retailers entering new markets or new product categories may have to engage in some promotional or discount pricing in order to make inroads in that market. Some retailers target a particular segment such as the low-income sector. This inevitably means that high prices are a “no-no” and low prices / high volume is the order of the day in terms of the cornerstone of the retail strategy.
However dynamic pricing in the context of changing prices frequently on the basis of market conditions and on the amount of data that is captured on an individual’s purchasing and demand patterns can enable retailers to maximise their revenue and margins.
As mentioned earlier we see this with airline tickets and hotel rooms. Uber, the taxi company bases its business model on charging customers what they think they are willing to pay, weather conditions, time of day and driver availability to name but a few influences.
At music festivals, where people are dehydrated and suffering in the heat, you can charge as much as £5 – £10 for a large bottle of water and not too many will complain. The need to quench their thirst overcomes any misgivings about paying such a high price.
For the shopper one inevitable conclusion is that they have to become more “savvy” and more precise in terms of how they go about monitoring prices on the web. If you lean towards this type of practice then it can be argued that you can benefit from the effects of dynamic pricing. If you can identify the occasions when prices are likely to drop then you can take advantage of such market conditions to benefit from lower prices.
However human nature and consumer behaviour suggests that many of us at best do not have the time or inclination to engage in such disciplined practices. Many of us are lethargic about such matters and only engage in purchases when we need to. By that time the price will most likely have taken a hike.
Think about how you purchase an airline ticket. How many of us plan ahead and buy a ticket three to four months ahead of the flight time? I thought so. In my case I tend to leave it to a week or so before I intend to fly. The software and algorithms used by airlines to analyse demand patters will ensure that prices are on an upward trajectory at this stage in the purchasing cycle.
Again we see the confluence of big data and technology. Amazon has long been the pioneer in this area and once again we are witnessing it driving forward the boundaries.
While many commentators argue for clarity and transparency in the area of pricing, it can be argued that Amazon’s approach is opaque and confusing.
In the fields of sport and entertainment, organisations are embracing dynamic pricing with some degree of enthusiasm. Fans are faced with a bewildering rate of change as they are presented with differing prices by the day and by the hour.
It can be argued that price leaders such as Amazon are in the ideal position to develop dynamic pricing strategies. I would make the observation that they are no longer applying such a strategy indiscriminately. Using big data and sophisticated software they are adopting a more targeted approach to individuals and with product categories. Analysis of shopper interest metrics such as sales performance and online abandonment rates, can provide retailers like Amazon with prescient data upon which to activate focused dynamic pricing strategies.
There is no doubt that shoppers will have to “acclimatise” to further and more extensive applications of this pricing approach. Those of us who remain in the lethargic and disinterested category are likely to end up paying more for items than those who adopt a more disciplined approach.
We can debate (and we have done in earlier blogs) the efficacy of dynamic pricing. As retailers equip themselves with ever-more sophisticated software and gain access to increasing amounts of big data, it is likely that they will be able to further improve their profitability.