Fixed pricing models: A thing of the past?
Industry specialists have predicted that we’ll see the end of fixed pricing models across retail stores within the next five years. In their place, flexible pricing models will rise, made possible through electronic tagging in-stores. These models will enable retailers to change pricing in real-time and respond to changing customer demands. Say a store is finding it hard to ship that latest line of smoothies, or the Christmas jumper range was too ambitiously priced for your target market – with flexible pricing you’ll be able to deal with those issues immediately by changing the price in real time.
Flexible pricing is one example of how bricks-and-mortar retail is becoming increasingly digital – and good data will help complete their digital transformations. Retailers need to have a strong grasp of customer and market data, and a powerful data management strategy to master flexible pricing.
Rather than being fixed entities, pricing models across the shop floor have been evolving for the last few years as retailers use new data streams to inform commercial policy. However, although electronic tagging has been used for goods for some time now, particularly across Europe, its potential is rarely used to the full in the UK. Where digital readouts exist, they usually display static prices. However, they could be updated more frequently to reflect and direct consumer buying behaviour.
We’re familiar with more fluid cost models being used online, and flexible pricing has been the norm in some sectors for some time. Airlines for example, and price comparison tools such as SkyScanner, use customer buying and browsing behaviour to increase and decrease flight prices in response to demand. Even Amazon sees prices raised and lowered regularly enough that it has to provide a price guarantee if you pre-order an item before its release.
It seems there is always a sale or discounted product being sold somewhere, whether in-store or online, and connected consumers know this. With smartphones and constant web access, the younger, more digital generations are far more likely to shop around to get the best price. Google Shopping and price comparison websites have helped move this on significantly, and as more people shop around for the best price, retailers need to use customer data to ensure they’re pricing their products in the best way to attract new business.
Taking advantage of retail data
Retailers should be thinking about how they can use customer insights to offer flexible pricing or ‘peak time’ pricing where the cost of items rises and falls according to demand, as shopping behaviour changes and items vary in popularity. Retailers also need to understand demand in greater granularity to drive different shopping behaviour - for example, reducing long queues at peak times by, say, encouraging customers to buy their lunches earlier in the day at a lower price. Deeper understanding of demand will also enable bundled offers based on external factors such as weather or local events. To achieve this, retailers need to understand customer buying behaviour so they can build a clear picture of product preference, returns, cross-sell opportunities and return-purchasing patterns.
Looking to a future of flexible electronic pricing in-store, retailers will need to deal with new problems. For example, if prices are set to be raised at midday, what happens if a customer picks up an item at 11:55am (when the price tag says £2.50), but doesn’t check out until 12:03pm? They may end up being charged more. What can retailers do to avoid upsetting or aggravating price-conscious customers?
Retailers will need to draw the line on precisely when the lowest prices are guaranteed so customers can get the best deals – for example, specifying clearly where the point of sale is – once lifted from the shelf, or at the check-out desk.
Data at the heart of flexible pricing
For retailers to make the most of this new model, they must have a clear view over all the relevant data in their systems. They need to be able to understand what customers are buying and when; detect patterns in purchasing behaviour and run analyses of the impact of changes in pricing. Does a price rise bring reduced sales, or does it actually prompt people to buy what has become a premium object? Is there an overall rise in revenues as a result of a price decrease? Can different pricing systems impact shopper behaviour?
Retailers need not only to be able to analyse these variables – they need to be able to measure them in the first place and aggregate, integrate and clean the relevant data to make it all possible. Without accurate, easily accessible data, flexible pricing is just guesswork.
Retailers have an opportunity to make pricing part of a more personalised, targeted shopping experience for their consumers, but in order to get there they must first take the time to get their data in order. From this perspective, a focus on data quality and creating a single view of the customer are foundational elements of a successful digital pricing programme.