New Strategies for Managing Prices to Maximise Profitability

A more strategic and planned approach to pricing in the current market and into an uncertain future set off by Brexit, represents one of the strongest opportunities to protect revenues while so many other tactics are failing to deliver, says Chris Field, Chairman of Retail Connections.

Even retailers that are making money during the current crisis are seeing profits slide. This is down to the costs of adjusting to the pandemic in terms of hiring staff, safety equipment, interrupted supply chains and wild variations in customer traffic that have thrown off their replenishment levels.

Online retailers appear to have had an easier ride because so much business has switched to them, away from stores, but they have faced many of the same upheavals as their offline counterparts, so in short, no one can claim to be business as usual.

The media has reported extensively on how well retailers have responded to the crisis, but dealing with changes in customer behaviour continues to be a major challenge. There is a paradox at the heart of the 2020 shopping journey; while price sensitivity is low for must-have items that are constantly threatened with scarcity as lockdowns trigger panic buying, it has risen dramatically for other items as consumers fear for their jobs and future incomes.

The new environment is unlikely to change soon. According to a recent report by Revionics, ‘Pricing strategies to create loyalty and profitability’, consumer sentiment and behaviour not only changed in the early days of the covid-19 crisis, but is still evolving.  Retail consultants are talking about the “homebody economy”: in most countries, more than 70% of survey respondents don’t yet feel comfortable resuming their “normal” out-of-home activities.

Demand patterns have therefore been disrupted and planning for these new behaviours is hard, made worse by previously store-only shoppers forced to move more of their purchasing online, where price transparency is much greater.

In this new world, current product lifecycle management models simply give away too much margin in three key areas:

Every-day price

Simply raising all prices does not work. Firstly, customers will simply not buy, particularly if they know that a competitor is cheaper, which increasingly they do. And secondly, the retailer’s price perception that they have worked so hard to build may be lost in an instant. So the margin of error for prices may be extremely small.

Promotions

Five years ago, Forrester found that consumer packaged goods (CPG) brands spend more than $500 billion on trade promotions annually and estimate that a third of that spend generates negative returns. Moreover, many retailers take upwards of 75% off, sell below cost, and gain only insignificant demand. Forrester also found that almost all promotions cancel each other out while 90% of revenue and 85% of profit is from the top 30% of items.

Markdowns

As a consequence of poor decisions made on initial pricing and promotions, markdowns are often thought of as a fire sale. They also generate a huge amount of waste for which supermarkets in particular have been criticised.

Solution

Each of these three areas is an opportunity to drive sales, protect margin and demonstrate sustainability through a reduction in waste, by using data science to understand the price elasticity of every SKU – whether profit margin can be boosted by raising the price or volumes increased by reducing the price.

Processing this much data across so many SKUs and setting prices dynamically (i.e. quickly and often), is not possible for merchandise teams using tried and true methods at human speed and scale. The retailers that evaluate the market through scientific approaches generally set prices, manage promotions and leverage markdowns most profitably. And supported by AI, merchandisers and price managers are then free to make strategic adjustments based on competitive or general market activity around consumer confidence, pandemics, spiking demand and so on.

Future

With a science-based approach in place, it then becomes possible for retailers to be even more responsive to demand. Once retailers understand each item’s price elasticity and a wider range of demand signals, they can start to make price changes weekly, daily or even, for grocers operating in the most fiercely competitive environments, in real or near-real time. Consumers are now used to seeing frequent price changes and price differences, particularly as the number of sales channels rises, as long as they result in a fair and non-arbitrary price for them in the moment of purchase. In fact, in a study with Forrester, Revionics found 78% of shoppers believe changing prices with data science is fair.

Tech-savvy shoppers will increasingly expect to receive the kind of highly targeted offers in store that they enjoy online. Being able to base pricing and promotions on real-time dynamic pricing solutions, and automating the distribution of updates to the shelf-edge, enables retailers with stores to price with flexibility and speed, reacting dynamically to the competition and always offering a fair price to shoppers.

Greater responsiveness to real demand can also be introduced using Zone pricing. Zone pricing is built by grouping stores based on demand behaviour, using local data to inform prices, promotions and markdowns. This is not new to many retailers who, before the pandemic, were already zoning based on competitor footprint, cost structures, customer demographics, climate patterns or regulatory conditions.

As the Revionics report shows, advanced pricing algorithms now enable retailers to dynamically execute their comp-etitive strategies across numerous zones as well as channels while maximizing profit potential on less-competitive items.