The price is right – with Data and Analytics

02 March 2017

Pricing is of key importance for any business. Setting the right price for your products and services can play a big part in your success or failure (even if you’re a not-for-profit) and it’s incredibly sensitive. Research suggests that a small increase in price can bring a substantial increase in operating profit – as long as that price increase doesn’t send your customers scuttling elsewhere.

Price matters, but hitting on the right price at the right time has always been a challenge. Certainly there is no shortage of theory around pricing. The most famous is ‘price elasticity’ – which essentially means that the price, if it’s going to maximise profit in the long run, should reflect the demand for the product against its availability in the market. But more often than not, the final decision has had more to do with gut instinct than detailed analysis.

But in a world increasingly hooked on internet shopping, getting pricing right requires a lot more than guts. Consumers are well-informed and internet savvy – some may even know pricing and promotions better than staff. Many willingly spend hours searching for the best deal and looking for a discount voucher before they buy. It has become normal behaviour. And consumers share information very quickly – unintended pricing slip-ups and anomalies can quickly turn into very expensive mistakes. This makes for a very fluid, risk-laden and, at times, unpredictable environment.

Fortunately, organisations have the ammunition they need, in the form of data. Businesses typically generate millions of pieces of data every day and there is a vast array of unstructured data available to them – in the form of emails, social media posts and other chatter about their customers’ and the public’s preferences, consumption, opinions and developing trends.

So if the availability of data to inform pricing decisions isn’t the problem, what is? Often the problem is that organisations struggle to use this data well and they can lack confidence in the basics. Namely that their data is correct, they understand their costs and that agreed price changes in the boardroom will actually flow through to products on the shop floor. Price is one of the most important data points for any organisation, so we have to ask: what can Data and Analytics do for pricing?

The answer is, a lot. Data and Analytics can, of course, give us far greater confidence in the underlying data needed for pricing decisions, but it can go much further than that. The ability to seamlessly combine data brings a whole new level of sophistication to pricing decisions; the use of artificial intelligence type techniques - to automatically predict and adjust pricing depending on market circumstances and buyer characteristics, for example – can bring even more exciting possibilities.

It’s possible to analyse pricing data in real time and see how pricing affects a single customer, or a larger group. We can see how macroeconomic variables and competitor price changes affect shopping behaviour, and identify pricing sensitivities for individual products and type of customer. Testing how a combination of pricing with other factors, such as shelf position or website layout can also be explored.

When using Data and Analytics in pricing, a good approach will have several critical elements:

  • Good quality data – which means it’s well governed, with solid controls and clear taxonomies so like is compared with like.
  • A well thought out strategy - so that it’s clear what is trying to be achieved and how activity will be tested and embedded back into the organisation if successful.
  • Clear lines of responsibility – which confirm who will be involved and who will have authority to make key decisions.

Pricing success today is all about data. And that means understanding its flow, its quality and the controls around it while making sure to ask the right questions and, vitally, measure the results at every stage. But to make sure the price is right and to gain true confidence in pricing, it’s not just about using data – it’s about using it well.

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