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IREU Top500 The Customer Report: 2018

IREU Top500 The Customer Report: 2018

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GUEST COMMENT The secret weapon of retail - predictive analytics

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GUEST COMMENT The secret weapon of retail - predictive analytics
GUEST COMMENT The secret weapon of retail - predictive analytics
Like most industries and sectors, retailers are driven by the need to provide exceptional customer service. In a crowded, competitive market, this need becomes more prominent. Gaining any kind of advantage becomes invaluable, particularly when it comes to understanding your market; the secret to which is having – and using – insights derived from data.


These days, retailers collect all sorts of information about their customers as they use their phones, shop in-store, buy online, withdraw cash from the bank and post on social media. And as retailers develop their go-to-market strategies to include multiple channels, the volume of internal and external data is increasing exponentially. Indeed, research commissioned by SAP has found that 89% of UK businesses say the amount of data that they collect has increased in the last year. The fact is, for retailers especially, more data means a more rounded view of the customer, insight into the market and awareness of potential risk. All of this insight can be used to make informed business decisions if interpreted correctly using predictive analysis software.

Customer insight

It’s becoming increasingly difficult for retailers to differentiate themselves based on products or pricing alone, which is why offering a unique customer experience has become so important. To do this, retailers first need to understand their customers. By looking at shoppers’ buying behaviour patterns, customer service history, response to promotions and social conversations, retailers can gain insight into each individual’s needs and preferences.

Predictive analytics allows organisations to analyse and anticipate behaviour – for example, if a customer bought a gas barbeque last year, will they need more gas canisters this year? And what is the purchase frequency to anticipate demand when they do buy? How can promotional cross-sell and upsell be incorporated to increase transaction size, number of items, and revenue? This information provides retailers with the ability to forecast, in real-time, the likelihood that a customer will buy, abandon or indeed default – which gives them the power to save the situation by providing targeted deals, or offering informed services if needed.

Retailers need to analyse and employ customer insights to develop a new level of understanding with them based on the results. By coordinating all channel interactions to attain a single view of the customer, retailers can encourage flexible customer shopping at any location, any channel and on any device.

Market trends

Predictive analytics can also be used to gain an understanding of the wider market environment, and where it’s headed in order to take advantage of opportunities and help drive supply and marketing decisions. In fact, 79% of UK retailers believe predictive analytics is primarily about exploiting opportunity. This could include things like gaining insight into pricing and promotion variations by channel or specific product/category performance to drive strategic goals and objectives.

Factoring in things like weather forecasts to predict demand for seasonal/promotional goods, as well as building behavioural models of customer demographics to anticipate what channels they want to use, can give retailers insight into what they should be doing to gain a competitive edge. By using sales and behavioural data alongside information about market conditions, retailers can accurately project demand for anything from cough and cold products to school supplies to a mobile optimised website.

The smartest retailers go beyond this to calculate and shape new trends before they saturate the market. By staying ahead of such trends as they develop, businesses can better manage planning, supply chain and merchandising.

Risk mitigation

Of course, alongside identifying opportunities is the need to monitor risk to the business. Retailers need to be able to predict gaps in supply chain efficiency, supplier stability, customer abandonment and the causes of attrition, in order to minimise risk. The software can examine unusual patterns to recognise anomalies and pinpoint where there are issues, all in real-time, allowing retailers to better control their losses and remain competitive.

It’s clear that there are numerous benefits that predictive analytics can bring to retailers, and those that recognise this will prosper in 2014. Getting access to – and understanding – data has until recently been seen as a complex and highly-skilled task, delivered by people with advanced degrees in statistics and prior analytical experience.

As predictive analytics technology evolves and becomes more intuitive and user-friendly, businesses are finding that the role of interpreting data is now filtering down to many parts of the organisation, across several lines of business. By providing education and training on advanced analytics, and marrying this with investment into intuitive technology, retailers will be able to drive real value and insight across their business.

When it comes to retailing, knowledge really is power. Gathering as much customer data as possible is important, but it’s what you do with it that counts. We’re in an era where it’s getting increasingly difficult for retailers to create a point of difference, and where shoppers are demanding ever-more personal, targeted service. Therefore, retailers need to turn the vast amount of data that’s at their fingertips into meaningful insights. With a workforce that’s empowered and equipped with the skills to use the technology, they will be able to do just that.

James Fisher is VP of marketing, analytic solutions at SAP
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