This vendor-written piece has been edited by Executive Networks Media to eliminate product promotion, but readers should note it will likely favour the submitter's approach.
For years, retailers have been ahead of the game in collecting consumer data. Consider loyalty card schemes: from the retailers' perspective, these have little to do with loyalty and a lot to do with gathering data and getting to know the customer. Some have been operating for decades - think of the wealth of data collected.
However, the landscape has changed, and such schemes offer one piece in a huge and complex business intelligence puzzle, as a smorgasbord of connected devices and new data sources have joined the mix. Big data analytics makes it possible for retailers to effectively connect the dots and bring actionable, data-driven insight to their decision-making processes.
Let's look at some of the key sources retailers can tap to win big with their data.
1) Customer data
Whether it's purchasing data from loyalty cards or online sales records, retailers collect a huge amount of data about customer buying behaviour, generating real insight into their customers, from identifying buying trends to monitoring behaviour patterns. However, to extract real value and deep insights, retailers must apply big data analytics at every stage of the retail process, turning analytics into actionable predictions.
Understanding what the popular products will be, predicting consumer trends, and accurately forecasting demand gives retailers an enviable competitive edge over the competition.
Big data analytics really comes into its own when dealing with historical information. By capturing large volumes of data, retailers can identify trends and begin to forecast what the future holds. By using predictive analytics to analyse customer activity captured over a long period of time, retailers have access to extremely detailed insight into consumer behaviour and likely actions.
Analysing all this historical data also enables retailers to detect and identify customers at risk of churn, identify product cross- and up-sell opportunities, and profile target demographics. Think about those long-standing loyalty schemes I mentioned - they get even more valuable when subjected to modern analytics tools.
Retailers can also utilise big data to vastly improve customer experience and ensure shopper satisfaction. Big data analytics offers an opportunity for interactions to be tailored to each customer by understanding their attitudes and factoring in elements like real-time location to deliver a personalised experience.
Such analytic insights are not excluded from the brick-and-mortar world. In-store beacon devices will also enable retailers to monitor the consumer buying journey as shoppers progress through the store. By applying big data analytics to this data, retailers can, for example, optimise the position of stock and promotional stands within the store to ensure greater customer engagement.
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