Today, it's a well-known fact that big data not only exists, but also has many benefits that enterprises can tap on. However, little has been said about its potential to disrupt certain industries, for example, the well-established retail market.
To be really successful, retailers need insights to what's happening on the ground. How do they know what products are always sold together and if their stock turn is at the right level to ensure efficiency of its business? In the same way that customer service has evolved to be a 24x7 service, real insightful analysis to create better opportunities and anomaly spotting is something that the majority of us take for granted.
Let's take a couple of examples. In retail for example, have we not come to expect Amazon or Qoo10 and other online retailers to recommend our next purchase based on prior buying habits? It's quite telling that Amazon claims 30 percent of its sales are generated as a result of its recommendation engine: "customers who bought this book also purchased..."
While most consumers now take it for granted that they receive personalised and tailored offers in the retail, utility and telecoms industries, these methods of offer are not as welcomed in other vertical sectors, for example public sector or government-based industries.
Those industries and vertical sectors that have easy and available access to customer or industry data to compare and contrast should be taking full advantage of this. At a time when cost comparison and running as leanly and efficiently as possible is crucial, all companies need to be looking for opportunities where they can also benefit and find growth. And many are.
As mentioned, the retail sector in particular is doing well out of analysing customer behaviour and patterns and being able to offer consumers coupons almost in real time. Two great examples are UK-based retailers, sandwich shop EAT and retailer giant Sainsbury's. Using business intelligence technology to pull together data on ingredient purchasing, weather, store visits and staffing, EAT has been able to purchase seasonally and staff according to demand. The other example is Sainsbury's, which is using big data to help it set prices, nearly in real-time, and shift inventory by giving loyal shoppers customised coupons.
There are definite similarities to be drawn between the retail space and other industries (such as Telecoms and Mobile). The most common advantage that these industries share is the consumer base and user data. Thanks to (mostly) longstanding customer relationships, the billing history can throw up a huge amount of insight on the individual shopper or mobile user and their habits. Some of the immediate benefits on offer would have appealed to the likes of local councils who want to measure how many people visit the high street after the introduction of free car parking, farmers' markets or late night shopping, for instance.
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