This article was originally posted on wns.co.za.
Customers are unpredictable and understanding their buying behaviour is simply not possible. Well, not actually. This statement is only true for companies who have not yet harnessed the power of predictive analytics to gain customer insights. Up until now, most companies tackled customer retention by taking corrective steps after they went wrong to avoid losing out on potential customers. Today, companies can use predictive analytics to anticipate customer spending and focus on creating the right opportunities to foster customer loyalty.
A lot is spoken about analytics, particularly customer analytics, which is not an entirely new phenomenon and has in fact been around for quite time. Back in the 1950s, when businesses began to realise that every customer is different from the next and each have their own needs and wants, they started gathering data about their customers to begin to understand how these needs can be met. This saw the rise of customer segmentation according to demographics, physiological and social metrics, among others.
Fast forward to present time and the picture is similar, however, the amount of customer data now available has grown exponentially and a number of tools and technologies are available to decode and understand it. It is easy for companies to get lost in a deluge of data and have no idea what to do with it. That is the purpose of analytics – to thoroughly interrogate the data and go beyond the data to find the underlying stories that can drive greater business success.
Analytics can be divided into three broad types; descriptive, predictive and prescriptive analytics. In simple terms, descriptive analytics looks at the data and summarises it, predictive analytics analyses data to determine what is likely to happen, and prescriptive analytics looks at what can be done and makes the necessary recommendations for sound decision-making.
Gartner research reports that by 2020, predictive and prescriptive analytics will attract 40% of enterprises’ new investment in business intelligence and analytics.
Painting Accurate Customer Portraits with Predictive Analytics
Predictive analytics can be particularly valuable to a company’s overall customer experience. Through analysing both the structured and unstructured data, this technology can highlight historical patterns in relation to customer behaviour and use this to forecast future behaviour for particular customers on an individual level. In addition to pattern matching, predictive analytics also makes use of various other techniques, such as predictive modelling, forecasting, regression analysis and multivariate statistics.
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