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“Knowing who your customers are is great, but knowing how they behave is even better.” – Jon Miller
The quote succinctly describes why it is critical for every company to put in place strategies for predicting customer behaviour. Customer needs, situations, expectations, and demands a constantly changing and evolving and there would be no way to understand them beyond ‘today’ without some manner of predicting customer behaviour. The good news is that predicting customer behaviour is easier now than ever before. With technology, so much information and ‘digital footprints’ that customers leave, companies have a lot more data by which they can predict customer behaviour quite accurately. The data around customers comes from their buying history, trends, and patterns, social media and other online activity, information forms and other such sources. Every company is frantically trying to access, store and analyse this data to their advantage – with so much competition however, predicting customer behaviour is not getting easier. Satisfaction and loyalty in customer circles are ephemeral and in order to hold on to these critical factors, companies must get creative in predicting customer behaviour or risk losing customers to competitors.
A company’s performance needs to improve consistently and it customers who decide whether the company is at par with what they expect. In order to keep pace with customers, it is imperative for companies to be able to predict customer behaviour such that they can cater to the needs of customers in the future too. Predicting customer behaviour is a tool for companies to consistently entice customers and keep them engaged for longer such that they not only provide repeat business but also become brand advocates for the company. Marketers understand that predicting customer behaviour is now an indispensable part of their jobs. While collecting current information, businesses could assess the existing problems, pain points, emotional reasons, and other such present data about customers. While this information can help to some extent, to ensure that a company can come up with sustainable solutions, predicting customer behaviour is critical.
While current customer insights provide companies with potent information about customers, they need long term and actionable data to improve engagement levels and loyalty from customers. By predicting customer behaviour, companies would also be in a better position to segment customers and ‘treat’ them basis the value they add to the company and the possibility of them becoming brand ambassadors. Such real time yet evolving information, will help companies to predict customer behaviour and put in place highly personalized offerings and customized solutions. In the case of customers and their needs, the biggest mistake a company can make is using guesswork to understand them. It would be much more prudent to put in place strategies that will allow them to understand thoroughly, customers and their current needs, making customers more amenable to sharing data that will help in predicting their behaviour. With the power to predict, companies would be able to save cost and effort by producing only those offerings that customers would instantly prefer.
Without predicting customer behaviour, companies would come up with offerings and solutions that they ‘believe’ would be best for customers. However, all the resources, time, and money would be of no use since customers may not need or like the offerings the company produced based on its assumptions. With resources already limited, such wastage could quickly lead to severe losses and irreparable damage to the company. It would be better for companies to refine their strategies and create their offerings by predicting customer behaviour, which would also help them to mould and shape customer behaviour in order to balance the needs of the company with those of the customers. The great thing about predicting customer behaviour now is that it is no longer a tough, time-consuming, onerous, and expensive task. Technological advances and a plethora of tools now ensure that engaging in this activity is a possibility for a larger number of companies, irrespective of size.
With CRM systems, companies now have unprecedented ability to not only predict but also mould customer behaviour, given the large amounts of data available. Companies collect customer data – both structured and unstructured – which when stored in a systematic manner can prove to be an indispensable method to dramatically improve current customer satisfaction levels and predict the behaviour and needs of customers. Companies obviously would not be able to manage the huge volume of data available if they did not invest in systems and technology to manage it. In addition to volume, the variety of data too can become highly unmanageable and unusable without proper systems in place. Top class customer service is now and will continue in the future as the competitive edge for any company.
Before predicting customer behaviour, using this data judiciously would enable companies to segment customers based on their needs and interests. In addition, companies would know whether it would be worth their while to try to influence certain customer groups and whether these groups would be persuaded enough to buy more than once. Based on this information, companies would not only be able to predict better, customer behaviour but could also have greater influence on the decisions customers may take with regard to buying. It would be possible to get customers to spend more time and money first on the customers who would be easier to influence and who would be willing to speak about their experiences to encourage others. The more such customers a company is able to gain, the easier it would be to influence a positive image about the company and its offerings. Predicting customer behaviour would become an even easier and more rewarding exercise.
The idea is to use the data and customer information in a way that influences the unsure ones, cements the influence you already have on the current ‘spenders’ and encourage them to help your company to switch over ‘doubters’ and ‘floaters’. Predicting customer behaviour of the last kind of customers is the toughest – they do not have a set pattern or buying history, but with the help of customers who are convinced of the efficacy of your company’s offerings, it may be possible to get them on your side.
While predicting customer behaviour, another error that some companies make is analysing the behaviour only of existing customers. While this is important to do, it would be prudent to reach out to a customer base that could be facing some problems with no apparent solution, and if your offerings would eliminate those problems, your company could find itself a new and highly satisfied customer group and a hitherto untapped market. There are several examples of companies that found huge markets and made them even bigger because they tapped into some unmet needs of the customers and provided solutions for them. This enabled them to control the behaviour of customers in the future too. The premise behind predicting customer behaviour should be to implement ideas that would allow people to find creative solutions to their problems. Such support and offerings from a company would deepen trust and confidence in the company, and the top predictions of customer behaviour would be loyalty and brand advocacy. Use customer behaviour prediction to drive your company’s customer engagement and loyalty strategy and put your company on secure path to success.
