Relationships between customers and businesses have drastically changed in the last decade. Loyalty is a relic from a time gone by and consumers are more scrutinising than ever before. Businesses are required to be completely proactive when it comes to customer satisfaction and identifying opportunities to sell more. In order to be proactive, businesses must understand their customers more than ever and are turning to ever more sophisticated methods of data mining.
What is data mining?
Data mining is the automated sifting of data (through mathematical algorithms that decipher patterns and use statistical probabilities to predict future patterns) into something meaningful and actionable for companies so they are anticipating customer needs rather than reacting.
Data mining is not a new concept, in fact it’s probably right alongside ‘supply and demand’ in Ye Olde Book of Sales. Once, small businesses would keep track of customer needs, preferences and demands in their heads. A local butcher would know that Mrs Norton comes in every Friday for a whole turkey and would have it prepared and packaged – an impressively personal service to Mrs Norton but relatively little work for the butcher. He would also be able to cross sell stuffing and condiments, thus increasing his profits. Over time his knowledge of her shopping habits would improve and that would help his purchasing and sales predictions as well as open opportunities to increase his product line.
This kind of detailed knowledge might seem impossible to scale for larger businesses but as far back as the early 90s, data was being collected and turned into something meaningful on an industrial scale. UK retail titan Tesco devised a loyalty card that, when scanned by the customer, would provide the customer with points to spend in store but crucially would provide Tesco with invaluable data they could work with to improve sales. This kind of loyalty program is now prevalent around the world with recognisable programs like Woolworths Everyday Rewards and Coles Flybuys.
This knowledge allowed Tesco, Woolworths, Coles, and others who followed suit, to anticipate customer desires, monitor stock and check purchases against competitors close to a customer to release conveniently timed coupons. These coupons would help avoid potential loss of sales as said customer no longer needs to head to a competitor to purchase a lower priced version of the product, where they might have picked up a few more items too.
Value of data mining
Companies are constantly required to reinforce their value to ensure their customers aren’t finding better value with someone else. There are more customers, products and competitors than before and due to our increasingly impatient nature as a species businesses have less time to react to customer needs. Customers no longer wait for you to catch up with their demands, they find someone who is already willing to meet them, and on their terms.
Knowing what your customers are going to start asking for is invaluable and data mining can help you determine what ‘affinity analysis’ (the “customers who bought…” links you see on almost every retail page these days) is most relevant for your customers. It’s powerful knowledge when put to use. And it’s not just retail that this applies to as this data can be reversed to find patterns to reduce fraud, target new customers and improve customer retention.
Converting data into rich learnings allows you to work out the key plot points before you turn the page so your customer’s stories are a surprise. Effective data mining will teach you how to make the right offer, at the right time, to the right person through the appropriate channel to increase conversions.
Understanding your customers better provides many benefits and is a measurable return on investment but it isn’t a magic solution – not on its own at least. Significant data mined patterns are only relevant when used in conjunction with effective marketing strategies, CRM and other technologies, for example, it can help improve customer retention by accurately targeting the customers most likely to use a competitor.
Data mining essentially extracts information database users were not aware of and presents it in actionable format. It predicts customer behaviour and, applied properly through campaign management software using advanced statistical, numerical and multivariate techniques, can directly target consumers on an individual basis.
Your company is probably already sitting on a diamond mine of data just waiting to be turned into something actionable. Employing the use of professional data mining will have a noticeable effect on your bottom line. The more data you can collect, decipher, and leverage the bigger your competitive advantage and the better value you can deliver to your customers. The more value you offer customers, the greater your revenue.
Vividus understands the value of customer data but more importantly, how to overcome challenges to leverage that data to create intelligent, actionable data. For more information on how to anticipate your customer needs contact Vividus on 07 3482 4262 or email@example.com.