Customer Relationship Management And Big Data
Blog Post By: Viktoria Langwallner, Teresa Döring, Seongjin Bien and Zahabiya Malubhoy
“The only valid definition of business purpose: to create a satisfied customer.” by Peter Drucker
So what is CRM? CRM stands for Customer Relationship Management, and it is about knowing your customer. This is mainly done through collecting, analyzing and acting upon given data about customers. This allows for maximizing lifetime value of customer relationships. Which allows businesses to keep and improve their relationships with their customers.
This can be achieved through the help of the CIF, the Customer Information File. This is a unified view of CI from ALL touchpoints (point of contact with a customer). It has created unique products for the customer to make them happy and in a way introduce customer loyalty. Some of these products are customer services and loyalty cards. However, many of the departments in big firms do not communicate effectively with each other, and hence there is a problem with creating these CIFs. There needs to be a process in turning this into a more productive and less problematic service and function.
Measuring and managing customer profitability. Become customer-centric
There are three Phases of CRM:
- Acquire new customers
- Which takes place through innovation and convenience
- Enhance profitability of EXISTING customers
- Through cross-selling & Upselling
- Encouraging consumers to buy additional products (complimentary products, such as Coffee + Cake, Phone + Charger, CD + CD player)
- One-stop shop
- Makes it easier for customers to interact with companies. Such as online shopping at Amazon.
- Through cross-selling & Upselling
- Retain profitable customers for life
- Listen & respond
- Listen and respond to complaints effectively in order to keep the consumers
- Achieve customer’s lock-on
- Listen & respond
There are a few challenges with CRM
- There is not enough information and there is no direct contact between the data collection, and the actual needs of the people.
With CRM the company would also need to consider the customers expectations and act accordingly. Some expectations customers have are:
- Expecting to get your money’s worth.
- Not to get treated badly
- Obtain certain benefits by doing business with a particular company
- Quality guarantee
- Future support and assistance
- Knowledgeable about their own products
If companies do not meet or understand their customers expectations, they will lose those customers, as there are usually other companies out there who are more than willing to listen and give the customer the service that they want. A common example would be people switching telephone providers, for example, someone switching from vodafone to telekom.
Customer Churn Analysis
Another useful application of Big Data is the Customer Churn Analysis, which in essence aims to understand how and why a customer behaves in the way they do so that a product which is more attractive and suitable for them can be created. The data gathered is organised into a structured format with Hadoop, and the customer’s behaviour inside and outside of the interaction with the company is analysed so that the relevant data can be gathered. There is a considerable amount of ethical issues associated with this, as it is for many of the other aspects.
An interesting fact that was discovered after analysing the behaviour of both loyal and new customers of companies was that a long-term customer brought much more business, and therefore profit, to the company than new ones. Also considering the fact that it costs much less to retain customers than to recruit new ones, where sometimes acquiring a new customer costed more than the initial business they brought, the approach to customers in general quickly changed to that of creating loyalty than creating numbers.
From this, a new philosophy was born: wallet share. It used to be that the strength of a company was based on the market share, or the percentage of customers using a particular company’s products, not the competitors. Yet, with the information, companies quickly realised that a loyal customer is worth the value of multiple non-loyal or new customers. For example, a 1% increase in sales to an existing customers would boost the profits up by 17%, while to a new customer the profits only increased marginally.
The profitability squeeze
So what did the data about customer loyalty suggest? For banks, it was found out that only the top 20% of the customers made most of the profit in their product lines, whereas the bottom 50% was actually not profitable to serve at all. This posed a new question: should they stop providing their services to the bottom 50%? In a strictly capitalistic sense, that would be a wise business move, yet such a decision would undoubtedly bring about a PR nightmare for any company that would have dared to do them. They adopted a slightly different approach: to reduce the costs of serving the bottom 50%.
An interesting way of creating a strong customer loyalty is by a method called customer lock-in, which means the customer has no choice but to choose that particular company’s product. Such strategy is common in the computer and technology industry. A major example of this is the Apple corporation. Apple devices are famous for having an entire ecosystem created and maintained by that company and that company alone, and the devices work extremely efficiently together. However, as soon as one tries to introduce other competitors’ products into the environment, it quickly becomes a great hassle. Thus, the customer is left with no choice but to go with Apple, because it would cost the user too much trouble and money to do otherwise.
Brand and Sentiment Analysis
With the increasing use of social networking services, there are increasingly more amount of data to be processed and analysed. Yet so much of these data cannot be used as-is — it must first be converted into a conveniently storable type. An important aspect of Big Data then is to come up with efficient ways to gather these endless ocean of data, process it into a readable form so that the customer’s behaviour may be better understood. While there are some rather advanced methods of doing this as of now, the technology is not perfect.