CRM and Retail and Analytics

We are discussing CRM and Retail and Analytics here from different perspectives. Let’s try to find out the correlation between CRM and Retail and Analytics. Rapid advancements in technology over the past decade have made it possible for retail managers to collect, condense and categorize information in a highly efficient manner. However, the ability of the decision maker to correctly interpret this information has improved very little. The accurate interpretation of information goes beyond the ability to correctly read rows and columns of numbers, percentages and absolute values. It begins with an understanding of where the information comes from, how it is obtained, and whether or not it is relevant to a particular business decision.

One problem retailers' face today is the impersonal, transactional nature of the shopping experience. In effect, customers pass through stores anonymously, forming little or no relationship with the retailer. Decision Support Systems (DSSs) offer a way to improve a store's effectiveness and efficiency and to build and direct their marketing strategy based on customer needs and preferences. Analytics form the core of DSSs often called CRM and Retail and Analytics, which help retailers, realize advantages in inventory management, buying, sales and marketing, and store productivity.

The retail landscape consists of a variety of players competing for a customer's business by constantly altering their merchandising mix while simultaneously differentiating themselves from competitors. The speed, at which decisions must be made today, along with the difficult market conditions of the current economy, means that the cost of failure is enormous. Success in this competitive world is dependent on attracting and retaining the most profitable customers. And that’s possible by using the perfect mix of CRM and Retail and Analytics.

Good CRM and Retail and Analytics systems allow users to explore the data and pursue a line of questioning without the penalty associated with traditional systems. Marketing must be allowed to be self-sufficient with respect to having a dialogue with the data in order to understand what the customers are saying.

For example, a leading retailer of hardware in the United Kingdom has been able to do that with CRM and Retail and Analytics. Instead of running complex queries that take hours, they can do them in seconds, changing the way they approach different marketing scenarios. The result is a complete change in how marketing looks at and uses customer data.

For instance, making catalog mailings more efficient by eliminating unresponsive customers was an early priority for this company because of the direct impact that the cost savings would have on the marketing budget. So the question became: which customers are unresponsive? Since the company sends its catalogs to small businesses across the United Kingdom, the answer required testing of ideas and a lot of different factors.  

When responses to unknown questions are immediate, the depth of understanding is much deeper because more ideas can be tested, refined or even discarded. As a result, not only one profile emerged but several others that allowed marketing to tailor its mailing program even further using CRM and Retail and Analytics.

All in all, CRM and Retail and Analytics will serve to be the backbone of intelligent retailing decisions, in this era of increasing competition and choice for the customer. While CRM and Retail and Analytics ensure effective use of data which is collected, it also renders itself to the tasks of data collection and maintenance. The competitive advantage for retailers will be the ability to devise innovative means to capture data from customer touch-points cost effectively, and channeling such data into actionable insights through CRM and Retail and Analytics.