A CRM solution that bridges service, sales, and marketing initiatives enables businesses to resolve problems quicker, increase sales, achieve customer acquisition more effectively, and greatly enhance customer loyalty.
It is an axiom of the marketplace that satisfied customers tell their friends about a supplier who maintains good customer relations. One of the most powerful ways to acquire customers is word-of-mouth referral from a friend, colleague, or family member. Businesses can harness these referrals when one of their customers adds personal comments to an alert and forwards it to others who may be interested in the information and/or opportunities the alert presents.
The CRM analytics model has evolved to meet modern-day requirements. Although the concept hasn't changed much from its early days, the process certainly has become far more scientific. Analytical CRM is the mining of data and the application of mathematical, and sometimes common-sense, models in order to understand the consumer better. By extrapolating useful insights into market and customer behaviors, companies can adjust business rules and react to customers in a relevant, personalized manner.
Because business is conducted with fewer face-to-face exchanges, getting to know and understand the customer has become more complicated. The rise of e-business has driven the demand for more comprehensive tool sets for data mining and knowledge interpretation. For an effective CRM initiative to accomplish its goals, CRM analytics need to be incorporated into the process. CRM analytics provide the comprehensive insight necessary for pinpointing revenue opportunities, enhancing sales channels, and mitigating cost risks. By providing meaningful insight into data as well as transactional predictions, CRM analytics enable businesses to ensure that rules and workflow are in step with customer demands. Analytics can be derived through several different channels, including
Retail point of purchase
Direct marketing activities
The challenge is to make sense out of the data gathered from customers from the multitude of customer touchpoints into the organization.
Analytical data mining solutions are a significant component of most CRM system packages, and call center personnel should have some understanding of the relationship of data mining to their own call/contact center roles. Data mining provides insight into corporate data stored in the data warehouse by using a variety of analytical techniques to isolate causes and correlations within the customer interaction model. Data mining analytics can perform predictive modeling of customer behavior, customer segmentation grouping, profitability analysis, what-if scenarios, and campaign management, as well as personalization and event monitoring. These functions take advantage of a customer's interactions with a business in real time. (see Figure 6.13) Strong analytics are necessary to give a functional view of data relationships in today's extremely complex business processes. By means of analytics, CRM can model future transactions, predict the interests and behavior of individual customers, and translate data into more traditional channels within the enterprise, such as the supply chain.
Figure 6.13: Elements and processes of data mining.
CRM is a highly iterative process. When data from any source are harvested and fed back into the system, the personalization capability of every customer transaction or e-mail campaign is improved. More traditional marketing techniques such as direct marketing often have months of lag time between a campaign's execution and its results. With each loop of the cycle, Internet-based CRM analytics are updating, tweaking, and improving delivery of personalized, relevant sales opportunities, all in real time. They also help build a more finely tuned relationship between a business and its customers.
In addition to the personalization that benefits a customer's purchasing decisions, CRM analytics can provide useful data to benefit enterprisewide processes and can also be integrated into the general operational workflow of noncustomer systems, including financial systems and manufacturing, to provide a more focused, single and collective view of customer-centric data than do the traditional, departmentally segmented views offered by a legacy CRM.
When all of this data is applied to a variety of systems, transactional decision making and enterprise planning—from cross-selling opportunities to supply-chain and just-in-time inventory control—become more effective. But it is good to keep in mind that CRM analytics is more of a process than a technology and so it demands a degree of human interpretation for the data to yield the most beneficial results.
Automation streamlines internal processes, but technology can also quickly depersonalize the customer's experience. CRM analytics offer insight and personalization that can go a long way toward improving that experience and building customer loyalty.
When they first start, all businesses have to focus on the needs of their customers. As businesses get larger and more complex, however, they become more inward-looking as they try to cope with their internal issues. Often, the customer gets treated as an afterthought. One goal of CRM is to make the individual customer become important once again at an acceptable cost to the company. Until relatively recently, it was impossible for large companies to form relationships with customers. With a customer base of millions, how can a company know their preferences or dislikes? This is where technology can help businesses. Realistically, businesses do not implement CRM because they have had a change of heart and decided to be nice to the long-suffering customer. Loyalty equals profit, and both customers and businesses can gain from it. The "management" part of CRM demonstrates that it is the business which ultimately controls the relationship with the customer. It provides the right information at the right time, it offers the right price to keep the customer happy enough to stay, it anticipates what else the customer would like to buy, and understands why. Thus, the business objective of CRM is to maximize profit from customers as a result of knowing them, treating them well, and fulfilling their needs.
Salesforce automation, customer contact solutions, multimedia routing, and data management tools—all have been claimed as the key to a CRM solution. All are useful and reliable aids to a business, but none of them on their own is a CRM solutions. They do, however, contribute to meeting CRM objectives.
Answers to the following questions can provide an organization with insight into its current customer-related practices:
Is there a single view of the customer across the enterprise?
Do employees fulfill customer needs regardless of where in the company they are working?
Do customers receive a high level of service no matter which channel they decide to use?
Does the organization proactively and intelligently inform customers about products and services they will be interested in and yet keep marketing costs under control?
Does the organization know who the most profitable customers are?
Are the strategy and tactics in place to keep them?