CRM Analytics: Reaching the Heart of the CRM Process

BOLSTERING THE BOTTOM LINE WITH ANALYTICS

As reported by James R. Borck, Insightful data mining brings customer expectations to enterprise decision making. The CRM (customer relationship management) analytics model is nothing new; it's an old-school concept that has evolved to meet modern-day requirements for recognizing customer desires. Analytical CRM is the mining of data and the application of mathematical, and sometimes common-sense, models to better understand the consumer. By extrapolating useful insights into market and customer behaviors, companies can adjust business rules and react to customers in a relevant, personalized manner.

Although the concept hasn't changed much from the halcyon days of small-town local grocers, the process certainly has become far more scientific. Because we conduct business with fewer face-to-face exchanges, getting to know and understand the customer has become even more complicated. The rise of e - business has driven the demand for more comprehensive toolsets for data mining and knowledge interpretation.

The InfoWorld CRM Survey provides strong indicators that CRM is of critical importance to the vast majority of the 500 respondents. But the results also reflect the nagging concerns most have in taking the CRM plunge. Part of the problem stems from a lack of consensus as to what precisely CRM is. For some CTOs, CRM is the ability to track customers and launch personalized e-mail campaigns. For others, it takes on a broader definition that encompasses automated sales force and marketing tools. CTOs tend to share two notions about CRM: Implementation is costly and complex, and the resulting solution often has poorly demonstrable ROI.

Despite the dearth of quantifiable benefits, most IT leaders recognize CRM as a critical component to long-term success. When planning a CRM initiative, CRM analytics are the one component that you cannot afford to overlook.

More than a technology, CRM is a process. More than mere reporting, CRM analytics provide 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.

Whether you are conducting business-to-business or business-to-consumer commerce, this has become an era in which your customers' expectations can be difficult to discern. CRM's capacity for predictive modeling can offer the necessary knowledge to clinch product and service availability and to shore up bottom-line profitability.

Analytics can be derived through several different channels, including the Web, retail point of purchase, and direct marketing. The difficulty is no longer in gathering data from customers but in making sense of the multitude of customer contact points coming into the enterprise.

With such a complicated number of information sources and with vast quantities of data updating business databases daily, how can you tap these disparate mountains of data and pan for nuggets of opportunity?

CRM is often thought to be data warehousing, but the reality is that CRM is more a function of statistical modeling than anything else. Analytical data mining solutions, part and parcel of most packaged CRM solutions, must be capable of providing insight into that wealth of data, using process and trend analysis to isolate causes and correlations within the customer interaction model.

Today's business processes are extremely complex, and strong analytics are necessary to give a functional view of interdata relationships. Through these dependencies, 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.

At its best, CRM analytics offer 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.

CRM is a highly iterative process. When data from any source is harvested and fed back into the system, it improves the personalization capability of the very next customer transaction or email campaign. More traditional marketing processes such as direct marketing often see months of lag time between a campaign's execution and the review of its metrics. With each loop of the cycle, Internet-based CRM analytics are, in real time updating, tweaking, and improving delivery of personalized, relevant sales opportunities. They also help build a more fine-tuned relationship between a business and its customers.

In addition to the personalization that benefits a customer's purchasing decision, CRM analytics will soon provide useful data that can benefit enterprisewide processes. CRM analytics will also be integrated more frequently into the general operational workflow of noncustomer systems, including financial systems and manufacturing, to provide a more singular view of customer-centric data than do the traditionally segmented departmental views offered by legacy CRM.

When all of this data can be interpreted to a variety of enterprise systems, transactional decision making and enterprise planning -- from cross-selling opportunities to supply-chain and just-in-time inventory control -- will be enriched.

As CRM evolves, one of the primary stumbling blocks to realizing its full potential will be the often piecemeal integration capabilities of vendors' current packages. Many early implementations tended to cobble together multiple vendors' products bridged with custom development and EAI (enterprise application integration) into existing systems.

Because implementing CRM can range from $100,000 for smaller companies to millions of dollars for full-blown implementations, many companies chose to build their solutions a little at a time. This approach also made surmounting the corporate cultural barriers that frequently afflict new application integration a little easier.

But take heart. In the next year, vendors will more frequently enrich their offerings with better interoperability, integrating as many customer data streams into the process as possible. A communication process, not unlike that which transpires between supply-chain applications, will go a long way toward developing a fully closed-loop, CRM ecosystem.

Although several vendors are providing ad hoc, niche CRM capabilities, only a handful have emerged with the driving analytics necessary to benefit enterprisewide decision making in a meaningful way.

Some CRM solutions, including SAS e-Discovery and the CRM component of Oracle's E-business Suite, offer integration across sales, call center, e - commerce, and marketing channels. But strong analytical products such as Broadbase's suite of E-offerings and the E.piphany E.5 platform have emerged with excellent Internet-based solutions capable of linking Web-based data resources with internal systems, such as call centers, existing CRM, and ERP (enterprise resource planning) applications. These solutions can jump-start your CRM competence.

Data mining and analytics are not without risks. The predictability of human nature is never a sure thing, so modeling real-world transactions carries a certain degree of error that can greatly affect the quality of the data influencing your decisions. CRM analytics, being more about the process than the technology, demand a degree of human interpretation for the data to yield the most beneficial results. The CRM tools merely fortify your abilities.

Although automation can go a long way toward streamlining internal processes, technology also quickly depersonalizes the customer's experience. CRM analytics offer insight and personalization that can go a long way toward improving that experience and building customer loyalty.

To thrive in this economic climate, you must have an in-depth understanding of both your customers and your business to effectively market, sell, and service your offerings. As the Internet has helped smaller companies gain a competitive advantage by narrowing the gap from enterprise competitors, CRM will help larger companies reduce the risk of losing revenue dollars to today's new, stronger "local grocers."