Different Strokes: Why Business Intelligence is Not CRM
This chapter is from the book
This chapter is from the book
This chapter is from the book
Analytical CRM when done right involves large amounts of cross-functional data. This data is often stored in a data warehouse, a repository of corporate data from various sources intended to facilitate business analysis.
Data warehouses are continuing to deliver critical knowledge in a range of industries, and generating returns on investment in the hundreds of millions of dollars. (My first book was about how data warehouses are providing businesses with information about their customers and products that were previously impossible to locate, let alone provide to business users, and the tremendous payback that has resulted.) The practice of using data warehouses to analyze business performance is known as business intelligence.
But data warehousing is not CRM, and neither is business intelligence.
While this may seem obvious, or even heretical to some, read a magazine article or attend a conference presentation on CRM and you'll likely hear one of the following claims:
We're using data mining to execute our corporate-wide CRM initiative. It allows us to predict what customers might buy next!
Our new CRM system allows us to analyze customer behaviors and to give our salespeople global customer information, rather than select bits and pieces like they had before.
Once we started doing CRM, we could access all of our customers from one system.
Customer relationship management allows the company to analyze claims data to better understand which types of claims are most prevalent for a given customer segment.
Halleluiah! We finally know which customers are buying which products!
Valuable as they are, none of these capabilities requires a CRM product. In fact, companies from brokerage houses to pharmaceutical firms were performing these duties long before the CRM acronym came along. The combination of data warehouses and analytical toolsets has given companies the ability to drill down into integrated data to reveal interesting even competitively differentiating findings. Rather than extrapolating what types of promotions to launch and guessing who will respond, companies are relying on business intelligence analysis to provide them with hard facts that help them make better, more informed decisions and reap unforeseen rewards.
But even the experts are confused about the differences between business intelligence and CRM, and the media often excacerbates the misunderstanding. Publications and conference presentations routinely confuse the two terms. Data warehouse vendors whose markets are waning—most large companies already have at least one data warehouse—are hanging the CRM shingle without refashioning the message. Likewise, CRM vendors who realized too late that data analysis capabilities were vital are now pitching CRM data marts along with their core products.
One popular CRM book concentrates the majority of its text and all of its case studies on decision support analysis. In August 2000, a high-profile management journal dedicated an entire issue to CRM, featuring a dozen "best practices," the vast majority of which involved analyzing customer data rather than focusing on deployed CRM applications. And there was the well-attended CRM conference presentation offering the "9 types of CRM," four of which—database, decision support, analysis and data mining, and "rules repository" 1—smacked more of business intelligence than the overarching business strategy of CRM.
While often misrepresented, the differences between business intelligence and CRM are distinct. Yes, they both involve critical business decisions, and both rely on information technology in order to deliver value. The examples in Table 1 illustrate the distinction:
Table 1 Business Intelligence versus CRM
|
Business Intelligence |
CRM |
CRM Rationale |
|
Display the name and address of business customer TechCo. |
Display TechCo's most recent inbound contact on my PDA, along with their current corporate address. |
Salespeople become aware of existing issues before meeting with the customer. |
|
Display customers who visit one of the video stores in our chain on a weekly basis. |
Once a month for the next six months, direct mail customers most likely to rent next month's new features who are not weekly visitors to the store. |
Convert casual visitors to frequent visitors. |
|
Display a list of customers who have lodged a complaint within the last 30 days. |
Contact all high-value customers who have lodged a complaint. Generate retention recommendations for each customer (using CRM product feature). |
Focus on retaining high value customers. |
|
Analyze the top 5 most popular office supplies and compare approved vendors' prices to prices of other potential suppliers. |
Identify the top 5 purchased office supplies and trial-run a Web RFQ system for limited quantities to test price improvements. |
Increase the likelihood of price improvements on commodity purchases. |
|
List the e-mail addresses for registered customers who abandoned their shopping carts during their last Web visit. |
Send profitable registered customers a $5 on-line discount if they fill in a form explaining why they abandoned their shopping carts. Send 10 percent off to the unknown visitor if they complete the form. |
Reward repeat customers who are profitable while gathering valuable prospect behavior data. |
Your first impression might be that CRM is more complex than business intelligence. In fact at most companies the number of true CRM users is a mere subset of the business population using business intelligence. However, business intelligence, when not exploited to its full potential, can result in analysis for analysis' sake.
The major difference between BI and CRM is that CRM integrates information with business action. In each of the above instances, the CRM action will be tested and further refined. CRM combines data analysis with the deployment of specific business actions. The ability to access data is, by itself, immensely powerful. But many business intelligence environments simply use data to confirm already-held hypotheses. It's the ability to act on that data and to change fundamental business processes to become more customer-centric that's the mandate of CRM.