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Volume Analytics:
Analyze Your Interest Pipeline

online columnist Guy Creese     Column published in DMReview.com
May 19, 2005
 
  By Guy Creese

We all recognize that analyzing the sales pipeline is a good thing to do. By tracking the progression of potential business as it moves through the stages of lead, qualified lead, intent to buy, booking and sale, businesses get pretty good at predicting what next quarter's sales will be. Through trial and error, companies learn the average attrition rate at each step and get to the point where they can say with authority, "100 qualified leads will yield three sales." Not bad - a nice, useful, rule of thumb. Get enough leads, and sales will go up. Or find a group of product enthusiasts who will buy no matter what, and sales will go up.

But what if you could extend the pipeline to view an even earlier stage? What if you could measure that first glimmer of a customer's interest, even before you got their name and number? The good news is you can - it's called the Interest Pipeline.

You Already Have an Interest Pipeline - It's Just Called Something Else

In the past, this was difficult. Companies couldn't look over their customers' shoulders as they riffled through catalogs or read product reviews. Today, however, customers do a lot of research online - and that can be tracked. This tracking capability has been around for over a decade. Initially, it was rudimentary, but these days it can be quite sophisticated. However, because the market typically describes the tools in technological terms - e.g., clickstream analysis, search analytics, marketing automation - business leaders don't always recognize their potential. However, when I talk to managers about how an interest pipeline feeds their sales pipeline, they typically say, "Hey, we should get one of those," and I reply, "You already have one. You just aren't watching it." Following are examples of how companies are watching and leveraging their interest pipelines.

Example 1: Automobile Manufacturers

For years, auto manufacturers have churned out cars and trucks and let dealers sell them. While they've avoided producing pink cars with purple steering wheels (at least since the 50s), the product mix has been somewhat haphazard, since the dealer always stood between them and the consumer, filtering customer demand. If a car didn't sell, the dealer just dropped the price until it did.

With the advent of the Web, auto manufacturers can directly observe what their customers want. Virtually every car manufacturer now has an area on their Web site that lets prospects build their dream car - visitors can specify the model, the engine, the exterior and interior colors, other options, you name it. By creating these virtual cars, customers are expressing their interest - which helps auto manufacturers in two ways. First, they're getting direct customer feedback on what to build - what their production plan should look like, in terms of car features. They're also getting a preview of how customers will act when they march into a showroom. For example, customers are buying fewer SUVs now due to higher gasoline prices. However, the auto manufacturers probably saw customers modeling fewer SUVs before they saw dealer sales drop.

Example 2: A PC Manufacturer

Several years ago, a PC manufacturer noticed that a lot of customers were searching for CPU memory on the support section of its Web site, trying to figure out which chips were compatible with their PC. The company viewed this behavior as intriguing - but not much else - until someone realized that people were searching for facts about memory because they were trying to buy it. At the time, the manufacturer made purchasing additional memory from within the search tool incredibly difficult. The Web visitor had to get out of the support area of the Web site, dive into the e-commerce section, find accessories and eventually consummate the deal: a total of probably 10 clicks. When someone finally realized that this interest pipeline should feed into the sales pipeline, the company put a "buy" button next to the CPU memory search results and sales skyrocketed.

Example 3: A Chip Manufacturer

The first two examples are from the B-to-C world; but interest pipelines apply in the B-to-B world as well. A well-known chip manufacturer has created a section of its Web site for design engineers, making it easy for them to design boards online. Board design is a discipline of trade-offs - juggling heat, space, power, expense and other characteristics until all of the components come together to create a coherent whole within the limits of the design constraints. Because it hosts this capability, the company can watch customers as they work through this multiweek design process. When board design is near completion, the chip manufacturer's sales rep gets on the phone and asks the customer's design engineer if he or she would like some chips to create a prototype board. Often the answer is yes; once the board is built and tested, the engineer often specifies the chip manufacturer's components and another sale is made.

Pre-Fill the Sales Pipeline

In the third example, most companies would track the sales pipeline from the point of explicit contact - from when the sales rep called the design engineer. What leading-edge companies are doing is tracking from on earlier point - from when the customer first expressed an interest, whether that is modeling a car, searching for compatible memory or beginning to design a board. They are also assigning metrics to those stages, enabling refinement of the interest pipeline in the same way that many companies today optimize the sales pipeline.

So look around your company and figure out what interest pipelines you have. Then, start tracking them with the same diligence that you use to tract the sales pipeline. By leveraging your interest pipeline, your sales pipeline can only get larger.

...............................................................................

For more information on related topics visit the following related portals...
Web Analytics.

Guy Creese is an analyst with the Burton Group, covering content management and search. Creese has worked in the high tech industry for 25 years, at both Fortune 500 companies and small startups, in positions ranging from programmer to product manager to customer support engineer.  He can be reached at gcreese@burtongroup.com.

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