Customer Management

By Baselinemag  |  Posted 2002-02-04 Email Print this article Print
 
 
 
 
 
 
 

The claim that information technology's benefits are real but not measurable is faint and, in this economic climate, dangerous praise. Luckily, it's also no longer the case: Corporations, analysts and academics are relying on tangible, new IT metrics to



Customer Management


Metric: Touchpoint Tracking
Definition: This marketing metric relies on IT to track each point of contact between customers and your company.
Example: Typically, companies establish a promotion that confers a tangible benefit or discount to a customer. The promotion code is delivered via one medium-direct mail, say-and is redeemable through any distribution channel.
Significance: Lets you track and understand consumer research and buying patterns so that you can gear each channel to the specific needs of customers and drive the customer toward purchases. Measuring "touchpoints" lets you see which channels your customer uses (and how many times) before an actual purchase is made, notes NetGenesis chief eBusiness intelligence officer Matt Cutler.

Metric: Freshness Factor
Definition: The frequency with which you should update features or content online to meet customer expectations.
Example: Your competitive intelligence site posts news about 35 market sectors every day. But 85 percent of your customers visit your site once per week. "What is the value to you, of changing your content all the time, if nobody really notices?" queries NetGenesis' Cutler.
Significance: The freshness factor (once per week) shows that the daily postings are inefficient. Either your company should reduce staff and aim for weekly postings, or rethink the marketing plan to increase the freshness factor.

Metric: Time to Resolution
Definition: The speed at which a particular help-desk issue is solved. This metric can be measured against internal or external service level agreements.
Example: A trading partner, promised 99.7% uptime annually, reports that the extranet link is down. The time to fix the outage from the moment of notification is the time to resolution.
Significance: Particularly important in cases where reliability is the primary indicator of customer satisfaction. Time to resolution, along with the frequency of breakdowns, can provide early warnings of an overburdened staff, a troubled system or a possible breach of a service level agreement. Also of particular importance as an "ecosystem metric," whereby a company such as Cisco Systems can assure that a customer will get the same high level of service "end to end"—even if a partner company has to provide support and service. For instance, Cisco might require four levels of case resolution in the event of a outage at one of its network gear customers, says Kevin MacRitchie, vice president of worldwide channels technical operations. And if by that time the ecosystem hasn't fixed the problem, notice reaches the desk of chief executive John Chambers.

Metric: Customer Data Management Payoff
Definition: The payoff of data cleansing. Divide the amount saved in improved data quality by the amount spent to clean that data.
Example: Duplicate customer records in a database can hurt earnings through unnecessary mailings. In this case:
# duplicates in database x mailings/year x cost/mailing
cost of data deduplication

You may also use the number of incorrect customer fields to find the percentage of data that is bad, then calculate the costs of customer interactions that depend on the accuracy of those fields to predict further the cost savings of data cleansing projects.
Significance: Companies often fail to understand the real effects of dirty data, according to customer relationship management software vendor Harte-Hanks. Showing a direct correlation with a tangible expense like shipping helps the business case of data-cleansing projects. A higher ratio is better.

Metric: Early Buying Signal
Definition: The click-through and usage behavior of a visitor to your Web site that corresponds to an increased propensity to make a near-term purchase.
Example: Analyze behavior of customers that have made purchases to infer patterns, then flag visitors that exhibit such patterns. Manny Sodbinow, senior analyst of the Patricia Seybold Group, gives this example: On its Web site, a chip manufacturer provides simulations modeling new types of chips. Engineers that have purchased components have (a) spent increasingly longer amounts of time viewing the simulations and (b) explored them in greater depth. Increases for other visitors in either (a) or (b) indicate a potential sales lead.
Significance: Using a buyer's behavior before purchasing closes down the sales cycle; customer is served; and sale is made with minimum friction.

SOURCES: Gartner Inc., The Alexander Group, Cisco Systems, Patricia Seybold Group, NetGenesis, Harte-Hanks Inc., MIT Sloan School of Management



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