Turning Data Into Sales: Measure, Analyze, ActAs the Web becomes a global emporium, it's obvious we need to more closely watch, understand and manipulate the commerce process. At this point in our evolution, what we measure (clicks, page views, impressions) has gone a long way to justify advertising on the Net, but doesn't help much when it comes to figuring out how to optimize response and conversion.
It's time to end the debates about click-through rates and focus on how we sell more, faster. One way to do this is to begin with base-line direct marketing principles:
• Behavior is the best predictor.
• Repeat behavior is a better predictor.
• Prospects who look like current customers are likely to be better prospects.
• Its easier and cheaper to sell more to current customers than to convert prospects into new customers.
• None of this is as easy to do as it is to say.
Avenue A, thinks it has discovered a better mousetrap when it comes to analyzing data on Web site visitors in ways that can drive more sales. Combining data mining with media planning and buying, the company claims its closed-loop system yields competitive advantages of speed, synchronization and insight.
With a mantra of "measure, analyze, act," it collects and studies data for 56 clients. This leads the company to generalize that newbies click more often, and that savvy surfers experience greater delays between message exposure and click-through. Surfers have finer filters and are more selective in reading and acting upon online messages. The quest is ultimately to make statistically significant decisions that drive sales.
As a direct marketer, Avenue A's immediate goal is to drive the cost of acquiring each customer as low as possible while maximizing sales and ROI. Like all good direct marketers, it tests its way into greatness by making an initial first guess and then continually refining the campaign based on performance.
And Avenue A is not afraid of a big challenge. The company placed 20 banners on 100 sites for one client. It tested 50 creative executions in $20,000, $50,000 and $100,000 combinations, and netted out top performers that were 75 times more likely to convert to sales than the also-rans.
The key metrics are: How soon can we read what's happening? How detailed is the data? How fast can we react?
Like a DRTV manager, Avenue A revises buys daily and weekly. The Internet gives the company a faster optimization in real time than we've ever seen in direct marketing. Along the way, Avenue A can track customer behavior to better leverage creative and messaging techniques.
For eddiebauer.com, Avenue A discovered that the following creative tactics yielded the highest correlation with sales: logo size, product specific banners, holiday-specific banners and a special offer. Color, banner size, banner placement on the page and price evidently didn't matter much.
It sees data as the engine for driving online campaign effectiveness. Staking a claim as the leader in online media accountability, it expects to hold site publishers' and ad agencies' feet to the fire to demand they create measurable sales for his clients.
Third-party ad serving made efficient data collection and mining possible, but data collection and processes are still in their infancy. The next steps are to improve the data sets and extend the mining, and to branch out into other new media applications, such as ATMs, Palm Pilots or Web TV.
If e-commerce is going to be a real factor in the U.S. economy - not just the 1 percent of sales it is now - counting, measuring and selling are necessary. Avenue A plans to lead that charge.