Thinking Beyond the Shopping Cart

  |  March 13, 2009 

The economic recession is the perfect time for retailers engaged in paid search marketing to think beyond the "thank you" page when establishing metrics to optimize campaigns. If you're a retailer and only consider revenue generated at the instant of the sale, you may be missing huge optimization opportunities.

Many marketers think online retailers have it easy because they collect revenue data online. Online shopping carts are the primary way that customers order, so these shopping cart pages -- and the resulting revenue -- are often the only means by which campaigns are optimized. The most common way that a shopping cart-based campaign is optimized is based on a return on ad spending (ROAS) ratio. This optimization metric and ratio works well if retailers:

  • Have a consistent profit margin across products.

  • Prefer to focus purely on the immediate measurable results of the campaign, thus ignoring:

    • Lost cookies: Tracking is generally accomplished via a piece of code called a cookie. A significant percentage of cookies are lost due to cookie blocking programs and cookie deletion. Conversions may therefore be occurring that aren't tracked. Estimates are that from between 10 to 30 percent of cookies are lost over a period of a single month.

    • Lagged conversions: Cookies have expiration periods and conversions sometimes occur after a cookie's expiration. Does this matter to you?

    • Cross-computer use: Some buyers research on one computer and then consummate the purchase on a different computer, for example work versus home computer.

    • Influencers and designated searchers: Some households or workplaces have a designated searcher. Sometimes this designated searcher uses one computer to locate a particular product. After searching and finding the requested product, the link to that product can be e-mailed or sent by instant message to the requestor, who subsequently makes the purchase. Cookie tracking isn't possible in this scenario. So, what fudge factor should you use to reflect influencers?

    • Brand lift or influence: Not every customer is ready to buy today, or even this week. Some marketers prefer to include lift in branding metrics as a success factor. Considered measuring or factoring in brand lift.

Other forms of optimization take the above issues into account either through a fudge factor or through testing or research. When information is available within your e-commerce platform at the time of the purchase, you have several choices for where to collect data for analysis and optimization. These choices include:

  • Collecting data in your e-commerce platform and attempt to reconcile or integrate data from the search engines (click price data, for example).

  • Using the tracking systems provided by the search engines to transmit the sales and related conversion data to the search engines so that you can see the ROI (define) or ROAS within their standard reporting formats.

  • Collecting data in your Web analytics platform via a tracking code similar to the one used by the search engines. Some Web analytics packages are owned by the search engines; others are independent. In both cases, there are instances where the analytics packages can import click cost data directly into the reporting provided by the search engines. This is important for generating the ROI or ROAS ratios.

  • Sending and collecting data in a campaign-management platform that will report the revenue and sales data in relation to the search campaign (by keyword and other metrics) and also make the appropriate bid changes to your keywords and adjust campaign settings to optimize your campaign. Campaign management platforms and systems typically let you optimize based either on a target ROAS, ROI, or CPA (define) basis, or you can provide a budget and the system will maximize revenue, profit or registrations based on that budget.

Campaign management starts once revenue, profit, or conversion data and cost data are combined to generate ROAS, ROI, or CPA information. A core element of campaign management is bid management, which comes in many flavors. The type of bid management system you'll need will depend on your campaign's size and your data needs.

Tracking conversions drives bid decisions. When conversion can't be tracked precisely, many marketers prefer to estimate conversions or use a process or mechanism to factor in gains in influence brought about by a SEM (define) campaign. Direct marketers are more likely to ignore these fuzzier metrics and focus exclusively on metrics that can be reasonably tied to an eventual sale. When an integrated solution isn't available, the happy medium is often to take as much quantifiable influence or customer value data and overlay this data on your ROAS bidding strategy.

Meet Kevin Lee at Search Engine Strategies New York March 23-27 at the Hilton New York. The only major search marketing conference and expo on the East Coast, SES New York will be packed with more than 70 sessions, including a ClickZ track, plus more than 150 exhibitors, networking events, parties, and training days.

Read "It's the End of SEO as We Know It" in the new digital edition of SES magazine.

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ABOUT THE AUTHOR

Kevin

Kevin Lee, Didit cofounder and executive chairman, has been an acknowledged search engine marketing expert since 1995. His years of SEM expertise provide the foundation for Didit's proprietary Maestro search campaign technology. The company's unparalleled results, custom strategies, and client growth have earned it recognition not only among marketers but also as part of the 2007 Inc 500 (No. 137) as well as three-time Deloitte's Fast 500 placement. Kevin's latest book, "Search Engine Advertising" has been widely praised.

Industry leadership includes being a founding board member of SEMPO and its first elected chairman. "The Wall St. Journal," "BusinessWeek," "The New York Times," Bloomberg, CNET, "USA Today," "San Jose Mercury News," and other press quote Kevin regularly. Kevin lectures at leading industry conferences, plus New York, Columbia, Fordham, and Pace universities. Kevin earned his MBA from the Yale School of Management in 1992 and lives in Manhattan with his wife, a New York psychologist and children.

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