Optimizing a Game of Tag

By  Oliver Elliott — November 19, 2010

It is common knowledge that ecommerce is one of the hottest channels in retail today. What's uncommon, however, is the retailer that has optimized its online strategy to ensure that its marketing channels are performing as efficiently as possible.
 
Having battled unsuccessfully to reward credit and sales commissions more fairly across all of its online channels, online apparel retailer Boden turned to universal tag management system TagMan. Using TagMan's single-tag technology, the retailer was able to plug the tags from its many online marketing providers into a single, universal container tag and system to gain one source of reporting for all of its digital activity.
 
The conversion report provided by TagMan offers insight into the entire path-to-conversion leading to a sale, providing a much greater understanding of how all online channels interact throughout a user's journey to making a purchase; the report also helps commissions to be spread according to a set attribution model. With a comprehensive view of a buying customer's path to conversion, the first phase of Boden's plan was to deduplicate between affiliate sales on a last-click model and to remove email as a potential last-click channel. The next phase is to design a weighted attribution model that recognizes influencing touch points, as well as last click.
 
Background
Boden operates in the United States, United Kingdom and Western Europe and sells apparel for women, men, children and infants through its catalogue, websites and two store outlets. Today, 75 percent of its sales in the United States are through the web.
 
With the business' success so tied to its websites and, therefore, the effective targeting of its online marketing activity, Oliver Elliott, online acquisition manager for Boden, spent several months seeking a technology solution to a critical marketing problem: how to understand the true role that different online channels play in influencing conversion and then to award the credit and commissions to those channels accordingly.
 
Elliott was aware that paying marketing partners only for delivering the "last click" in a path to a sale failed to help him recognize and reward any activity that helped contribute to that last click and also didn't help him understand how online channels worked together to deliver customers.
 
Having worked fruitlessly for more than a year with his web analytics provider to develop a complete view of user journeys and to award credit and commissions more appropriately, Elliott turned to TagMan.
 
Strategy
TagMan worked with Elliott's internal marketing and web development teams to implement its universal container tag. The tag would be used to replace all the tags on its web pages from marketing technologies such as web analytics, affiliates, display ad servers, and Google AdWords; it would also re-house those various tags in the TagMan system and interface.
 
With all the tags and -- most crucially -- all the data they delivered housed in one place, Boden would be able to see the precise, step-by-step journey (including direct-to-site and SEO) that its converting customers took on the way to completing a sale. Boden would achieve immediate savings in being able to identify which affiliate really delivered the last click in any path and so deduplicate where more than one affiliate claimed the same sale.
 
TagMan research has shown that the average online business has a 13 percent duplication rate and among its own clients (largely ecommerce businesses), duplication rates of up to 80 percent have been observed, with an average rate of 25 percent to 35 percent. With the full path to conversion reported, Boden would also be able to use the system to identify the different roles that online channels play in acquiring customers. With this insight it would be able to develop marketing attribution models to spread credit and commission from sales across all online channels.
 
Implementation
The TagMan implementation for Boden had a remit for four international markets. It was initially rolled out to the U.S. and U.K. markets, with Germany and Austria following. The initial conversation detailed the structure and scope of the implementation requirement with TagMan then creating and delivering the containers for the Boden developers to install. As the Boden developers plugged TagMan into the Boden global sites, TagMan was busy adding the tags into the containers on their behalf.
 
The tags covered analytics (Google), retargeting (Criteo), affiliates, search, display and more. Once the containers were live and the testing was complete, the tags were deployed to live by TagMan and then removed from the page by Boden in a seamless process (to prevent duplicate tagging). This allowed the deduplication to be switched on for the performance marketing channels so that Boden can benefit from the savings associated with the removal of duplicate commissions. Boden received full training on the reporting and tagging interfaces so that the retailer can have full access to its tags, campaign and attribution results. Moving forward, Boden also will be hosting the TagMan data feed so more rich marketing data can be funneled directly into the Boden internal CRM system.
 
Outcome
Boden uses the insight that TagMan provides to better understand its customers' online journeys and act on that insight to optimize all of its online campaigns. For example, it enables a single view of customers: Boden first used TagMan as a central reporting tool to see how all of its online channels are performing. The path-to-conversion data shows the marketing events that converting customers were exposed to on their way to a sale, including paid and natural search and the keywords used, display ads viewed and clicked on, email campaigns and affiliates.
 
This insight has transformed Boden's understanding of the role different online channels play in the user journey. It has, says Elliott, given "us a more informed view of the impact of online display, and a more informed view on exactly which search terms are contained within paths to conversion."
 
Actionable Insight
Acting on this data is the next step and Boden has already made great strides. The first step, says Elliott, has been to optimize paid-search campaigns. TagMan data revealed for the first time that generic terms such as "women's clothing" often appear in a customer's path to buying, even though branded terms (such as "Boden") most often deliver "the last click."
 
Knowing this, Boden now optimizes against these generic terms with full confidence that -- even though they do not deliver the last click -- they do drive sales.
 
Boden was also able to achieve immediate savings in the commissions it pays to CPA channels such as affiliates. Elliott, using the path-to-conversion reports, was able to apply a common-sense rule to the commissions he paid affiliates where his own email marketing also appeared in the conversion path.
 
Boden traditionally has used a strong email strategy to target existing customers, and Elliott figured that marketing interactions upstream of email clicks played little part in the buying decision, being of little value to customer retention and certainly of no value to customer acquisition. Interested in transitioning affiliate focus to higher-value new customer interactions, he set rules through TagMan to pay commission only where email did not appear in the conversion path, or appeared after email.
 
"We wanted to dedupe some of the overlap between affiliates. But, it wasn't really about saving money, it was about optimizing spend and performance along common-sense and well-researched paths to conversion," says Elliott.
 
"There has been very little come-back from affiliates. We spent a lot of time and effort communicating our intention and explaining our rationale behind the chosen scenario. We felt the argument was an easy one to make as it clearly aligned with our business goals and, with other advertisers having already set a deduplication precedent but pushing further, also being seen as fair," he says.
 
The decision has proven prescient.
 
Deduplication against email strategies has yielded about 10 percent overlap, showing that affiliates by and large have been delivering new customers, not converting existing ones already reached by Boden through email.
 
Next Steps
Having proven the value of TagMan, Boden is keen to explore how to be smarter in its online marketing using the insight that the universal container management system provides. The retailers plans to use the data to better understand to what degree its new display retargeting system is delivering incremental sales. Boden also intends to develop a smarter attribution model that rewards all channels fairly.
 
"Using TagMan has gained us: immediate savings in affiliate commissions and network overrides; a more informed view of the impact of online display; and a more informed view on exactly which search terms are contained within paths to conversion, enabling optimization on generic terms that frequently drive sales through to a branded term endpoint," Elliott says.
 
"There are still many things we are trying to crack but, in the end, it is about understanding the performance of our online channels in conjunction with each other. Most of all we want to understand what the golden cross-channel cooperations are," he says. 

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