[X+1] NexTargeting Conference: Cross-Channel Attribution and Online Ad Scalability Remain Hot Topics


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Continuing my adventures in online ad measurement, I attended [X+1]‘s NexTargeting Summit last week. This reinforced and refined my conclusions from last month’s OMMA Metrics conference, which identified the burning industry issues as:

– better understanding of the interactions between online and offline events (both advertising and results), and

– better scalability for successful online advertising programs.

The online / offline connection was covered by MarketShare CEO Jon Vein, who presented studies that showed including the “indirect impact” of online display ads can dramatically improve their reported return on investment. He also said his firm has found that marketing mix models with complete data can explain as much as 98% of the variance in revenue, while optimization based on mix models can typically improve marketing effectivness by 10% to 15%. Although I don’t recall Vein mentioning it during his actual presentation, he did tell me in a side conversation that his firm purchased JovianData last year in order to expand its ability to work with individual-level data. MarketShare and [X+1] announced an alliance last month to combine MarketShare’s cross-channel analytics with [X+1]’s digital targeting.

Scalability was covered [X+1] itself, which announced extension of its Media+1 audience targeting platform to combine information from direct media buys and ad exchanges. The relationship between that extension and scalability is a bit complicated, but it boils down to this: combined information lets marketers control the number of ads served to individual consumers across both types of media buys, which segment-level purchases do not. This means that marketers can expand their budgets by targeting ads to new individuals (=effective scaling) rather than bombarding the same people with more messages (=ineffective scaling). That this mimics the reach and frequency measures used in traditional mass marketing (i.e., television) is a happy bonus.

I’ve skipped some of the subtleties of the Media+1 product. These include tracking the degree of overlap between the audiences of different direct-buy Web purchases; identifying optimal message frequency by customer segment; using direct-buy Web sites to establish a base of impressions and then supplementing these on a customer-by-customer basis through real time bidding on ad exchanges; and using scorecards to track performance after initial customer acquisition. The bottom line on Media+1’s beta client was reallocating 40% of the online ad budget to achieve a 20% improvement in results.

[X+1] also used the conference to announce an even broader product, called Origins, scheduled for release this summer. This will build a customer-level data hub that combines data and sends targeted messages across display ads, Web site, email, and mobile. I asked [X+1] CEO John Nardone whether it’s actually possible to identify the same customer across all those channels, and he said it’s not an issue in many cases, since you can often give the customer a reason to log in or otherwise identify herself.

Of course, the big exception is acquisition, which seems like a pretty big exception indeed. (“Other than that, how did you like the play, Mrs. Lincoln?”) But tracking mechanisms do get better all the time and there’s plenty of value in better treatment within existing customer relationships. So it’s definitely a good start.

Republished with author's permission from original post.


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