Cross-channel audience analysis and re-marketing

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Most e-mail and database marketers do some level of audience analysis on their e-mail lists to find patterns and propensity to convert.  Some of them join these databases with the richer demographic datasets provided by companies like BlueKai or eXelate to further improve their models. But the majority still overlook some very important items to consider, including:

1.      If the audience analysis model incorporates how the e-mail channel is helping other channels to improve their business KPIs, and conversely, if the other channels help the e-mail channel to improve its business metrics. Channels like online display, search and  affiliates normally gets a lot of lift from e-mail channel and TV, print, radio advertising provide lift to the e-mail channel. 

2.      The whole is greater than the sum of its parts: A carefully orchestrated TV, e-mail and search advertising can generate about than 43% more overall conversions than these channels executed in silos.

3.      The e-mail channel can be used to re-market to the users based on the behavioral insights derived from other channels. For example, somebody who has searched the keyword “Aruba vacations” is more responsive to an e-mail offer of “20%-off” for their next Aruba trip rather than getting a generic e-mail, but you first need to know that this person searched for that keyword.

4.      Marketers too often confuse media metrics like contacts mailed or open rate, with actual business metrics like conversions and ROI. To maximize business metrics, you need to integrate the customer data with your media data.

To address the points above, e-mail marketers need to think more seriously about deploying an attribution model. A good attribution model tells how the channels help each other and allow marketers to device holistic campaigns that work across the channels. An attribution system compiles all touchpoints of a single user from all channels with timestamps, so marketers can better attribute sales back to your e-mail campaign.

For example, John Smith has seen an online display ad offering a “5% off” deal on vacation travel at 10:23 pm on March 2nd, and then an e-mail with “$200-off” offer on March 27th. When he then searches for “Hawaii vacation deals” on March 28th and makes a purchase, we must give credit to the e-mail and display channels also because we know these touchpoints are of the same person.

E-mail works as the superglue between the other channels and delivers the richer demographic datasets. It adds quality to the input data sets for attribution models, which tends to predict better for higher ROI goals.

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