Walking a Fine Line With Web Analytics Data

Sending email based on web analytics data is not a new concept in the email marketing space. As most email marketers know by now, web analytics data can be used in abandoned shopping cart campaigns (ReMarketing), browser behavior campaigns, and other targeted campaigns. But to me, the most important aspect of these campaigns is how the data is being used and what the net effect is on the subscriber base.

Here's my real-life example that illustrates the issues surrounding web analytics/email integration:

I am a frequent shopper of the online retailer Amazon.com, where I have purchased books, electronics, and baby items exclusively. Last week, however, I received an extremely targeted and somewhat perplexing email promoting Amazon.com’s variety of gourmet and specialty meat selections. Wild Boar 10 Rib Rack anyone?, asked the email. The first line of the message was “As someone who has shown an interest in gourmet meat…”

What? Gourmet meat? Me? From Amazon.com? Huh?

Then I realized what had happened. About three weeks ago I was doing a search on how to best cook beer can chicken. After re-tracing my steps, I recalled landing on an Amazon.com meat page, clicking around about five times, and leaving. I do not think this makes me a lover of online gourmet meat…but maybe it does?

Items to consider:

1. Personalization was not used in the subject line. If Amazon knew I clicked on a handful of pages, surely the company knows my name, right? Would name personalization make this message more or less intrusive given that it is based on browse behavior?


2. How do we differentiate a user's definite "interest" in a particular subject area versus just casual browsing?


3. The timing of the message was smart and relevant – this is prime BBQ season, after all. Had it been sent in the dead of Winter, I would have found the message less useful.

Takeaways:

1. Browse behavior messages should be targeted, but not so targeted that users are looking over their shoulders to see who is watching them.


2. Marketers need to be selective in choosing which pieces of behavioral data are used in an email.


3. Be sure to carefully define what "showing an interest" means. Long browse durations, cart abandonments, repeat visits, etc. all seem to be strong indications of user interest rather than casual browsing.

I'd like to hear from you. Can an email be overly targeted? Where should email marketers draw the line?