Information

                            going Beyond the Click

Email communication can be dynamic, targeted, automatic, triggered by action, behavior or preferences. With complex business rules driving the email distribution, the campaigns can be extremely effective.

 

Historically, the effectiveness of an email is measured by the inbox delivery, open rates and click rates, leading to a desired conversion. The intelligence in SocketLabs allows an email’s effectiveness to be measured Beyond the Click.

Depending upon the audience, industry, subject line, sender’s reputation, etc., an email might be opened by 20% of the recipients. Then, assume that 20% of those individuals click through to the destination web site. If this hypothetical email was distributed to 100,000 recipients, that would mean that 4,000 ((100,000 x 20% open) x 20% click) people would have entered the web site. Assuming a moderate conversion rate of 0.5%, this would equate to 20 transactions.

 

This may seem fine, but the real question is what happened to the other 3,990 people that entered the web site and did not complete a transaction? What did those people look at and how long did they hold it in their virtual hands? What does their behavior tell us and what are their preferences? How can this information be collected?

 

Standard email reporting looks something like this;

From the review of this rollup, it would appear the Email #5 and #9 performed the best with 15.5% and 23.7% open rates, followed with 16.2% and 14.0% of the emails being clicked.

 

When data is extracted from SocketLabs, standard email reporting can be expanded to look like the following;

With this information, Emails #5 and #9 do not appear to be as effective as previously thought. While Email #5 had a 16.2% click through rate on opens, those individuals spent an average of 6 minutes on the web site looking at 8 web pages. That equates to about 45 seconds per page.  Email #9 had similar metrics with its ‘clickers’ spending and average of 5 minutes on the web site, viewing 14 pages, equating to about 20 seconds per page.

 

Email #4 and #6 had an average click to open rate of 7.8% and 9.2%, spending 11 minutes on the site. While on the average they viewed fewer pages, they appeared to be more engaged with 2.75 and 3.67 minutes per page.  This segment of individuals would be the logical target of a follow up email, personalized with what product they were most interested in.

The enhancements to the email metrics help to identify the behavioral characteristics that indicate an individual’s engagement in the purchase decision process. The next stage of data enrichment adds the user’s preferences by aggregating which pages were viewed, which products were viewed, on the web site. Then, this information is augmented with all of the user’s web activity, beyond that of actions from one email. Ultimately, accumulation of this knowledge supports scoring and prompts the appropriate ‘automated’ communication, via the appropriate channel (i.e., email, direct mail, call center, sales call, etc.).

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