As an email marketing agency, we are constantly faced with the challenge of beating our clients’ goals. For one such client, whose goal was based on the number of new leads created, we were steadily increasing the number of leads generated each month. After working with this client for over a year, we started to see the number of new leads generated plateau. We had previously focused our attention on improving the effectiveness of batch emails sent to prospects, as well as establishing new acquisition sources. We decided we needed to find a new way to reach prospects when they were ready to buy.


The client’s database had thousands of prospects that did not convert during the first 30 days. After such time, we found their likelihood to convert declined significantly. The key to re-engaging these prospects was finding the right time to target them with the right message.  If we knew when these prospects were browsing the website and which pages they were visiting, we could target them with the appropriate email messaging and convert them.


In addition, the client’s database contained email addresses that were not subscribed to promotional emails. We had permission to email these prospects, but had not been doing so on a regular basis. We did not want to start including them on batch email for fear that they could affect our engagement and deliverability stats.


The proposed solution was a highly targeted, automated email program triggered by the last webpage visited. This solution solved both problems we faced; it was a way to target prospects when they were most likely to convert, and it gave us a method of engaging with those prospects not currently subscribed to our promotional emails.


This particular client is still on E9, and we had no way to target prospects based on the last page in their website visit. To get around this limitation, we created a hierarchy of pages visited in order to route leads to the correct program. The first step in the setup process was to tag all of the appropriate pages. Page tags were created for each URL, including subsequent pages in the path. Next, we created a series of programs specific to each page visited and a feeder program to route leads to the correct path.


The feeder program allowed us to prioritize the pages a prospect visits in order to route them to the best converting offer if they visited more than one page category. Prospects could enter the program several times, and were routed to the next subsequent offer each time they visited the page.


The program was enabled in November 2014, and since that time over 500,000 prospects have gone through. Several of the emails in the program were previously sent to the prospect base as one-off batch sends. We used these results as our baseline for success. To date, the website visit trigger program has outperformed the baseline by 182% for click to open rate and 53% on lead conversion to open rate.


This client is a service provider that works on a yearly contract. The next step for this program is to estimate prospects’ current contract end date with their service provider and message them accordingly. We will use the date the prospect was created as our best estimate for contract end date, since people most likely started shopping the first time their contract was about to expire. We will target messaging based on that date, getting more aggressive as they near the end of their current contract.


As an agency, we learned that it is important to not merely test and improve status quo, but continuously think outside the box. Finding prospects where and when they are ready to buy can be like finding a needle in a haystack, but when you hit even just a little pocket of success, it can make all the difference.


On a side note, we have been working with this client to migrate to E10, and will hopefully be completing a migration sometime this summer. Once a migration takes place, we will look back at this campaign and re-evaluate our approach in order to optimize it for E10. With the new efficiencies and capabilities of the E10 platform, we are hopeful we will be able to gain more incremental growth in the program.


Classes that helped: E10 Web Profiling, Program Builder Overview