Winning business from email newsletter subscribers

If you send out a regular email newsletter, how many of the readers convert to business?

More specifically, what can you be doing to nurture people towards doing business with you?

One thing you can do is use website analytics to reverse engineer certain website visitor patterns back to the original email newsletter subscriber.  Here’s a recent example to show how it works, in this case using A1WebStats (tracking) in combination with Campaign Monitor (used to send out and monitor the email newsletters) …

Step 1 – find something worth digging into

One of the Custwin email newsletters referred to A1WebStats, providing a link to the website.  We, of course, can see where website visitors originated from.  Looking at the screenshot below you can see that the person came in to the A1WebStats website, via a Custwin blog (see the ‘Referrer’ line) and they looked at the pages showing the prices and how to make A1WebStats work for them …

At this stage we think “hmmm, there may be an interest there, because they went further than the blog itself”.

Step 2 – track backwards

That person entered the A1WebStats website at 12:08.  By looking at our Custwin webstats we can see that only one person was looking at the website around that time and so it has to be them.  If you look at the screenshot below you can see similarities (e.g. location, browser, IP address etc.), so it’s clearly the same person.  You can also see that although they appeared to spend 2 minutes 44 seconds looking at the Custwin blog entry, that was the time they went off to the A1WebStats website, which they left at about 12:09 and then continued looking at the Custwin blogs at 12:10  …

The picture we’ve built up so far is that the person who ended up on the A1WebStats website and was looking at pricing, initially landed on the Custwin website and looked at blogs.  We also know that they came from our email newsletter that was sent a couple of days beforehand.

Now all we need to do is match up the date/time that the person landed on the Custwin website (2^nd December, around 12pm) with our Campaign Monitor information …

Step 3 – identify the person

We looked at our Campaign Monitor data and found only one person who clicked through from our email newsletter on 2^nd December around 2pm.  The screenshot below shows what they were looking at on the email newsletter around that time …

Ignore the fact that the location is Camberley, vs Leatherhead in the A1WebStats information – that’s purely down to IP techie stuff.  The person is actually from neither location and we know who they are.

In fact, the person is actually someone who is perfect to be white-labelling A1WebStats for their own clients.

Step 4 – nurture

So having identified the person, do we contact them and say “hey, we saw you were looking at A1WebStats and we’d love to have a chat”?  We could do, but the whole ‘webstats tracking’ thing can appear a bit creepy to some people so it’s often better to be more subtle.

We actually had a message from them recently about having a catch up.   We replied but nothing got organised.  We’ve now been back to them again about meeting up.  As part of that conversation, we’ll be talking about A1WebStats and we’ll know that they already know a certain amount about it.   There will be the opportunity to show that person how it can benefit them and their clients.   There are, of course, no guarantees but it’s always worth trying.   If that moves forwards we may blog about it as a follow up in the future, to demonstrate how the flow of business often starts from blogs/newsletters/information and can lead onto a lot more.

Conclusion

For most companies the process of analysis is really easy and can boil down to a few steps …

1. Create a regular email newsletter containing various articles, and always linking people back to your website.
2. Ensure that email newsletter is sent out using a system that allows you to track when people open and click on articles.  Commonly used systems are Mailchimp and Campaign Monitor.
3. About a week after the email newsletter has gone out, go to your webstats package and highlight the people who have landed on a particular website page (one of your articles linked to from your email newsletter).
4. If any of those website visitors went further than the article(s), e.g. to look at pages showing the services you offer or people you work with, then that could be a potential buying signal.   You would typically expect to see perhaps 1 in 20 people go further than the page they landed on from an email newsletter article.  They become ‘the potential’.
5. For those website visitors who looked as if they may be interested in more than just the article they read, reverse analyse their path to your website.  This is simply a case of matching up the date/time they landed on your website with the dates/times that people clicked through from your email newsletter (which you can see from systems such as Mailchimp or Campaign Monitor).
6. Then consider how you may be able to nurture that person in a non-threatening way.

Time-consuming?  Yes – perhaps.  A job that anyone in your company could do, if they’re taught what to look out for?  Absolutely.  All YOU want to know is the useful information and if you’ve got someone else who can be looking out for it then it makes sense to work in that way (says me, who has gone through the process here myself!!).