Sending a message to someone hasn’t really changed since wax seals and quills. We send exponentially more messages per person but the concept hasn’t changed that much, the characters are in pixels rather than on parchment.
Whether you’re a mass marketeer sending to a distribution list of millions or a love struck teenager writing to your sweetheart, it’s still a message sent between two people, this has to be considered. The author of the love letter thinks of their intended reader with every word, but the mass marketeer will all too often be absorbed by the message they want to convey and not the individual recipient.
Remember just because the email is important to you doesn’t mean it’s of any interest to your recipients!
To ensure the message is interesting it has to be relevant, the ultimate goal is for the recipient to feel it was written for them and to them, not quite a love letter, but with them in mind.
Use the comparison of the days mail on the doormat, sorting junk mail usually starts at first sight with further sorting the ‘Occupier’ letters to the junk selection for the recycle bin. The email experience is similar, scanning the inbox subject lines, it’s the on sight sorting and the design won’t make a difference if the message isn’t relevant. Once your emails are considered uninteresting it’s a short step to the junk folder.
Bells, whistles, videos and animations won’t ensure your email is read.
Ironically it’s usually the fully addressed plain brown envelopes that get opened and the colourful ‘engaging’ marketing letters that are binned. We have to considered these engrainded processes as transferred to the email variants.
Putting the recipients name in the email doesn’t make it personal or relevant. Mail merge isn’t worth the effort, in fact it’s worse if it’s the only attempt at addressing the individual. Personalisation starts with the send list, this has to be a carefully chosen, based on real understanding of the readers and matching them to the message.
Having a database of 2 million addresses does not automatically equate to a high value list.
The value of any list is in the associated data that enables the selection of a recipient with interests that matches the message being sent. The selection of the send list can only really be accurate when there is real data on each and every potential recipient.
This data should contain all historical interactions with previous messages, engagement analytics from website visits, preferences, interests, and in the case of an ecommerce site it should contain purchase history and any other data that will inform the level of engagement with the brand.
The common approach to first create the message and then create a send list can be reversed with good data, seeking common information in the data will allow making matches to business needs. This allows the customer needs and wants to inform and direct the message. This is a far more challenging task to the marketeer but one that will yield far greater results.
The current general perception for large send marketing emails is to expect small percentage open rates and a fraction of that to actually click through. If you expect 5-15% open rates and 2-10% click through rates, you have to amid, you’re doing something wrong! Don’t believe the stats given out by ESPs, there’s clear conflict of interest with these.
Definitely don’t be blinkered into taking ESP data as your only reference for performance, most ESPs provide open rates and then provide a click through rate as a percentage of the open rate. This gives an inflated click through rate making you feel warm and fuzzy about the CTR, when it actual fact it’s tiny. Bear in mind that not all recipients will download images, especially mobile users, but they may still click through, in fact this segmentation is important as it shows your message is striking a chord without any visual enhancements. This should actually be a benchmark stat.
In fact why take ESP data as a primary source of data at all, if your hosting images yourself then you have open rate values and all associated data with the HTTP request, you also have the click through and the most important data, the onward journey after the click through, ESPs cannot tell you who how many and where recipients converted!
Enrich your own data, don’t rely on someone else with blinkered snapshot tell you how engaged your readers are.
All the data you need and wish to have is within your own web analytics (you are using your web analytics aren’t you?) with all the rich details of every web and email interaction, providing you with all the data you need to talk effectively and naturally with your customers.
Consider how you collect email addresses very seriously. If your collection points are transactional, take this into account, recipients may not have any interest in your messages and will eventually unsubscribe. If the collection point is support based or general enquiries these should be considered far colder leads than product enquiries or purchase point collections.
Assessments on how the address was collected and important initial interactions will enable you to understand the recipient and engage with them in positive communication that is rich with understanding and natural.
When working with new clients on campaigns I will sign up with several email accounts at several different collection points, one of which I never interact with, I don’t download images from the emails sent and I do not click through. Another I will occasionally download images and a third I engage with every one, but only one particular aspect of it. This should start to generate different messages and paths of communication, 95% of the time each address just gets the same emails bombarded at them with no sign of any applied insight.
Don’t massage your database ego with dormant or dead data, prune it, clean and polish it.
The account I used to engage fully should generate lots of data from interaction points and onward journey, but in actual fact the low hanging fruit is the non-engaged subscription, the lack interaction should show the marketeer that this recipient is not interested and/or not engaged with the messages. Combined with the subscription point data, this gives an easy to read and simple send list to generate.
Build a send list of all recipients that have not interacted in any way and send them a message asking them if they’d rather just be removed from the list, it shows your listening and trying to understand. If you do not get a response from one or two of these messages, move the address to the dormant list. Don’t count it to pad your database ego.
Engage with your customers with understanding based on real data generated by their interactions, this takes time and requires work to understand the data, but is the road to successful and engaging messaging.