"the single most important piece of data for a successful email program is the email address. You may think, "Hey Bob, thanks for that blinding glimpse into the obvious." The truth is, this is a piece of data that if often beyond the control of the email team to actually gather, as this is usually a function of the web team. "
In building an email program, you are often flooded by choices – choices about testing. Choices about timing. Choices about tracking and sales lift. But one of the most important – yet overlooked – choice is one of data. While email marketers often talk about being data-driven, precious little talk is given to what sorts of data are the most valuable. Gathering data is not always easy, so hopefully this guide can help direct which levels of data you should spend your time gathering, presented in order of importance.
OK…here we go.
1. Email Address – the single most important piece of data for a successful email program is the email address. You may think, "Hey Bob, thanks for that blinding glimpse into the obvious." The truth is, this is a piece of data that if often beyond the control of the email team to actually gather, as this is usually a function of the web team. There are more than a few web marketers out there who think that email is spam and that spam is bad. They don't care about business results beyond their own silo...and the email program (and the whole company) suffers for their ignorance.
Gathering an email address is not an invitation to go out and do something stupid like buy a list...but in a surprising number of cases web team make it exceptionally difficult for consumers to "join the team" by making it easy to sign up for emails. Other companies will ask for your email address in order to unlock content...which usually just leads to a bunch of bad email addresses.
Think of asking for an email address like you're asking for a person's phone number. You don't want to do it too early. You don't want to force them into giving it to you. But if you never ask for it ...you'll never have a chance to follow up.
If you could spend all your data time on one thing, this is the place to start.
2. Previous Purchase Data – While we all hear horror stories about buying a gift for mom and then receiving an unending stream of mom-jeans offers, previous purchase data is a critical factor in the success of an email program. Why? Because when you send out a similar offer to previous purchasers, they will buy at 4-5 times the rate of your normal list.
The second reason for capturing previous purchase data is that it is an excellent place to build look-alike models. Some products have natural affinities – for example, skis and ski goggles. Knowing the correlations of purchase between categories gives you a powerful ability to build logic-based look-alike models that are significantly more powerful than response-based statistical models (and are way easier and cheaper to build.)
3. Email Click Data – Your own email is a great source of harvesting consumer behavior that you may not be aware exists. In most organizations, the email links you create are consistent – ie – www.bobfrady.com/redirect/product/tracking. When someone clicks on that link, you know that this person has at least a passing interest in this product...allowing you to build very effective mailing segments. It's not as good as previous purchase data, but it is 2-4 times more effective than a general email list based upon things like age on a file.
There are two other reasons why I love email link harvesting. The first is that it allows you to (re)introduce discovery to your email programs. You can – in a properly constructed discovery email – add dozens of links across products that you do not know are relevant to a particular consumer. It allow the consumer to both discover more things about your company while passively opting into receiving more targeted communications from the company. Sometimes, being more irrelevant will actually allow you to be much more relevant.
The second is that it allows you to mail your entire file. Which you should do at regular intervals (at least weekly for B2C efforts.) Since the goal of this email is primarily to gather information, you can "sell it" internally much easier. You'll also happen to make a lot more money that day...but you can always show that later. Mailing your entire file every week will allow you to also identify the "HFU"S!" (Hard Bounces, Feddback Loops and Unsubs) quickly and efficiently – making for a much cleaner file.
4. Web Click Data – Now we start to break out of email centric data and into a data silo that you (as the email marketer) may not control – your web site visit and click data. It is a treasure trove of user behavior...but like many treasures, it can be both fiercely guarded and difficult to reach.
Web click data is actually MORE valuable than email click data harvested from links because it does not artificially restrict the number and types of products you can show in an email. Given that it can be very difficult to get – and is usually out of the control of the email marketer - it drops down a spot on our list.
There are two things that are difficult about harvesting web data. The first is linkage – you have to be able to link the customer data back to an email address. For many sites, this is a problem – especially if cookies aren't persistent for a long enough period and/or your site requires a login and won't associate the click data with the consumer/email address. Many web developers in organizations both large and small simply don't think about the usefulness of this data in email – it's too "downstream" to worry about when you're building a super-fantastic web experience. To be fair to the developers, as people cross devices it adds a lot of difficulty to successfully identify individuals – cookies are not always up to that task. You have to work closely with your web team to develop and implement a method for recognizing your consumer. It has traditionally been icky work for marketers...but as marketers become more digital it's getting easier to solve.
The second difficulty is access to the data. It's one thing to identify the consumer, quite another managing what can easily become a flood of click data. Many legacy systems aren't set up very well to store this data, much less have tools that can easily utilize this data across what can be millions of records. Your ESP or internal teams need have database approaches that span both relational and denormalized data sets – as relational data sets can choke on the volume. Again, it's the sort of work that marketers have typically shied away from...but one that's well worth getting your hands dirty.
5. Customer Preference Data – What's that? Customer preference data so low on this list?
Personally, I love the idea of customer preference data. The problem is – as a whole – most consumers really don't really seem to be interested in telling you what they want. Plus, why rely on what someone says when you have a site-specific census of what they actually DO. The utility of preference center data is now mostly limited to email newletter list opt ins and frequency/cadence preferences. It's probably going to be used by less than 10% of your consumers but can be very valuable for those specific consumers.
The other type of valuable customer preference data is where data is extracted from another source on a user's computer. For example, if you're a music or entertainment site, you can build tools that directly extract what's in a user's iTunes directory, then store that data in a customer preference table. If the users want your content, they will give you consent to use this data on their behalf. Not every application is quite so straightforward but consider finding the places where your consumers store information you might find valuable, then ask for permission to link to that data by creating a compelling proposition around the use of that data.
6. Deliverability Data – This data includes campaign level data, IP-specific data and third party data from monitoring companies. While these tools will not necessarily help you at the individual consumer level (except for hard bounce data, of course), they can provide you great insight as to how individual ISPs are treating your data. After all, a message never delivered to the inbox is a lost opportunity to communicate with your consumers. The deliverability world can be a dark and mysterious place – make sure you have the tools that help you to decode the riddles.
For brands with either a limited product offering, limited access to data or simply a bad relationship with IT and/or the web team, deliverability data would be higher on this list – it's a data element you can control. For organizations that are sending on shared IPs this data is not that valuable...and if you've read this far and have shared IPs...congratulations.
7. External Data – The last category of data is compiled third party data providers.
Compiled data is – essentially – a conversation that is reported by a third party. Reported conversations by third parties are not nearly as valuable as conversations you have directly ("first party" conversations) with consumers. Like many third party conversations, you can have a problem with accuracy. Plus, more does not always equal better – having too many extra data variables can seem valuable but it often a distraction/crutch from getting at your consumer-driven internal data.
Here's a harsh reality of email – it's cheap. Which means that you can send much, much deeper into your file before becoming unprofitable. Much of the value of external is built around understanding more about your consumer so you can send fewer direct marketing pieces (aka – segmentation.) Since email has such a light cost burden – and the fact that external data can be expensive – external data can cost more than it delivers in value. If you're regularly sending discovery emails, your customers will tell your from your actions both what they want and how valuable they find your program.
I've tried multiple times to make compiled data work in my email programs...but its value pales in comparison to the rich and valuable data I can "compile" myself from web, email click data and profiling data I build up over time. Once you've full mined your own data, then go out and try to find the external data elements that work for you. It can add value...just not as much as what you have internally. On the other hand, it's easy data to gather- especially valuable if your relationship with IT and/or the web team not good and your internal politics resembles an episode of Game of Thrones.
As email/digital marketers, you have a gold-mine of data at your fingertips. Getting at this data is can be difficult. Working with links and data tables can be daunting. SQL can be scary. But if you're looking for the most valuable data you can possibly find, make the choice to go mining for gold!