Data. You know you need it — a lot of it. But once you’ve got it, then what? What are you supposed to do with it, and how? And what role does your email vendor play in making all of this happen?
If you are taking the first steps or ready to go beyond with use of your data, this is of influence to your complete email marketing or automation program. Here’s how to get started.
Going beyond the basics, what does data really mean?
There was a time when “data” might only mean knowing a customer’s gender, or even just their name. (Remember when “Dear Cameron” was a big deal?) When it comes to data, the basics are still useful. At the one end of the spectrum where a marketer might only be collecting bare bones data on a customer, that data might include the gender, plus where they live, and their age/birthday—all good stuff to know.
As technology has exploded in capability, so has the kind of data marketers can now access, collect and use. Today’s dataset on a customer can include which emails were opened and clicked on, items browsed on a website, date of last site visit, items purchased, average purchase size, Lifetime Value, etc.
A marketer can even use data analysis to predict the future behavior of a customer by building Data Models and “Model” what combination of actions/demographics will most likely result in a positive engagement.
What do we mean by data? The image above by Peppers & Rogers group, shows the difference in relevance levels with more use of data for segmentation and personalisation. We want to be more relevant, so that is a good starting point. The kind of information you find useful to improve the relevance with which you’re talking to your audience.
What do you want to do with that data?
Data is obviously important, but only if you use it, and this is where your email vendor becomes part of the equation. Having the data and not being able to use it is like not having the data at all. So figure out what it is that you want to be able to do.
You want to know upfront what you will be doing with the data, so that you can ensure you have the correct data to drive your marketing program. You also want to make sure your email vendor provides the functionality you need. This is a big item because many email vendors do not support relational data and expect your IT teams to perpetually flatten the dataset thereby removing lots of the richness—plus this prohibits the ability to quickly change or test other metrics in your program.
Some of your options for data use include the following, although your organization might have specific needs not described here — and that’s fine! The key thing is to know what it is you want to be able to do, so you can find the technology provider that can do it.
Segmentation: Segmenting is perhaps the most obvious use of data, and one well worth the effort. A smaller, more targeted list will perform better, because it allows for more targeted and relevant content.
Personalize: This is personalization beyond the “Dear Cameron.” This is data-driven (aka real-time) personalization we’re talking about, personalization that puts data to use in the moment. According to DMNews , marketers using real-time personalization see improved engagement, customer experiences and lead generation. This kind of content can be data-driven based on all kinds of behaviors, for example, based on the browsing a customer did at a website, or based on a previously opened email. Today, “personalizing” means sending customer-specific content, not just including a name. In fact, today the term personalized can also be used to describe the images that are served up in an email based on customer attributes.
Identify, model and convert: Using data, you can turn prospects or website visitors into customers, or you can convert occasional customers into long-term loyal ones. Using your transactional data, you can also determine who your best and most loyal customers are and then target them specifically with special offers designed to increase sales as well as deepen loyalty. Additionally you can look at the customers who have converted and build “Models” of those customers so you can identify other prospects moving through the steam and message to them differently.
Automate: Data can be used for smart automated marketing that triggers messages based on a user’s actions, such as downloading an ebook, abandoning a shopping cart, clicking on an email link, completing a purchase, and so much more. (The reverse of this is using automated email to remind people to keep their preferences up-to-date by sending occasional reminders that in turn keep your data accurate.)
Retarget: Data is most definitely useful for retargeting cart abandoners or even browsers who didn’t get as far as putting items into a cart.
Target customers via social media: Data can help you target customers outside of email too, and gain new customers that way. The more information you have about your customers, the better able you are to target new customers via social media such as Facebook ads because you can build a profile based on your best customers, then target people that fit that profile with your ads. The more you can define your customer and understand what data attributes they are likely to possess, the better you can build look alike audiences.
Test and refine: Yes, data can definitely be used to do stuff. But it can also be used to improve. This can include just about anything, from subject lines to calls to action to you name it—even the imagery you use. It’s less about what you should be testing, rather simply that you should be testing—constantly and continuously—and using your data to see what works and to further refine.
(If you’re looking for more ideas of what you can do with data, George Bilbrey from Return Path offers a myriad of ways to put data to use in this post.)
Making that data usable
Now that we’ve gone over many of the ways data can be used, the next question is, how do you make that data usable? Once you’re gathering the data, how do you put it to work as part of your email marketing program?
Aggregating and integrating data from disparate sources should be among your highest priorities as an email marketer. However, there is no simple answer to the “how to” question because you really need to start from the end. How you set this up depends on three key factors:
- What email programs do you want to build?
- What segments you want to create?
- What content you want to send them?
- How do we make our programs smarter?
First you determine the answers to these questions, then you work backward from there to determine how you will set up your data structure to achieve your goals. The structure won’t build itself at this point, but at least you’ll have a much better idea of your needs and a starting point for creating the structure.
Ideally this is something you’ll do a little at a time rather than trying to eat the whole elephant in one sitting. We talk to a lot of marketers with grandiose plans with their data, but those grandiose plans can quickly lead to getting nothing done at all.
Instead, we suggest focusing on what you can accomplish in a 3- to 6-month period only. That way, everyone can get behind your new data initiative and you can actually get something done.
Starting simple might be your only choice too, if your email service provider offers only flat file databases. Manipulating data in any kind of sophisticated way requires a relational database, and not all ESPs offer that. In fact, relational data is fundamental if you want to use data in any kind of powerful way.
You can definitely get started using data for more relevant marketing with a flat file database! But the question becomes, can you build on that?