A good detective knows that often there's much more to a case than what the witness tells you. When it comes to solving the marketing mystery of increasing conversions, return on investment (ROI) and profitability, the same thing holds true. Your email subscribers may tell you all sorts of things - age, gender, location … perhaps even their shoe size - but there's much more to the story.

Every time subscribers interact with your email marketing or your website, they're giving you clues as to their motivations, wants, and needs. Being a good email marketing detective requires a willingness to gather evidence from all sources. By combining what your subscribers tell you about themselves (self-reported data) with the data that shows you how they interacted with your content (behavioral data), as well as their past purchase history, you're doing a thorough job of collecting all of the evidence.

Once you have the evidence in hand, it's time to begin interpreting it and drawing inferences about why people did or didn't take a particular action. By drawing inferences you'll be connecting the dots between self-reported, behavioral and past purchase data, and taking the first steps toward making educated decisions on how to best segment and communicate with email subscriber groups.

Drawing Inferences from Subscriber Data

Are you a regular Sherlock Holmes when it comes to gathering and interpreting the evidence, or are you out on a wild goose chase? Put your sleuthing skills to the test! One of the best ways to hone your inference-making skills is to try them out on some hypothetical (but realistic) real-world marketing scenarios. Let's take a look at a few sample marketing cases that need to be solved. Can you pick up all of the clues necessary to draw the right inference?

The Case of the Curious Fan Base

First, imagine you work for an online ticketing merchant. You've identified a group of email subscribers who have self-reported that they are between the ages of 19-24 and female. You aren't surprised when you realize that this group shows a keen interest in the upcoming Rihanna concert. You are surprised, however, to find that a certain sub-segment of this group is also purchasing tickets for upcoming football games, always in pairs of two. What does the evidence tell us about this sub-segment?

Your inference: One might infer that these 19-24 year old women are diehard football fans. After all, more women are serious sports fans these days. But take a closer look; the fact that this group is typically purchasing two tickets at a time implies that they're taking someone with them - a date, perhaps? If you infer that this sub-segment is likely purchasing the tickets as a gift for a significant other, you're on the right track.

The Case of the Upside Down Sales Calendar

Now you're an online marketer for an online office supply store, and you've identified a group of email subscribers who tell you they are female and between the ages of 35-49. You notice that their purchases tend to spike during July and August, and tend to be low in December. They also tend to buy products like markers, glue sticks and colored pencils. You see that these purchasers order multiple numbers of the same products. What motivates these subscribers to buy during the dog days of summer?

Your inference: For purchases to be down in December and up in July and August is unusual, as summer months are often some of the slower times of the year for online retailers. So what happens around July and August that is driving their purchase habits to vary so widely from the norm? Well, summer is coming to an end and school is starting - that's it! These are back to school shoppers!

But what else can we infer about this group? High schoolers don't have much of a need for glue sticks, so they’re most likely to be purchasing for younger students. So now we can infer that this group is likely comprised of back to school shoppers looking for items for elementary and middle schoolers.

Anything else? Yes! Let's examine the fact that they purchased multiples of the same product. Certainly, this could be a mom who is making sure that her child is prepared, but with the order volume, it's more likely that she is a teacher making purchases for her classroom.

The Case of the Nervous Necessity-Seekers

Next, imagine you're a marketer for a store that sells baby clothes and products online, and you notice a customer group that identifies themselves as married, with an average order amount of $100. These customers tend to focus on items like car seats and baby furniture, and are more likely than the average visitor to click through the product page to see additional product reviews. These visitors are also more likely than average to visit the “Guides and Advice” section of your website. What can you infer about these advice-focused visitors?

Your inference: Perhaps these are simply affluent gift-givers who can afford to buy expensive gifts for family and friends who are expecting? However, these married visitors are browsing and buying things like car seats and baby furniture that are more necessities than luxury or gift items. Therefore, it is likely that this particular group consists of parents making purchases for their own babies.

We can take this a step further and infer that they're most likely first time parents, because experienced parents would have already developed stronger opinions about an item's brand and features, and would be less likely to visit the advice-focused sections of the website.

The Case of the Flying Guys

Finally, let's imagine that you're in charge of marketing for a small regional airline and you notice a group of male subscribers between the ages of 35-42. This group shares a number of common criteria: they typically purchase more than two tickets at a time; they tend to book trips during the summer months; they're more likely than average to post several months in advance. This group also clicks through on your promotions offering "free days at Disney". What's the deal with these flying guys?

Your inference: Looking at just the self-reported data, we know very little except that this group of guys that occasionally flies is approaching middle age. Are they golf buddies going for a trip to the links? Maybe, but by combining their demographics with the behavioral data on the site, a clearer picture begins to emerge.

This group purchases more than two tickets at a time, in the summer (which keeps our golf buddies in the running), but also seems keenly interested in your Disney promotions - not exactly a golf-focused activity. Looking at all of the evidence, you can infer that this group is likely one made up of fathers planning their family vacations.

Mysteries Solved. Now What?

Being a good email marketing detective takes patience, practice and access to data - but the payoff of better understanding your customer segments is well worth the effort. By looking at subscribers' self-reported data and uncovering the behavioral clues they leave behind, you'll be better equipped to make educated guesses about their motivations. Doing so can help you develop relevant content and offers based on their needs, which in turn can increase engagement, conversions and sales.

So what happens next? It's elementary, my dear Watson! The reality is that while collecting evidence and drawing inferences based on the data is an important part of establishing the common links in your email subscriber base, it is only the first step in the process. Once you have developed hypotheses about subscriber behavior, it's time to take action and test your hypotheses. Stay tuned! We'll talk more about just that topic in next month's Inside Lyris HQ newsletter.

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About the Author

Mike Weston is VP UK & EMEA Sales for Lyris. He's a leading figure and a regular speaker on the London digital marketing scene, with a particular focus on customer communication tools including email marketing and social media marketing.

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