Luckily for marketers, the process of creating bespoke, perfectly tailored marketing messages can be achieved with the right data tailor on your team.
Forbes published an article in 2008 that opened with how the tailors at Oxxford Clothes…
"Take over 15 measurements of a client's body to create a bespoke suit. It's a process that involves first making a paper pattern that the tailor marks up for details, such as button holes and trouser cuffs; and then, for particularly difficult fits, creating a sample suit from scrap fabric. Six weeks, two or three fittings and around $5,500 later, the client takes home his perfectly fitting suit."
I don't have a survey to source or official statistics to back up my next statement, but I'm confident that it's accurate: the majority of people are wearing off-the-rack clothing that has never seen the inside of tailor's shop.
This article got me thinking about how some organizations approach their marketing and measurement efforts with a similar "off-the-rack" approach. I'm not implying that there isn't thought put into creating marketing campaigns or shaping user experiences on a website, but I'm aware that these efforts aren't as finely tuned as they could be.
Sure, marketing teams pore over research, seek out customer feedback, and base decisions off the results of A/B testing efforts and the numbers that come in from Google Analytics before launching campaigns, so maybe it would be best to classify these attempts as not quite bespoke, but not quite off-the-rack either.
Any way you look at it, there is usually room for improvement in this area. It's like taking an off-the-rack suit to a neighborhood tailor who works on all types of clothing. He'll probably make the suit fit better, yes, but if you want the suit to fit as well as it possibly could, you might consider heading to Chicago to talk to the guys and gals at Oxxford Clothes who specialize in perfectly fitted suits.
Hire a Data Tailor
Luckily for marketers, the process of creating bespoke, perfectly tailored marketing messages can be achieved with the right data tailor on your team; someone who can create Custom Dimensions within your Google Analytics data pulls.
Out of the box, Google Analytics provides basic location-based information harvested from IP addresses. If you want to know more about exactly who's on your site and what they do when they visit, you'll need to work with a developer to create Custom Dimensions that will reveal more specific demographic information.
Customizing Google Analytics 101
Let's use the example of a college textbook website that wants to understand the difference in click and site visit behaviors between students and professors. Or maybe they just want to know the ratio of visitors who are female versus male, Hispanic versus Caucasian, etc.
Google Analytics will tell them how many people visit their site and which pages they navigate to, but without additional customization, it won't reveal this more specific user data.
In order to discover this additional information about their customers, the website owners could include demographic questions in their initial site registration, for example, by asking new users specifically whether they're a student or professor. This information could then be stored in the user database alongside all of the other information associated with that user.
A developer can then attach a Google Analytics function to the login script so that when someone logs in to the site, the login process checks against the user database to grab that user's demographic information and populate that information into Google Analytics as a Custom Dimension. This allows a visitor's session to be tagged and tracked.
The site owner can then log in to Google Analytics to see reports about who is visiting her site (e.g., male/female, student/teacher, Hispanic/White) and understand how differing segments of the population behave: the pages they engage with most, the items they place in the shopping cart, the offers they respond most to, etc.
These Custom Dimensions can be set at three different levels: visitor, session, and page.
Tailored to a Tee
In the example regarding the publisher site above, if that publisher site wanted to get even more nitty gritty with their data, they could combine the page level of custom dimensions with a session level of custom dimension to understand engagement levels per section in correlation to specific user demographics. For example, on average, women from California spend 34 seconds on politics-related pages versus 42 seconds on technology-related pages.
If you're thinking that a bit of data tailoring could help you in developing some bespoke customer analytics, you'll need to do two things to get started:
Once the highly tailored data starts coming in, you'll be in a better position to create effective marketing collateral that works specifically to engage the exact people who come to your site.
Image on home page via Shutterstock.
Aubrey is the director of marketing programs at Salted Stone, a digital marketing agency in Southern California. She specializes in brand strategy and inbound marketing, working with emerging tech companies and B2B providers to identify their voice and create revenue-driving content plans.
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December 2, 2015
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