So it’s no surprise that Google has launched its own audience-based product, called Customer Match. This will allow advertisers to use their list of email customers, match these to logged-in Gmail users, and then market to these customers on Gmail, YouTube and Google Search.
To be clear, this launch is not as comprehensive an offering as Facebook’s Custom Audiences product, which also allows advertisers to create “lookalike” audiences: audiences of people who Facebook has algorithmically determined are likely to act similar to your existing customer list. But this is also just the first of what will probably be many iterations by Google, and it would not shock me to see many more features launched in the coming months.
From a macro perspective, every major online marketing channel – SEM, display, social, mobile – has embraced first-party data (FPD) as an important signal available to advertisers. So now might be a good time to get really good at using your FPD! As I see it, excellence in FPD comes down to three core competencies:
I’m going to assume you have ready access to an accurate file of your customer emails -- competency #1 -- and will spend the remainder of this article discussing data segmentation and why it is important.
Imagine a marketer who has one million customer matches with Google. Among these customers, 20% buy something from the retailer weekly, 20% buy annually, 20% have bought something once, and 40% have never bought anything but subscribe to the retailer newsletter. If you don’t segment this audience, your marketing message by definition has to try to appeal to everyone on your list. Inevitably that means that you’ll probably miss the mark at the extremes of your audience – either a message that is too subtle for the non-purchasers, or too aggressive for your regular customers.
The better solution, of course, is to create separate audience lists based on audience segments. The simplest way I’ve seen to segment customers is through the RFM technique. which divides them based on which customers purchased most recently (recency), most frequently (frequency), and spent the most money per order (monetary). A customer who is in the top 10% of all three categories, for example, might receive a different message or offer than a customer who is in the bottom 10%.
Savvy SEMs know that keyword performance is always improved by targeting, be it geographic, day-parting, device, or something else. Think of data segmentation in the same way, as targeting that improves your audience campaigns. Combine FPD with RPM, FTW!