As a general rule, the marketer with the most actionable data wins. There are many types of data but the most useful kind — the GlenGarry data — is first-party data. This article will show you how you can use the data you already have about your best (and worst) customers to improve your online marketing ROI.
Before I dive into use cases, let’s quickly define what first-party data is. Here’s a basic primer on the three types of data you likely have access to:
If you are currently running a retargeting/remarketing campaign, congratulations — you are using first-party data! Data that is gleaned from user behavior on your website or app and then used to make retargeting bids/ads/landing pages is a common use of first-party data.
This is, however, a light use case, since your access to this information is really held by the ad network that has given you the retargeting pixel (examples would include Google, AdRoll, and Retargeter).
In other words, you can only use data after you’ve installed a pixel and the pixel has started collecting information. If you’ve got decades of weblogs but only installed your pixel yesterday, you are out of luck. Note that Facebook’s FBX product (which is just retargeting on Facebook) falls into this category as well.
Retargeting lists for search ads (RLSA) is an infrequently used but powerful first-party tool available to all AdWords advertisers. With RLSA, you can use retargeting pools to modify your SEM bids and ads. For example, with RLSA implemented you can:
Facebook and Twitter have first-party data ad products that enable you to merge your company’s email list with Facebook and Twitter user profile. In other words, if someone has subscribed to your email list and used the same email list on Facebook, you can start to market to this user on Facebook (known as Custom Audiences). On Twitter, this is known as Tailored Audiences. Example use cases:
Note that Facebook can also match off phone numbers and other sources. On top of that, Facebook also offers “lookalike” audiences that are based on your customer database. A lookalike is a group of people who have characteristics similar to your customers. This can be a great way to find new customers.
You can use email addresses or postal addresses to run display banner campaigns as well. Companies like LiveRamp and ReTargeter allow you to use this data to connect to programmatic ad exchanges like the DoubleClick Ad Exchange and reach your customers across millions of publishers.
On the Google Display Network, you can also use lookalike audiences to expand your customer base based on existing customers. Of course, Google couldn’t call this a lookalike, because they need their own name for everything (you know, like remarketing), so they call it “similar audiences.” On programmatic exchanges, lookalike modeling is very common.
Last but not least, you can use first-party data to improve your landing pages. Imagine, for example, that you buy a keyword on AdWords and a user clicks through to your site. Pixel information you’ve collected suggests that this user loves expensive items so – voila! – you instantly change the landing page to show your most luxurious products available.
In an attempt to decipher all of these different options, I create a basic Excel chart — initially for me — that will hopefully be valuable for you, too.
To be honest, this gets confusing really fast and I’m not 100% certain I captured all the information properly, so please comment with corrections and I will update this chart as needed!