Over the last few years customer data platforms (CDPs) have become a critical technology infrastructure layer for many organizations looking to manage customer data and leverage it for business value. And while CDPs can be used for a variety of applications due to their breadth of functionality, advertising is one of the top use cases for many companies considering a CDP to improve your ad spend.
While a lot of the advertising use cases are centered around unifying first-party data and then pushing it out to advertising channels to affect the customer experience (CX), a CDP can also be used to drive ad spend savings for your company.
Let’s take a look at a couple of common use cases that almost every organization can take advantage of in some capacity with the help of their CDP.
Improve Your Ad Spend by Managing Global Suppression Lists
The first key to improving your ad spend is to remove as many people from your ad activations as possible who currently aren’t in the market for your product or who shouldn’t be receiving your ads. And while this might sound easy enough for a simple scenario of stopping retargeting ads after a purchase, it gets more complicated when you want to manage a list of individuals who have recently opened a support ticket or warranty claim.
The good news is being able to connect your service ticket system with your advertising channels can easily be accomplished with a CDP. Once marketers realize the potential of this tactic, you can leverage the same concepts in many different areas of the business.
For example, how would you like to remove a contact from lead generation (top of funnel) ads after they’ve opted in, especially if it happened through a channel not tracked by a pixel? Or maybe you could change the communication channel after a prospect filled out the online quote form on your website?
Connecting data from your customer relationship management (CRM) platform, call center, live event registration, or enterprise resource planning (ERP) platform all become easier with a CDP. Merged data with a unified profile allows you to be more focused on who you don’t advertise to so you aren’t spending money with display or social campaigns that won’t drive a click.
Improve Your Ad Spend by Focusing Your Lookalike Audiences
Now that we’ve gotten smarter about who we aren’t going to advertise to, let’s look at a way to improve targeting for those we do want to advertise to. Lookalike audiences are a staple of many advertising campaigns and programs, but often I’ve found with clients I’ve worked with that the seed audience (what is used to create the lookalike) are too broad and generic to be effective.
For example, one common seed audience is customers who have made a purchase in the last 90 days. While this is worth testing, often this audience is too broad for the lookalike audience to really find hungry prospects for your business. This is compounded when you sell different product categories or solutions that service different audiences.
Using the first-party data being collected as part of your relationship marketing efforts, along with enrichment services adding demographic/psychographic data, you already have a key amount of data to find similarities or differences within your audiences. Focusing your audiences down to multiple micro-audiences will allow the machine learning based lookalike algorithm to start with less noise and be able to find much more accurate audiences.
A few micro-audiences to think about:
- Product Categories
- Spend Groups (Average Order Value, Total Spend, etc)
- Geographic Differences
- Use Cases or Solutions
- High Profit (Margin) customers
Starting with these smaller audiences allows you to offer more targeted advertising to a more relevant audience, thus increasing your return on ad spend by not targeting too broadly.
Improve Your Ad Spend by Decreasing Retargeting Pools
This final strategy is focused on eliminating automated marketing campaigns that don’t benefit your overall funnel or strategy. Too often retargeting audiences are based on visitors to a page/site who don’t take the required action, thus they automatically get added into the retargeting pool tied to that device or account if leveraging walled garden publishers (Facebook for example).
But let’s take a look at a scenario where you wouldn’t want to add a customer to a retargeting pool automatically. That’s when you already have them in your database and are marketing to them as a known profile. This type of scenario happens when a prospect visits your website on a new device (maybe a tablet) but they don’t opt-in or make a purchase. All of the sudden they are in a generic retargeting campaign even though you’ve moved them to a lower sales stage in the funnel.
By combining the first strategy of suppression lists, and by using cookie stitching or identity resolution strategies we can identify new devices as owned by a known prospect… even if we currently haven’t linked them to profile yet. By keeping a prospect out of a generic retargeting serves a dual purpose. It improves the overall customer experience and lowers your cost because you’re not targeting a device with ads even though they are customers/prospects on another device.
Smaller Audiences Cost Less
We’ve discussed three strategies all aimed at lowering advertising costs. All these strategies focus on a key theme with smaller, more focused audiences. Marketers can save our limited resources for people who are more likely to be interested in their products/services.
A CDP’s job is to bring all of your organization’s data about a customer/prospect together and then systematically make it available to other systems so those systems can be smarter and more efficient. By eliminating the data silos and manual list loads from various sources, all of the strategies listed above can be automated as well, which is a big win for resource strapped marketing departments.