Retargeting is a concept that can be confusing and one topic that we get more questions about than almost any other. Here is a clear explanation and examples of the benefits of both a targeting and retargeting campaign as described by Blair Jeffris of the blog Retargeter:
Your audience data is as good as gold (probably better) when it comes to the returns you can earn from it. We call it Return On Audience Data (ROAD). You’re probably familiar with Return On Ad Spend (ROAS), a key performance metric in advertising. ROAS and ROAD are related, so let’s start by clarifying the relationship between Ad Spend and Audience Data.
ROAS = Revenue ÷ Ad Spend (there are variations, but we’ll use this one)
How do you calculate Ad Spend?
A partially true statement: Ad Spend = Cost of Media
A truer statement: Ad Spend = Cost of Media + Audience Data
In fact, 2nd and 3rd party audience data is often more expensive than the cost of media for digital display advertising, sometimes much more expensive.
1st party audience data is the data you already own. It wasn’t necessarily free to acquire it, but now you own it. Your audience data includes the visitors to your website that you cookie, your email lists and CRM data, your app users, and more. When you use your own audience data for digital display advertising, we call it retargeting or remarketing. With retargeting you eliminate a major expense in your advertising, data, and you amplify your revenue. Retargeting is one example of how we build Return On Audience Data (ROAD).
MEASURING ROAS AND ROAD
To better understand the importance of ROAD and how it can drive ROAS, let’s look at examples of Audience Targeting and Retargeting campaigns and compare results.
Audience Targeting. Let’s say we run an ad campaign to reach a new audience using 3rd party audience data. We are buying data from other (3rd party) sources to reach this audience. It’s an audience we want to reach, but it’s not yet our audience data. We call this Audience Targeting:
Audience Targeting campaign assumptions:
Media CPM = $3.00 (inventory cost per 1,000 impressions served)
Data CPM = $3.00 (data cost per 1,000 impressions served; when you buy audience data to target a specific audience, you pay the data provider each time you serve an ad to this audience)
Impressions served = 1,000,000
Click-thru rate = .1%
Conversion rate = 1.5%
Average order value = $200
Using the assumptions above, we calculate ROAS:
Ad spend = ($3 + $3) * 1,000,000 ÷ 1,000 = $6,000
Revenue = .1% * 1,000,000 * 1.5% * $200 = $3,000
Audience Targeting ROAS = $3,000 ÷ $6000 = $.50
The upshot? For every dollar invested, we generated $.50 in revenue on this campaign. We actually have negative ROAS on this Audience Targeting campaign, but that’s okay with us because we acquired 15 new customers and each customer has a lifetime value (LTV) of $1,200, so we’ll generate a return on this campaign over the customer lifetime, especially when we combine this campaign with our Retargeting campaign.
Retargeting. Now let’s make some assumptions about a campaign we run using our 1st party audience data. This is our retargeting campaign. There are different types of retargeting including Site Retargeting, Facebook Retargeting (FBX,) CRM Retargeting and more. We’ve adjusted some of the assumptions, because this is an audience we’ve already engaged and they behave differently than an audience we’ve not engaged. Note that this audience includes users we acquired through our Audience Targeting campaign:
Retargeting campaign assumptions:
Media CPM = $3.00
Data CPM = $0
Impressions served = 1,000,000
Click-thru rate = .13%
Conversion rate = 3%
Average order value = $300
Using the assumptions above, we calculate ROAS:
Ad spend = ($3 + $0) * 1,000,000 ÷ 1,000 = $3,000
Revenue = .13% * 1,000,000 * 3% * $300 = $11,700
Retargeting ROAS = $11,700 ÷ $3000 = $3.90
The upshot? For every dollar invested, we generated nearly $4.00 in revenue on this campaign! By using our 1st party data, we didn’t incur a data cost and our ad spend was cut in half, which by itself effectively doubles our ROAS! Furthermore, the audience we reach using our 1st party data converts at a higher rate and spends more than the audience we reach using 3rd party data. Using our 1st party audience data v. 3rd party audience data, we generated an incremental return of nearly $3.50 for each dollar spent! That’s an example of how we build Return On Audience Data (ROAD).
About Jim Dolan: Jim is EVP Revenue Strategies for Enradius, a Baltimore based digital agency specializing in geo-targeting/geo-fencing and cross device matching. Jim can be reached at [email protected]
