The first audience that most advertisers work with is their own website visitors. After all, retargeting campaigns perform better when a high concentration of traffic comes from high-value search keywords or newsletter clicks. This is true because customer data-driven audiences and retargeting audiences are one in the same.
The challenge with this audience is, of course, scale. Marketers can only serve so many ads to a user before fatigue sets in and return on spend is diminished with the cost of over saturated impressions. So, most marketers figure out the frequency sweet spot and cap budgets in some proportion to the audience size — but where do we go from here?
Navigating Datasets
With companies such as LiveRamp and Adobe providing an ocean of data marketplace, it’s challenging to know what datasets are going to actually improve the targeting and effectiveness of media spend comparable to your target audience. Some data varieties found in these marketplaces include:
- Demographics, such as income, age, ethnicity, lifestyle, children in household, education, profession and more;
- Interest-based audiences where customers have self-selected topics of interest;
- Past browsing history of consumers who have been at some point to a specific category or specific website;
- Direct mail lists selected from databases including registration, employment or purchase history data; and
- Behavioral audiences that are constructed based on a consumer’s observed behavior that would be relevant to an advertiser.
The differentiator in audience effectiveness is a combination of product/solution relevance and the buyers’ place in their buying journey. Many datasets allow users to reach consumers that will likely be a good fit in the future, but the trick is finding that subset of users who are actively looking to make a purchase.
Unlocking Behavioral Opportunities
The catalogue industry developed the concept of customer lifetime value and recency, frequency and monetary (RFM)-based marketing, which are the most reliable leading indicators used in direct response. For example:
- A customer who recently bought something is more likely to buy another product if marketed to than a person who bought something two months ago;
- A customer who has made frequent past purchases is more likely to respond; and
- Someone who purchased an item at a lower monetary value than average will respond in a more favorable way.
These are all behavioral characteristics that present windows of opportunity for marketing. Aligning outreach right after the expressed RFM behavior is when a prospect’s response will be strongest — as the behavior fades, so does the purchase intensity. After a certain amount of time, these once-ripe prospects are no more responsive than others in the marketing pool who might fall into a similar audience but aren’t in product acquisition mode.
Website retargeting audiences certainly fit within the behavioral category. These are people who recently searched something on Google or clicked a link in a newsletter that led them to a site. Once exhausted, where can we tap into additional behavior signals that will allow marketers to focus advertising on those most ready to act?
One approach may be to form partnerships with others in your category or in similar categories, which would include adding an audience tracking pixel to these websites where visits are a clear indicator that they are ready to buy and targeting those alongside your own website retargeting audiences.
High-funnel marketing to broader demographics, interests and so on is important in the long term. But ultimately it is the ability to isolate behavioral intent signals that drives marketing efficiency in the last mile.
Ezra Doty is the Founder and CEO of Quorum, a public affairs software.
