In a recent article by ConvertMedia’s Yoav Naveh, “Retargeting is Not Prospecting”, Yoav made mention of a few very important and noteworthy concepts when it comes to an online prospecting campaign. The high-level idea that retargeting is fundamentally different than prospecting is an important one. That said, here at TruSignal, we were most interested in Yoav’s opinions that a) prospecting explores a wider array of data signals for correlation and b) marketers must look beyond last-impression or last-click attribution. These two concepts are key considerations for prospecting campaigns.
Prospecting campaigns should prompt high-value prospects, who you aren’t currently reaching today, to learn more about your product or brand. This new demand increases conversions of your existing bottom-funnel campaigns such as paid search, organic search, behavioral targeting and retargeting. While prospecting campaigns are very complementary to your bottom-funnel efforts, they should not use the same data or measurement metrics as your conversion campaigns. Let’s further explore Yoav’s considerations.
Prospecting Explores a Wider Array of Data Signals for Correlations in Order to Drive Awareness and Intent
In order to justify incremental marketing dollars to educate new customers, they certainly should be in your target market and among the most valuable or profitable. Finding high-value prospects early in their consideration cycle requires a tremendous amount of offline profile data and the analytical horsepower to find the right signal. To find strong indicators of your most desirable prospects, you need to look at who they are (i.e., profile data).
There are many different kinds of profile data available for audience targeting. A great place to start is by understanding the characteristics of your existing, profitable customers. These raw data attributes can take the form of demographics, hobbies, interests, psychographics, asset ownership, lifestyles, financials and past purchase activity.
For online audience targeting, the key is finding a set of characteristics that are predictive and actionable. So, you might ask, “How can I find the right data signals amongst all the noise?”
Predictive analytics lets you combine tens of thousands of data points to create an audience of users who look like your existing, most profitable customers. A lookalike audience model uses your existing best customers as a template and appends many different sources of third-party data. The modeling algorithm analyzes the appended data points and mathematically determines which ones are the best for predicting your target audience. Since some data elements are more important than others, a good algorithm also will assign different weights to each relevant data element. By incorporating many attributes of your existing customers and the interrelation between those attributes, a custom predictive model creates a powerful prospecting audience.
Marketers Must Look Beyond Last-Impression or Last-Click Attribution
Given their mid-funnel marketing focus of educating new customers, prospecting campaigns should be judged on the ability to influence “high-value” users and generate incremental demand. While some users exposed to prospecting campaigns do convert on a last-click basis, approximately 80 to 95% of conversions will occur through a series of marketing touch points. The last touch point (click or view) for most conversions will be a conversion campaign.
For example, a prospecting campaign will prompt a user to execute a search or navigate to a brand’s URL without recording a click. The campaign data that we’ve tracked illustrates that search is the largest beneficiary of prospecting campaigns. In other words, the prospecting display campaign sparks the demand and the search campaign closes the deal. While it’s nice to see a spike in the volume of inquiries, the value of those inquiries is paramount.
To measure the value of users who are being influenced by a prospecting campaign, it’s important to have transaction-level tracking on both view- and click-through conversions. With transaction-level tracking, it’s possible to assess the value of each conversion influenced by the prospecting campaign by tracking down to the ultimate financial transaction.
Measuring Incrementality Is Key
“Incrementality” measures how much new demand is being created. In other words, how many new customers are influenced by the campaign who would not have just converted on their own?
One way to measure incrementality is with a controlled A/B test. For the experimental group, execute a prospecting campaign and measure the number and quality of the new customers associated with the campaign on a view-through basis. For the control group, execute a prospecting campaign under the same conditions as the experimental campaign, but use creative units that make no reference to your product or company. Everything else must be the same. When you compare the results between the control and experimental groups, differences in the magnitude and quality of sales can be attributed to the impact of the prospecting campaign. A well-executed prospecting campaign should deliver high-value demand and incremental demand.
Are you looking for high-value prospects and an opportunity to feed your funnel with new demand for tomorrow’s conversions? If so, it might be time to add data-driven prospecting campaign using a custom audience to your marketing mix.