Value-based optimization delivers up to a 45% better response from high-value customers, and improves return on ad spend by up to 80% for companies in financial services and technology sectors, according to a DataXu study released Thursday. The stats come along with an emerging marketing objective from the company.
DataXu CEO Mike Baker said brands and agencies have been asking for value-based optimization. It factors in the price of the item that consumers view or purchase to identify the value of customers. The information is used to automatically optimize campaigns not only based on volumes of sales, but on the most profitable customers. The strategy relies on measuring against an aggregated baseline driving cost per action (CPA) and integrating in real time online shopping cart values and sales data.
"You now can use ad exchanges and DSPs to maximize profitable sales," Baker said. "One brand told us that even though they drive many sales online, many of them are ROI negative because they have ad networks that they're paying for conversions, but the conversions are a very low value. They hope one out of 10 of those conversions are a high-spending customer, but that's a random hope."
For the first time, advertisers can run bidding through DSPs like DataXu to find profitable customers. The most profitable are identified through data models consisting of consumer segment, content and creative pieces. DataXu's platform learns patterns, and along with analytics, can determine the most valuable customers for a specific client.
At Goodby, Silverstein & Partners, return on investment remains the primary metric for direct-response campaigns. But when marketers optimize campaign metrics that are tied to actions such as orders, rather than revenue, it can present problems.
So, Dong Kim, group communication strategy director for the agency, began working with DataXu toward the end of last year to set up a program to change the optimization strategy and the metrics.
Since the cost for products differs, there's a big difference between selling something for $30 vs. $200. So Kim's group had to maximize the amount of revenue brought in for the budget being spent. Value-based optimization allowed his team to optimize campaigns for an unnamed technology software maker based on value of customers to improve ROI.
"In the past few months we've begun to see more advanced optimization strategies emerge," Kim said. "We're also beginning to see ways to optimize on softer metrics such as brands."
Although known for its creativity, Goodby, Silverstein & Partners built an analytics and data strategy. Although it may seem a little progressive today, one year from now, more agencies offering online ad campaigns will need to adopt the same format to survive and thrive. Agencies will need to build a data strategy. They will not have a choice.
When asked whether the same strategy works for mobile and tablets, Kim said, "we are trying to figure that out because certain products need to be downloaded and don't work the mobile phones, which means you lose the connection."
The next step is to apply this strategy across other market verticals, and integrate the lifetime value of a customer. "We're just starting to see the very beginning of online advertising integrate with enterprise data systems such as CRM," Baker said.