Balancing Platform Automation with Advertiser Controls in Performance Media
MAXIMIZING DIGITAL MARKETING PLATFORM AUTOMATION
If digital marketing automation platforms have the best opportunity to identify the right consumers at the right time, how can we make sure that we’re still able to integrate your crucial business goals into the algorithm? Because not every $1 of revenue on Product A from Customer A is equal to a $1 of revenue from Customer B and Product B. How is that considered?
At a basic level, we know that two items of the same price could potentially have different values to your business – one could have more margin or profit after we exclude the cost of goods sold, pick, pack, ship costs, etc. This sort of data is easily fed back into automation algorithms to better identify customers whose individual order is profitable (or not).
But, what if your merchant team bought three times as many red bicycles because they thought “they’ll sell better this holiday” than blue bicycles. Even with the exact same margin, we may want to value a red bicycle sale more than a blue bicycle sale because there are carrying costs involved and it helps ensure we’re not going to be stuck with unbalanced or out-of-season inventory.
Taking the example further, what if you knew that for every customer whose first purchase is a red bicycle, they’re twice as likely to return and buy more premium accessories within two months, whereas customers who buy blue bicycles on their first purchase rarely buy again in the next 12 months. We want to make sure that the platform automation has some understanding to help direct it toward consumers who show a higher Predicted Customer Lifetime Value (pCLV).
But, how does an advertiser help convey all of these signals into the ad platforms?
ENTER, ADLUCENT INDEX™
Adlucent Index™ is Adlucent’s proprietary technology that is integrated directly into platform automation tools (including Facebook Conversion API, Google Search, Smart Shopping, and Performance Max automation) to customize the value of each transaction – in real time – in order to better guide automation tools to find the right customers and transactions for your business.
Before, managing keyword bids and modifying bids based on different signals was considered the best-practice approach to optimize platform targeting and performance. Now, we optimize real-time bidding algorithms after a conversion takes place, by scoring or weighting that conversion based on data points derived from business objectives and 1st party data.
With Adlucent Index™, we’re able to bring those data points together into platform automation like Google’s Smart Shopping or tROAS to include those factors dynamically, along with the targeting factors that platform automation uses to evaluate the next right customer.
Adlucent Index™ is the only tool that combines platform-level data about a consumer (e.g.: non-client interaction behavior across Google) with client-level data (e.g.: product, pCLV, merchant insights, etc.). Adlucent Index™ also integrates proprietary category-level insights from our own Deep Search™ platform (e.g.: product price landscape, industry shopping trends, etc.) to refine targeting to capture not just more sales but sales from the right kinds of customers for your business.
And, as always for our retail customers, we know that the customers acquired during the ever-changing holiday season, or during key sales tentpoles, may or may not be different than the core customers you drive throughout the whole year. We tailor the Adlucent Index™ weights and inputs factoring in these sales periods and key holiday drive times.
So while the Adlucent Index™ allows us to tailor conversion values based on latent consumer information for each order, there are other tactics and strategies available to get more from the leading Google Platform Automation features like tROAS and Smart Shopping. The third part of our Ad AI series comes out next; we’ll provide ideas you can implement today to drive better results from these campaign types.
Ryan is VP of Strategy at Adlucent. He has over 15 years experience working with digital and multi-channel marketers to drive better results from their programs. His perspectives of online marketing are based on analyzing data-driven insights from an array of advertisers - from enterprise to start ups - as they capitalized on customer-centric, full-funnel programs across search, social, shopping and digital media.
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