CLV Case Study
Google won the bid management war. Now retailers can take the spoils with CLV-based advertising
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Still using third-party bidding tools to optimize paid search campaigns?
You’re missing out on massive growth opportunities. Not only will a shift to Google Smart Bidding increase your ROAS-based campaign’s efficiency, but adding a data-activated approach means you can refocus your efforts towards margin and CLV.
About the retailer
02 The Challenge
Evolving from third-party bidding tools while improving effectiveness
Retailer X felt its paid search strategy had room to improve. Even as a mature, well-penetrated market leader, it knew there was new customer growth to be found. And even more so, it felt that its current efficiency-based KPI set was stopping it from exploring new areas of opportunity.
The retailer asked Crealytics to test both its existing assumptions on third-party bidding tools and uncover a more robust, longer term, KPI foundation.
From a technical perspective, it had long used third-party tools for campaign automation and bid management. While these tools use the available data to do an adequate job of calculating bid values, they don’t have access to the same set of signals that Google represents.
But while Smart Bidding might have solved for additional efficiency, it doesn’t answer the question of customer quality. The retailer knew it needed to acquire new, high quality, loyal, customers.
So from a strategic perspective, the retailer needed to go beyond better bid precision. In fact, it needed to shift its KPI rationale completely – moving away from transactional, efficiency-based metrics to a more customer-oriented bidding model.
A solution to this challenge required the best of both worlds. The retailer needed to combine Google Smart Bidding’s efficiency with more relevant, enterprise-friendly KPIs: margins, new customers and Customer Lifetime Value.
03 The approach
Overlaying Smart Bidding with data activation
CLV shines in its ability to go beyond real-time profits. Unlike efficiency-only metrics such as ROAS, it considers data points like profitability and transaction margin: KPIs crucial to long-term business health. And by combining transactional-level new customer values with the predicted value of secondary and tertiary transactions, it yields value in current and future transactions.
Key to the retailer’s success would be the ability to adapt Google Smart Bidding to take advantage of this predictive CLV. By providing the system with data inputs that reflected the eventual impact of each customer, we’d be able to teach the system which customer represented a potential new loyal shopper, and which represented a lower valued buyer.
From there we let the algorithms do their work. Our data-activated approach encouraged optimal budget distribution: assigning higher bids to products that generated higher new customer rates, higher future profits, and higher CLV.
04 The Results
New customers up 59%, margins rise by 34%, and more...
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