Hilton Worldwide, a global leader in the hospitality industry, is comprised of more than 4,600 properties in 93 countries across six continents. For the last four years, it has partnered with iProspect on digital marketing, including the brand’s expansive and complex paid search initiatives. Through the combined efforts of this innovative team, Hilton Worldwide has seen consistent improvements in process and performance despite the maturity of the program, which has already benefited from 4 years of strategic and operational optimization.
In 2015, Hilton Worldwide challenged iProspect and its partner Kenshoo to develop and execute a plan that would either:
The ultimate goal of this experiment was to maximize revenue holistically across all 4,600 properties and their respective markets without sacrificing efficiency–under or overspending–or compromising the team’s ability to effectively pace shifting budget over defined spend cycles.
The combined team arrived at these goals as the natural progression of the work they’ve been doing together over the past few years under Hilton Worldwide’s EDGE model. A holistic approach to budget allocation, the EDGE model is based on applying a single budget to an aggregate of all Hilton Worldwide’s properties, markets, and branded vs. non-branded search efforts.
In order to achieve the established objectives, the team needed to be able to optimize multiple accounts against a single goal via a unified policy. They needed a process that would ultimately assess and rank the performance of more than 300 account profiles representing various combinations of property/market/branded vs. non-branded attributes, and then – based on the applied policy, and according to the EDGE strategy – efficiently and accurately handle spend and bid optimization across the entire spectrum of profiles in a holistic manner.
Over a series of meetings with their combined strategy and tech teams, iProspect and Kenshoo determined that they could develop a solution that met the requirements of the campaign.
In order to maximize insights, the team decided to run tandem tests on two sets of profiles: one test group would consist of profiles that had previously been managed via Kenshoo Portfolio Optimizer (KPO) bid policies, and the second test group would be made up of profiles that had not yet been managed under any policy. Because they drive the highest traffic and have the most consistent budgets, profiles in both groups would be associated with branded keywords.
Kenshoo, meanwhile, worked to evolve its budgeting and forecasting technology, Halogen, to enable this new way of managing multiple profiles against a single goal; the result was an innovative product known as Cross-Profile Halogen. In addition to the already-robust features of Kenshoo’s existing KPO, the new Cross-Profile Halogen solution provided an aggregate forecasting function that uses performance data to project the effect of increasing or decreasing spend across multiple profiles. Kenshoo Halogen also allowed campaign managers to adjust budget caps on the fly, and because it enables management across multiple profiles, saved hours of time that would otherwise have been spent manually optimizing individual profiles.
After the one-month test period was over, it was clear that the team was onto something.
The best results were for the test group of profiles that had previously been individually managed under a regular KPO policy. For this group, the team saw a 9% increase in ROI driven by a 5% increase in revenue and a 4% decrease in costs. The results for the other test group – profiles that had not yet been managed via an individual policy – were also positive.
In addition to meeting the primary ROI, revenue, and spend goals, this campaign also increased efficiency by greatly reducing the amount of time spent inspecting profiles (previously approximated at 4 hours each day based on inspecting 50 profiles at 5 minutes each). Also, the aggregated forecasting available via Halogen made it much easier for the team to identify patterns and trends across multiple profiles, thus improving overall stability through more accurate predictions that helped the team keep spend steady and hit their budgets.
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