Restaurant.com’s Data-Centric Strategy Drives Conversion Lift

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RestaurantEditSince its inception in 1999, Restaurant.com has helped customers save $1 billion by offering more than 50,000 gift certificate options at dining destinations across the country. Its premise is simple – help diners and restaurants discover one another, and encourage loyalty to local merchants by brokering savings through discounts.

Restaurant.com also acts as a stand-in website for smaller merchants that don’t necessarily have the resources to host their own. By tapping into Restaurant.com’s services, restaurants gain access to a marketing net that spans SEO, paid search, social, SMS and mobile campaigns.

It was vital for Restaurant.com to have workable data on site visitors and deeper insight into their search patterns. “It was all hypothesis-driven, but we lacked a way to get results,” Sarah Nelson, Restaurant.com’s VP of customer acquisition, told AdExchanger. As one example, Restaurant.com’s marketing team “wanted to test adjusting the search cues we use on our homepage that instruct users how to find restaurants that they want to dine at.”

The team had a couple of different ideas, which crossed the chasm from the more “formal,” e.g. “enter a city and state or a restaurant name here,” to the casual, such as prompting site visitors to answer, “What would you like to eat?” or “What are you in the mood for?”

Using Adobe Analytics and Adobe Target, both part of the Marketing Cloud, Restaurant.com was able to test and optimize its search experience, and ultimately uncover the fact that “casual messaging was a big winner for us.” Initially, the company saw an 11% lift in revenue by simple optimization of search cues.

From a paid-media perspective, Nelson says the Adobe Analytics product lets the team look at and dig deeper into display-ad or paid-search results, which “allows us to drill even further into that data down to a segment level” to better understand how people are interacting with the site and how Restaurant.com can properly alter and influence the “copy and display messaging we have out there.”

Even before Restaurant.com realized an 11% increase in revenue, the results were small but impactful, Nelson said. For instance, teams collaborated much more in their testing and optimization of everything from site graphics to the introduction of an “add-to-cart” capability on restaurant detail pages, which yielded a 5% uptick in conversions.

Over the next few months, Restaurant.com has plans to roll out Adobe’s Recommendations engine, which can also be used to help advertisers surface targeted ads, and to present personalized restaurant recommendations to site visitors.

“Restaurant.com is an example of a company that uses these insights to think about, ‘How do we automate the experience?’ whether it’s a landing page that you get when you search for a Thai restaurant in Palo Alto and it brings you to the Restaurant.com home page, or, it’s very specific to the experience you have as a loyal customer who is already using the Restaurant.com app on a smartphone,” Kevin Lindsay, Adobe’s director of conversion product marketing, told AdExchanger. “You have to know who they are and what they’ve done in the past and what bookings they’ve made” in order to tailor ads and product recommendations.

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