OpenTable’s Data Creates Revenue Opportunities

Recently, Priceline purchased OpenTable for a 46% premium!  This may seem high for the restaurant reservation service, but I can see why Priceline would pay $2.6 billion for the company.  The company still has a great opportunity to further expand its reservation and software sales into domestic and international markets, as they have only captured a small portion of these markets.  The purchase also allows for Priceline to provide a dining experience for its traveling customers.  But I am more interested what Matt Roberts, OpenTable’s CEO, said in the 2013 Annual Report “we serve and engage users in new ways that create active, loyal customers for life” and I believe these “new ways” will not only foster a greater customer engagement, but will also drive new revenue opportunities through its data knowledge of its 15 million users.

Data Collection

In order to drive both customer loyalty and new revenue streams, OpenTable will leverage the data it collects on its 15 million users and 31,600 installed customers (restaurants). Before we get into the growth opportunities, let’s first review what data is collected (see OpenTable’s privacy policy) and how it may be used by OpenTable to understand its users and restaurant customers.  The list below is what data OpenTable collects and its uses:

• Name: So, your name may seem simple, but your name can indicate you gender and can provide your general age based on the name’s popularity in a given year.  This enables OpenTable to target marketing email campaigns based on gender and age.
• Email Address: Your email address allows OpenTable to target marketing campaigns to users.  These email campaigns and the links clicked in emails can be tracked to determine the effectiveness of a campaign.
• Zip Code and Street Address: Based on the user’s zip code and street address OpenTable can assume a user’s income level, race, and spending habits by digging through the piles of information collected from U.S. Census Data. 
• Phone Number: With a user’s phone number, OpenTable has the ability to contact the user and can roughly verify the user’s general location from the area code.
• Special Requests: OpenTable provides users with the ability to specify if the user is gluten-free, vegan, etc.. OpenTable can then tailor restaurant recommendations to the user’s request.
• GPS/IP Address: This information allows for geomarketing.
• Credit Card/Debit Card: OpenTable’s payment services can collect the amount spent on the user’s meal and at which restaurant. 
• Reservations from Users: The collection of historical reservations can be used to see what type of food category the user frequents, the price levels of restaurants the user reserves, the user’s favorite city to dine outside of his or her local area (a synergy for Priceline’s travel marketing) and what day and times the user prefers to dine.  Aside from the reservations made, OpenTable collects the search and click history on its applications and the cancellation rates.
• Reservations from Installed Restaurant Customers: The data collected from the restaurants can include the total number of reservations on a night, the peak time for reservations, and the number of reservation no shows by users.   

Customer Engagement and Revenue Opportunities through Data Collection

Now that we know what information OpenTable can access regarding its users and restaurateurs, we have identified further customer engagement opportunities and revenue streams it could engage in because of its data collection.

• Partnerships: By providing information on user demographics to partners like the automaker Kia, OpenTable can provide a unique experience to its users. Last year I participated in “The Cadenza Experience”, which was an invite-only free dinner for two at a Michelin Star Restaurant, a walk down the red carpet, and a test drive of Kia’s new Cadenza sedan.  The offer and the partnership was brilliant! OpenTable provided Kia with a selected group of its users that fit Kia’s target market.  The group represented a certain age group in a defined income bracket that lived in a group of zip codes.  The event benefited Kia by having its target market test drive its new car, allowing it to conduct additional data gathering onsite, and facilitating a follow up survey about the driving experience. The restaurant also benefited from the event, as it had the chance to serve new and existing customers.   The event for Kia must have been somewhat successful as they are embarking upon a second event this summer to introduce its K900 car. OpenTable’s ability to define this group of users shows the power of its data, and I would not be surprised to see more of these types of partnerships in the future. 
• 250 Point Tables: With all of the data OpenTable collects, I would have to believe it reviews predictive analytics on its users and their dining habits.  Through predictive analytics, OpenTable can determine when users usually make reservations, what types of restaurants they frequent, why users make a reservation, and how users click through the applications.  With this information, OpenTable can then overlay additional data sources that impact user behaviors like weather.  The offering will be similar to OpenTable’s 1,000 point tables (1,000 point tables cost the restaurant $7.50 per reservation instead of $1.00 per reservation), but the purpose is to entice users to select one restaurant over its competitor. So let’s say it’s a snowy Tuesday night in Boston at 7:00 pm and there are three pieces of data that indicate the user is choosing between two restaurants.  By adding a customer loyalty element, like a 250 point table, the user’s decision may be swayed with the potential for additional points, which translates to additional revenue for OpenTable by charging its restaurant customers for the points.  
• Restaurant Industry Index: I know OpenTable currently has a Restaurant Index, which tracks year over year reservation data, but can they take this data further by selling aggregated segments of data to stock research and economics firms?  The data OpenTable collects is an indicator of disposable income, which provides insight into the overall health of the economy.  Overlaying the year over year reservation data with restaurant price categories and age range of users, an analyst can determine how much, on average, an age category is spending on a night out.  The more spent on more expensive restaurants at a higher frequency in the age group of 25 to 34 may indicate a stronger economy, as it would show that this group has more disposable income.  If we take this analysis down a different avenue and see that reservations for steakhouses have declined, an analyst may be concerned with a declining demand for beef.  As a result of declining demand, the price of beef in the futures markets may decline, assuming the supply of beef remains constant.  Overall, the opportunity for OpenTable to provide its data to stock research and economics firms could generate a revenue stream without much additional work.
• Restaurant Benchmarking: Now I have no idea if OpenTable provides its installed restaurants the ability to benchmark themselves against other restaurants within their area, class of service, or cuisine, but benchmarking tools can provide a new revenue opportunity.  The process of benchmarking is to compare oneself against one’s peers to determine what needs to improve, analyze how peers are achieving success, and improve performance.  For example, an Italian restaurant is running lower than its peers in reservations booked.  Reviewing the benchmark report, it finds that it is priced too high for its market.  After analyzing its peers’ performance, it also determines its menu size needs to change.  By adjusting the menu to maximize the ingredient usage across each plate, the restaurant is able to reduce inventory cost and waste.  As a result the restaurant can reduce its menu prices and be more competitive in the market.  This type of proactive engagement with OpenTable’s installed customers will foster stronger customer loyalty (by giving the customer valuable insights) and an additional source of revenue.
• Competitive Analysis Tools:  The last of the potential revenue streams is a competitive analysis tool targeted to new restaurateurs.  The tools would provide data like locational market and competition analysis, the likelihood of success by food category, and the disposable income levels of your potential customer base.  For example, a new pizza and craft beer restaurant is deciding whether to open.  Using OpenTable’s competitive analysis tool, the potential restaurateur discovers there are enough OpenTable users in the target age and income demographic and a true demand for a pizza and craft beer restaurant.  With this news, the restaurateur digs deeper into the competitive analysis tool and recognizes that the pizza market is saturated, but it lacks a restaurant that serves a wood stove made pizza.  However, this style of pizza is in demand with like demographics in other geographical locations.  As a result, the pizza restaurant opens with great success after it perfects wood stove oven pizza and offers a diverse craft beer selection.  The tool provided an opportunity to create a niche in the market and helped the owner to avoid opening just another pizza restaurant that serves beer and, potentially, a doomed business venture.

Overall Priceline’s purchase of OpenTable is an opportunity to provide a complete travel package to its customers.  Along the same lines, OpenTable can provide a more complete service to its users, installed restaurant customers and third parties through its data.

If you would like to learn more about developing new opportunities for your business through your data or acquired data, please visit us at www.prosperityanalytics.com.