{"id":1797,"date":"2018-10-24T10:56:23","date_gmt":"2018-10-24T10:56:23","guid":{"rendered":"http:\/\/bisk-preprod.go-vip.co\/msu\/?p=1797"},"modified":"2020-02-20T13:33:49","modified_gmt":"2020-02-20T13:33:49","slug":"dining-on-big-data","status":"publish","type":"post","link":"https:\/\/bisk-preprod.go-vip.co\/msu\/resources\/business-analytics\/dining-on-big-data\/","title":{"rendered":"Dining on Big Data: How Analytics is Reshaping the Restaurant Industry"},"content":{"rendered":"

Big Data is changing the way the restaurant industry works and thrives. In its report on the top \u201cbusiness-shaping forces\u201d for 2018,\u00a0Restaurant Business Online<\/a>\u00a0put the implementation of Big Data at number four, stating, \u201cData drives everything.\u201d<\/p>\n

From personalized marketing and menus\u00a0to smart kitchen tech, to deep demographic dives, analyzing and implementing strategies based on Big Data is now the standard of the restaurant industry. New independents and emerging chains are using their tech-savvy and agile size to become competitive, while familiar legacy brands are going all-in on data-driven analytics to maintain market share and grow new customers.<\/p>\n

Gathering and Using Big Data<\/h2>\n

Restaurants are integrating new technologies to record and utilize data to improve their efficiency and the dining experience. For many, that starts with how a customer orders and pays for their meal. Restaurants are using a greater assortment of digital tools, such as kiosks, mobile apps,\u00a0and table-side tablets. Besides offering a more convenient ordering and payment process, these devices can offer greater customization and personalization by mining data from customer order history. Through\u00a0qualitative analytics<\/a>, restaurants can create datasets of customer purchasing profiles.<\/p>\n

\u201cOnce you know that people who buy \u2018A\u2019 also like item \u2018B,\u2019 you’re getting a lot of insight from the consumer on not only a promotional standpoint but also on a bundling standpoint and that information can help you adjust your menu,\u201d says\u00a0Mike Lukianoff, Chief Analytics Officer at Fishbowl Marketing Analytics<\/a>.<\/p>\n

Data-gathering sensors placed strategically throughout a restaurant can track how guests and employees use the space, creating an opportunity to improve a restaurant\u2019s overall efficiency concerning wait times and traffic flow. Cava, a chain of Mediterranean-style restaurants currently in nine states and the District of Columbia,\u00a0mined customer-flow data\u00a0from sensors placed along its queues to improve the ordering process and the guest experience.<\/p>\n

The Internet of Things means more appliances and kitchen tools are also connected, data-gathering tools. This smart kitchen tech can monitor inventory and food preparation for improved efficiency and order accuracy.<\/p>\n

With these multiple sources of data, it\u2019s becoming more crucial for restaurants to integrate their systems for effective data warehousing. Some ways to go about this include implementing agile and adaptable data models that work for data analysts, standardizing data preparation so the data is ready for analysis, and facilitating seamless data acquisition from those various gathering points. Then, restaurants should enrich that source data by applying predictive models and\u00a0relevant metrics<\/a>, such as historical sales trends, the number of new versus returning guests and the frequency a menu item is ordered, to achieve enhanced business intelligence for competitive advantages.<\/p>\n

Data and Demographics<\/h2>\n

While the efficient mining of Big Data may provide a competitive edge, the industry\u2019s embrace of data and customer personalization is mainly driven by customer expectations, especially Millennials.<\/p>\n

A 2017\u00a0U.S. Department of Agriculture report<\/a>\u00a0showed that compared to other generational age groups, Millennials eat the highest share of their meals out at fast-food or fast-casual establishments, get prepared food to go or use a delivery service. When it comes to the food they\u2019re eating, Millennials prefer fresh, natural, organic and even locally sourced offerings on the menu. Restaurants have rushed to appeal to this demographic by overhauling menus, re-designing dining spaces to be social media friendly and adding the convenience of app-based reservation and delivery systems.<\/p>\n

Applebee\u2019s, a stalwart of the casual dining segment, chased these trends only to miss the mark. After a retooled menu of trendy items failed to attract Millennials, Applebee\u2019s stock prices decreased by 50% and forced the closure of 99 restaurants in 2017, with\u00a0Applebee\u2019s president John Cywinski<\/a>\u00a0declaring that the pursuit of a \u201cmore youthful and affluent demographic\u201d had caused Applebee\u2019s to \u201cintentionally drift from\u2026its Middle America roots. While we certainly hope to extend our reach, we can\u2019t alienate Boomers and Gen-Xers in the process.\u201d<\/p>\n

At a February 2018\u00a0Investor Day presentation<\/a>\u00a0by Dine Brands Global, Inc., the parent company of Applebee\u2019s, Cywinski reiterated the brand is \u201cgetting back to our roots\u201d with \u201cfamiliar, indulgent favorites,\u201d while Dine Brands CEO Stephen Joyce highlighted investment in \u201cnew technology to enable future growth\u201d through greater guest access, new platforms and \u201cgreater emphasis on data and advanced analytics\u201d to make the brand \u201cguest-led and insight-driven.\u201d<\/p>\n

Data is the first \u201cD\u201d in what\u00a0Adrian Butler, Dine Brands SVP & Chief Information Officer<\/a>, outlined as the company\u2019s \u201c4D technology strategy\u201d of \u201cData, Discovery, Dining, Delivery.\u201d The focus is on \u201cleveraging data and analytics of our guests and operations to craft personalized experiences. We\u2019re aggregating data about our guests that can be used to provide better offers and services,\u201d with the end goal being a personalized one-to-one marketing and dining experience.<\/p>\n

\u201cPersonal tastes when it comes to food is very unique. There\u2019s nothing generic about what you order off a menu and how you want to order it,\u201d says Dine Brands CFO Thomas H. Song, who echoed the Applebee\u2019s commitment to data-based menu, marketing and ordering decisions in his presentation at\u00a0CL King & Associates Best Ideas Conference 2018<\/a>: \u201cWe\u2019ve had a significant shift in mindshare towards technology over the course of the last 18 months. On the IT side, we\u2019ve invested significantly in our data warehouse capabilities to provide a lot of that information to the consumer insights folks.\u201d<\/p>\n

Those insights are being gathered via a variety of touchpoints. Over\u00a05.7 million Applebee\u2019s customers<\/a>\u00a0provided feedback via tabletop device surveys, showing a 7% improvement in overall guest satisfaction by the end of 2017. The relaunch of Applebee\u2019s To-Go doubled from 9% to 18% of revenue in 2017 and was optimized with the improved Applebee\u2019s app spearheading the brand\u2019s mobile-first strategy.<\/p>\n

By leveraging data-driven insights, Applebee\u2019s has been able to cut through the (mis)perceptions and stereotypes to aggregate customer demographic data, revealing that generationally, Applebee\u2019s diners are pretty evenly split: 26.4% Baby Boomers, 28.3% Generation X, and 29.9% Millennial. When Generation Z guests are considered, 45% of Applebee\u2019s guests are 34 or younger, according to their\u00a0\u00a0Investor Day presentation<\/a>.<\/p>\n

While Applebee\u2019s may have mis-stepped on the attempted Millennial-driven menu, the brand is betting on the analytics and the technology-driven experiences and conveniences these young digital natives expect for continued growth.<\/p>\n

Providing Food for Thought<\/h2>\n

Gathering Big Data is an important step, but effectively interpreting and putting that data into action is the key to success in understanding and meeting diners\u2019 expectations. The\u00a0business analytics professionals<\/a>\u00a0who capture, structure, interpret and apply this data can provide restaurants with effective solutions and game-changing strategies, whether that\u2019s a global chain restaurant or the local diner.<\/p>\n","protected":false},"excerpt":{"rendered":"

Big Data is changing the way the restaurant industry works and thrives. In its report on the top \u201cbusiness-shaping forces\u201d for 2018,\u00a0Restaurant Business Online\u00a0put the implementation of Big Data at number four, stating, \u201cData drives everything.\u201d From personalized marketing and menus\u00a0to smart kitchen tech, to deep demographic dives, analyzing and implementing strategies based on Big […]<\/p>\n","protected":false},"author":20,"featured_media":1798,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2},"_wpas_customize_per_network":false},"categories":[11],"tags":[],"class_list":["post-1797","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-business-analytics"],"jetpack_publicize_connections":[],"jetpack_featured_media_url":"https:\/\/bisk-preprod.go-vip.co\/msu\/wp-content\/uploads\/sites\/3\/2018\/11\/restaurant-analytics-data.jpg","jetpack_shortlink":"https:\/\/wp.me\/pa8xwI-sZ","jetpack_sharing_enabled":true,"_links":{"self":[{"href":"https:\/\/bisk-preprod.go-vip.co\/msu\/wp-json\/wp\/v2\/posts\/1797","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/bisk-preprod.go-vip.co\/msu\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/bisk-preprod.go-vip.co\/msu\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/bisk-preprod.go-vip.co\/msu\/wp-json\/wp\/v2\/users\/20"}],"replies":[{"embeddable":true,"href":"https:\/\/bisk-preprod.go-vip.co\/msu\/wp-json\/wp\/v2\/comments?post=1797"}],"version-history":[{"count":4,"href":"https:\/\/bisk-preprod.go-vip.co\/msu\/wp-json\/wp\/v2\/posts\/1797\/revisions"}],"predecessor-version":[{"id":7526,"href":"https:\/\/bisk-preprod.go-vip.co\/msu\/wp-json\/wp\/v2\/posts\/1797\/revisions\/7526"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/bisk-preprod.go-vip.co\/msu\/wp-json\/wp\/v2\/media\/1798"}],"wp:attachment":[{"href":"https:\/\/bisk-preprod.go-vip.co\/msu\/wp-json\/wp\/v2\/media?parent=1797"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/bisk-preprod.go-vip.co\/msu\/wp-json\/wp\/v2\/categories?post=1797"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/bisk-preprod.go-vip.co\/msu\/wp-json\/wp\/v2\/tags?post=1797"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}