Table of Contents
Executive Summary
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- Market drivers
- Competitive context
- Offerings
- Marketing
- Ordering method
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- Figure 1: Ordering methods at restaurants, January 2014
- Technology drivers
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- Figure 2: Technology drivers at restaurants, January 2014
- Preferred deals
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- Figure 3: Deal preferences at restaurants, January 2014
- Technology behaviors
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- Figure 4: Technology behaviors at restaurants, January 2014
- What we think
Issues and Insights
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- Marketing and feedback: How to reach consumers most effectively
- The issues
- The implications
- Loyalty programs: How can operators encourage repeat business?
- The issues
- The implications
- Ordering and payment: Will tech be an effective way to gain efficiencies?
- The issues
- The implications
- In-store technology: How to encourage consumers to dine-in?
- The issues
- The implications
Trend Application
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- Trend: Influential
- Trend: Secret, Secret
- Mintel futures: East Meets West
Market Drivers
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- Foodservice and drinking place sales have inched upward
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- Figure 5: Adjusted foodservice and drinking place sales, January 2010-December 2013
- Restaurant Performance Index lingers around the 100 mark
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- Figure 6: Restaurant Performance Index, January 2010-December 2013
- Economic indicators
- Cost and inflation of food items
- Corporate responsibility
- Healthy diet and active lifestyle
- Governmental legislation
- Gluten free and allergens
- Millennials drive usage
Innovations and Innovators – Mobile Applications
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- Ordering
- Payment
- Reviews
- Feedback
- Integrated apps
Innovations and Innovators – Loyalty Programs
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- Third-party programs
- Restaurant apps
- Loyalty programs based on dollar spend:
- Restaurant non-app programs
Innovations and Innovators – In-store Experience
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- Reservations and waiting
- In-store experience
- In-store ordering
- Interactive activities
- Technological toys
Innovations and Innovators – Back-of-House Tools
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- Inventory
- Menuing
- Marketing
- Customer relations
- Training
- Miscellaneous
Competitive Context
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- Vending machines
- Food trucks
- Kiosks
- Catering & delivery
- Convenience stores
Featured Companies
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- Vapiano
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- Figure 7: Vapiano, February 2014
- Twisted Root Burger Co.
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- Figure 8: Twisted Root Burger Co., February 2014
- Farmer’s Fridge
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- Figure 9: Farmer’s Fridge, February 2014
Marketing Strategies
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- Overview of the brand landscape
- Vine
- Social media
- Endorsements and cobranding
- Sweepstakes and contests
- Crowdsourcing marketing
- Crowdsourcing decisions
- Video games
- Games
- Push marketing
- Out of home
- Causes and charity
Social Media – Technology Use in Restaurants
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- Key points
- Market overview
- Key social media metrics
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- Figure 10: Key social media metrics, February 2014
- Brand usage and awareness
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- Figure 11: Brand usage and awareness for selected restaurants, January 2014
- Interactions with restaurants
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- Figure 12: Interaction with selected restaurants, January 2014
- Key online campaigns
- Mobile and social payments
- Location-based applications driving foot traffic
- Using social media for product launches and fan involvement
- What we think
- Online conversations
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- Figure 13: Online mentions of technology use in selected restaurants, by month, March 1, 2013-February 28, 2014
- Where are people talking about restaurants?
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- Figure 14: Online mentions of technology use in selected restaurants, by page type, March 1, 2013-February 28, 2014
- What are people talking about?
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- Figure 15: Mentions by topic of conversations, technology use in selected restaurants, by month, March 1, 2013-February 28, 2014
Consumer Data – Overview
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- Restaurant usage
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- Figure 16: Usage of restaurants, by dayparts, January 2014
- Ordering method
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- Figure 17: Usage of restaurants (column nets), by dayparts, January 2014
- Changes in behavior around technology usage at restaurants
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- Figure 18: Changes in tech usage at restaurants, January 2014
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- Figure 19: Changes in tech usage at restaurants, by dayparts, January 2014
- Technology behavior at restaurants
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- Figure 20: Technology behavior at restaurants, by dayparts, January 2014
- Deals preferences at restaurants
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- Figure 21: Deal preferences at restaurants, by dayparts, January 2014
- Technology drivers influencing consumers
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- Figure 22: Technology drivers at restaurants, by dayparts, January 2014
- Attitudes of consumers that use ethnic limited-service restaurants
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- Figure 23: Agreement with consumer attitudes toward technology in restaurants, by dayparts, January 2014
Consumer Data – By Gender
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- Key points
- Men value the in-store entertainment and like online brand interactions
- Women use coupons and are enticed by loyalty programs
- Consumer tables by gender
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- Figure 24: Usage of restaurants, by gender, January 2014
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- Figure 25: Usage of restaurants (column nets), by gender, January 2014
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- Figure 26: Changes in tech usage at restaurants, by gender, January 2014
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- Figure 27: Technology behavior at restaurants, by gender, January 2014
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- Figure 28: Deal preferences at restaurants, by gender, January 2014
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- Figure 29: Technology drivers at restaurants, by gender, January 2014
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- Figure 30: Agreement with consumer attitudes toward technology in restaurants, by gender, January 2014
Consumer Data – By Generation
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- Key points
- Younger Millennials seek customization, deals, and technology
- Older Millennials like tech but are hesitant; interested in health
- Older consumers prefer a more traditional dining experience, sans tech
- Consumer tables by generation
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- Figure 31: Usage of restaurants, by generations, January 2014
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- Figure 32: Usage of restaurants (column nets), by generations, January 2014
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- Figure 33: Changes in tech usage at restaurants, by generations, January 2014
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- Figure 34: Technology behavior at restaurants, by generations, January 2014
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- Figure 35: Deal preferences at restaurants, by generations, January 2014
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- Figure 36: Technology drivers at restaurants, by generations, January 2014
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- Figure 37: Agreement with consumer attitudes toward technology in restaurants, by generations, January 2014
Consumer Data – By Income
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- Key points
- Lower-income consumers are apathetic to tech and seek single-use deals
- Middle-income consumers well-suited for online and mobile functionalities
- The affluent find in-store technologies disruptive to the dining experience
- Consumer tables by income
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- Figure 38: Usage of restaurants, by household income, January 2014
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- Figure 39: Usage of restaurants (column nets), by household income, January 2014
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- Figure 40: Changes in tech usage at restaurants, by household income, January 2014
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- Figure 41: Technology behavior at restaurants, by household income, January 2014
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- Figure 42: Deal preferences at restaurants, by household income, January 2014
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- Figure 43: Technology drivers at restaurants, by household income, January 2014
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- Figure 44: Agreement with consumer attitudes toward technology in restaurants, by household income, January 2014
Consumer Data – By Race and Hispanic Origin
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- Key points
- Whites seek traditional dining experiences, brand interactions, and deals
- Blacks are less likely to use dine-in but are enticed by in-store technology
- Asians are tech-savvy but are hesitant to adopt mobile loyalty programs
- Hispanics like in-store technology
- Consumer tables by race and Hispanic origin
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- Figure 45: Usage of restaurants, by race/Hispanic origin, January 2014
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- Figure 46: Usage of restaurants (column nets), by race/Hispanic origin, January 2014
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- Figure 47: Changes in tech usage at restaurants, by race/Hispanic origin, January 2014
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- Figure 48: Technology behavior at restaurants, by race/Hispanic origin, January 2014
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- Figure 49: Deal preferences at restaurants, by race/Hispanic origin, January 2014
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- Figure 50: Technology drivers at restaurants, by race/Hispanic origin, January 2014
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- Figure 51: Agreement with consumer attitudes toward technology in restaurants, by race/Hispanic origin, January 2014
Consumer Data – By Region
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- Key points
- Midwesterners are likely open to online or mobile loyalty programs
- Northeasterners visit full-service restaurants, particularly fine dining
- Southerners are enticed by Wi-Fi and post visits on their social media page
- Westerners are more likely to visit limited-service ethnic restaurants
- Consumer tables by region
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- Figure 52: Usage of restaurants, by region, January 2014
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- Figure 53: Usage of restaurants (column nets), by region, January 2014
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- Figure 54: Changes in tech usage at restaurants, by region, January 2014
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- Figure 55: Technology behavior at restaurants, by region, January 2014
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- Figure 56: Deal preferences at restaurants, by region, January 2014
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- Figure 57: Technology drivers at restaurants, by region, January 2014
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- Figure 58: Agreement with consumer attitudes toward technology in restaurants, by region, January 2014
Consumer Data – By Parents
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- Key points
- Parents look for in-store tech, online brand chatter, and loyalty programs
- Parents with toddlers seek in-store technology and better-for-you options
- Parents with children enjoy online interaction and in-store entertainment
- Parents with teenagers visit restaurants with at-table tablets for payment
- Parents with adult children have traditional, established dining behavior
- Consumer tables by parents
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- Figure 59: Usage of restaurants, by parents with children in household, January 2014
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- Figure 60: Usage of restaurants (column nets), by parents with children in household, January 2014
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- Figure 61: Changes in tech usage at restaurants, by parent/guardian living in household, January 2014
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- Figure 62: Technology behavior at restaurants, by parent/guardian living in household, January 2014
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- Figure 63: Deal preferences at restaurants, parent/guardian living in household, January 2014
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- Figure 64: Technology drivers at restaurants, by parent/guardian living in household, January 2014
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- Figure 65: Agreement with consumer attitudes toward technology in restaurants, by demographics, January 2014
Appendix – Additional Tables
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- Consumer tables by segment
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- Figure 66: Usage of restaurants, by segments, January 2014
- Figure 67: Usage of restaurants (column nets), by segments, January 2014
- Figure 68: Changes in tech usage at restaurants, by segments, January 2014
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- Figure 69: Technology behavior at restaurants, by segments, January 2014
- Figure 70: Deal preferences at restaurants, by segments, January 2014
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- Figure 71: Technology drivers at restaurants, by segments, January 2014
- Figure 72: Agreement with consumer attitudes toward technology in restaurants, by segments, January 2014
- Consumer tables by limited-service concept
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- Figure 73: Usage of restaurants, by LSR, January 2014
- Figure 74: Usage of restaurants (column nets), by LSR, January 2014
- Figure 75: Changes in tech usage at restaurants, by LSR, January 2014
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- Figure 76: Technology behavior at restaurants, by LSR, January 2014
- Figure 77: Deal preferences at restaurants, by LSR, January 2014
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- Figure 78: Technology drivers at restaurants, by LSR, January 2014
- Figure 79: Agreement with consumer attitudes toward technology in restaurants, by LSR, January 2014
- Consumer tables by full-service concept
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- Figure 80: Usage of restaurants, by FSR, January 2014
- Figure 81: Usage of restaurants (column nets), by FSR, January 2014
- Figure 82: Changes in tech usage at restaurants, by FSR, January 2014
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- Figure 83: Technology behavior at restaurants, by FSR, January 2014
- Figure 84: Deal preferences at restaurants, by FSR, January 2014
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- Figure 85: Technology drivers at restaurants, by FSR, January 2014
- Figure 86: Agreement with consumer attitudes toward technology in restaurants, by FSR, January 2014
Appendix – Market Drivers
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- Health and lifestyle
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- Figure 87: American adults by weight category as determined by body mass index (BMI), 2008-Oct. 28, 2013
- Childhood and teen obesity – highest in decades
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- Figure 88: Prevalence of obesity among children and adolescents aged 2-19, 1971-2010
- Consumer confidence
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- Figure 89: University of Michigan’s index of consumer sentiment (ICS), 2007-14
- Unemployment
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- Figure 90: US Unemployment Rate, by month, 2002-14
- Figure 91: US unemployment and underemployment rates, 2007-14
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- Figure 92: Number of employed civilians in US 2007-14
- Retail channels
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- Figure 93: Distribution of expenditures on food for off-premise consumption, by channel, 1993-2012
- Racial, ethnic population growth
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- Figure 94: US population by race and Hispanic origin, 2009, 2014, and 2019
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- Figure 95: Households with children, by race and Hispanic origin of householder, 2013
- Shifting US demographics
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- Figure 96: US population, by age, 2009, 2014, and 2019
- Figure 97: US households, by presence of own children, 2003-13
Appendix – Social Media
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- Key social media metrics
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- Figure 98: social media metrics—Starbucks, February 2014
- Figure 99: Social media metrics—Domino’s, February 2014
- Figure 100: Social media metrics—Taco Bell, February 2014
- Figure 101: Social media metrics—Applebee’s, February 2014
- Figure 102: Social media metrics—Pinkberry, February 2014
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- Figure 103: Social media metrics—Fazoli’s, February 2014
- Online conversations
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- Figure 104: Online mentions of technology use in selected restaurants, by month, March 1, 2013-February 28, 2014
- Figure 105: Online mentions of technology use in selected restaurants, by page type, March 1, 2013-February 28, 2014
- Figure 106: Mentions by topic of conversations, technology use in selected restaurants, by month, March 1, 2013-February 28, 2014
- Brand usage or awareness
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- Figure 107: Brand usage or awareness, January 2014
- Figure 108: Domino’s Pizza usage or awareness, by demographics, January 2014
- Figure 109: Starbucks usage or awareness, by demographics, January 2014
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- Figure 110: Taco Bell usage or awareness, by demographics, January 2014
- Figure 111: Fazoli’s usage or awareness, by demographics, January 2014
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- Figure 112: Pinkberry usage or awareness, by demographics, January 2014
- Figure 113: Applebee’s usage or awareness, by demographics, January 2014
- Activities done
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- Figure 114: Activities done, January 2014
- Figure 115: Domino’s Pizza – Activities done – I have looked up/talked about this brand online on social media, by demographics, January 2014
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- Figure 116: Domino’s Pizza – Activities done – I have contacted/interacted with the brand online on social media to, by demographics, January 2014
- Figure 117: Domino’s Pizza – Activities done – I follow/like the brand on social media because, by demographics, January 2014
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- Figure 118: Domino’s Pizza – Activities done – I have researched the brand on social media to, by demographics, January 2014
- Figure 119: Starbucks – Activities done – I have looked up/talked about this brand online on social media, by demographics, January 2014
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- Figure 120: Starbucks – Activities done – I have contacted/interacted with the brand online on social media to, by demographics, January 2014
- Figure 121: Starbucks – Activities done – I follow/like the brand on social media because, by demographics, January 2014
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- Figure 122: Starbucks – Activities done – I have researched the brand on social media to, by demographics, January 2014
- Figure 123: Taco Bell – Activities done – I have looked up/talked about this brand online on social media, by demographics, January 2014
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- Figure 124: Taco Bell – Activities done – I have contacted/interacted with the brand online on social media to, by demographics, January 2014
- Figure 125: Taco Bell – Activities done – I follow/like the brand on social media because, by demographics, January 2014
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- Figure 126: Taco Bell – Activities done – I have researched the brand on social media to, by demographics, January 2014
- Figure 127: Fazoli’s – Activities done – I have researched the brand on social media to, by demographics, January 2014
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- Figure 128: Applebee’s – Activities done – I have looked up/talked about this brand online on social media, by demographics, January 2014
- Figure 129: Applebee’s – Activities done – I have contacted/interacted with the brand online on social media to, by demographics, January 2014
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- Figure 130: Applebee’s – Activities done – I follow/like the brand on social media because, by demographics, January 2014
- Figure 131: Applebee’s – Activities done – I have researched the brand on social media to, by demographics, January 2014
Appendix – Trade Associations
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