Can (and Should) Retail/Wi-Fi Analytics Help Retailers Survive in the Age of Amazon?


Published on

This Frost & Sullivan Analyst Briefing introduces an approach that is helping retailers better understand both their customers and their own operations by harvesting analytics from the Wi-Fi that many of them are already providing to shoppers.

- Designed to benefit a wide range of attendees, including:
- Every retail or e-tail organization, and individual retailers of all types and sizes
- Every brand that sells through either the retail or e-tail channels
- Every brand that utilizes mobile technologies for sales and retention activity
- Every company that plays a role, or could, in equipping retailers to better compete

Listen On Demand:

Published in: Technology, Business
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide

Can (and Should) Retail/Wi-Fi Analytics Help Retailers Survive in the Age of Amazon?

  1. 1. The HUMAN BOUNCE RATE: Can (and Should) Retail/Wi-Fi Analytics Help Retailers Survive in the Age of Amazon? JEFF COTRUPE Global Program Director Big Data & Analytics (BDA) Stratecast | Frost & Sullivan
  2. 2. Today’s Presenter Jeff Cotrupe, Global Program Director, Big Data & Analytics Stratecast | Frost & Sullivan Follow me on: Industry Expertise: Big Data, analytics, and business intelligence (BI) incorporating these component areas: - Big Data core: platforms, applications, systems, and services - Online/digital analytics and marketing including site, social, mobile, and video - Customer experience management (CEM): application performance monitoring (APM), customer service assurance (CSA), quality of experience (QoE), and customer experience analytics (CEA), and social network analysis (SNA); key area of focus: Video QoE - Mobile commerce management (MCM), a category Jeff defined that includes mobile marketing, advertising, and commerce infrastructure, ecosystems, and solutions Operations/business support systems (OSS/BSS); Cloud; enterprise IT management 2
  3. 3. Interested Parties Every retail or e-tail organization, and individual retailers Every brand that sells through either the retail or e-tail channels Every brand that utilizes mobile technologies for sales and retention Every company that plays a role, or could, in equipping retailers to better compete with e-tailers (and each other) 3
  4. 4. Retailers Face a Cartful of Challenges Declining incomes Brand switching Brand extension = brand confusion Smartphones make smarter (or at least more elusive) shoppers – Battleground in the Aisles – Groupon, Living Social 4
  5. 5. Battle For Customers: E-tailers Have Big Data Advantage Source: Euclid Analytics 5
  6. 6. Retailers Are Checking Out Retail/Wi-Fi Analytics RWA calculates times, locations, MAC addresses of devices – …with Wi-Fi turned on – …detected within coverage area of a Wi-Fi network By logging MAC address: retailer (or any organization) can identify and track devices RWA applies location and other advanced analytics to the data 6
  7. 7. Source: STRATECAST
  8. 8. RWA Bears a Striking Resemblance to Online Analytics Retail/Wi-Fi Analytics: SHOPPERS How many mobile devices pass by a store, and how many enter? How many total shoppers are in a store, both on average and at specific times? How many visit more than once, and how often do they visit? How much time do they spend per visit, and what do they do? Which purchases occur when a given mobile device passes through a store checkout? Online Analytics: SITE VISITORS How many visitors enter a site, from which referring pages? How much traffic is a Web site receiving? What are its busy and quiet hours? How many unique site visitors? What is their visit frequency? What is their visit duration and level of engagement? How many conversions is the site achieving, with which (and which types of) visitors? Stratecast defines the rate at which customers leave a store, in less time than would make them likely merchandise buyers, as The Human Bounce Rate. 8
  9. 9. 9
  10. 10. Leading RWA Providers, and How They Collect Data PROVIDER METHOD Shoppers have retailer’s mobile app on smartphone Shoppers log into retailer’s Wi-Fi network No action required by shoppers 10
  11. 11. Other Important RWA Providers 11
  12. 12. RWA is Touching Off Privacy Concerns… RWA functions similarly to “cookies” on the Web: it allows commercial interests to instantly access personally identifiable information (PII) about shoppers. By triangulating MAC addresses against point of sale (POS) data, retailers can find out exactly who shoppers are Even if users/shoppers do remain anonymous, as RWA providers and other advocates claim… – RWA can help retailers develop extremely detailed profiles about shoppers – This can support highly intrusive marketing behavior 12
  13. 13. …and Action by Government and Watchdog Groups Future of Privacy Forum (FPF) – Think tank led by Internet privacy experts Jules Polonetsky and Christopher Wolf – Seeks to advance responsible data practices Wireless Registry – Do Not Call Registry in the U.S.: telemarketing – Wireless Registry: RWA. (Protect consumers from retailers tracking/using personal and behavioral data) Mobile Location Analytics Code of Conduct – Sets industry-wide standard for protecting privacy re: mobile device data – Defines rules of engagement for retailers/providers – Key contributors: FPF, U.S. Congress (Sen. Chuck Schumer), RWA providers Some providers getting ahead of the curve: opt-outs, in-store notices 13
  14. 14. Stratecast: THE LAST WORD Retailers and RWA providers: respect shoppers; respect PII HOWEVER… Focusing privacy concerns solely on bricks-and-mortar retailers is naïve: every move consumers make on an e-tailer’s site is tracked/analyzed/leveraged for some commercial purpose Proven for 100 years: consumers more than willing to be inconvenienced or give away private info in exchange for value – Put up with commercials in exchange for entertainment: radio-TV-cinema-video – Any consumer who has ever submitted personal information on a Web site, or filled out a card for a raffle Retailers may do a better job serving customers if they can collect and crunch Big Data to figure out what customers want Retailers should turn a negative into a positive: – Build RWA into promotional strategies – Shoppers who do not opt out of monitoring for RWA purposes get access to DEALS and CONTENT no one else receives 14
  15. 15. Next Steps Develop Your Visionary and Innovative Skills Growth Partnership Service Share your growth thought leadership and ideas or join our GIL Global Community Join our GIL Community Newsletter Keep abreast of innovative growth opportunities Phone: 1-877-GOFROST (463-7678) Email: 15
  16. 16. Your Feedback is Important to Us What would you like to see from Frost & Sullivan? Growth Forecasts? Competitive Structure? Emerging Trends? Strategic Recommendations? Other? Please inform us by “Rating” this presentation. 16
  17. 17. Follow Frost & Sullivan on Facebook, LinkedIn, SlideShare, and Twitter 17
  18. 18. For Additional Information Britni Myers Corporate Communications Information & Communication Technologies (210) 477-8481 Jeff Cotrupe Global Program Director Big Data & Analytics (BDA) Stratecast (760) 643-0921 Perry Somers Sales Manager Stratecast (360) 416-4982 18