Top 5 Trends in Retail Data Analytics
ShiSh (twitter: @5h15h)Retail Industry Solutions DirectorMicrosoft Corp
My insights from NRF 2017
Modern retail is data driven
Location sales Remote sales
Try on and try out productsFace-to-face info
In-store behavior
Social connection/user reviews
Product/price comparisonOnline history
Digital transformation enables the best of online &
offline
Top 5 Takeaways for Retail Data AnalyticsPersonalizationArtificial IntelligenceBlockchain in Retail Autonomous Retail Stores/Frictionless ShoppingIot
Sam Quinn, 27TRAVEL BLOGGERLAST VISIT: DEC 21
You’ve
been
on th
e mov
e!
Hiking
boots
on
sale t
his w
eek
Selina Stuart, 17HIGH SCHOOLERLAST VISIT: APR 16
Diana Jones, 16HIGH SCHOOLERLAST VISIT: APR 23 WELCOME Still looking
for a prom dress?Talk to an associate to see the items from your wish list!
BROWSE
Retail Personalization001
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Weather
Auto-generated Offers
LocalEvents
Time ofDay
RecognitionSoftware
CustomerProfile
POSData
Digital Footprint Audience Wearables
Wish list Hiking boots sale
Grab and go
Marketing Objective
More Frequent visits
Increased SalesHigher Foot TrafficLocation
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Sarah Calvert, 36WORKING MOMLAST VISIT: MAR 3
ContosoEyewear
Connect with customers at the right time, right place with the right offers• Generate relevant and
targeted offers using integrated data sources
• Deliver timely offers based on customer location and time of day
Predict what customers want before they tell you• Anticipate customer
purchases based on profiles, needs and significant events
• Create natural cross-sell and upsell opportunities using predictive analytics solutions
Ensure transaction continuity
• Strengthen next best action engine by using outcomes of every customer decision
• Improve offer uptake with better propensity algorithms
• Prevent duplicate offers across channels
Boost customer loyaltyand profitability• Keep customers engaged
and delighted with personalized, event-based offers
• Deliver engaging in-store experiences using digital assets to support interactions with informed sales associates
Streamline operations
• Become an data-driven organization
• Evolve from reactive to proactive to help build, monitor, and improve your brand
• Keep pace with rapid change and innovate with cloud infrastructure
Your order is ready!Pay in-app to grab and go.
1
Engaging customers for repeat visits7-Eleven
Objectives7-Eleven wanted to connect various sources of customer data to provide a single customer view, and use mobile & live data to track the purchase cycle and engage customers in real-time
TacticsThe Plexure solution uses a mobile app, IoT orchestration, and beacons to tailor customer promotions to personal preferences and purchasing history
Results• Linked fuel purchases to
convenience purchases, positioning 7-Eleven as the convenience store of choice
• Encouraged customers to return to 7-Eleven locations, taking up more offers more often
Built on Microsoft Cloud Technology
Frictionless Shopping
• Enable Self Checkout & BYOD
• Frictionless Shopping Experiences
• Grab and Go• Cognitive Services• Artificial Intelligence
Artificial Intelligence/Cognitive Services & Robotics
• Detect Misplaced Products
• Detect Out of Stock• Detect Wrong Pricing
Labels• Analyze & Respond to
Customer Behavior• Uses Image Recognition
/Cognitive Services / Artificial Intelligence
Mars Drinks optimizes operations, boosts customer satisfaction using IoT & Analytics
Challenge • Avert downtime and
out-of-stock products• Improve operational
efficiency of partners in the field
• Deliver better customer service
Solution• MARS DRINKS
identifies the optimum time to stock and service its vending machines by using Internet of Things (IoT) technology
Benefits• Improves timely product
stocking and operational efficiency
• Increases customer satisfaction
• Drives business insights from consumer behavior data
“Putting machines online, considering how a space is used, and looking at people’s beverage consumption will unlock a wealth
of information that we haven’t been able to easily access before.”
— Jamie Head, Chief Information Officer, MARS DRINKS
Blockchain decentralizes data in a trustless environment
Traditional System
Centralized system with stored ledger
Blockchain System
Distributed system with distributed
ledger
• Traditional ledgers are centralized and use 3rd parties and middlemen to approve and record transactions• Blockchain safely distributes ledgers across the entire network and does not require any middleman• The technology maintains multiple replicas like p2p torrent file sharing
Webjet Uses Blockchain in First-Of-A-Kind Travel Bookings Solution
Challenge • Webjet handles thousands of hotel
bookings every day that pass through multiple operators. The high volume of transactions and number of parties involved in each transaction can lead to discrepancies.
• Booking errors negatively affect customers’ experiences and undermine trust between Webjet and its partners, and can also have serious financial consequences.
Strategy• Webjet and Microsoft
developed a first-of-a-kind blockchain solution.
• The solution creates secure, independent transaction records that all parties can see. Known as ‘Smart Contracts, they streamlining the booking and payment process, and reducing errors.
Results• The use of blockchain removes the risk of
data inaccuracy, boosts security and efficiency, and enhances trust and accountability between Webjet and its partners.
• The solution gives Webjet a competitive edge and could set a new industry standard.
• Webjet has an exciting opportunity to grow by facilitating transactions across the travel industry and selling its solution into other sectors.
“Microsoft’s ongoing investments in building the industry’s most trusted cloud platform around the principles of security,
privacy and control, compliance and transparency, along with its deep heritage in guiding businesses, including Webjet,
through periods of significant IT transformation made the decision to go on this journey with Microsoft a no-brainer.” — John Guscic, Managing Director, Webjet
© 2013 Microsoft Corporation. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries.The information herein is for informational purposes only and represents the current view of Microsoft Corporation as of the date of this presentation. Because Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft cannot guarantee the accuracy of any information provided after the date of this presentation. MICROSOFT MAKES NO WARRANTIES, EXPRESS, IMPLIED OR STATUTORY, AS TO THE INFORMATION IN THIS PRESENTATION.
Top Five Strategies for Retail Data AnalyticsMy findings of NRF 2017Eric Thorsen (@ericthorsen)GM Retail and Consumer ProductsHortonworks
13 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
NRF 2017 Recap
35,000 attendees– All 50 states represented– 94 countries represented
HR was a theme – in addition to technology, data, and automation Five observations based on NRF 2017 Big Show
– Data was a key element of many presentations– Consumer experience continues to be central to retail strategy– Unique ways to avoid distraction during systems implementation – Technology (and data!) continues to grow exponentially– Omnichannel is less a buzzword and more of an expectation
14 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
Overwhelmed by Data New types, new sources, new systems
Retailers are reporting an overwhelming variety and volume of data– Not always “big data” by volume, can be complex data by variety– Retail Data Analytics improve with greater access to all data types– 4 V’s (Volume, Variety, Velocity, and Veracity) – Veracity provided by Blockchain (per Shish)
“Identity is the core of personalization” and identity is composed of dataJeff Rosenfeld – Neiman Marcus
“Sometimes you just need to buy a lightbulb. But customers expect the light bulb to be in stock, and data can help ensure this happens.”Dave Abbott, The Home Depot
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Consumer Experience
Impact of Millennials– Do not behave predictably– Most mature retailers have built business on
backs of boomers– Spontaneous, impulsive, distracted, but loyal
Expectation of personalization– Sharing data to promote deeper relationship– Introduction of “comfort factor”
Whitney Walker, GM Stores, SONOS– Importance of consumer experience
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Retail Systems Leadership – Signal vs. Noise
Focus on business impact– Essence of simplification
Mike McNamara – CIO of Target– 5 Post-it notes
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Technology continues to increase pace New “Moore’s Law”
– Data is doubling every year– First reported at NRF 2014 by Ginni Rometty (80% in last two years)
Process Automation and Automated Assistants– Amazon Echo will be in 40 Million homes by 2020– Evolution of drones for last-mile delivery– Automated picking and shipping in DC’s– Continued evolution of business process efficiency
Trends in Data Management– The number of U.S. firms using big data in the past three years has jumped 58 percentage points to
63% penetration– 70% of firms now say that big data is of critical importance to their firms, an astounding jump from
21% in 2012. That’s one of the fastest tech-adoption rates ever. – The title of chief data officer — the C-Suite manager of big data — a title that until recently didn’t
even exist, is now found in 54% of companies surveyed.
New Data
Traditional Data
18 © Hortonworks Inc. 2011 – 2016. All Rights Reserved
We need a new channel definition
Omnichannel fails to summarize experience Consumers demand personalization
– Online– On application– In store– By phone
To Legacy
API
ALGORITHMS
DATAData
Ingest
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How to benefit from trends and data in retail
Engagement of Hortonworks to identify and focus on business-driven prototypes• Big Data Scorecard
• Assist business leaders understand and evaluate the essential focus areas for accelerating business transformations
• Joint Innovation Program• Focus on business impact to create “Vision to Value”,
addressing key executive questions
• Design Thinking paradigm of ideation and prototyping towards vision
• Use Case Workshop• Staffed with customer architects and business leaders to
identify low hanging fruit for self-funding projects
Business( Viability )
People(Desirability)
Technology(Feasibility)
DesignThinking
Experience InnovationEmotional
Innovation
Functional Innovation
ProcessInnovation
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