Why Consumer Empowerment is moving retailers from Product Centricity to Customer Centricity

Transcription

1 Why Consumer Empowerment is moving retailers from Product Centricity to Customer Centricity

2 CONSUMER TRANSFORMATION TIMELINE Transformation Phase Transformation Phase Transformation Phase Transformation Phase Introduction of Self Service Retail Introduction of convenience Consumerization of technology Data-Driven Retailing /31/2013 Teradata Confidential

3 DATA-DRIVEN RETAILING 3 10/31/2013 Teradata Confidential

4 NEW CATEGORY INSIGHTS FROM BIG DATA Petabytes Terabytes User Generated Content User Click Stream Mobile Web Web logs Web Offer history A/B testing Dynamic Pricing Big Data Sensor Sentiment Social Network External sources (Weather) Business Data Feeds Gigabytes CRM Segmentation Affiliate Networks Search marketing Digital Video Speech to Text Megabytes ERP Purchase detail Purchase record Payment record Offer details Customer Touches Support Contacts Behavioral Targeting Dynamic Funnels Product/Service Logs SMS/MMS Today s retail data is now more complex, connected and interactional in nature being able to leverage this is the key to success 4 10/31/2013 Teradata Confidential

5 SENSOR MOVEMENT TO DETECT CATEGORY INTEREST Shopping cart will track the consumer s every move 5 10/31/2013 Teradata Confidential

6 BEHAVIOUR ANALYSIS TO UNDERSTAND CATEGORY INTEREST Improving on-shelf availability with cameras 6 10/31/2013 Teradata Confidential

7 PERSONALIZED OFFERS BASED UPON CATEGORY PREFERENCES Personalised prices based on personal shopping data 7 10/31/2013 Teradata Confidential

8 SOCIAL SHOPPING/COOKING FOR CATEGORY PARTICIPATION Social network and retailers combining online and offline 8 10/31/2013 Teradata Confidential

9 CATEGORY ANALYSIS THROUGH SOCIAL CHANNELS People with pets tend to talk about them a lot on social networks 9 10/31/2013 Teradata Confidential

10 CONSUMER PRODUCT INTEREST THROUGH FACEBOOK LIKES Facebookenabled coat hanger tracks the number of likes Photo C&A Brazil/DDB Brazil 10 10/31/2013 Teradata Confidential

11 PRE-TRANSACTIONAL BEHAVIOUR OF CATEGORY PREFERENCES Customer pre-transaction from interaction on the website 11 10/31/2013 Teradata Confidential

12 CONNECTED GLASSES ENGAGEMENT WITH PRODUCT CATEGORIES Connected glasses, allow hands-free operation and onthe-go data access to smartphones and the internet Photo: Antonio Zugaldia/Wikipedia.org 12 10/31/2013 Teradata Confidential

13 DATA-DRIVEN RETAIL APPROACH 13 10/31/2013 Teradata Confidential

14 THE NEW RETAIL DATA-DRIVEN APPROACH ANALYZE & DISCOVER EXECUTE & DELIVER INTEGRATE & UNDERSTAND ACT & OPTIMIZE 14 10/31/2013 Teradata Confidential

15 TESCO CATEGORY WEATHER ANALYSIS Tesco improves forecasting using a weather-based sales model and data from Teradata. Challenge Teradata Solution Tesco needed to reduce the amount of discounted items past their sell-by date (500 million items annually) With unpredictable weather patterns, a 10 C temperature change dramatically affects sales 2 INTEGRATE & UNDERSTAND ANALYZE & DISCOVER Analysis of weather data and customer buying behavior 1 Development of a weather-sales model EXECUTE & DELIVER ACT & OPTIMIZE 3 4 Optimized internal processes Regular upload of sales forecast to Tesco Results Tesco saves 6 million food waste per year Weather-based sales forecast improves closing shelf gaps each week during hot weather Lower wastage and ordering interventions are reduced 15 10/31/2013 Teradata Confidential

16 SHOP DIRECT CATEGORY ANALYSIS Shop Direct benefits by being able to accurately steering offers to the right channels Challenge Teradata Solution Shop Direct needed a single view of its customers across multiple sales channels In the past six years, Shop Direct saw a fundamental change in its business model. 2 ANALYZE & DISCOVER Analysis of browsing behavior and offline sales data EXECUTE & DELIVER Steering offers to the right channel 4 Today, 80% of total sales comes from website 20% of the online purchases are done via a mobile device. INTEGRATE & UNDERSTAND 1 Integration of behavioral data into data warehouse ACT & OPTIMIZE Segmentation based on multi-fact behavior 3 Results 1% growth in online sales 50% reduction in catalogue cost and 28% increase in sales from Significant reduction in paid search and affiliates 16 10/31/2013 Teradata Confidential

17 COOP DENMARK CATEGORY TARGETING Coop Denmark deploys multi-channel, personalised next-best offers in real-time Challenge Teradata Solution Coop Denmark wanted to increase offer response rates It already had a customer segmentation based on previous purchases 2 ANALYZE & DISCOVER Analysis of purchasing behavior EXECUTE & DELIVER Real-time offers across 6 synced channels 4 But everyone in the segment got the same offer INTEGRATE & UNDERSTAND 1 Predictive models for customer's willingness to respond to an offer ACT & OPTIMIZE NL Website App Receipt Price verifier Campaign Mgmt Software creates best offer-mix per customer in-store Kiosk 3 Results Doubled response-rates compared to non-optimized offers Distribution of offers across six channels coordinated with real-time sync 17 10/31/2013 Teradata Confidential

18 DATA-DRIVEN RETAIL ROADMAP 18 10/31/2013 Teradata Confidential

19 THE ROADMAP FOR DATA-DRIVEN RETAIL ANALYZE & DISCOVER EXECUTE & DELIVER Execute & Deliver Digital Messaging INTEGRATE & UNDERSTAND ACT & OPTIMIZE Act & Optimize Real-Time Decision-making Integrated Marketing Analyze & Discover Big Data Integrate & Understand Analytical Insights Integrated Data Theme Single view of your Retail Business Gaining insight into your Retail Business Analyzing Big Data Digital Insight Planned & Data Driven Communications Inbound Marketing to your Retail Customers Delivering relevant messages to your Retail Customers Deliverable Prioritize business objectives linked to data in the business Deploy Data Model Predictive Analytics Analyze additional subject areas Grow User base Non relational insight into Digital Data/ Interactions Marketing Operations - Campaign Mgt Optimization Real-Time Next Best Offer Real-Time Channel Integration Integrated and mobile messaging Business Focus Obtaining a single view of customers; Operations and Products Market Basket Cust Segmentation Store Operations Performance Marketing Attribution Web Behavior Path to Purchase Communication with Customers Event Based Mktg Marketing Efficiency Leveraging Inbound Contacts Best Contextual Messaging Engage with Customers with Personalized Content Business Capabilities Core Reporting BI insight to understand your business Complex queries across multiple subject areas Data Mining Analysis of Digital Data with Traditional Data in an Omni- Channel view Targeting Planning & Workflow Multi-Step Dialogue To deliver a personalized message in Real Time To use Digital messaging to drive an Omni-Channel Execution Teradata Enabling Technology & Services Teradata Platform rldm BI Capability Master Data Mgt SMBB Advanced Analytics Services Analytical tools Teradata Warehouse Miner Teradata ASTER Hadoop Celebrus Relationship Manager Marketing Operations Closed Loop Reporting Real-Time Interaction Manager Channel Interaction Manager Celebrus Digital Messaging Centre ecircle Media Services 19 10/31/2013 Teradata Confidential

20 20 10/31/2013 Teradata Confidential Always remember to start with the question not the Data

21 THANK YOU PaulWinsor /31/2013 Teradata Confidential