DECODING BIG DATA: W H A T B R A N D S + R E T A I L E R S N E E D T O K N O W T O D R I V E T H E B O T T O M LINE

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1 DECODING BIG DATA: W H A T B R A N D S + R E T A I L E R S N E E D T O K N O W T O D R I V E T H E B O T T O M LINE A n o v e r v i e w p r e s e n t a t i o n e x t r a c t e d f r o m t h e 3 h o u r w o r k s h o p l e a d b y :

2 I N T R O D U C I N G BIG DATA

3 THEN Hard Data: TRANSACTIONAL Skus Marketing reach Discounting Product Development Traffic Transactions Demographics / NOW Soft Data: BEHAVIORAL Engagement Open rates, click thrus Social media interaction Inquiries Product reviews Location

4 THEN NOW TRANSACTION BEHAVIOR Rather than treating each customer the same as part of a blanket segment, the future of Big Data allows businesses to easily and automatically treat customers as individuals, with a greater impact to the bottom line.

5 Q: BUT, HOW?

6 A: Predictive Analytics

7 Getting big data into a format that is digestible, useful and valuable for the customer and the business requires 3 key steps: 01. Implementing the appropriate technology to crunch the increase in data volume. 02. Tracking Business Intelligence: Start asking the questions about the hard data that s being captured 03. Make predictions that allow businesses to anticipate future behavior so we can ask What will happen instead of What has happened?

8 C O N S U M E R I N S I G H T S & INDUSTRY TRENDS

9 K E Y I N D U S T R Y TRENDS OVERARCHING MEGA TRENDS } Rise in Power of the Millennial Globalization of the consumer & marketplace Role definition for business innovation TECHNOLOGY TRENDS } In-Store Technology Wearable Tech Internet of Things Customization of the mobile experience

10 T H E F U T U R E O F BUSINESS IS CONSUMER CENTRIC

11 MORE & MORE... Customers are demanding relevancy at an individual level. and their expectations are rising...

12 ULTIMATELY, these mega trends and technology trends lead to more personalized experiences for your customers at the individual level.

13 BURBERRY D I G I TA L LY INSPIRED FLAGSHIP Regent Street digital goes physical -SAP custom-built clientelling tool (transaction history, social media comments, contact details, recommendations)

14 KEY TREND CUSTOMER INTELLIGENCE ENABLES BUSINESSES TO OFFER A NEW DEGREE OF PERSONALIZATION

15 B R A N D S T H A T D O N O T B E G I N T O W O R K W I T H B I G D A T A T O O F F E R A M O R E P E R S O N A L I Z E D C U S T O M E R E X P E R I E N C E W I L L G E T L A P P E D B Y THOSE THAT DO

16 A WINNING MODEL

17 H O W H A S D A T A H E L P E D U S U N D E R S T A N D O U R CUSTOMERS? / / THEN NOW FUTURE Customers were grouped based on anonymous segments (i.e. age, location, average order value) Customer behavior is known, (i.e. affinity graphs, social graphs, product preferences) Using predictive analytics, we can determine with high accuracy a customer s future behavior at an individual level.

18 THE CHALLENGE: CURRENT TO BEGIN TO TURN BIG DATA INTO THE RIGHT DATA YOU NEED: A NEW SUBSET OF DATA + A NEW METHOD OF ANALYZING THE IMPACT ON THE CUSTOMER

19 IDENTIFYING ROADBLOCKS WHAT ARE THE MAIN CHALLENGES TO SUCCESSFULLY LEVERAGING BIG DATA? 51% 45% 42% 39% 29% Lack of sharing data internally Not using data to personalize communications Can t link data at individual customer level Data collected too infrequently or not fast enough Little or no customer data is being captured Monetate

20 BUILDING THE RIGHT CONNECTORS WILL: { 01 } Make the data available { 02 } Organize the data effectively { 03 } Allow data to be operational (internally) & visible (externally)

21 H O W T O G E T STARTED

22 WHERE TO BEGIN? 1. ANALYZE WHERE THERE IS ROOM FOR GROWTH 2. DETERMINE WHERE YOUR BRAND IS LOSING STEAM

23 THE CHALLENGE: CURRENT TAKE DATA THAT FUELS THE BUSINESS & RE-INTERPRET IT TO EVOLVE THE CUSTOMER S EXPERIENCE

24 S TA RT I N G STRONG: FIRST { 01 } { 02 } THING S 1ST... Ensure your existing database is clean. this means no duplicates, incomplete or incorrect fields, etc Ensure your existing data is available at customer touch points so you can deliver personalized marketing.

25 WHAT S POSSIBLE? WHAT SHOULD BRANDS & RETAILERS DO WITH THIS DATA? Segment customers Test campaigns and approaches Hone-in on specific marketing channels Detect & Prevent customer drop-off

26 I S O L A T E, A N A L Y Z E & IMPROVE 1 CHANNEL OFTEN, IS THE MOST STRAIGHT- F O R W A R D A N D I M P A C T F U L C H A N N E L T O START WITH.

27 MAPPING THE CUSTOMER JOURNEY Most Valuable Customers Repeat Buyers Buyers START> Lookers

28 The key is to prevent customer drop-off at critical points in the customer journey. For most companies, over 50% of their database haven t purchased in the last year. By focusing on customer retention using predictive analytics, brands + retailers can add a whopping 30% to their bottom line. Plus, it s 10x cheaper to re-activate a customer than to acquire a new one.

29 IF YOU CAN CONVINCE NEW CUSTOMERS TO COME BACK A 2nd TIME, YOUR CHANCES OF RETAINING THIS CUSTOMER INCREASE FROM 30% TO 70% question: HOW DO YOU DO THIS?

30 TAKING ACTION CAMPAIGNS New customer Welcome Replenishment or Re-order message Pro-actively target at-risk customers Post purchase upselling, recommendations Re-activate lost customers VIP messages Product-focused messaging Geo-targeted campaigns Mobile campaigns

31 DEVELOPING A GAME PLAN Determine your brand s maturity Create use-cases and conditional campaigns Take learnings from singular channel and apply in an onmichannel approach Hone in on the business functions big data can drive the most improvement for Implement + measure Overlay your CRM with your actual customer experience and determine any new data points that can be easily captured

32 FOR BRANDS & RETAILERS, W H A T A R E T H E P O S S I B L E SOLUTIONS? Developing a proprietary platform (ex. Burberry s Customer 360 program) Working with a partner that has the established algorithms, predictive marketing conditions and campaigns to clean your existing database and connect directly to the ESP, CRM, inventory and/or social media profiles you already have in place (ex. AgilOne) Create an internal process between the marketing, sales and IT departments to determine what data to capture, how to organize and analyze it, and what conditions and campaigns to put into place to act on it.

33 RESOURCES a collection of helpful articles Three Predictive Analytics Pitfalls in Data-Driven Marketing Personalization: The Key to Successfully Using Big Data Leverage Big Data for your 2014 Marketing Plan How Machine Learning Can Restore Customer Intimacy Holding Your Agency Accountable for Big Data and the Bottom Line

34 CONTACT Yen Nguyen AgilOne Predictive Marketing Consultant (408) (Office) (408) (Mobile) Dominique Levin AgilOne VP Marketing (650) (Google Elizabeth Canon Fashion s Collective Founder & President m. (+001)

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