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Putting Consumers first using Data Science uncover valuable insights into what customers want, where they want it, and how much they’re willing to pay.

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Presentation on theme: "Putting Consumers first using Data Science uncover valuable insights into what customers want, where they want it, and how much they’re willing to pay."— Presentation transcript:

1 Putting Consumers first using Data Science uncover valuable insights into what customers want, where they want it, and how much they’re willing to pay for it

2 Thank You about

3 What we do – the ‘elevator pitch’ dunnhumby is the world’s leading customer science company. We analyse data and apply insights from more than 400 million customers across the globe to create better customer experiences and build loyalty. Our insights and strategic process help clients create competitive advantage and enjoy sustained growth.

4 WHY We’re passionate about loyalty and partnering for future growth HOW We place customers at the center of every decision and personalize their experience WHAT Our capabilities build loyalty and emotional connections with customers that create a lasting competitive advantage Our mission

5 Our approach

6 © dunnhumby 2014 | Confidential 6 “We have loyal customers” Assort based on sales and margin Growing gross margin by vendor/class Marketing to mass or broad group Episodic customer insights Acquisition based promotions PRODUCT-CENTRIC ORGANIZATIONS The best retailers put the customer at the center of every decision “We are loyal to our customers” Right products for the right customers Grow share of customer wallet, profitably Personalized targeted marketing Continuous test and learn CUSTOMER-CENTRIC ORGANIZATIONS

7 © dunnhumby 2014 | Confidential 7 Data allows you to see customers as individuals VALUE CONVENIENE VALUE EXPERIENCE VARIETY CONVENIENCE

8 © dunnhumby 2014 | Confidential 8 And personalize the experience across your business MASS DIFFERENTIATED (Segmented) PERSONALISED PRICE & PROMOTION ASSORTMENT COMMS SELECT THE BEST PROMOTIONS TARGETED PRICE INVESTMENTS MY PERSONAL PROMOTIONS SELECT THE CORE RANGE DIFFERENTIATED STORES MY SHOPPING LIST EVALUATE IMPACT ON LOYALTY CUSTOM CONTENTMY PERSONAL COUPONS

9 © dunnhumby 2014 | Confidential 9 We use data to maximize the relevance of 1:1 communication 1:1 COMMUNICATION FREQUENCY & CADENCE Timing of touch points CONTENT Customized content CHANNEL Reaching the customer with relevant touch points TARGETING Finding the right customer OFFER Relevant offers

10 © dunnhumby 2014 | Confidential 10 SEGMENTATION TARGETING 15 % BUYING BEHAVIORAL SEGMENTATION 22 % ENHANCED HOUSEHOLD TARGETING 31%31% CUSTOMER RESPONSE 48 % 1:1 RELEVANCY 55 % We know that make things more relevant to customers drives sales % of households engaging in communication over time

11 © dunnhumby 2014 | Confidential 11 I feel like this is just for me. This is something I am interested in. I feel they really know me. “ WOW WOW applies to every 1:1 connection with the customer including offers, content, messaging and more. The theory of And helps to win the hearts and minds of your customers

12 © dunnhumby 2014 | Confidential 12 Focus on customer loyalty Relevant, timely, personalized customer communication by channel Measurable and sustainable ROI- value for your money Ability to handle complexity Complete package at scale (Strategy, technology, analytics, and execution) Custom Designed Solutions Unsurpassed expertise in analytics & insights Broad scale experience in retail The option of pursuing a broader customer insights Unique capabilities including advanced social media advocacy We can help to shift the focus to the customer WHAT DUNNHUMBY CAN PROVIDE WHAT MAKES US DIFFERENT

13 CASE STUDIES

14 Macy’s

15 Macy’s Custom Books leveraged data to deliver each customer with more relevant content A single Custom Book campaign could produce over 500,000 unique versions of the book, reflecting the shopping behavior of each customer Custom Books were personalized by featuring the most relevant combination of product categories for each household Content/category selection driven by customer shopping data Offers, promotions, and creative execution were the same between Custom and Traditional books 15

16 16 “effective reach” is a critical concept…you don’t need to talk to everyone about everything to drive category sales 36-MENS SPORTSWEAR X COLL 79-TRADITIONAL SPORTSWEAR Category Lift per HH Custom Book vs. Base Book 16-WOMENS SHOES 85-HOUSEWARES 3-PETITE SPORTSWEAR 7-HOSIERY 81-TEXTILES 33-COLOR AND TREATMENT 38-FRAGRANCES 26-KIDS 6-FASHION JEWELRY 5-MENS COLLECTIONS 25-MENS FURNISHINGS 8-HANDBAGS 35-FINE JEWELRY 12-CASUAL SPORTSWEAR 28-WOMEN'S SPORTSWEAR 84-LUGGAGE 13-DRESS ACCESSORIES 31-MENS TAILORED CLOTHING 86-FURNITURE 22-INNERWEAR 87-MATTRESSES 82-TABLETOP 10-JUNIOR SPORTSWEAR 68-DEC HSWRS/TABLE LINENS/DECOR 19-SILVER 27-BOYS NEO COLLECTIONS 20-COATS Sales for most categories in the Macy’s Custom Book matched or beat the “Traditional Business as Usual” Book in spite of the category only appearing in books for 30% of households (on average)

17 Our experience shows the longer term benefits of relevant content 5 Relevancy is about continually engaging customers with the right content over time Impact of relevant content on Lift (37 weeks) 17

18 Kroger

19 Kroger’s MyMagazine brings personalized custom publishing to the grocery space Targeted editorial content Increased emotional connection Customer shopping data drives content targeting Balanced coupon offering 8 ranked retention offers 8 ranked acquisition offers

20 And delivers seamless experience online Open rates significantly higher than industry average Personalized version outperformed previous campaign 2:1 Customers reaction was overwhelmingly positive “Finally! Thank you for making the magazine and the coupons digital.” “Neat. I like this being tailored to my shopping habits.”

21 How Does Exadata Enable This

22 ? Several examples of why dunnhumby has been successful using Exadata Exadata performed 8x better than the next-closest competitor for our workload! Speed in data manipulation facilitates more data science and therefore more relevancy Concurrency was key SQL – A simple, yet powerful way to manipulate the data for analytical readiness Sharing and packaging SQL is easy 70% of our analysis done right in the database using SQL Oracle R enables deeper modeling without moving the data How Exadata makes this possible

23 dunnhumby Engineered Architecture

24 Some fun technical bits

25 ? In addition to ETL staging and processing, we perform all full and incremental backups to the ZFS Appliance Roughly 14Tb per hour Full backups are then offloaded to tape Using the ZFS Appliance saves Exadata resources Backups using the ZFS Appliance

26 ? Where are we headed with the Big Data Appliance Near-line storage for historical data Low cost distributed processing for analytical modeling Platform for machine learning Just the beginning Use Cases for the BDA

27 ? dunnhumby is excited about the future Utilizing the ZFS Appliance for TEMP tablespaces Approximate DISTINCT COUNT functionality – a dunnhumby addition In-Memory Columnar Database R&D on creating RAM disk for TEMP tablespaces What about tomorrow?

28 Thank You


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