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Optimizing Shopper Insights For Grocery Retailers

Analytics have become a vital element in grocery retailers’ toolboxes, helping them to hone in on best practices in order to improve customer service. From space management and promotion planning to price optimization and assortment planning, analytics are delivering the insights that help grow the business and improve the bottom line.

Retailers around the world are finding success with insight-driven analytics. Representing the largest grocery cooperative in Finland, Ilkka Alarotu from the S Group will share his expertise and experiences with analytics in an upcoming webinar.

Joining Alarotu during the webinar, industry consultant Jim Hertel from Willard Bishop will discuss his perspective on the benefits of analytics; and Cyndy Renfrow from SAS will share grocery case studies highlighting innovation and analytics.

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Optimizing Shopper Insights For Grocery Retailers

  1. 1. Ilkka Alarotu, Jim Hertel, Cyndy Renfrow,S Group Grocery Trade Willard Bishop SAS Institute Inc.
  2. 2. Welcome to the WebinarYour GoToWebinar Attendee Viewer is made of 2 parts: 1.  Viewer  Window   2.  Control  Panel   Type  your  ques9on  here  
  3. 3. Follow this Webinar on Twitter #LiveWebinar hashtag.
  4. 4. About Retail TouchPoints  Launched in 2007  Over 20,000 subscribers  To provide executives with relevant, insightful content across a variety of digital mediumFree subscription to our weekly newsletter:www.retailtouchpoints.com/signup
  5. 5. PanelistsIlkka Alarotu Jim Hertel Cyndy RenfrowDirector, Customer Managing Partner Senior Director, EMEAOriented Assortment Willard Bishop Retail/FMCG Practiceand Pricing - Food and SAS Institute Inc.Daily Consumer GoodsS Group Grocery Trade Moderator Debbie Hauss Editor-in-Chief Retail TouchPoints
  6. 6. Unique Challenges Facing Grocery Retailers   Commodity pricing pressures   Decreased household wallet share due to fewer shopping trips   Increased competition from non-grocery retailers, including deep discounters   Empowered consumers   Numerous in-store departments   Fresh food management   Mountains of SKUs and UPCs   Need for a highly optimized workforce   Siloed internal business processes
  7. 7. Insight-Driven Analytics Boost Grocery Profits And Revenue Insight-driven retailing can break down the barriers/silos and provide transparency across the value chain  Supermarket retailers can expect to increase same-store sales 5% to10% when becoming more shopper-centered – Jim Hertel, Willard Bishop  Mobile Technology and Social Media will greatly impact the grocery business and analytics will play a key role. “Location-based information … represents the most important single feature of mobile.” – Richard Hastings, Global Hunter Securities  Retailers must institute “outside-in” thinking in order to analyze customer sentiment and deliver actionable insights 
  8. 8. Insight-Driven Analytics Boost Grocery Profits And Revenue Smart retailers will respond with a focused optimization strategy featuring 4 key components:      1.  Assortment Optimization 2.  Campaign Planning, Marketing and Promotion Optimization 3.  Pricing Optimization 4.  Demand Forecasting
  9. 9. 10/12/11 SOK Päivittäistavarakaupan ketjuohjaus 9
  10. 10. 1.  S Group in brief2.  Value Chain Optimization: Big Picture3.  Space Optimization4.  Price Optimization5.  Interactive social media services6.  Summary 10
  11. 11. 1.  S Group in brief2.  Value Chain Optimization: Big Picture3.  Space Optimization4.  Price Optimization5.  Interactive social media services6.  Summary 11
  12. 12. –  The S Group consists of 22 regional cooperatives and the SOK Corporation, which is owned by the cooperatives.–  S Group has operations throughout Finland, in the Baltic Countries, and in St. Petersburg, Russia.–  Retail sales: EUR 12,267 million (+5,0 %)–  Profit before exceptional items: EUR 296 million–  Bonuses paid: EUR 333 million–  1,636 outlets–  39,646 employees SOK Grocery Trade Chain Management 12
  13. 13. Grocery sales Service station stores Department stores and fuel sales and speciality goodsHotels and restaurants Cars and Agribusiness automotive goods Other S Group’s restaurants S Group’s car dealerships 13
  14. 14. “Higher quality at a lower price”S Group leads the industry with consistentlylower prices, wide variety and high customersatisfaction. 14
  15. 15. –  Every Day Low Price (EDLP) requires Every Day Low Costs (EDLC)–  Best demand-based assortment always (continuously) available–  Easiest place to shop in all locations 15
  16. 16. 16
  17. 17. 17
  18. 18. 1.  S Group in brief2.  Value Chain Optimization: Big Picture3.  Space Optimization4.  Price Optimization5.  Interactive social media services6.  Summary 18
  19. 19. 1. Forecast 2. Forecast 3. Forecast •  •  S Group total / •  Store / Product / •  Store / Product / Day Product / Period Week • 28 days before Optimization Customer-oriented Storeassortment planning Space/product ReplenishmentPricing optimization: In-store efficiency Labour planning volume scenarios Logistics costs Logistics operations Sourcing Display methods Automated ordering Delivery Pack size Pricing Vendors: Vendors: Vendors:Auctions ->Orders Labour plans Logistics plans Raw material Production drivers Inventory levels purchasing Logistics Production plans Capacity operations 4 – 8 months 2 months 21 days – 48 hours 19
  20. 20. Orders for vendors 2. Forecast 3. Forecast •  Drivers: •  Store / Product / •  Store specific Store / Product / Week space allocation Day • 28 days before 1. Forecast •  100% Shelf availability Optimization •  S Group total / Display methods Tentative Order Product / Period Picking and delivery efficiency pack sizes In-store Store (warehouse / supplier) Recommended merchandizing Replenishment facings / System Wastage product level Replenishment Inventory cycle Order level at store (logistical costs) Sourcing Decisions Assortment Decisions Space optimizer Pricing Decisions Store Specific Space in units / Planograms Product / Store 4 – 8 months 2 months 21 days – 48 hours 20
  21. 21. 1.  S Group in brief2.  Value Chain Optimization: Big Picture3.  Space Optimization4.  Price Optimization5.  Interactive social media services6.  Summary 21
  22. 22. Base drivers1.  Shelf availability (100 % availability)2.  Store specific sales forecast by product3.  Store specific space allocation by categoryBusiness performance optimization1.  Efficiency in store activities •  Labour cost of shelving2.  Logistics efficiency •  Drop size •  Drop times •  Store replenishment cycles •  Warehouse picking3.  Vendor efficiency •  Order volume of delivery pack sizes4.  Total wastage in supply chainCustomer centricity = Best assortment – Easy to shopCost reduction in supply chain 22
  23. 23. Analyzing,ReportingStore layout, total area Total space utilization Store layout incl. sections - sales area - auxiliary area - concept developmentSales area Macro level allocation Allocation of sections to product categories -  effectiveness of space - development of allocation Space optimization on store/category level recommendationsDisplay groups Micro space allocation - effectiveness of space allocation for products Automated production of store specific planograms - assortment optimization Space optimization on store/product level Automated replenishment process 23
  24. 24. 40,000 store-basedplanograms perassortment period 24
  25. 25. 1.  S Group in brief2.  Value Chain Optimization: Big Picture3.  Space Optimization4.  Price Optimization5.  Interactive social media services6.  Summary 25
  26. 26. Lower prices, better margin1.  More forecasting power: Price elasticity calculations –  When product A price changes, what happens to the product A volume –  When product A price changes, what happens to the product B volume2.  More analytical power –  What is the best combination of prices: –  Brand leader price is fixed (competition). There also are rules for economic products. What are optimum prices for other products than brand leader to get best margin possible? –  How we could use customer owner information to improve our pricing? –  Best customers: what do they buy and what they do not ? 26
  27. 27. Scenario -example –  Maximize Margin (%) such that –  Units sold is not sacrificed (Units sold ≥ Units sold LY) –  Competitor price rules are not violated10/12/11 SOK Grocery trade chain management 27
  28. 28. 1.  S Group in brief2.  Value Chain Optimization: Big Picture3.  Store Localization4.  Space Optimization5.  Price Optimization6.  Interactive social media services7.  Summary 28
  29. 29. Foodie.fm - Facebook for groceries Personalized product and recipe recommendations Answers to a simple question: What would I buy and eat today? Unique server technology for personalized product and recipe recommendations. Empower people to consume smarter Foodie tailors recommendations based on your preferences. Use relevancy search to find products that fit your preferences and taste profile. Social grocery discovery Social interaction influences consumer behavior. Connect family to co-shop and share. Follow friends to discover new ideas and recommendations. 29
  30. 30. Foodie.fm – Social shopping where ever you are Mobile Facebook & Web SMS & Email iPhone, Nokia & Android Shopping  list:   CocaCola,   Arla  Cheese,   Milk   Widgets Retailer & checkout assortment link 30
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  32. 32. Benefits–  Social media speeds up fragmentation of consumer needs: Personalization technology provides a state of the art way to meet the unique needs of consumers.–  Get the shopper before they buy: Service enables very transparent and interactive way of being part of everyday life of consumers. Create link to checkout from social discovery.–  Analytics: Ability to feed back analytics from social shopping process. 32
  33. 33. 1.  S Group in brief2.  Value Chain Optimization: Big Picture3.  Store Localization4.  Space Optimization5.  Price Optimization6.  Interactive social media services7.  Summary 33
  34. 34. Summary–  Best demand-based assortment and availability every day, every hour, every store–  We are ambitious in developing world class productivity and business analytics–  Value Chain Optimization connects all operations together to get the maximum output–  Social media speeds up fragmentation of consumer needs: we need a new level of personalized digital and mobile services for our individual customers 34
  35. 35. Jim Hertel Managing PartnerSeptember 2011
  36. 36. There are Dramatic Differences Between “Best” and “Worst” Front Page Items Top 10 Bottom 10 Source: Willard Bishop, Chain 12-store transaction data, for 12 weeks beginning 12-31-2008 to 3-18-2009. Shopper-centered merchants select Front-Page promotions based on Top Shopper appealCopyright © 2011. All Rights Reserved. 36
  37. 37. Good Loyalty Programs Invite Collaboration External (Trading Partners) Internal   Shopper insights   Shopper insights   Data access   Behavioral   Custom research   Attitudinal   Shopper marketing   Shopper marketing: internally funded   New vendor resources investment   Shopper-centered merchandising   Marketing services foundation   Efficient and effective demand generation   Gaining full value starts with placing the shopper at the center   Retail trading partners will add to retailers’ investments, accelerating impactCopyright © 2011. All Rights Reserved. 37
  38. 38. Over the Past Two Decades, Traditional Supermarket Retailers Have Lost Significant Ground Market Share by Segment Source: Willard BishopCopyright © 2011. All Rights Reserved. 38
  39. 39. Accelerating Growth through Innovation SAS Grocery Case Studies October 12, 2011 Company Confidential - For Internal Use OnlyCopyright © 2009, SAS Institute Inc. All rights reserved. Copyright © 2010, SAS Institute Inc. All rights reserved.
  40. 40. Consumers are increasingly difficult to keep up with…   In Store Catalogue Web Email Social 4500 212 3344LoyaltyProgram Mobile Call Centre Direct Mail Credit 40 Copyright © 2010, SAS Institute Inc. All rights reserved.
  41. 41. How do we break our operational silosHow do we offer personalized Should we open alternate down to better server our customers How do we improveservice to our customers? channels? coming to us across the Omni-channel? profitability? How do we reposition with Where do we open moreWhy are we losing share of deep discounters coming in to stores? Which format?wallet to our competition? our market? How do we innovate and create a unique differentiation? Should we open alternate channels?How do we listen to our How do we continue tocustomers to better understand maintain market dominance?what they want next? How do we provide better value? 41 Copyright © 2010, SAS Institute Inc. All rights reserved.
  42. 42. Engineering the Solution with SAS Grocers must successfully execute a combination of these five fundamental processes to be competitive. Localize assortments Segment and engage shoppers Add stores to markets Rationalize store space and Target market Close non-performers assortments Optimize prices Remodel to retain and attract Optimize Promotions SAS Enablers   Regular Price OptimizationAnalytics and ESRI ArcGIS   Analytics   Category Management   Promotions Optimization   Customer Insights   Assortment Planning   Marketing Automation   Marketing Optimization   SKU Rationalization   Promotions Optimization   Assortment Scaling   Customer Sentiment Analysis   Space Management SAS Forecasting – Predictive Analytics 42 Copyright © 2010, SAS Institute Inc. All rights reserved.
  43. 43. Creating Automated Continuous DialogueSAS Marketing Operations SAS Media Mix Analytics Management SAS Marketing Automation/Optimization Customer Sentiment Analysis Omni-Channel Marketing Store level data Inventory Data Pricing Data Offline Customer History Content Server SAS Real-time Decision Manager Online Customer History 43 SAS for Customer Experience Analytics Copyright © 2010, SAS Institute Inc. All rights reserved.
  44. 44. Dynamic Intelligence-Driven Personalization Headline Driven by Search Text Offer Driven by Data MRM Price Offer Driven by Data Product Driven by Data MA/MO RDM CXA Real-time Dynamic Collection Technology 44 Copyright © 2010, SAS Institute Inc. All rights reserved.
  45. 45. Innovation… 45 Copyright © 2010, SAS Institute Inc. All rights reserved.
  46. 46. Applying SAS Innovation in Grocery 46 Copyright © 2010, SAS Institute Inc. All rights reserved.
  47. 47. Leveraging Customer Insight to Generate Competitive Advantage  Company Large U.S. national grocer with over 1,500 stores and in excess of $ 50 billion in sales.  Opportunity Create “competitive advantage that is better allowing the company …. to target customers’ needs and wants” – Deborah Weinswig, Citigroup Global Markets, August 10, 2008  Results  “The promotions in these (retailer) mailings have a 40% redemption rate.…which compares to an industry average of 2%” – Deborah Weinswig, Citigroup Global Markets, August 10, 2008  “Helped (retailer) boost sales by 5%” – Business Week, September 22, 2008 47 Copyright © 2010, SAS Institute Inc. All rights reserved.
  48. 48. Gain Greater Customer Insight, Loyalty and Spend with SAS  Challenge Large North American grocer was facing increased competition, customer defection and eroding margins. They wanted to gain better customer insight, which would drive better merchandising decisions and offers, and increase share of customer’s wallet.  Solution Licensed SAS Retail Intelligence Solutions to better understand its customer segments and buying patterns by analyzing all point-of-sale data and customer data.  Results Using SAS, the retailer has gained greater customer insight to drive better merchandising and promotion decisions. The projected ROI is a 3-5% increase in sales. 48 Copyright © 2010, SAS Institute Inc. All rights reserved.
  49. 49. Delivering Margin Performance “Rising Prices are Here to Stay” A long-standing regional supermarket chain doing business in the U.S. under multiple banners has always stood for real quality and value. Their reputation stands not only on always delivering a quality product, but on constantly striving to find new ways to improve that qualityBusiness Issue Solutions Results•  Ability to deliver competitive   Leverage SAS to create a rules   Increased the total margin pricing to customers while based regular price optimization performance of pilot categories by protecting profit margins for the tool that considers (Retailer’s) 2.5 % to 8% company. competition in creating price elasticity curves. as developed by Deloitte LLP. 49 Copyright © 2010, SAS Institute Inc. All rights reserved.
  50. 50. Improved Forecasting and Customer Insight Lead to Precise Pricing A U.S. regional retailer with more than 1,000 stores doing business across 13 banners.Business Issue Solutions Results  Increased competition and eroding SAS® Revenue Optimization   Better forecasting to inform margins precise pricing   SAS® Regular Price Optimization  Growing number of customer   Establishment of comprehensive choices made it difficult to retain   SAS® Promotion Optimization product and price relationships to customers and increase loyalty SAS® Shopper Insights improve category management  Increase responsiveness to   Multiple margin and market market conditions strategies  Maximize margins and market   Expected return 2-5% increase in share margin 50 Copyright © 2010, SAS Institute Inc. All rights reserved.
  51. 51. Increased Store Comps while Reducing Inventory Levels A fortune 500 Retailer with more than 5,000 stores is one of the largest, fastest- growing retailers in the United States. It offers both quality brand name and private-label products at value prices.Business Issue Solutions Results  Sustain rapid company growth SAS® Integrated Merchandise   Adjust Merchandise Assortments Planning quickly to meet consumer demand  Continue to know customers   Integrated Merchandise Planning   Long term sustainable results  Desire to improve customers’ Suite including Merchandise expected from new program / shopping experience Financial Planning and Assortment platform  Desire to add optimization and Planning   Short-term results achieved analytics SAS® Business Intelligence in this economy include:  Desire to tailor assortments,  Includes ad-hoc and standard   Maintain IMU pricing, store formats; move away reporting, built-in analytics and   Increase inventory turn from “one size fits all” graphics   Increase GMROI 51  SAS® Demand Forecasting Copyright © 2010, SAS Institute Inc. All rights reserved.
  52. 52. Gaining Accurate Visibility into Forecasted Demand Supermarket chain in Europe has established itself as a leader in quality and choice, combining the convenience of a supermarket with the service of a specialist shop.Challenge Solution Results SAS® Demand Forecasting  To utilize forecasting analytics to   Forecasting business processes   Improved margins with highly view spatial performance. that account for demand accurate forecasts differences across all stores,  To create optimized assortments geographies and product lines   Automated exception based tailored to market requirements forecast management reduces the   Includes models for basic product need for manual inputs and  To provide numerous lifecycle and seasonal products. forecast updates   Create weekly forecasts/ updates   Forecast Performance reporting to automatically with exception validate forecasting decisions   Forecasts incorporate operational   Enable users to identify the right updates (re-alignments, re- forecasting level for item/ locations classifications, promotions, for specific operational need introductions, etc.) 52 Copyright © 2010, SAS Institute Inc. All rights reserved.
  53. 53. Personalized Offers Supermarket chain in Europe has successfully targeted their marketing campaigns to customer profiles supporting tailored promotions.Business Issue Solutions Results  Need to Streamline process   SAS® Shopper Insights   Integrated Analytics  Need to replace current CRM   SAS® Campaign Management   Highly Targeted, Personalized system Offers  High total cost of ownership   More Automated Campaigns  Campaign management platform   Consistent process for all types of not tightly integrated with customer campaigns analytic models   Streamlined process because of integrated analytics reduced time and effort and increased user satisfaction   Lower cost infrastructure 53 Copyright © 2010, SAS Institute Inc. All rights reserved.
  54. 54. Customer Insight Drives Customer Loyalty and Greater Share of Wallet Large North American grocery store chain addresses eroding margins and customer attrition with SAS Analytics.Business Issue Solution Results  Increased competition and eroding SAS® Shopper Insights   Using SAS, the customer gains margins. greater customer insight to drive better merchandising decisions,  Growing number of customer which will in turn increase choices made it difficult to retain customer loyalty and spend. customers and increase loyalty.   The expected ROI is a 3-5%  Want to gain better customer percent increase in customer insight, which would drive better spend or revenue. merchandising and marketing decisions  Drive offers to increase share of customer’s wallet  Need to prevent decline in revenues and profit. 54 Copyright © 2010, SAS Institute Inc. All rights reserved.
  55. 55. Value of Predictive Analytics and Optimization• Assortment Optimization: National U.S. general merchandisechain – 5% to 15% sales increase, margin up 2% to 3%• Regular Price Optimization: Sales 1+% - 3%, margin +2% - 5%• Assortment Optimization: European department store chain – 5% sales increase via average basket growth• Promotion Optimization: Sales + 1% - 12%, margin +5% - 20%• Markdown Optimization: Sales + 0 - 5%, margin +6 – 10% - Gartner (Former AMR Research) “(Customer Insight) helped major grocer boost sales by 5%” - Business Week 55 Copyright © 2010, SAS Institute Inc. All rights reserved.
  56. 56. Enabling The Infusion Of Deep ConsumerUnderstanding Into Planning Decisions Action Pricing Strategy Brand Assort- Pricing ment Tailored Assortments Services Service Insight Communi Promo - cations Customized Interaction Layout Location & Space Effective Promotions Bricks & Direct Mail/ Web/Internet Mortar Catalog Customers Customers Customers Optimized Planograms Cross Channel Customers 56 Copyright © 2010, SAS Institute Inc. All rights reserved.
  57. 57. Q&A SessionYour GoToWebinar Attendee Viewer is made of 2 parts: 1.  Viewer  Window   2.  Control  Panel   Type  your  ques9on  here  
  58. 58. Q&A | PanelistsIlkka Alarotu Jim Hertel Cyndy RenfrowDirector, Customer Managing Partner Senior Director, EMEAOriented Assortment Willard Bishop Retail/FMCG Practiceand Pricing - Food and SAS Institute Inc.Daily Consumer GoodsS Group Grocery Trade Debbie Hauss Editor-in-Chief Retail TouchPoints
  59. 59. Thanks for attending!You can download thispresentation & view thewebinar On-Demand here: http://rtou.ch/optimize-shopper-insights
  60. 60. Contact the PanelistsContact Ilkka at: Contact Jim at: Contact Cyndy at:Ilkka.alarotu@sok.fi Jim.Hertel@willardbishop.com Cyndy.Renfrow@sas.com

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