Commercial students can become pilots

Prof. Dr. Stephan Rüschen. AI in retail. Prof. Dr. Stephan Rüschen (DHBW Heilbronn) Frankfurt, October 10th Trend Forum Retail


1 KI in Retail (DHBW Heilbronn) Frankfurt, October 10, 2019 Page 1

2 professor for food trade (since 2013) trade marketing, corporate management, forms of business, customer satisfaction, category management / purchasing Baden-Württemberg Cooperative State University (DHBW) in Heilbronn Ca trading students Metro Cash & Carry Marketing, corporate development, non-food purchasing, ecommerce Germany, Hungary , West-Europe Tengelmann Group Corporate Development, Food Purchasing, Controlling Source: DHBW Heilbronn, own illustration Artificial Intelligence in Retail Non-Food Congress Page 2

3 95% of commercial students are not trained in Heilbronn during their practical phases From Rügen to Singen and from Aachen to Dresden Germany & Austria Source: LZ v, DHBW Heilbronn Artificial Intelligence in Retail Nonfood Congress Page 3

4 Digitization Everyone is talking about and a wide range of possible uses Source: Cap Gemini: Mobile Apps in Retail, Berlin 2017, p. 6 page 4

5 Digitization Everyone is talking about and a wide range of possible uses Source: Cap Gemini: Mobile Apps in Retail, Berlin 2017, p. 6 page 5

6 Web and app use leads to higher satisfaction and more competitive advantages Source: Kundenmonitor Deutschland 2019 page 6

7 fields of application of AI in various industries and areas Data analysis with AI Deutsche Bahn Source: DKFI / Bitcom: Artificial Intelligence, 2017; aitrends 2018 page 7

8 AI in retail is more than just a buzzword? Source: Internet page 8

9 Artificial intelligence has become an important topic in retail Source: EHI 2019 page 9

10 target image ??? Source: Internet page 10

11 Gartner Hype Cycle Retail Technologies 2018 Technological trigger Peak of exaggerated expectations Valley of disappointment Path of enlightenment Plateau of productivity Source: Gartner 2018 page 11

12 muffin or puppy? Source: Gala (2018), Electronic Frontier Foundation (2017) page 12

13 Components of an AI 4 Learning From Coding to Training 1 Perceiving 2 Understanding 3 Acting Audio Video Text Data Deep Learning / Machine Learning Natural Language Processing Analytics Rule Setting / Decisions Controlling Devices Triggering Processes Outputting Texts Outputting Images Source: Mark Purdy / Paul Daugherty: Why Artificial Intelligence is the Future of Growth, Accenture 2016, p. 10f .; DKFI / Bitcom: Artificial Intelligence, 2017, p. 32 page 13

14 Control of assortments in branch systems - status Control of branch-specific assortments is complex, therefore simplification strategies are used: small / medium / large east / south / west city / country. Source: Own illustration, page 14

15 Moment Of Truth Source: Own illustration, page 15

16 But customer needs are becoming increasingly differentiated Source: Spiller / Zühlsdorf (2012): Wheel of Nutrition Trends; Internet page 16

17 target groups differ from store to store. Only what gets measured, gets be done. Source: Div .; real, - page 17

18 Target Group Management and Category Management as a matrix organization Source: Rüschen, Stephan: Category Management in Nonfood at Metro Cash & Carry, in: Riekhoff, Hans-Christian (Ed.): Retail Business in Germany, Wiesbaden 2004, p. 385 page 18th

19 Should assortment control be location-specific? Yes!!! Customer requirements are becoming increasingly heterogeneous. Customer structures differ from store to store. Competitive situations can differ significantly. Store sizes and structural conditions can vary widely. With simplification strategies, the sales potential of an individual store can only be achieved to a limited extent. Source: Own illustration, nutrition wheel, real page 19

20 Data-driven product range selection at store level Shopping data per store Local data (residents, purchasing power, competitors) Market trends / strategy Customer data Source: Div .; Own illustration on page 20

21 AI can determine branch-specific assortments Strategic decisions by category managers (strategic role, trends, etc.) System support by AI for the implementation of branch-specific assortments - within the framework of the strategic guard rails - at item and store level. Source: Own illustration, page 21

22 Total Store components should be decided on a store-by-store basis Source: GfK SE and GS1 Total Store Optimization 2019 page 22

23 Great impact of better pricing on EBIT sales 100 EK margin +25 Personnel costs -13 Div. Costs EBIT +2 1% higher sales due to higher prices due to intelligent pricing => + 50% EBIT increase Source: Own illustration on page 23

24 One-to-all customers Customer One-to-one price differentiation at store level, and increasingly also at customer level Price differentiation at individual customer level Customer 1 0% discount customer 2 5% discount customer 3 10% discount store + AB 0 .99 1.99 Always the same price for all customers in all branches Source: Own illustration AB 1.19 2.29 0.99 1.99 0.89 1.79 Store differentiation in clusters (e.g. cheap, medium, expensive) Stores AB 1.19 1.99 0.99 2.29 0.89 1.79 0.99 1.99 0.89 2.29 Price decision at store level page 24

25 App s & ESL as enabler for AI driven pricing policy Source: Rossmann, Payback, Internet page 25

26 Using price differentiation to optimize sales and above all earnings Source: Internet, LZ, Oracle, Wirtschaftswoche Artificial intelligence to improve Ceconomy's pricing strategy Ceconomy's CFO Karin Sonnenmoser announced that the retail giant in Germany will introduce centralized pricing based on data analysis and artificial intelligence from the summer . In this way, we always want to be one step ahead of our competitors, said the manager. Page 26

27 O&G transcription management at Albert Heijn Source: Page 27

28 Classic flyer advertising seems to be losing its importance Source: EHI (2018) page 28

29 The changing shopper journey Source: GS 1 page 29

30 Social media increasingly dominate communication and the shopper journey Source: Div. Page 30

31 App s for personalized promotions Penny App Lidl App Source: Rossmann, Penny, Edela, Lidl Page 31

32 Why? Also because digital is easier to measure. Source: SO1 (2019) page 32

33 Personalization and relevance drivers of communication You can personalize almost anywhere: in the online shop, in the app from the smartphone, in the newsletter or in personalized mailing with customer-specific offers. (Jens Scholz, board member prudsys) Relevance is the new currency in marketing communication. And relevance does not arise from attacking your customers with masses of undifferentiated messages in the wrong place and at the wrong time. (Prof. Dr. Hans-Christian Riekhof, Göttingen University) Source: Div. Page 33

34 The end of mass marketing in retail for 100% one-to-one marketing. X Source: Div., SZ page 34

35 AI also has a wide range of possible uses in Category Management Assortment: Location-specific product ranges Pricing: Location-specific pricing Pricing: Customer-specific prices and discounts Pricing: Management of the sales process Marketing: One-to-one communication and offer design Source: Own illustration, page 35

36 Will the category manager's role change? Artificial intelligence You have to be able to let go. Source: Own illustration, Internet page 36

37 Contact Professor for Food Retail / Food Retail Baden-Wuerttemberg Cooperative State University Heilbronn (DHBW Heilbronn) Bildungscampus 4 D Heilbronn Tel .: +49 (0) 7131 / Mobile: +49 (0) 157 / Source: Own illustration on page 37