Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

MLSEV. Use Case: Online and Offline World in the Retail Sector

108 views

Published on

Cluster Analysis and Association Discovery in the Real World: Online and Offline World in the Retail Sector. Friends or Enemies? - by Good Rebels.
MLSEV 2019: 1st edition of the Machine Learning School in Seville, Spain.

Published in: Data & Analytics
  • Be the first to comment

  • Be the first to like this

MLSEV. Use Case: Online and Offline World in the Retail Sector

  1. 1. 1st edition March 7-8, 2019 1
  2. 2. BigML, Inc Online and Offline World in the Retail Sector Friends or Enemies? Miguel Blanco Data Scientist, Good Rebels Team work: Mar Castaño & Sergio Vázquez 2
  3. 3. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 3 Who are we? Good Rebels is a digital strategy and creative company. 
 We help our clients to innovate at the intersection of people, brands & technology. We engage customers daily with our unique
 Smart Social methodology.
  4. 4. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 4 4
 OFFICES MEXICO CITY 60
 CLIENTS 30
 CAPABILITIES 9M€
 TURNOVER 120
 PEOPLE BARCELONA MADRID BRIGHTON + ++ Who are we?
  5. 5. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 5 PERFORMANCE INTELLIGENCE Developing deep insights and strategy that help our clients put people at the heart of everything they do. EXPERIENCE Creating culturally relevant products, services and consumer experiences. Delivering and measuring real business impact. Accelerating change, empowering people and transforming organizations. ENABLEMENT I E P E CREATIVITYDATA TECHNOLOGY PROJECT MANAGEMENT Who are we?
  6. 6. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels •Big company in the retail sector. •76 stores in Spain. •Powerful e-commerce. •It buys and sells products to its customers. 6 Our case
  7. 7. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels How to improve the e-commerce performance through digital marketing using offline information 7 Our question
  8. 8. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels •E-commerce: •Info about the client (location). •Info about the transaction (price). •Info about the purchased item. •Where the item is stored. 8 Our data •Stores: •Info about the visits to the store. •Info about the opinion of the store (Google Reviews). •Location. •Zipcodes level. •Info about the location. •Population. •Average spend per home. •Average income per home. •Background. Online world Offline world External data: geographic and demographic
  9. 9. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 9 Our tools Python Tableau Geographic information system (GIS) BigML
  10. 10. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 10 Our tools … as a kitchen Python Tableau Geographic information system (GIS) BigML
  11. 11. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 11 Our project To cluster the territory to optimize the digital marketing strategy
  12. 12. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 12 Data exploration Around 12k zipcodes in Spain. Sorry Canaries. 45M people
  13. 13. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 13 Data exploration Disparity in zipcodes sizes. But we focus on the background.
  14. 14. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 14 Data exploration Disparity in zipcodes sizes. But we focus on the background.
  15. 15. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 15 Data exploration With GIS, we have calculated the distance to the nearest store
  16. 16. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 16 Data exploration With GIS, we have the distance to the nearest store
  17. 17. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 17 Data exploration We focus on the assumption of 20 km as a limit
  18. 18. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 18 Data exploration Around 25M people have a store in less than 20 km.
  19. 19. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 19 Data exploration
  20. 20. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 20 Data exploration
  21. 21. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 21 Data exploration
  22. 22. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 22 Data exploration
  23. 23. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 23 First discovery Awareness problem in places far away from a store
  24. 24. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 24 First action First and easy segmentation by distance to the nearest store
  25. 25. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels Two groups 25 Population Customers Total estimated income E-commerce bill
  26. 26. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 26 We attack each group separately Places far away from the store Places near the store Info about the place. The e-commerce. Demographic. Info about the place. The e-commerce. Demographic. + Info about the store Two groups
  27. 27. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 27 First big group Let’s begin with those far from the store
  28. 28. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels Places far from a store 28
  29. 29. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 29 Places far from a store
  30. 30. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 30 Places far from a store
  31. 31. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 31 Places far from a store
  32. 32. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 32 Places far from a store
  33. 33. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 33 Places far from a store
  34. 34. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 34 Places far from a store
  35. 35. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 35 Population Customers Total estimated income E-commerce bill Two groups, back again
  36. 36. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 36 Places near the store Let’s move to those that are near the store Places near the store Info about the place. The e-commerce. Demographic. + Info about the store
  37. 37. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 37 Places near the store What about the store? We’ll use the Google Reviews
  38. 38. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 38 Places near the store More than 10k reviews From the 76 stores Rating from 1 to 5 And text
  39. 39. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 39 Places near the store
  40. 40. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 40 Places near the store
  41. 41. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 41 Places near the store
  42. 42. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 42 Places near the store
  43. 43. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 43 Places near the store
  44. 44. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 44 Places near the store
  45. 45. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels Were we talking about zipcodes or stores? 45 Places near the store
  46. 46. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 46 Places near the store
  47. 47. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 47 Places near the store
  48. 48. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 48 Places near the store
  49. 49. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 49 Places near the store
  50. 50. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels 50 Places near the store
  51. 51. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels Conclussions •Awareness problem in zipcodes far from the store. •Info to improve campaigns by location. •Mechanisms to cross-selling between e- commerce and store. •Associate territory characteristics to customers (to e-mail strategy). •Reviews analyzed to help stores to identify strengths and weakness. 51
  52. 52. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels Take aways •All machine learning projects need work. •You need to work hard on the data: sources, format, … •You need expertise on the field. •You need the basics on math and stats. • But the most difficult part can be simplified. 52
  53. 53. BigML, Inc #MLSEV: Online and Offline World in the Retail Sector: Friends or Enemies? / Good Rebels Questions? Now… or to miguel.blanco@goodrebels.com 53
  54. 54. 54

×