Using AI for online merchandising
Download as PPTX, PDF1 like257 views
The document discusses the potential of AI in online merchandising, emphasizing its role in enhancing revenue growth for e-commerce teams. It outlines the limitations of traditional approaches and highlights the need for organizational changes to effectively implement AI solutions. A report is available for further insights into how AI can transform marketing strategies.
Using AI for online merchandising
- 1. 1 #DigitalPriorities Digital Marketing Priorities 2019 brought to you by Discussion: The opportunity of AI for online merchandising Dr Dave Chaffey, Smart Insights Andrew Fowler Country Manager, Apptus UK
- 3. 3 The big question ‘With all the AI options available, why haven’t more e-commerce teams adopted this technology more readily?’ 55% of retailers investing in AI report substantially accelerated revenue growth Source: Oxford Economics report
- 4. 4 Agenda • The challenge and the opportunity of AI? • Limitations of traditional online merchandising • How does AI impact online merchandising • How and why not all AI solutions are the same • Organisational changes needed by AI? • Q&A
- 5. 5 Our new report Download: https://www.apptus.com/reports/making-a-case-for-ai-in-online-merchandising
- 6. 6 Understanding the challenge and opportunity
- 7. 7 What is online merchandising A (very) simple example
- 8. 8 Exploiting the long tail
- 9. 9 1 2 3 Etc 4 x 3 x 2 x 1 = 24 Only 4 products to rank 1 2 Etc 10 x 9 x 8 x 7 x 6 x 5 x 4 x 3 x 2 x 1 = 3,628,800 Only 10 products to rank The true complexity
- 10. 10 The limitations of traditional online merchandising?
- 12. 12 PRODUCT AND CONTENT DATA RULES AND ALERTS CUSTOMER SEGMENTATION CUSTOMER BEHAVIOUR RESULTS ANALYSIS BUSINESS OBJECTIVES BUSINESS OBJECTIVES Automation Traditional rules-based approach
- 13. 13 House keeping update • A recording for the webinar will be sent via Email • Slides will be available via Smart Insights Slideshare • Please get involved: • Do ask questions at any point via the Questions panel • Q&A at end
- 14. 14 How does AI impact online merchandising?
- 15. 15 PRODUCT AND CONTENT DATA INSIGHT FROM BEHAVIOURAL ACTIVITY Automation Exposure Strategy Advanced Algorithms Predictive Analytics Machine Learning Machine learning is the science of getting computers to act without being explicitly programmed Predictive analytics is the branch of data mining concerned with the prediction of future probabilities and trends The AI-based approach MONITORING & “LIGHT TOUCH” INTERVENTIONS BUSINESS OBJECTIVES
- 16. 16 Search term persists for re-use Search terms in “normal” font Suggests products based on AI analysis of behaviourClearly shows that there are more results available Example
- 17. 17 Search term – “Red dress” Before After
- 18. 18 Filters now above list (as per mobile approach) Ranking sequence influenced by “red” and AI analysis based on behaviour Ranking sequence is dynamic based on behaviour (AI). Caters for trends
- 19. 19 How and why not all AI solutions are the same
- 20. 20 Using AI for spotting trends 10 1 4 6 8 9 5 7 32 Consistent seller Hot seller Trending Trending Consistent seller Trending Consistent seller Consistent seller Consistent seller Hot seller
- 21. 21 Predicting the impact of a change of strategy
- 22. 22 Organisational changes needed by AI
- 23. 23 How could AI change the way you work? 25% 35% 25% 15% 25% 15% 10% 50% Current Work Allocation New Work Allocation Assuming a 37.5 hr week, 55.5 hrs of additional “creative time” per person per month
- 24. 24 For more, details, see our new report Download: https://www.apptus.com/reports/making-a-case-for-ai-in-online-merchandising
- 25. 25 Q&A - Your questions please! • Thank you for listening! • Please ask questions via the Questions tab • Include contact details