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Data-driven strategies using customer intent trends | Sophie Moule | Figaro Digital Marketing Summit

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Read the full write up here: https://www.pi-datametrics.com/data-driven-strategies-customer-intent-trends/

Sophie Moule, Head of Marketing at Pi Datametrics, takes to the Figaro Digital stage to showcase the importance of customer intent and behaviour data in creating a commercially successful, business-wide strategy.

- Think of the customer needs first, and tech after
- Use search trends as customer research data
- Look at value not just volume
- Get organisational buy-in for your data, for aligned planning
- Integrate with other datasets for a truer view of customer intent

Published in: Marketing
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Data-driven strategies using customer intent trends | Sophie Moule | Figaro Digital Marketing Summit

  1. 1. Data-driven strategies using customer intent trends Sophie Moule Head of Marketing | Pi Datametrics @SophieMoule
  2. 2. 2@SophieMoule | @PiDatametrics | Pi-datametrics.com 3.5 billion searches Localisation Personalisation ‘Mobilisation’ The next “big thing” Voice Ai Where is the biggest opportunity?
  3. 3. 3@SophieMoule | @PiDatametrics | Pi-datametrics.com Biggest source of customer research available
  4. 4. 4@SophieMoule | @PiDatametrics | Pi-datametrics.com discover... commercialise... ...customer needs analyse... predict...
  5. 5. 5@SophieMoule | @PiDatametrics | Pi-datametrics.com Step 1 I Discovering customer trends I Beauty sector Body care Electrical Dental Fragrance Hair care Nails Makeup Skin care ‘Fragrance‘ searches peak during Q4 ‘Nails’ peaks in summer ‘Nails’ peaks again in Christmas ‘Hair care’ top category
  6. 6. 6@SophieMoule | @PiDatametrics | Pi-datametrics.com Step 2 I Commercialisation I Beauty Sector Body care Electrical Dental Fragrance Hair care Nails Makeup Skin care ‘Electrical’ is one of the most valuable categories ‘Makeup’ is also a valuable category ‘Hair care’ is 4th
  7. 7. 7@SophieMoule | @PiDatametrics | Pi-datametrics.com Step 3 I Spotting Patterns I Beauty Sector Body care Electrical Dental Fragrance Hair care Nails Makeup Skin care
  8. 8. 8@SophieMoule | @PiDatametrics | Pi-datametrics.com Body care Electrical Dental Fragrance Hair care Nails Makeup Skin care Xmas peak Xmas peak Xmas peak Xmas peak Step 4 I Analysing Patterns I Beauty Sector
  9. 9. 9@SophieMoule | @PiDatametrics | Pi-datametrics.com Step 4 I Analysing Patterns I Beauty Sector Body care Electrical Dental Fragrance Hair care Nails Makeup Skin care 3rd top Top categoryTripled over 3 years
  10. 10. 10@SophieMoule | @PiDatametrics | Pi-datametrics.com Step 4 I Predicting trends I Beauty Sector Body care Electrical Dental Fragrance Hair care Nails Makeup Skin care
  11. 11. 11@SophieMoule | @PiDatametrics | Pi-datametrics.com Who’s capitalising on these searches? - Beauty Sector Body care Electrical Dental Fragrance Hair care Nails Makeup Skin care
  12. 12. 12@SophieMoule | @PiDatametrics | Pi-datametrics.com Use search trends to build strategies Plan. Influence. Peak. Repeat
  13. 13. 13@SophieMoule | @PiDatametrics | Pi-datametrics.com P.I.P.R. I SEO TEAM Planning + publishing content Planning + publishing content Peak purchase Peak purchase Repeat?Evaluatewhetherthis isapeaktrendornot Repeat?Evaluatewhether thisisapeaktrendornot Influence customers in research phase Influence customers in research phase Example: “festival clothing”
  14. 14. 14@SophieMoule | @PiDatametrics | Pi-datametrics.com P.I.P.R. I DIGITAL DEPARTMENT Build value PR, Social, etc. Build value PR, Social, etc. Peak purchase re-target Peak purchase re-target Switchoff Switchoff Activate paid media during influence stage Activate paid media during influence stage Build cookie pool Build cookie pool Example: “festival clothing”
  15. 15. 15@SophieMoule | @PiDatametrics | Pi-datametrics.com P.I.P.R. I WHOLE ORGANISATION Review & optimise trading plan Review & optimise trading plan Key merchandising period Key merchandising period Peak Peak Discount/clearstock Discount/clearstock Example: “festival clothing”
  16. 16. 16@SophieMoule | @PiDatametrics | Pi-datametrics.com Measure success Example: Fashion retail
  17. 17. 17@SophieMoule | @PiDatametrics | Pi-datametrics.com Who’s winning in fashion retail? … have all experienced significant commercial success over the last year: ● Asos: Revenue up 33% (£1.88bn), pre-tax profits up 145% (£80m) ● Next results signal a good Christmas for UK retailers” Data for the date: 17 Jan 18
  18. 18. 18@SophieMoule | @PiDatametrics | Pi-datametrics.com Identify star performers... and what they have in common
  19. 19. 19@SophieMoule | @PiDatametrics | Pi-datametrics.com Put customer data first
  20. 20. 20@SophieMoule | @PiDatametrics | Pi-datametrics.com Give this data even more oomph! Integrate it with other datasets
  21. 21. @SophieMoule | @PiDatametrics | Pi-datametrics.com 21 Discussion and search trends Discussion volumes (Brandwatch) Search volumes (Pi Datametrics) Building a story - aligning datasets - Financial Sector: Personal Debt Matching trends: Users’ interest in debt peaked at the start of the year +
  22. 22. @SophieMoule | @PiDatametrics | Pi-datametrics.com 22 Student debt: Conversations (Brandwatch) Student debt: Searches (Pi Datametrics) Identifying external factors Financial Sector: Personal Debt Combining datasets can help identify when external factors are at play Discussion and search volumes: Student Debt +
  23. 23. @SophieMoule | @PiDatametrics | Pi-datametrics.com 23 Social Vs Search Topics +
  24. 24. 24@SophieMoule | @PiDatametrics | Pi-datametrics.com • Think of the customer needs first, and tech after • Use search trends as customer research data • Look at value not just volume • Get organisational buy in for your data - for aligned planning • Integrate with other data sets for a truer view of customer intent Key takeaways
  25. 25. Thank you Email: info@pi-datametrics.com Web: Pi-datametrics.com Twitter: @SophieMoule | @PiDatametrics

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