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Feedvisor –The algorithmic repricing solution 
HOW WE LET OUR PRODUCT DESIGN ITSELF 
Feedvisor’s Revenue Intelligence Dashboard 
-a case study
Feedvisor –The algorithmic repricing solution 
A bit of Background 
•Feedvisor is a repricing solution for Amazon Sellers 
•We manage over 300,000 products, worth over $2b 
•We make over 25 million pricing decisions every single day, based on billions of data points.
Feedvisor –The algorithmic repricing solution 
A bit of Background cont. 
•Established in 2011 
•Mid 2012 –3 employees 
•Mid 2013 –10 employees 
•Mid 2014 –35 employees… and still growing! 
•Strong financial and technical backing from Israel and the US.
Feedvisor –The algorithmic repricing solution 
The customer demand 
•Customers wanted access to their data, to monitor their KPIs and make strategic decisions. 
•Prior to this, we’d use all their data for accurate repricing but hadn’t shown them their performance along the way.
Feedvisor –The algorithmic repricing solution 
Our challenge 
•Find out what data was the most critical to the customer. 
•Display data in a clear and accessible way, without overloading the user.
Feedvisor –The algorithmic repricing solution 
The answer –Organic product design 
•Essentially, we let the customers design the product. 
•They show us exactly what they want without us directing the process in any specific direction. 
•No initial interviews, questionnaires or prototyping (yes, we broke all UX/UI rules ).
Feedvisor –The algorithmic repricing solution 
Organic product design –the process 
•First, we gave the customer exactly what they asked for –the raw data! 
•It looked something like this…
Feedvisor –The algorithmic repricing solution 
Organic product design –the process 
•We told them to analyse the data however they wanted and to send it back to us with any calculations or formulas they had used in their analyses. 
•This is what they sent back…
Feedvisor –The algorithmic repricing solution 
Organic product design –the process 
•We then offered to pre-insert all these formulas and calculations for them. 
•We sent the data back to them and told them to analyse it again.
Feedvisor –The algorithmic repricing solution 
Organic product design –The process 
•We repeated this process numerous times, each time taking their comments and edits and improving our version of the spreadsheet. 
•This took over 10 iterations, over which time we added complex formulas, graphics, and even alerts!
Feedvisor –The algorithmic repricing solution 
What we learnt 
•This was the bestway to learn. Rather than the user telling us what they thoughtthey wanted, they showed us what they actuallyneeded. 
•We discovered exactly what the user caresabout. (stock, prices, inventory, sales, profits…) 
•We discovered exactly what the user needsin order to make decisions. (margins, trends, selling potential, replenishment…)
Feedvisor –The algorithmic repricing solution 
Traditional UI methods 
•We then reverted to traditional UI methods in order to tweak and refine our product. 
•Interviews, questionnaires and prototyping.
Feedvisor –The algorithmic repricing solution 
First 5 Sketches –Ordered by complexity
Feedvisor –The algorithmic repricing solution 
First 5 Sketches –Ordered by complexity
Feedvisor –The algorithmic repricing solution 
First 5 Sketches –Ordered by complexity
Feedvisor –The algorithmic repricing solution 
First 5 Sketches –Ordered by complexity
Feedvisor –The algorithmic repricing solution 
First 5 Sketches –Ordered by complexity
Feedvisor –The algorithmic repricing solution 
Final Sketches
Feedvisor –The algorithmic repricing solution 
Final Sketches
Feedvisor –The algorithmic repricing solution 
Wireframes
Feedvisor –The algorithmic repricing solution 
Wireframes
Feedvisor –The algorithmic repricing solution 
FINAL PRODUCT
Feedvisor –The algorithmic repricing solution 
THANK YOU 
Any Questions?
Feedvisor –The algorithmic repricing solution

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How we let our product design itself - Shmuli Goldberg, Feedvisor

  • 1. Feedvisor –The algorithmic repricing solution HOW WE LET OUR PRODUCT DESIGN ITSELF Feedvisor’s Revenue Intelligence Dashboard -a case study
  • 2. Feedvisor –The algorithmic repricing solution A bit of Background •Feedvisor is a repricing solution for Amazon Sellers •We manage over 300,000 products, worth over $2b •We make over 25 million pricing decisions every single day, based on billions of data points.
  • 3. Feedvisor –The algorithmic repricing solution A bit of Background cont. •Established in 2011 •Mid 2012 –3 employees •Mid 2013 –10 employees •Mid 2014 –35 employees… and still growing! •Strong financial and technical backing from Israel and the US.
  • 4. Feedvisor –The algorithmic repricing solution The customer demand •Customers wanted access to their data, to monitor their KPIs and make strategic decisions. •Prior to this, we’d use all their data for accurate repricing but hadn’t shown them their performance along the way.
  • 5. Feedvisor –The algorithmic repricing solution Our challenge •Find out what data was the most critical to the customer. •Display data in a clear and accessible way, without overloading the user.
  • 6. Feedvisor –The algorithmic repricing solution The answer –Organic product design •Essentially, we let the customers design the product. •They show us exactly what they want without us directing the process in any specific direction. •No initial interviews, questionnaires or prototyping (yes, we broke all UX/UI rules ).
  • 7. Feedvisor –The algorithmic repricing solution Organic product design –the process •First, we gave the customer exactly what they asked for –the raw data! •It looked something like this…
  • 8. Feedvisor –The algorithmic repricing solution Organic product design –the process •We told them to analyse the data however they wanted and to send it back to us with any calculations or formulas they had used in their analyses. •This is what they sent back…
  • 9. Feedvisor –The algorithmic repricing solution Organic product design –the process •We then offered to pre-insert all these formulas and calculations for them. •We sent the data back to them and told them to analyse it again.
  • 10. Feedvisor –The algorithmic repricing solution Organic product design –The process •We repeated this process numerous times, each time taking their comments and edits and improving our version of the spreadsheet. •This took over 10 iterations, over which time we added complex formulas, graphics, and even alerts!
  • 11. Feedvisor –The algorithmic repricing solution What we learnt •This was the bestway to learn. Rather than the user telling us what they thoughtthey wanted, they showed us what they actuallyneeded. •We discovered exactly what the user caresabout. (stock, prices, inventory, sales, profits…) •We discovered exactly what the user needsin order to make decisions. (margins, trends, selling potential, replenishment…)
  • 12. Feedvisor –The algorithmic repricing solution Traditional UI methods •We then reverted to traditional UI methods in order to tweak and refine our product. •Interviews, questionnaires and prototyping.
  • 13. Feedvisor –The algorithmic repricing solution First 5 Sketches –Ordered by complexity
  • 14. Feedvisor –The algorithmic repricing solution First 5 Sketches –Ordered by complexity
  • 15. Feedvisor –The algorithmic repricing solution First 5 Sketches –Ordered by complexity
  • 16. Feedvisor –The algorithmic repricing solution First 5 Sketches –Ordered by complexity
  • 17. Feedvisor –The algorithmic repricing solution First 5 Sketches –Ordered by complexity
  • 18. Feedvisor –The algorithmic repricing solution Final Sketches
  • 19. Feedvisor –The algorithmic repricing solution Final Sketches
  • 20. Feedvisor –The algorithmic repricing solution Wireframes
  • 21. Feedvisor –The algorithmic repricing solution Wireframes
  • 22. Feedvisor –The algorithmic repricing solution FINAL PRODUCT
  • 23. Feedvisor –The algorithmic repricing solution THANK YOU Any Questions?
  • 24. Feedvisor –The algorithmic repricing solution