The Accuracy of Amazon Product Research Tools


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Greg Mercer of Jungle Scout is with us to talk through the accuracy of Amazon Product Research Tools and his approach to assessing this using real data in as transparent a manner as he can find so people can make their own judgements.

  • The accuracy of Amazon Product Research tools is the focus
  • Case study with spreadsheets and analysis to assess tools

The Case Study

  • Jungle Scout estimates the sales of any product on Amazon
  • First one to come out with it and the algorithms for estimating have changed over the years
  • The sales estimates are a key metric for users
  • Have invested in the data science around this with our internal data nerd team
  • How to prove the quality and accuracy of the algorithm
  • How to make a bullet-proof case study

Real Data against Tools

  • Got a bunch of Amazon Sellers to donate their data to JungleScout
  • Letting JS log into their Seller Central accounts of 50 Sellers with real data
  • Posted in FB groups and ads for people to join the sae study
  • Purchased all of the competitor tools and went into each person’s account and ran the tools against the data
  • Pretty hard to poke holes in this 80hrs of tools testing against the real sales data
  • Hired VAs to go through and run all the different tools
  • With the data we’re then able to show it to our customers
  • Had 50 Sellers in total share their data to assess the accuracy of amazon product research tools
  • Full breakdown of very detailed analysis
  • 100% transparent as we’re 100% confident
  • An overall error percentage with Jungle Scout coming out on top

Data Results

  • Unicorn Smasher error percentage was 92% so about as useful as flipping a coin
  • Estimating 1,000 units a month would really be somewhere between 80 and 2,920
  • So a free tool with data that is so far out is hardly worth it
  • Jungle Scout (25%)
  • Viral Launch is 2nd (34.34%)
  • Amaze Owl  3rd (44.29%)
  • Helium 10 4th (46.44%)
  • A re-cut of the data will be coming out again in Spring 2019

Tools Don’t equal success

  • Having the tool does not guarantee success but gives better insights into what products to select
  • Helps understand the demand in the market and niche
  • Using Unicorn Smasher with such a high margin of error impacts your ability to be successful in that niche

The Spreadsheets that assess the accuracy of Amazon Product Research Tools

  • You are welcome to use the data in any way you like to make your own assessment of the accuracy of amazon product research tools
  • Started with 20 different graphs and analysis of the categories
  • Decided the overall errors percentage was the best metric to help identify this
  • Presented with PHD level analysis in the spreadsheets and also presented more for the layman as well
  • You can do your own analysis of this data
  • The median overall error percentage is the best metric we’ve come up with

Jungle Scout Improves Accuracy

  • Going from 25% to around 12% on Jungle Scout
  • So plus or minus 12% on the data
  • Good to see Viral Launch in 2nd as a new entrant
  • Nice to see competition and raising people’s games
  • Jungle Scout has 3 x Full Time Data Scientists and one part time with 3 x PHDs
  • About £1m per year just to run these systems for sales estimates
  • The bigger players can invest more in this

Jungle Scout Supplier Database released

  • Releasing the Supplier Database feature in Jungle Scout this week
  • Import data into the US released through the Freedom to Data info
  • To let you know who the best factories are for them
  • Helps to find new factories and sources
  • Anyone with a Jungle Scout subscription will get access
  • Find out which factories your competitor is using
  • Look for best rated product on Amazon
  • Figure out their legal entity
  • Search in the Supplier Database for the factories as you know they are high quality already

Factors to look for

  • Quality is high
  • Trusted supplier
  • High quality product
  • Pricing quotes based on the competitor’s sell price
  • Speeds up the whole process and removes a pain point for Sellers

More Case Studies coming

  • Data Driven case studies coming
  • Launch tests on Giveaways, PPC, etc.
  • Actually doing the launches and reporting the data back as case studies
  • Do dispel myths and prove what works

 

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