The Accuracy of Amazon Product Research Tools

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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