Repricing Experiment – Part 2: The Results


Today’s blog post is long overdue.  Many of you have been asking (pestering and nagging may be more accurate terms, but I finally listened!) for an update on my repricing experiment, and I’m excited to share those results with you.  So… let’s bring on the data!

Setting the Stage:  If you’d like to read the full back story about the repricing experiment, you can check it out here.

For those who would prefer the Cliffs Notes, here they are:

  • Sample size – 2 batches of 100 books each.
  • Matched pairs – I assembled similar batches of books to give an accurate comparison. If I found two books ranked 1.2 MM that I would price at $14.99, I split them apart and put one in each batch.
  • Batch metrics:
    • Batch 1 – average rank: 678k, average list price: $16.50
    • Batch 2 – average rank: 650k, average list price: $16.46
  • Blind pricing – I priced both batches as I normally would, without knowing which batch would be the control group and which one would be repriced automatically.
  • Coin flip – A 1985 US quarter was used to select which batch would be repriced, and Batch 2 won the toss and elected to receive. Tails never fails!
  • Repricer settings – RepriceIt was the software I selected, based on feedback from dozens of other booksellers I trust. I employed basic settings as follows:
    • Inventory was repriced three times a day (morning, noon, and night)
    • Software analyzed FBA offers only, MF prices were ignored
    • Condition was ignored, to give a better chance for the software to actually “see” competitive offers (plus I don’t believe condition matters all that much)
    • Floor price was set at $7.99

Hypothesis:  A quote from my original post: “My hunch is that I will sell more books out of Batch 2 but I will sacrifice price to do so.  The question at the end of this experiment is whether or not the loss of price is worth the additional unit sales.”

My hypothesis factored in Amazon’s API limitations, which mean that if there are no FBA offers in the lowest 20 offers, then the API won’t return those values.  Thus, because I wanted to compare my prices to FBA offers only, in many cases I figured the repricing software wouldn’t be able to “see” any competitive offers and wouldn’t be able to reprice many of my items.

I do believe a repricer plays a crucial role in moving older inventory.  If a book hasn’t sold in six months, you can compare it to MF offers in an effort to flip it quickly, even at a lower price.  Now that Amazon has removed the single-unit exemption for long-term storage fees, it’s critical to sell older inventory instead of waiting for the right Prime buyer to come along.  Although the long-term benefits of using a repricer are clear to me, I believed there would be minimal, if any, short-term benefits.

Experiment Results:

Units sold over time – I thought Batch 2 would sell more items than Batch 1, but perhaps only marginally so.  Here’s the chart of units sold over the first six months:


As you can see, Batch 2 beat out Batch 1 early and often.  By the end of week four, Batch 2 had nearly double the sales of Batch 1 – 28 compared to 15.  Even after three months, Batch 2 had 25% more sales than the non-repriced batch.  It’s hard to argue with those metrics.  So far, the repricer seems to be earning its monthly fee.

But surely the repricer would have to drop prices significantly in an effort to earn those extra unit sales, right?  Let’s take a look.

Price change over time – If the repricer gave up too much price, it could potentially wipe out any gains experienced from the increased unit sales.  After the first week, I thought my hypothesis was going to be spot on, as the repriced batch had sold 6 more books than the control group, but had dropped prices by 5% on average to generate those sales.  Go me!  But as I was in the middle of patting myself on the back, the week two results came in.  That week, the repricer actually earned me an extra 9% compared to my original list prices, which brought the cumulative price change up to a positive 1%.  Wowzer.

By the end of three months, the repricer had actually earned me an additional 1% compared to my initial pricing.  Here’s how the chart shook out.  You’ll notice that in months five and six the prices had begun to drop a bit, which is to be expected with older inventory:


How many items were actually repriced?  After 3 months, Batch 2 had sold 53 items.  Only 32 of those had different prices than the initial list price.  This means that 21 items – or 40% – were NOT repriced, either because the software agreed with my price or because it couldn’t “see” enough FBA data to reprice them.

Out of the 32 items that were repriced, here are some interesting insights:

  • 11 items were sold at higher prices, for a total gain of $52.95 ($4.81 per book increase)
  • 21 items were sold at lower prices, for a total loss of $43.82 ($2.09 per book decrease)
  • Net price INCREASE of $9.13 overall

So not only did I sell MORE items, but I actually sold them at an overall HIGHER price than my original list price!  There goes my hypothesis…

Total sales over time – Let’s look at how the sales stacked up over time between the two batches:


Batch 2 had $120 in extra sales compared to Batch 1 after the first four weeks.  After six weeks, Batch 2 had an astonishing $206 in additional sales.  Those increased sales mean you can turn a profit faster and pull more money out to buy more books, pay your mortgage, etc.  And honestly, apart from Notorious B.I.G., who doesn’t want more money?

Recommendations:  This data really blew my mind.  I had been holding firm to my beliefs that the API limitations would render repricing software virtually useless.  And even once I saw the results, I was still trying to find reasons to disprove them.  It’s a small sample size, with only 100 items in each batch, but it’s hard to argue with the results from my experiment.

I still believe it’s important to price your items carefully at the time of listing, since 40% of the items sold were not repriced at all.  But I intend to challenge that assumption as well by running another test where I price a batch at $200 and allow the repricer to kick in from there.  Stay tuned…

What are YOUR experiences with repricing software?  Does this data make you reconsider your strategies?  For me, it does.  Remember to trust the data.  If not, your mind can easily lead you astray and cause you to mistakenly hold on to your misguided ideas.


Disclaimer:  I am not affiliated with any repricing software, and make no commissions or referral fees if you choose to sign up for any of them.  I’m writing this article based solely on my experience with the software from, and I desire to share those results with a wider audience.  If the founder of RepriceIt wants to reward me with a branded t-shirt, or a lifetime supply of golf tees, I wouldn’t turn either offer down!


  1. Great news. Clear-headed, too. Thank you for putting the time in and sharing. This is really very useful info to me and I expect to many more. Definately want to see what the software does when you start at $200. I have assumptions about that, too. But that is the holy grail for me, to not even have to price at all when listing. Haven’t been able to make it work to my standards. Seems to work for Nathan Homlquist, though. Thanks again.

    • Thanks for reading! Even if a standard price of $200 worked for 60% of the items, it would save you some time initially pricing items that would have been repriced anyway. The data nerd in me wants the actual data at the time of listing so I know my average list prices and can analyze the quality of a sale or thrift store. The key for me is giving up some control in exchange for processing more titles…

  2. What do you think about the new AZ repricer?

    It can see all the FBA info, but has less options right?

    Maybe you can experiment with that too?

    • The Amazon repricer has too many fundamental flaws for me to use it. First, it can never reprice up, only down. The larger issue is that if two people are competing, there is no slow “race” to the bottom – the software simply picks a winner and leaves the other person at their established minimum. For example, if there’s a book where the lowest FBA offer is $19.50, and Seller A puts their minimum price at $8.50 and Seller B puts their minimum price at $9.99, Amazon’s repricer will knock Seller B’s price down to their floor of $9.99 and put Seller A at $9.98. Once Seller A sells their copy, the repricer will not bring Seller B’s price back up to the market price of $19.50 – it will leave them exposed at $9.99, leaving too much money on the table for me to consider it.

  3. I see two things in this data.

    1) There is a spike in both # and $ for Batch 1 between weeks 12 and 13. Without access to the granular data, we can only assume that this is an anomaly which should be smoothed, perhaps even removed, for a proper statistical look at this data. Some consideration needs to be taken, at any rate, because it is also the only large jump that was not mirrored in the Batch 2 data. There had been a similar jump between weeks 10 and 11, but this was seen in both batches, so makes sense.

    2) By week 4, Batch 2 had already made all the difference (in $) that it would make by the end of week 24. It had also sold nearly twice as many units. This makes sense when you think about it. The repricer had made a certain set of units (probably good to mid sales ranked items, but we don’t really know) more desirable to buyers. But it sets up a problem with the rest of the test.

    Batch 2 had already sold 28% of its inventory, while Batch 1 had sold only 15%. Since it is likely that the faster-selling units were the ones selling this early in the test, we have effectively removed twice as many fast-selling units from Batch 2. We can then expect that Batch 1 will still sell all of the similarly ranked items long before week 24, meaning that there will be little difference seen in the final data.

    From week 4 forward Batch 2 will have not only worse-ranked units to sell (because the good ones sold so soon), but it will also have fewer units left to sell overall. With only 70% of its original titles left, and with them being a lower sales rank, we can expect Batch 2 to sell more slowly and then for Batch 1 to catch up over the next 5 months. And this is exactly what happened.

    So, my interpretation of this data? The repricer did a good job of improving sales for the better ranked units, but performed only on-par for the longer tail units.

    This is good news. It means that the repricer, in the end, returned the same ROI. But it did so in such a way that, had the units been replenished to the original count of 100 at the end of every week, would have compounded greatly over the total course of the test.

    Disclosure: I do not use a repricer, but have just been convinced that I should.

    Thank you for publishing data like this!

    • Very astute observations, Jeff! You’re spot on that both batches end up with similar ROIs at the end of the 6 months, but the repriced batch returns profits to the business faster which can then be used to buy and flip more titles. Turn rates are critical in this business!

    • Man you guys are way to smart for me. But thanks for the great input.

  4. Excited to see the 200$ one. Will be back in 2 years

  5. Thank you so much for this data. I’ve been on the fence about repricers and now I think I’m going to try one. Can you share your repricer settings? Or where you got them from? Thank you!

  6. Just a thought, If we all started using repricers, wouldn’t it be a race to the bottom?

    • Thats why you set to match fba price instead of undercut, but most sellers dont do this and thus create the race to the bottom.

  7. I don’t sell books in volume these days and what I do offer is MF. To continue my contrariness, I reprice manually, no more than once per day. I think 3x repricer is pushing the price down which seems counter intuitive.

    I also don’t like to reprice books daily with a rank over 400,000. Once a week is enough IMO. These books are generally falling out of favor and not in demand. So I believe that hammering the price down might make the title more attractive . But if nobody cares… and the price decline continues en masse, for 2-3 months , that title is greatly discounted for 1 or 2 buyers that have casual interest.

    We could say that its good for a buyer to get that bargain. But I think , as a group of many sellers repricing frequently, we may have been over aggressive on repricing.

    I know there has been 1000’s of discussions about re-pricing. But I hold the position that if you do a certain level of re-pricing manually you will have better knowledge
    of what the health is of your book inventory.

    Another point- seasonality is a big factor. Oct my avg book sale was $16. For Nov it is $13. And my book sale volume increased 20%. Half of that (20%) is due to ‘ changes in purchase inventory Oct vs Nov. But I am working harder for more sales, prices are certainly dropping on comparable titles on the MF side.

    I think we will see a Dec gift effect on books- but the book prices will be lower than they should due to the ‘psychology of seller re-pricing ‘.

    I expect almost everyone to have a somewhat different experience since most here FBA. But I do go by my #’s. Thanks

  8. This is great Caleb! I have been playing with RePriceit for several months but still haven’t let it go live. Instead, every couple of days, I run reports, go through them, check and recheck what they want to do, and then accept their suggestions on most of them (not all, but most). I think I can let go and give control over to the software. Thanks for your time and effort tracking this!

  9. Caleb, great post. My experience with a repricer: first time, horrible. I rushed it, didn’t study enough, etc. Dropped it within the 30 day free trial. Second time: totally different. Read Manny Camaano’s book on repriceit which really helped me to understand much of the process and structure. As a result, I now run only ONE template, for aged stuff, 6 months and over. I do not reprice compared to MF at this time, just FBA, but may do it as we get closer to the Feb. 15 LTSF. Looking back, I don’t see how I could have possibly repriced all this stuff by hand. Really cleaning out the old stuff without giving it away, and not causing any races to the bottom, it just puts the price in the sweet spot that I want…90% of the time, definitely NOT 100%. Has really increased sales, and every book I sell now over 6 months old is saving me approximately 38 or 40c in additional storage fees. That’s my experience so far. Plain and simple.

  10. Well there you go; I’m getting a repricer software. Thank you so much Caleb. I ‘ve been on the fence and now overwhelmed with the manual process that I’m behind in my repricing. Frankly, I’m relieved because your information has helped me. The comments have added a lot of insight as well. Thank you all!

  11. Caleb, your disposal rate should also decline as a result of having for relevant pricing.

  12. Excellent, valuable post. I would like to point out the many times I have sold a book because I DIDN’T reprice it, and everybody else’s repricers adjusted the book price above mine, sometimes even the merchant-fulfilled offers. It happens sometimes. However the new Amazon storage fees put more urgency to sell faster so your data is useful

    • Yeah I wrestle with that – you’re never going to win a repricing battle with the larger sellers, many of whom have custom software that reprices nearly instantaneously. But if you don’t reprice at all, you could risk sitting on duds more than selling the occasional book at a higher price point. Just my $0.02.

  13. How do you keep track of what the price was before using RepriceIt and the price it was sold for? I’ve started using reprice it, but when items sell now, I’m unable to tell if it was sold above or below my original listed price.

  14. Caleb, what was your profit like on each of these books?

  15. Found it! Thank you for the follow up. How do I learn to set up the repricer? I am not on facebook so joining the group mentioned above won’t work for me. I can see how this would be useful to keep my books priced at what is selling so they aren’t sitting there for 6 months. I also spend a lot of time manually repricing, which is good experience but is boring. Can you see what books are not being repriced so you can manually check them yourself? In Batch 1, did you leave all prices alone or did you continue with your manual repricing on those items?

  16. So by the end of the experiment Batch 2 had a sell through rate of 8% more? is that correct or am I interpreting it incorrectly?

    How much did using a repricer increases sell through rate on average each month?


    • Check out the chart about halfway down – it shows cumulative percent sold per week. Yes, Batch 2 sold 8% more in total, and got off to a faster rate of sales early in the process.

  17. Thanks for this post. Very helpful.

    I’ve been running RepriceIt for about 2 weeks now and I haven’t made a single sale (about 280 books in my inventory). I’m very frustrated with it. I’ve been pretty much matching the lowest FBA offers.

    The biggest problem I have with it though is that it will not find enough competitive offers on a LOT of books. I set a unique default price and then created a second template to go in and grab only the books at that default price and compare them to FBA and MF offers. The thing is, that second template never seems to work. I end up with a bunch of inventory priced high and then Amazon deactivates a lot of my listings. Grrrrrrrrr. I’m so frustrated with it. Can anyone help?

    • Check out Manny Caamano’s repricing eBook on Amazon, or find him on Facebook and ask him questions. Try lowering the number of competitive offers. If the API can’t “see” enough data (which is the case nearly 50% of the time), then it can’t reprice your inventory. All of the repricers have this same limitation.

  18. Hey Caleb, Thanks for all of your helpful info! 🙂 How do you handle pricing and repricing textbooks and other items with seasonal spikes in prices? Or stuff that for other reasons may benefit from a closer eye on the pricing and repricing? Thanks! Of course I’m interested to hear how others do this too. Currently I’m using Amazon’s repricer but that costs a lot of time.

    • Pricing is a tough nut to crack. In general, you can drive yourself crazy if you go in and look at your prices every few hours. There are larger sellers with “bigger guns” who will beat your prices just as soon as you lower them. I go in about mid-August and early September and reprice all of my textbooks by hand (it’s a good excuse for a Netflix day!), otherwise I mostly leave textbook prices alone.

  19. So in the end how did your profits relate to the cost for the repricing tool?

    • It’s hard to make true comparisons when you only have 100 books in your test batch. The more books you have in inventory, the more a repricer can assist you, especially in re-positioning your old inventory to keep it moving.

  20. Caleb, I’d love to know if you ran that experiment you mention at the end of the post where you price everything at $200 and then let the repricer do its thing.

    That’s what I’m currently doing right now and I’m having issues with it seeing enough competing offers. I’m really dreading having to go in and manually reprice about 2000 books.

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