Greetings, fellow flippers!
Side Note 1: I’ve been busy working on a few software projects (related to books) and have been neglecting the blog. It’s time to rectify that with today’s post! (If you’re interested in learning more about these software projects, you can fill out the brief survey here, and I’ll even select a few of you to help me out with some beta testing.)
Side Note 2: I’m curious if any of my readers have fully embraced the 100 book weekly challenge. If you’ve jumped right in and have a success story to share, I’d love to hear from you! Please drop me a line at firstname.lastname@example.org and I may even feature you on a future blog post…
The Back Story: There have been a lot of questions circulating around the bookselling community related to the use of repricing software. Since I’m a self-proclaimed “Data Nerd”, I wanted to see if there was any substantial data out there in support or in opposition to using a repricer. My search came up empty, so I decided to kick off my own experiment to analyze the effects of repricers on my sales and profitability.
Before we get into the details of the experiment, let’s make sure we’re on the same page about repricing softwares.
What Does Repricing Software do Anyway?
In a fluid market such as Amazon, prices are constantly changing. For example, your book may have had the lowest FBA price of $14.99 when you listed it a month ago. When you pull up the listing today, however, you may discover that a half dozen other sellers have undercut your price.
In this situation, you would have two viable options:
- Lower your price to be more competitive – and hopefully get the sale more quickly
- Leave your price the same and wait for the lowball offers to sell out
Basically, a repricing software handles this price adjustment for you automatically, based on the pricing parameters that you select when you set up your account.
Side Note 3: If you want to read a controversial article by Peter Valley on the topic of undercutting other FBA sellers, you can check his post out here.
I won’t dive into the “ethics” of pricing in this post… but let’s just say I believe strongly in the free market. This is America after all – price your inventory as YOU see fit!
The Catch: On the surface, these software solutions seem like great time-saving tools, especially if you have an inventory of several thousand items. Who wants to spend their precious time combing through that many items every few weeks?! Once we look deeper, though, there are a number of reasons why a repricer may not be such a wise business decision after all.
- Software glitches – Software tends to malfunction from time to time, and if you are trusting your entire inventory to a repricing algorithm you may lose out big time if a glitch occurs. Check out this story about some glitches that occurred with RepricerExpress where they dropped the prices all the way down to a penny for thousands of their customers’ items. I’m not trying to use scare tactics to convince you to avoid repricers, but the threat is out there. What’s worse, you won’t be getting a penny back (pun intended!) from the repricing companies (unless you know a great lawyer), so the losses will come entirely out of your own pocket.
- Added costs, unknown benefits – Depending on which software provider you select, the monthly costs can run as much as $30-$150 per month. Will they increase your sales? Most likely. But will you lose out on more profits than if you waited it out and eventually got some of those sales on your own? No one knows for sure.
- Amazon’s API limitations – Regardless of how you feel about the above two points, the major shortcoming of EVERY repricer currently on the market is the limitations on the data that Amazon shares within its API. When applications send requests for pricing data to Amazon, they only receive the lowest 20 used prices and the lowest 20 new prices. If there are no FBA prices within these datasets, then your repricer won’t know how to price your items compared to other FBA offers. This is the same reason why your scouting apps sometimes show that there aren’t any FBA offers, yet when you click through to the Amazon page you may find more than a dozen FBA offers on the listing. If you are selling books FBA – and you should be – many of your listings won’t be able to be repriced based on these API limitations. Even if the software claims that it can price against only FBA listings, it can only do so if there are FBA prices in the lowest 20 offers. But the software companies won’t admit that readily on their websites, or fewer of us would sign up for their services. For that reason alone, I have been hesitant to jump on the repricer bandwagon.
Full Disclosure: Don’t cancel your repricer subscription just yet! Allow me clarify a few things…
- Repricers make a ton of sense for non-media items where you can actually get the coveted Buy Box. If you have inventory outside of books, you may get a lot of benefit out of using a repricer.
- I actually do use a repricer (gasp!) for inventory older than 6 months in an attempt to clear out some of my slower-moving items.
- I implement a floor price to avoid dumping my books at a loss. I’ve already made my money on those older books, so any increased sales are icing on the proverbial cake.
- I’m still working on the best solution for dealing with older inventory. A repricer may play a vital role in that process – only time will tell.
Alright, that’s enough background information on repricers and my philosophies on them. Let’s get to the good stuff!
The Experiment: To start with, I carefully assembled two batches of 100 books each. As much as possible, I split the books into matched pairs based on sales rank and my proposed FBA price. The goal was to make the two batches as close to identical as I could. I even put the same number of penny books into each batch, provided I could still list them FBA for at least $8.00. Here’s what the two piles looked like before I listed them:
I then proceeded to list the books using my normal pricing philosophies, but I coded the SKUs as Batch 1 or Batch 2 for tracking purposes. One important note: I did not include any textbooks in either batch since I price them completely different than “normal” books. Here’s how the batches shaped up:
- Batch 1 – average rank: 678k, average list price: $16.50
- Batch 2 – average rank: 650k, average list price: $16.46
Once all of the books were listed and sent to Amazon’s warehouse, I flipped a coin to determine which batch would be repriced and which batch would be left alone. The coin came up tails, so Batch 2 won the battle and will be subjected to daily repricing courtesy of RepriceIt. I set the parameters to only compare to FBA pricing, so many of the books in that batch won’t be repriced at all (due to the API limitations discussed earlier).
My Hypothesis: 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. Only time will tell!
Stay tuned as I’ll provide updates on this experiment over the next few months…
What are YOUR predictions on the outcome of this experiment? Leave a comment below to share your thoughts.
As always, happy flipping!