The eBay “Best Match” Position Bias Modifier Hypothesis
In this article I detail further the idea further on a sudo “modifier” that maybe in-place on eBay to restrict or amplify the exposure, thus sales given to merchants as a “group”.
It is only now possible from the discussion in the earlier article titled “Why do eBay Sales Stay Consistent?“. If you’ve not read this article, then I strongly suggest you do as this recognises that there is a limitation to any marketplace and what the implication of this means.
This entire article is hypothetical. I question myself throughout the article and I’ll let you make your mind up if you think I am “on to something” or not.
I have toiled with this concept in the past, but now I am now even more certain that this is being used and I only now can I fully understand & comprehend the potential motivations behind this.
The hypothesis is:
Part of the “best match” algorithm on eBay modifies the sales velocity made by merchants (outside of the published factors) on a daily basis to share sales across multiple merchants.
Lets consider this for a moment, as we’ve already considered the ultimate boundaries of what stops a merchant from selling more product, over any single day there is a limited number of customers on a specific marketplace (eBay in this example, but applies to all).
For the sake of example 5% of all eBay buyers are looking to buy footwear today. Now there are lots of “footwear sellers” on eBay, so we’re going to narrow this down further to say that there is 1% of buyers looking for “mens work boots”.
Also for ease, I’m going to use the number of shops on eBay as a reference for the number of sellers with these products, a search here says that we have 180 matching stores, judging that the the numbers of items in these shops tail off pretty quickly and an estimate of 80 is fair. Also assuming that only 20% of eBay sellers are eTRS (Top Rated Sellers) then we’re left with just 16 sellers with matching products.
To summarise we have 1% of the total traffic of eBay looking for “mens work boots”, there are a lot of sellers with these products, however only approximately 16 worth while considering for this example.
Question 1 – What would I do?
I am now going to ask the question:
If I were eBay, what would I do?
What I would do and the results you’re probably seeing are about the same. Because exactly what I would do, is to share the buyers looking for ”mens work boots” across multiple sellers.
To clearly spell this out:
I would purposefully limit the sales across all sellers in a specific category, to keep them all busy.
Thus, 16 “happy sellers”, rather than just 1-2 taking all the sales and thus reducing risk, but still allowing the newer merchants to move up a scale over time.
Question 2 – Which factors?
I’d also take this a stage further and work out what is a sensible sales limit for each of them, like a score rating, but hidden. Some of these are going to be factors included in the published “best match” algorithm, but this is from a different view, a view to spread sales across multiple sellers on a specific day.
Taking into account the following factors:
- Age of the account
- Ratio of sales to ALL disputes (including PayPal)
- Use of a 3rd party tool/API usage
- If the seller has defaults on their listing/FVF fees
- eBay Shop level
- Number of items listed
- Account level (basic, enterprise and so on)
- Historical conversion ratio of views v’s sales
And lots of other factors that I have not thought of either (this list could be endless). However to form a profile of the seller, to essentially see how trust-worthy they are, what their capabilities are and where they are comfortable.
Using a quote from the ChannelAdvisor Strategy & Support Centre in the “Optimizing For eBay Best Match Results” article:
eBay incorporates the seller’s feedback information and overall performance as a factor in the Best Match search results. The Best Match algorithm gives a preference to users that have high DSR scores and policy compliance at eBay. Those sellers with lower DSR scores are demoted in the search results, which likely makes it even more challenging to achieve sales and improve the ratings.
With the SR2 release in September 2009, eBay introduced Top Rated Sellers as a new status to supercede the previous PowerSeller status. These sellers are promoted directly in the search results with an icon that denotes the seller is one of eBay’s Top Rated Sellers. As the seller account has very high performance on DSRs, the seller’s listings will already be preferenced and be at the top of the search results. With the additional notation from eBay that this seller is one of the Top Rated Sellers on eBay, it will influence the buying decision of shoppers on the site.
We already know that eBay take a number of factors into consideration when returning results already, this was indicated in quite some depth by Olivier Dumon in 2009 at the eBay DevCon, but they’ve removed the video’s from here.
Question 3 - And what would I do with these?
This is curious, because if you have a finite amount of buyers for a finite number of products on a specific day then, spreading the sales around the sellers would be beneficial as it would keep them all interested and busy. Which leads me on to “The Modifier”.
I’ve got a fair idea on how this would be implemented and this article is about the why and the how, so moving into the how, this is how I’d do the above.
At the start of each day I would give each seller a modifier. This modifier would increase and decrease the exposure rate of all the 16 merchants I used in the earlier part of this article for the keyword set.
Starting off with a modifier of 0.5 in the morning, then as the day progresses, I would decrease the modifier to slow sales for a specific merchant if they have already had a strong mornings worth of sales and inversely, if a merchant has had low comparable sales for the morning, increase the modifier, so that more traffic is delivered to that merchant.
This one has been bugging me for quite some time also and have enjoyed finally put it into writing and exploring it as I have formed this article.
We can all understand and would desire eBay to hold off/restrict sales from new merchants (as they do with selling limits), they’re untested businesses; however I’m not quite sure we’re ready yet to entertain the idea that seasoned merchants could also be under such limits also.
Google unlike eBay, who have left pretty hefty hints on what people should do to help them move forwards with their content & rankings. Beyond, what I class as the basics of DSR’s eTRS, recent sales, impressions (to sales ratio) and free shipping, very very little is known. This article could of course be complete rubbish and its unlikely we’ll ever find out.
Think of Bingo, but rigged. I’d work out who the top punters are and ensure that they “looked after”, but still leave room for others to also win and to become a “top punter”.
The overall game would to be deliver the results (sales) across all 16 merchants as evenly as possible over time, keeping within the factors I mentioned , so that all of them are kept busy, but not overwhelmed in a single day and allow the possibility for lower merchants to move up, over time.
I’m not suggesting this is a core modifier for results, however it easily could be a second or third level modifier behind eTRS, so that when “best match” is dealing with 16 top rated sellers that appear to be equal, this could be the deciding factor on who gets which sales (by product visibility).
I’ll leave you with this thought/question:
If it[eBay] was me, then I’d certainly entertain such a modifier to smooth out the risk and sales across multiple merchants. Would you?
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