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Best Match

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eBay’s Best Match search algorithm has sellers up in arms because, in many cases, their auctions never make it to the first page of eBay’s search results. There’s been speculation on what the eBay Best Match algorithm considers when generating the order in which search results are listed. Forbes Magazinespeculates that search results are predominately a factor of seller feedback and powerseller status (effectively squeezing out the small eBay sellers). AuctionBytes has suggested that eBay’s Best Match algorithm might be a function of many things including: powerseller status, shipping options, feedback ratings and Detailed Seller Ratings, and use of item specifics in the description and the titles. A number of sellers on the forums have speculated even more conspiratorial theories of the factors they think are influencing the ranking algorithm. I’ve always been a fan of facts vice speculation and guesses, so I hit Google looking for some answers. After a few hours of research, I managed to track down eBay’s Best Match patent application.

The bulk of the patent application describes the relationship between search terms, the text in the auction title and how relevance and desirability are determined. The Best Match patent does describe other factors that can influence search result rankings including (but not limited to):

  • pictures available
  • seller ratings
  • price range
  • geographic proximity of searcher to seller
  • shipping prices
  • time left in an auction
  • number of bids
  • Buy it Now

Update – For a less technical explanation of Best Match, view Best Match Made Simple

The Best Match patent application describes how these factors can be included and weighted in the basic algorithm to influence the search results. Indeed, eBay has already announced that sellers with low Detailed Seller Ratings for shipping and handling would no longer rank highly in their search results — so we know this a factor that influences the algorithm.

But the base algorithm involves strictly auction titles and this is was we need to have a fundamental grasp of as we decode the eBay Best Match search algorithm.

The patent application describes the eBay Best Match algorithm as “a system and method to sort search results based upon [a relevance score and] a desirability value.” It goes on to say…

This desirability value may be based upon the difference between a demand value and a supply value. Demand may be based upon user activity such as click-through, purchases, price, or location. Supply may be based upon a supply of keywords that may be the number of times a word is used in search or item title. The system and method may include receiving a search query, associating a first numerical value with a keyword that is a part of the search query, tracking user activity associated with the keyword, associating a second numerical value with the keyword based upon the user activity, finding a difference value between the first and second numerical values, associating this difference value with the keyword, sorting keywords based upon the difference values, and returning the search results of the sorting.


Please allow me to attempt an explanation…

Determining Relevancy Score

When a visitor to eBay inputs one or more keywords into the search box, the search algorithm returns the auction listings with keywords in the title that match those included in the user’s query. The eBay Best Match algorithm now assigns a point value to each and every word in the title text string displayed to the user. Initially this point value is zero, but this will change based on the actions of the searcher.

Good Keywords Get Rewarded

If the user clicks on an auction title in order to view a particular listing, each of the words in that auction title are awarded a point. These points are used to evaluate the relevance of auctions in future searches. If the user takes further actions such as adding to watch lists, placing a bid, or actually purchasing the item up for sale, those words are awarded additional relevance points.

For example, if a visitor to searched for “iPod nano,” the default search results would return all auctions with the words “iPod nano” in the listing title. If the user then clicked on an auction with the title “Brand New iPod nano 4 GB Black MP3 Player Sealed,” each of the words in the title would be awarded a relevancy point. These points would accumulate over time and keywords that accrue more points would be considered more relevant in future eBay Best Match searches for the query “iPod nano” and help determine the sort order when the results are presented on the results page.

Bad Keywords Get Punished

The converse is also true. The eBay Best Match algorithm identifies unique key words in auction titles that don’t get clicked and assigns a negative point value to those words. It will only assign a penalty to those words that don’t match keywords in the auctions that do get clicked.

For example, if when our eBay user searched for “iPod nano” and clicks as described above, but does not click on the auctions entitled “New iPod nano leather case” or “Used iPod nano USB charger,” the words “leather,” “case,” “used,” “USB” and “charger” would receive negative points towards their relevancy score because the searcher did not click, add to watch list, bid or make a purchase auctions with those words in their listing title.

Keyword Relevance Scores are Determined over Time by User Actions

Over time, keywords develop a relevance value by accumulating positive and negative points. The more visitors to eBay that click on auction titles, place bids, add to watch lists, and ultimately buy, the more positive points are awarded to keywords in those auction titles and these words are considered more relevant to future searchers.

When eBay visitors fail to click auction listings with certain keywords in their titles, those keywords are considered less relevant and points are deducted from their relevancy score.

Keywords can have a negative score. If, over time, users who search for the “iPod nano” just are not interested in auction titles with the word “used” them, and thus hardly ever click on titles with that keyword, “used” will accumulate a significant negative relevancy score for that search query.

Calculating an Auction Listing’s Relevance Value

Although this is a simplification of the eBay Best Match algorithm, part of an auction listing’s relevance value is the sum its title’s keywords scores for that particular search query. Let’s say for the search query “iPod nano,” the keywords below have accumulated the following relevance scores:

  • iPod (1.39429)
  • nano (1.10132)
  • MP3 (1.11403)
  • New (1.08399)
  • Sealed (0.553271)
  • Case (-0.107664)
  • Used (-0.117723)
  • Charger (-0.173231)
  • 4GB (0.530753)
  • Player (0.86456)
  • USB (0.00000)

Note: These are hypothetical scores

Hypothetical Examples

Therefore the Best Match relevance value for an auction with the title, “New iPod nano MP3 player ~ sealed” would be 5.010141(1.08399 [new] + 1.39429 [iPod] + 1.11403 [MP3] + 0.86456 [player] + 0.553271 [sealed] = 5.010141).

A relevance value for an auction with the title “Used iPod nano USB charger” would be 2.204656(-0.117723 [used] + 1.39429 [iPod] + 1.10132 [nano] + 0 [USB] – 0.173231 [charger] = 2.204656).

Interestingly, the relevance value for an auction with the title “4GB iPod nano with charger and case” would only be 1.351178(0.530753 [4GB] + 1.39429 [iPod] + 1.10132 [nano] – 0.173231 [charger] – 0.107664 [case] = 1.351178). Even though this is probably a better value than the first example (because it includes some accessories), this auction has a lower relevance score because it includes the words “charger” and “case” in the listing title. In our hypothetical example, these words have a negative relevance score for the search query “iPod nano,” because bidders who use this term have been more interested in the actual MP3 players than auctions for just accessories.

Determining Desirability

Another factor influencing eBay’s Best Match search results is something termed “desirability.” This is a relatively basic function of supply and demand. If most searchers using the query “iPod nano” are actually looking for the MP3 player vice accessories then demand for auctions selling MP3 players is high. If most of the listings with the keywords “iPod nano” in the title are actually auctions for accessories, then the supply of iPod nano MP3 player auctions is low.

Supply and Demand

Thus auctions for items in which demand is high and supply is low are considered “desirable” and score highly for desirability. Auction listings with a high relevance score and a high desirability score are going to rank higher in the Best Match search results than auctions with a lower combined score.

Auction where supply is high and demand is low are going to score poorly for desirability.

How Supply is Calculated

According to eBay’s Best Match patent application, “the total occurrence of every unique keyword in all the titles is first determined. Then the percentage occurrence of each keyword in the result set [(the auction titles)] is determined. For example, if there were 1000 items in the results [for the search query ‘iPod nano’], and the word ‘charger’ occurs in 900 items, then the supply percent of charger is 90%. If the keyword ‘player’ occurs in 50 items, then its supply percentage is 5%.”

How Demand is Calculated

“The percentage that each keyword is used in an activity data set, [‘demand’], is calculated in the following manner. Activity data is collected on a daily basis, data that includes activities such as clicked, bid, bought, or added to watch list… are associated with keywords used in item titles. For example, if for the query ‘iPod nano’ 1000 click-throughs are collected and we know the item title of each one, then the occurrence of every unique keyword in this set of titles is calculated. The percentage occurrence of every keyword in the same set is calculated. Thus, if the keyword ‘charger’ occurred in 100 of these 1000 titles, the percentage of charger in the ‘demand’ is 10%. Similarly, if ‘player’ occurs in 950 titles, its demand percentage is 95%.”

Calculating Desirability

The formula provided in the Best Match patent application for calculating “desirability” is as follows:

Desirability = log2(1.0+(dw*d))-log2(1.0+(sw*s))


  • d= demand
  • dw = demand weight
  • s = supply
  • sw = supply weight

The patent application notes that demand weight “is set to 3 by default,” while supply weight “is set to 1.” This means that demand is three times as important than supply when calculating desirability in the eBay Best Match algorithm.

Putting it All Together

The patent application is particularly vague in how the Relevance Score and Desirability Score are combined to produce a value that is used to determine the ranking in the Best Match search results. Obviously, a higher combined relevance and desirability score will rank higher in the search results than lower scores.

Additional Factors Affecting Best Match Search Result Ranking

Recall that the patent also mentions other factors that can influence the final Best Match search results placement. The factors specifically mentioned include:

  • Price range
  • Geographic proximity of seller to searcher (as determined by the seller’s address on record and the IP address of the searcher’s computer)
  • Time until auction close
  • Number of Bids
  • Seller Feedback
  • Pictures
  • Buy it Now
  • Current price compared to average sale price (is it a bargain?)

The patent specifically mentions that these factors could be weighted differently or not at all depending on corporate decisions and that additional factors could be included. We already know that sellers with low scores in their Detailed Seller Ratings for “Shipping and Handling Charges” are receiving, according to eBay “considerably reduced visibility.” This means that their auctions are buried in the search results. Therefore at least one aspect of the Detailed Seller Ratings is a factor (with substantial weight) in the eBay Best Match search algorithm.

Optimizing Your Auction Listings for eBay’s Best Match

Just as webmasters optimize their web pages for Google, eBay sellers can optimize their auction listings for Best Match search results. Your objective here is to be at the top of the first page of the search results.

The area in which the seller can exert the most influence on their Best Match ranking is the title. The title has always been important, but now it’s even more critical.

You’ll need to do a little investigating to determine what words to include in your title, and just as importantly – what words to exclude.

Search for an item on eBay, but put yourself in the buyer’s shoes when you think of the term that you are going to enter into the search box.

Next, sort by Best Match if the search results are not already sorted in that manner.

Take a note of the words used in the titles of the auction listings returned on the first page of the Best Match search results.

Now go to the middle of the Best Match search results and note what words are in the titles of the auctions listed. Does anything stand out?

Finally go to the last page of the Best Match search results and note the words included in the auction titles there? Does anything stand out?

Determine the Good Keywords

Are there any words that are more prevalent in the titles near the top of the search results that are less prevalent in the middle and the bottom of the search results? If so these are good keywords that have a high positive relevance score.

Determine the Bad Keywords

Are there any words that are more prevalent in the titles near the middle and bottom of the search results that are less common in the titles of the auctions that made it to the top of the list? These are bad keywords that have a low or negative relevance score.

Include the Good and Avoid the Bad

You want to avoid including keywords you suspect have a low or negative relevance score and include those keywords that you think have a high relevance score.

Important– Only include keywords that apply to your auction listing. Including keywords that are irrelevant or misleading just because you suspect they have a high relevance score is considered keyword SPAM. eBay is quick to cancel auctions that SPAM their auction titles and competing sellers are quick to report offenders. As eBay’s Best Match search algoritym matures, auctions with titles like “like NEW MP3 PLAYER better than IPOD NANO” are apt to be cancelled or penalized in some manner as to make them irrelevant.

Other Factors You Might Influence

As you explore sample auctions that rank well or poorly in eBay’s Best Match sort results, take note of other things that might be influencing the results of the algorithm.

  • Are there pictures? How many? Are they hosted by eBay’s picture services or some external host?
  • Is there a Gallery image? Any other features?
  • How long until the auction ends?
  • What are the shipping costs?
  • Etc.

You might just notice patterns that will tip you off to some of the different factors that are currently influencing the Best Match search algorithm. Some of them you may be able to influence and some of them you might not. Concentrate on the affecting the things that you can change.

Experiment. Build on your successes and learn from your mistakes.

Star Wars Comic Case Study

Briefly examining the Best Match search results for the query “Star Wars Comics,” a couple of things jump out at me. The keyword “lot” (ie more than one comic) is obviously a term with a high relevance score because the majority of the titles on the first page of the search results include the term. Jump back to page five of the search results, we see many of the same comics, closing during the same timeframe that have the keyword “pack” or “pak.” They are offering the same deal (a bundle of comics), but obviously the algorithm considers the keyword “lot” more relevant than “pack.”

Lesson:Sell comics in bundles and use the term “lot” in the title. Avoid the term “pack.”

Additionally, the time until the auction closes is also a factor influencing the listings search rankings. The first 4 pages of search results are pretty much limited to auctions closing in the next 48 hours. The next 4 pages include auctions that are closing in 72 hours.

Lesson: Consider the 3-day auction span to keep my auction near the top of the listings throughout.

All but two of the listings on the first page had shipping prices specified. As you went deeper into the search results, a greater percentage of the results listed the shipping costs as “not specified.”

Lesson: Specify the shipping and handling rate in the form when you are listing an auction. Simply including the shipping charge in the item description appears to be insufficient under Best Match.

The Bottom Line

Just remember, the Best Match search algorithm is about making eBay money. They want to feature the auctions that are most likely to result in a click, in a bid, and ultimately a purchase. So they want to put the auctions in front of the potential bidder that are most likely going to result in those actions.

Your objective now is to make sure that eBay puts your auctions at the top of their Best Match search results – so you, along with eBay, get the click, the bid, and the sale.

Good Luck!


28 Responses to “Decoding eBay’s Best Match”

  1. tekgems on January 20th, 2008 10:11 am

    Thank you – this is excellent analysis on Best Match. It’ll be interesting if sellers that sell iPod Nano Cases & Chargers will exclude the “poisoned” words (stop words) to score their relevancy higher on short keyword searches (e.g. iPod Nano instead of iPod Nano Case).

  2. Randy Smythe on January 20th, 2008 10:32 am

    Thanks for the research. In theory Best Match will learn over time and search results should improve.

    I agree that sellers need to re-evaluate their listings, keywords, etc to improve their position. As long as eBay grows listings and grows GMV this will eventually become the default sort on all of eBay. If they make it default for the entire site you will know that it has improved their numbers so as a seller if your number have not improved you have some work to do.

  3. Steve L. on January 21st, 2008 10:13 am

    Great post! Your hard work is appreciated. I wonder if the SEO experts will add eBay to their list of services.

  4. Warning: Don’t write off eBay’s Best Match just yet » on January 21st, 2008 1:46 pm

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  6. bits-n-pieces on January 22nd, 2008 4:48 am

    Once again this is a case of ebay trying to push a round peg in a square hole. This ranking may work for new items where there are lots of listings for basically identical items but it totally falls apart in the antiques and collectable categories. The word pottery or glass returns 10’s sometimes even hundred’s of thousands of results but by the criteria you have explained will carry a high value which is think will be out of proportion to returning good results. Very few of my customers are geographically near me – lots from overseas and majority of US are more than 800 miles away. Why should location matter in the least. Buyers can already exclude item locations and include ships to info. When I search, I want to see the results I have asked for, not some compilation of what everyone else has been looking at. The paltry number of characters we are allowed in titles will make it very difficult in many categories to include enough differentiating keywords to make this work the way ebay thinks it will. Those of us who sell a wide variety of items will not have the time to do indepth research of search results for every item we want to list. I hate this whole concept, both as a seller and a buyer!

  7. AuctionWire on January 22nd, 2008 7:07 am

    Decoding eBay?s Best Match…

    eBay?s Best Match search algorithm has sellers up in arms because, in many cases, their auctions never make it to the first page of eBay?s search results.  There?s been speculation on what the eBay Best Match algorithm considers when generating the…

  8. Amble Outdoors ® on January 22nd, 2008 8:54 am

    Excellent research and analysis. Keep up the good work.

  9. Mario on January 22nd, 2008 9:35 am

    Great article! You have provided a grass roots guide into one of eBay’s most impacting feature. I strongly believe you will find this url pretty interesting :)



  10. Bob Winfrey on January 22nd, 2008 7:52 pm

    Great reseach, great article. My sales are down so far after two years of doing well I am almost ready to throw in the towel. I may keep my products on e-bay long enough to “weigh in on this new search”

  11. eBay Optimization | The Latest at eBay on January 22nd, 2008 8:24 pm

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  12. susan on January 23rd, 2008 8:49 am

    im curious how this could possibly work in categories like original art, antiques etc, where every single item is unique and buyers buy with their eyes (not some predetermined keywords like you can have in electronics), by browsing until they come across something that jumps out at them, and mostly not by using keywords or any specific searches (aside from some circumstances).. anyone? anyone???

  13. tekgems on January 24th, 2008 1:41 am

    Its not clear to me either. As I learn more about Best Match on – its my understanding that browsing in Categories using the Best Match view uses a slightly different way to present the items. If an item ending sooner is pushed back, that usually means there are unfavorable keywords in the Title, Seller DSR is lower than others in the browse, or other factors that is lower the rank of that product. eBay has an internal tool that lets you view what the rank of each item is but, of course, its not available to the public for obvious reason. :)

  14. Marian O'Shaughnessy on January 25th, 2008 8:15 pm

    Very interesting. Thank you for posting this!!
    I can’t wait to peruse results:)

  15. Peter Leeflang / CEO of Leeflang Archives Corporation on January 27th, 2008 7:53 am

    1) A superb analysis. You should work for Ebay. They need such brains there. Maybe that will save their site?

    2) Susan has hit the nail with her comment. The problem of (rather) unique items vs. commodities is one of the major flaws that makes Best Match fail. It will never work for (rather) unique items. Our sales of antique magazines has tanked thanks to best match, especially since we have summaries with 2000+ keywords in each, describing the content. I’m sure most of those keywords diminish our visibility as they get ‘negative ratings’ in Ebay’s new system.

    3) It would be interesting to visualize the Best Match method vs. the old method, as an extra analysis to show the differences. It would illustrated WHY the Best Match is doomed to fail. In essence a department store (Ebay) has decided to move its rotating visibility of all products on sale to a system where only the most ‘popular’ will show in fron and the others get relegated to the basement. That kind of merchandising does not work in the real world, especially since vendors all pay the department the same fee, while they do not get the same product visibility in exchange. That is not a good business proposition and therefore the patent has no commercial value in this context. No one will pay any royalties to use it.

  16. Andrea 'Enthal on February 17th, 2008 11:00 am

    One thing I suspect (though it isn’t in your article) is that they are going to use their Paypal as a weighting factor, advancing the rank of Paypal only and Paypal preferred (so they can get 12% instead of 9% out of any sale) and burying the non-Paypal members listings even if all the keywords are a hit.

    They just changed their checkout to make it very difficult to get a seller’s address without clicking past two ads to open a Paypal account–and that is only to see if the seller’s address is there–which it often isn’t any more.

    Do you see evidence that they are going to use this search the same way they redesigned the list your item form, and now the checkout system, to further punish non-Paypal members, or am I paranoid?

    I know the best match does not work for me. I enter a plural, because I only want to see entries with multiple items, and get pages and pages of items that are singular.
    I need an opt out for the best match search.
    It is worst match for me.

  17. Lori on February 22nd, 2008 12:12 pm

    according to all this information I’m seeing my titles are dooming me!

    I sell china and according to the tool mentioned above putting the pattern and mfr name in my title is bad according to ebay’s best search

    according to that tool…

    I should list – Soup Bowl
    Because soup bowls sell… but apparently Noritake Yasim Soup Bowls don’t sell well enough to be warranted a good title.

    This is down right frightening.

  18. Doug Feiring on February 22nd, 2008 5:58 pm

    What is the search term that you think your target bidder would type in when looking for your auctions?

    If it’s “Noritake China” then some of the title keywords that would help you raise your Best Match score would be (in addition to Noritake China):
    – Set 70%
    – piece 40%
    – pc 40%
    – pattern 30%
    – place 20%
    – japan 20%
    – for 20%
    – vintage 20%
    – service 20%
    – 12 20%
    – setting 20%
    – 6 20%
    – 8 20%
    – fine 20%
    – rare 20%
    – new 20%
    – plates 20%
    – gold 20%
    – of 20%
    – mint 20%
    – occupied 10%
    – 4 10%
    – plate 10%
    – lot 10%
    – 5 10%
    – dinner 10%
    – pcs 10%
    – cup 10%
    – saucer 10%
    – bone 10%
    – antique 10%
    – and 10%
    – boat 10%
    – pieces 10%
    – gravy 10%
    – settings 10%
    – serving 10%
    – platter 10%
    – dinnerware 10%
    – 10 10%

    You can play around the eBay “BayEstimator” at to get more ideas.

  19. MOORE, Ernie Jr. on February 25th, 2008 4:26 pm

    On first look, calculation of Demand seemed the same as calculation Supply. Or the such.

    “Activity data is collected on a daily basis, data that includes activities such as clicked, bid, bought, or added to watch list… are associated with keywords used in item titles.” Associated with yet “The percentage occurrence of every keyword in the same set is calculated. Thus, if the keyword ‘charger’ occurred in 100 of these 1000 titles, the percentage of charger in the ‘demand’ is 10%. Similarly, if ‘player’ occurs in 950 titles, its demand percentage is 95%.”

    There are associated with values however, according to the just put quote it seemed to me as though they might not be included.
    “the total occurrence of every unique keyword in all the titles is first determined. Then the percentage occurrence of each keyword in the result set [(the auction titles)] is determined. For example, if there were 1000 items in the results [for the search query ‘iPod nano’], and the word ‘charger’ occurs in 900 items, then the supply percent of charger is 90%. If the keyword ‘player’ occurs in 50 items, then its supply percentage is 5%.”

    If you are looking in the search querry, that seems as though it might should relate to Demand. Since the person demanding the item is Searching. Ifv there is a search “Que” which might be the Results, then that could be related to Supply

  20. MOORE, Ernie Jr. on February 25th, 2008 4:44 pm

    To have negative there would be zero or neutral point. I think values that are merely referred to as higer values or lower values might be more correct.

    As a formula, do the occurance percentage but allow each factor a value of one to increase its rating…

    a word used in descriptions with an occurance value of 12%=12 yet four of those listings sampled has owners with stores store ownership is a value of one (subject to change–the other than occurance values should be assigned values which would be added to the occurance percentage value to yield the result of a Demand Value–that for which you ask plus the stuff the seller has going-on…) if no other factors involved The Demand Value is 13.

  21. MOORE, Ernie Jr. on February 25th, 2008 4:50 pm

    I think volume of positive feedback could be a factor. I think that percentage of positive feedback of total feedback could be a factor. I think these are different things and might be options of factors when using such a resource as an optimizer type of thing.

    I think that this sort of thing is not the standard but a feature. Standards for searches might should be categorized–date, price, location, time started, time ending, time remaining…

    MOORE, Ernie Jr.

  22. Jeremy on March 21st, 2008 4:50 pm

    I found this article to be very interesting. I’ll do my best to use ‘best match’ to my advantage as a seller but as a buyer personally I find it to be totally useless and am dismayed that it is the new default setting for searches. I have to constantly remind myself to change it to “ending soonest” lest I miss the auction that is ending in five minutes for the one that is ending in an hour.

  23. Jason on July 13th, 2008 9:33 pm

    Thanks for the hard work. I found this very interesting. It was an exceptional expose’ of the Best Match algorithm.

  24. Jason Heap on July 15th, 2008 4:06 am

    Very sound article here and it is much appreciated.

    I have just one question though. Do you know if this also applys to all other eBays?

    We have accounts in just about all of the eBays and we do not actually see the best match in affect at all, or in the same way.

    Any input would be great.

  25. Doug Feiring on July 15th, 2008 6:37 am

    My best source for information on what is happening on the international eBay sites is the TameBay Blog. According to them, Best Match is live on the UK & French sites, and affects the auction style listings on the Italian site. My own research indicates that it’s live on the site, but not the default on eBay Australia.

    Best of luck,

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  27. a huge list on January 17th, 2010 8:10 am

    I have no idea why ebay is still pushing this flawed search method. As a buyer I automatically change to time ending soonest or other options.

  28. Saptaj on January 30th, 2010 6:48 am

    Your analysis is excellent but it ignores one important fact: many buyers do not search by keywords but browse entire categories. You did not analyze Best Match according to this practice, in other words, how does best match work when no keyword is used at all but buyer goes directly to an entire category and then browses page after page? How then is a category organized?

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