eBay’s Smart Search: A Peek into the Future of Best Match
Filed Under Best Match, Industry News & Analysis | 1 Comment
eBay recently acquired the internet start-up Positronic and brought aboard the firm’s two founders, Christopher Payne and Dane Glasgow as Vice President of Search and Vice President of Engineering respectively. This move provides some indication that eBay’s recent and significant changes to their search and sort algorithms are but the tip of the iceberg. eBay is obviously committed to expending additional resources and energy to search in the future.
Both Payne and Glasgow were executives involved with the production and fielding of Microsoft’s Live search engine prior to leaving a couple of years ago to found Positronic. According to Wikipedia:
A positronic brain is a fictional technological device, originally conceived by science fiction writer Isaac Asimov. Its role is to serve as a central computer for a robot, and, in some unspecified way, provide it with a form of consciousness recognizable to humans.
This although it is not entirely clear what Positronic was specifically working to create, the firm’s name indicates their purpose was the development of artificial intelligence and “working in the areas of data mining, machine learning, and predictive models, all applied to search.”
Indeed, previously the Positronic web site had the following statement displayed on their home page (It now has a statement indicating the firm has be acquired by eBay):
Are you inspired by Isaac Asimov’s vision of thinking machines? Ever pondered how and when the break-through will come to make it possible?
Wow! That’s heady stuff! eBay’s management has obviously been “inspired by Isaac Asimov’s vision of thinking machines.” According to the corporate blog, “eBay has acquired Positronic to help with efforts at leveraging machine learning to provide a more predictive and compelling customer experience.”
Here’s some personal predictions on the future of eBay search & sort…
Prediction #1
eBay will monitor, track and store users browsing and shopping activity on the site in order to provide search results sorted in a manner relevant to the individual based on that person’s past actions.
Here’s a hypothetical example. Accessories compatible for a Dell XPS M1130 laptop computer will be listed at the top of the search results when I conduct a search using the query “laptop battery.” This is because the site will remember that I purchased that particular model on eBay a few months ago.
Or perhaps the smart search and sort algorithm will note that I have a penchant for the original Star Wars comics series published by Marvel vice those published more recently by Dark Horse comics. The algorithm will know this because I click on listings for Marvel Star Wars comics and ignore those from Dark Horse. So, in future searches, the algorithm will determine that Marvel comics are relevant to me (or anybody using my User ID) and sort them at the top of the search results accordingly.
Something like this is already happening on eBay. On the main page, the site displays a collage of listings it considers similar to one’s you’ve viewed recently.
This, of course, will raise all kinds of privacy concerns and will be difficult for eBay to implement without causing a ruckus.
Prediction # 2
Completing the Item Specifics form will become required when listing an item for sale. This is currently optional.
Item Specifics are the details sellers have the opportunity to provide when they list their product for sale on eBay. For example, a listing in the Book category might provide the seller the ability to enter details such as hard cover or paperback; new or used; fiction or non-fiction; year published; etc. The Item Specifics function varies by category and may duplicate information the seller has included in the listing’s description. This data allows eBay’s software to know specific information about the item in a format the site can use to help potential bidders find a listing.
Currently all eBay has to determine the relevance of a product associated with a listing are the 55 characters in the title and the details included in the item’s description. Since there is no standard format for details included in the description, eBay can’t effectively use that information to ascertain the details associated with a product.
But, then again – Positronic was working on data mining, so I could be dead wrong here. Therefore my revised prediction is Item Specifics will be required, then abused by sellers (much like meta keyword tags were in the early days of search engine optimization). Item Specifics will then fall out of favor, to be replaced by the data mining techniques introduced by the Positronic folks.
What are your predictions for the future of Best Match and eBay’s Smart Search?
I’m pleased to announce this morning that the second edition of my free eBook, Best Match Made Simple is available for download at on this page.
This edition required extensive revisions to encompass all of the changes and the information that has come available since the original was published in June of 2008. I’ve added 30 pages of information and the book now weighs in at a hefty 128 total pages.
Many members of the eBay community have asked why I would take the significant time and effort required to produce an eBook with such valuable information and just give it away. In fact, as I’ve worked on this project, I’ve often asked myself the same question. Simply put, my goals with Best Match Made Simple are to establish my credibility in the industry, to encourage you the reader to visit AuctionInsights, and to gain the experience of writing, publishing and promoting an information product for future, paid projects.
So, here it is. I invite you to share this free eBook with other eBay sellers who might benefit from knowing how Best Match works, and how they can use that knowledge to improve their sales on eBay.
What’s in the book?
123 pages. Here’s the table of contents:
- Forward
- Introduction: Best Match – Adapt or Perish
- Chapter 1 If You Don’t Have Time to Read this Book
- Here’s the Bottom Line Up Front
- Listing Format
- Time Remaining
- Auction Style
- Fixed Price
- Demand Data & Relevancy
- Keywords
- Relevancy
- Desirability
- Product Information
- Shipping and Handling
- Item Specifics
- Trust Factors
- Seller Performance
- Conclusion
- Product + Traffic + Conversions = Profit
- Chapter 2 Introducing Best Match and Best Match Optimization
- How Things Used To Work
- Best Match’s Impact on Sellers
- Why Is This Important?
- Best Match Is About Business
- Same Name – Different “Best Match”
- Introducing Best Match Optimization
- Score The Most Points
- Best Match and You
- A Word About Product Sourcing
- Chapter 3 Listing Type: Auction or Fixed Price
- Auction Style Listings
- Fixed Price Listings
- Multi-Quantity Listing Overview
- Improving Fixed Price Rankings With Recent Sales
- Recent Sales Carry-Over When You Re-list
- Tips to Get the Recent Sales Advantage
- Featured First
- Featured Plus
- Best Offer
- Conclusion
- Product Sourcing Part II
- Chapter 4 Trust Factors
- Seller Performance
- Feedback
- Detailed Seller Ratings
- Buyer Satisfaction Rating
- The Seller Dashboard
- Include a Return Policy
- How to Specify Your Return Policy
- Conclusion
- Product Sourcing Part III
- Chapter 5 Product Information
- Include Item Specifics
- Geographic Distance
- Shipping Prices & Methods
- Conclusion
- Active Traffic Generation Techniques
- Chapter 6 Demand Data and Relevancy
- Desirability
- Include Best Match Keywords
- Identify the Valuable Keywords
- Analyze Your Niche
- Conduct Your Analysis
- Test Your Auction Title
- Make the Most of Your Listing Title
- Never Use Negative Keywords
- If You Don’t Own Your Traffic, Who Owns Your Business?
- Chapter 7 Optimize Your Keywords with the BayEstimator
- How the BayEstimator Works
- Conclusion
- A Word About Conversions
- Chapter 8 Best Match Manipulation
- Misleading Keywords
- Keyword Repetition
- A Dynamic Algorithm
- Making eBay Work for You
- It’s time to take back your business and dreams!
- The bottom line?
- Appendix A: Decoding the Best Match Patent Application
- Appendix B: The Best Match Patent Application
Download your free copy at http://www.auctioninsights.info/bestmatchbook
While working on the second edition to my free eBook, Best Match Made Simple (available now BTW), I noticed that the data returned by eBay’s BayEstimator for one of my examples (query: Star Wars Comics) was exactly the same as an image I pulled almost a year ago for a post explaining how to use the tool.
Exactly the same? Uh oh… That could mean one of two things. Things haven’t changed much in the Star Wars comics niche on eBay (entirely plausible) or eBay has stopped feeding data to the tool.
This second scenario is not good news for eBay sellers – especially those who sell items that have recently become popular. Using the BayEstimator to identify title keywords that score well is (was?) the quickest and easiest route to improving your listings rankings in eBay’s Best Match search results. If the BayEstimator tool is no longer using current data, it may provide suggestions that are no longer relevant to the actual Best Match algorithm that is in production on the site.
Or, in the case of listings that were not popular prior to whatever point eBay cut off the data feed to the tool, the BayEstimator may not provide any suggestions at all.
A quick test for the term “Palin” strongly indicates that the data in the BayEstimator is old – real old. The tool does not even recognize the search string “Sarah Palin.” Most of the suggested keywords are associated with Micheal Palin, the British actor from Monty Python. Based on a search conducted on eBay using the query “Palin,” I would expect the BayEstimator to suggest words like “campaign,” “McCain,” “glasses,” “bobblehead,” and “button.”
What does this mean to you?
If you’re selling something that became trendy only recently, the BayEstimator is not going to be particularly useful to you. If you are selling something for which there was an established niche some time ago (spring 2008 or earlier by my best guess), the BayEstimator is still useful, but there may be keywords that have recently come into prominence that the tool might be omitting due to the old data feeding it. Conversely, the tool might be suggesting a keyword that has fallen out of favor on the live version of Best Match which might hurt your listing’s rankings if you include it in your tile.
Before you blindly accept the suggested keywords, it’s important that you do a little old-fashioned sleuthing. Type in a couple of search queries that you think your potential customers would use to find the product you intend to list. Look at the titles that are listed at the top of the search results on page one. (Ignore the featured listings – they pay to be at the top. Look at the items below the phrase “Optimize your selling success! Find out how to promote your items” injected at the bottom of the featured area.)
Pick out the adjectives that are common amongst the high ranking listings – especially in the auction style listings that aren’t closing for a while relative to the others on that same page. If they pertain to your listing, try including those keywords in your listing’s title.
The BayEstimator is still a good tool, but it no longer is as relevant as it used to be. A little investigation and experimentation on your own might lead you to discover keywords that sellers who rely solely on the BayEstimator might miss. This lead to higher rankings in the Best Match search results and a competitive advantage for you.
eBay Needs To Stick With It’s Core Competency: Auctions
Filed Under Industry News & Analysis | 2 Comments
In yesterday’s quarterly earnings announcement, eBay revealed that the company experienced its first-ever quarterly revenue decline (16%). This after John Donohoe, the CEO, decided when he took over last year to basically abandon the firm’s core competency – online auctions – and compete directly with Amazon in the marketplace of fixed-price consumer commodity products. eBay blamed “a weakness in consumer spending and strength in the U.S. dollar, which reduces the value of overseas sales,” but it seems that Amazon (which announces earnings next week) was unaffected. In December, Amazon reported its most successful Christmas ever, selling 6.3 million products during the holiday shopping period.
eBay needs to sit down an think deeply about the company’s core competency. According to Wikipedia:
Core competency is something that a firm can do well and that meets the following three conditions:
A core competency can take various forms, including technical/subject matter know how, a reliable process, and/or close relationships with customers and suppliers.
The core competency that led to eBay’s success was the online auction marketplace model. Acquisition of PayPal fundamentally supported that model. Branching out into and an eventual focus on the fixed-priced marketplace in the name of continued growth has caused eBay to stray from their core competency – with dire consequences. (Who knows where Skype fits in?)
It’s time for eBay to get back to its roots. Re-focus on the auction format. Make selling fun again. Sellers are actively looking for an alternative to you eBay – something that reminds them of how you used to be. Don’t be afraid of transforming yourself into that alternative for us. Remember Coke Classic?