Wednesday, May 2

Live Product Search Images Follow-up

I posted last week on MSN's update to their product search.

Ling Bao from the product search team responded to my comments on the post:
Jeff, you make a good observation. We've verified your queries and all the offers without images are from Product Upload Beta feeds where the merchant has blocked our image bot. In terms of the categories that have more images, this is heavily skewed by what merchants are uploading.

Additionally, I think the big difference between our numbers is due to two reasons. Part of it is because of sample size. The other cause is that we're getting more feeds over time, exacerbating the problem.

As you can imagine, we are actively working to address the image issue with feeds in coordination with merchants.

I agree, I only tried three queries -- so my sample size was tiny. I guess I wonder how the numbers would change over a larger query set. Having products with images only matters if those are the results that appear first in the search results. In short, the overall percentage of products with images can differ drastically from what users actually see in search results.

Good luck to the team on working on the arrangements with merchants to get your crawls. You can also read the team's full post on the MSN Product Search Blog.

In the post on their blog they asked for some feedback on ranking product results. Here are some of my thoughts:

From the their post: Is the product what the user was looking for given the query? The example given was a query for "speaker" and both speaker stand and speaker system both contain the desired search term in the product name.

Here are my thoughts:
It would be nice if the search engine recognized the speaker was a modifier/adjective of stand and not a speaker itself. This would solve the speaker stand vs. speaker system problem (this may not be as easy as part-of-speech tagging)...

Can you cluster the results by similarity (features include: manufacturer, price, dimensions, weight, etc...) and then bias the results toward prevalent product clusters (i.e. expensive large, expensive speaker systems are probably more prevalent than cheap and light speaker stands)? Factoring in aggregate product popularity might be important here...

Factors in Product Result Ranking
1) How popular is this product? I tend to be biased towards more popular (higher selling) items. (like the Amazon SalesRank)

2) How is the item rated? I like Amazon because it not only provides the overall rating, but also provides the number of ratings the items received and properties of those reviews (are there recent reviews? are there constant reviews over a long period of time?). Is it rated by consumer reviews or other rating services?

4) Who manufactured the product? I am going to probably prefer products from major name brands -- Wusthoff, Sony, Canon, Microsoft, Apple, etc...

5) When was the item first released? I am going to prefer newer items / models.

6) What are the seller's shipping rates / policies? I am going to prefer sellers that have cheaper shipping fees and that can get me my item faster.

7) Seller proximity for some items. For some large items I might want to be able to pick the item up and local sellers are better than distant sellers. (I probably won't ship a large screen tv or large piece of furniture).

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