In the course of thrashing over search results for our eCommerce site, a stakeholder suggested that we look into "context-sensitive" search. Now what did they mean by that? What is context?
"Context" is nothing more than the words and vision and words in the user's mind when they are searching. It's the motivation for and the desired outcome of a search. How do you deduce that when you're handling on-line queries? Do you make a guess based on previous searches by that user? Are those searches during the current session or do you consider past sessions? Or do you extrapolate based on the most typical searches by all users of your site?
The stakeholder quickly saw that we were already in deep philosophical waters so they offered a shortcut. "Let's just look at where the user is on the site (i.e, a catalog) and limit the search results to that section."
"For example, if the user is on menswear, whatever they search for, only show menswear results or at least, only show clothing with the menswear ranked first." Some people in the discusssion thought this sounded reasonable.
But let's think again about shoppers and how they behave. My first jobs during school and after graduation were in big department stores -- 10 years, and a lot of it spent on the selling floor working with customers. I observed several basic patterns to shopping that we can extrapolate to eCommerce searching. The first two we don't need to worry about; that's the expert who already knows their way around and has devised their own shortcuts; and the explorer who just wants to wander and browse for the sheer fun of finding something they didn't expect.
The rest of the shoppers want help and they have three ways of letting you know - the first kind comes in the door and immediately asks, "where can I find X?" That's it - "X" is the context. Nine times out of ten, "X" is nowhere near the door or aisle where the customer is now. All you can do, if you don't recognize what they mean by "X", is engage them in a little dialog and then direct them to some spot far away.
The second kind of shopper goes to the approximate area they are interested in and then asks for help to filter something down by brand or size or style or price point. Think of a lady standing next to the cold medications who asks where to find the aspirin.
The third type is a combination of these two. They've gotten what they want in aisle one and now they want to know how to find something that's in another department. They may be working a list that's in random order or some logical order known only to them, either way, their order may not match up to your site layout -- what they want may still be the equivalent of five aisles away, across the store, on another floor, etc. The immediate surroundings are not going to help in this situation either.
So 3 out of 5 search scenarios depend on getting help and 2 those cannot infer a solution from the immediate context (surroundings). What's a web site designer to do? All you can do is compensate for the salespeople who who were left behind in the brick-and-mortar world.
"Did you mean this?" (show list of similar and related terms)
"People who bought that also bought this."
"Would you like to look in this department first?" (show list of facets)
"Here are things you've bought before. Are you looking for something similar today?"
Unfortunately, those strategies mean you have to spend time collecting search terms and analyzing post-search traffic patterns. You have to collect histories of your customers and mine the profitable ones for patterns. And ideally, you can hire an information architect to optimize your navigation and map search terms to likely synonyms. All of which goes right back to those philosophical questions and the fact that fine-tuning search takes an investment in time and expertise. There are no shortcuts.
Showing posts with label key word search. Show all posts
Showing posts with label key word search. Show all posts
Friday, April 8, 2011
Context and Searching
Sunday, March 13, 2011
Overriding a Keyword Search?
My most recent project has taken an interesting turn into keyword search. We're using SOLR for our search engine and the philosophical question on the table is how to fine-tune it or do we fine-tune it?
That is, we are in a tug-of-war over whether the most prominent results should be the products management wants to feature and also, if the results are inherently flawed because some other things are showing up. Specifically, some stakeholders are insisting that we find a way to re-interpret what the user is searching for or override the results the search engine brings back.
Well that sounds rather Orwellian, and maybe not a good thing. At least not something I care to endorse. But let me explain the dilemma a little more.
First, this is an eCommerce site, not social networking or information sharing. It's all about connecting shoppers to products, and consequently, reinforcing marketing goals for the business.
Second, we are grappelling with two problems: iconic brands/products and context-sensitive search. The question at hand is how to get balance between iconic brands and products and the apparent randomness of context-sensitive search.
To illustrate the problem, let's think about grocery shopping. And let's imagine your search word is "Kellogg's". What are you searching for? Breakfast cereal? Probably. And what images are in your mind that signal "Kellogg's" and breakfast cereal? Maybe a box of cornflakes? Not that you want to buy cornflakes or even like them but it's the product that built the company and it's an image that strongly signals your search has landed you in the right place.
That's an iconic brand and an iconic product. And the problem is that people have such strong expectations about iconic brands and products, they may believe the search is broken if these brands or products don't show up according to their expectations.
Think about Kellogg's Cornflakes again. Where did you imagine this product would appear in your imaginary Kellogg's search? Near the top? In the middle? On Peapod, the dominant Chicago-area online grocery, a search on "Kellogg's" sorted by "Best Match", puts Kellogg's Cornflakes in 100th place, trailing a long mix of other cereals, breakfast bars, frozen waffles, and fruit roll-ups. Surprised?
Maybe that is an accurate reflection of the market or maybe the search algorithm is flawed; after all, we don't know Peapod's criteria for "Best Match", or their preferences for sorting results, but it's not hard to imagine a brand manager somewhere being rather upset and insisting something must be wrong if Cornflakes is not among the top 10 or 12 things you see.
We're not in the grocery business but our client makes and distributes several iconic products and brands and carries others in its inventory. These iconic products and brands are not always obvious in our search results, either. A lot of parts, supplies, and accessories show up first when you search solely for the brand name. And yes, this seems a little odd, or at least, hard to explain. To switch analogies, it's like showing you the windshield wipers and floor mats before we show you the car.
Our search engineer and I are convinced it's just a matter of examining the relevancy logic and re-weighting some variables or adding some variables so that the ancillary products lose relevancy. But how finely do you tune the search when you don't have any real data to work with?
To complicate matters, this is a B2B site that is not in production yet and we have no budget for user research; we don't really know what kind of search habits and expectations our customers will have. We know that searching on product numbers (full or part) works fine and that is something our users have been doing for a long time on the legacy site. But soon, they'll have the power of text search over the full product specifications and descriptions and we have no clue how they'll respond to that.
Meanwhile, our stakeholders and product owners are experimenting with keyword search based on their own preferences and guesses, which means a lot of searching for the iconics, and they are seeing too many parts and accessories in the results.
Some of these managers are certain the best bang for their money is to stop spending it on search engine support and start spending it on workarounds; like trapping for brand and product names and running hard-coded queries or highly limited searches instead of letting the search engine do its thing.
The more I struggle with these discussions, the more it hits me that we are getting sucked down a dead-end. If these brands and products are so central to the business and the site's identity, why should we be spending time and energy on the idea that our customers would be typing these brand names into a search box?
If these brands are so central to the business, why should any customer have to search for them? They should be front and center on the home page and every page. There should be "Famous Brands" and "Featured Products" links and lists and icons everywhere you look. All of these hot-button items should be one click away ... not something that customers will have to manually spell out and then hit "Go".
If we haven't put those features and shortcuts in place, (but we mostly have, as well as effective facet filtering *), then all of our time and energy should be on fixing that deficiency. Not fiddling with the search engine.
Let the search engine do its thing and return lots of branded parts and compatible parts for brands. Parts are hard to find; parts require searching. Parts are where you make your margin. ("Give away the razor; make a bundle on the blades.") Let's not take a chance on breaking that before the real users have had a chance to make their habits known.
* You can generally filter a result set in the 1,000's down to less than 50 items, usually under 25, in about two or three screens.
That is, we are in a tug-of-war over whether the most prominent results should be the products management wants to feature and also, if the results are inherently flawed because some other things are showing up. Specifically, some stakeholders are insisting that we find a way to re-interpret what the user is searching for or override the results the search engine brings back.
Well that sounds rather Orwellian, and maybe not a good thing. At least not something I care to endorse. But let me explain the dilemma a little more.
First, this is an eCommerce site, not social networking or information sharing. It's all about connecting shoppers to products, and consequently, reinforcing marketing goals for the business.
Second, we are grappelling with two problems: iconic brands/products and context-sensitive search. The question at hand is how to get balance between iconic brands and products and the apparent randomness of context-sensitive search.
To illustrate the problem, let's think about grocery shopping. And let's imagine your search word is "Kellogg's". What are you searching for? Breakfast cereal? Probably. And what images are in your mind that signal "Kellogg's" and breakfast cereal? Maybe a box of cornflakes? Not that you want to buy cornflakes or even like them but it's the product that built the company and it's an image that strongly signals your search has landed you in the right place.
That's an iconic brand and an iconic product. And the problem is that people have such strong expectations about iconic brands and products, they may believe the search is broken if these brands or products don't show up according to their expectations.
Think about Kellogg's Cornflakes again. Where did you imagine this product would appear in your imaginary Kellogg's search? Near the top? In the middle? On Peapod, the dominant Chicago-area online grocery, a search on "Kellogg's" sorted by "Best Match", puts Kellogg's Cornflakes in 100th place, trailing a long mix of other cereals, breakfast bars, frozen waffles, and fruit roll-ups. Surprised?
Maybe that is an accurate reflection of the market or maybe the search algorithm is flawed; after all, we don't know Peapod's criteria for "Best Match", or their preferences for sorting results, but it's not hard to imagine a brand manager somewhere being rather upset and insisting something must be wrong if Cornflakes is not among the top 10 or 12 things you see.
We're not in the grocery business but our client makes and distributes several iconic products and brands and carries others in its inventory. These iconic products and brands are not always obvious in our search results, either. A lot of parts, supplies, and accessories show up first when you search solely for the brand name. And yes, this seems a little odd, or at least, hard to explain. To switch analogies, it's like showing you the windshield wipers and floor mats before we show you the car.
Our search engineer and I are convinced it's just a matter of examining the relevancy logic and re-weighting some variables or adding some variables so that the ancillary products lose relevancy. But how finely do you tune the search when you don't have any real data to work with?
To complicate matters, this is a B2B site that is not in production yet and we have no budget for user research; we don't really know what kind of search habits and expectations our customers will have. We know that searching on product numbers (full or part) works fine and that is something our users have been doing for a long time on the legacy site. But soon, they'll have the power of text search over the full product specifications and descriptions and we have no clue how they'll respond to that.
Meanwhile, our stakeholders and product owners are experimenting with keyword search based on their own preferences and guesses, which means a lot of searching for the iconics, and they are seeing too many parts and accessories in the results.
Some of these managers are certain the best bang for their money is to stop spending it on search engine support and start spending it on workarounds; like trapping for brand and product names and running hard-coded queries or highly limited searches instead of letting the search engine do its thing.
The more I struggle with these discussions, the more it hits me that we are getting sucked down a dead-end. If these brands and products are so central to the business and the site's identity, why should we be spending time and energy on the idea that our customers would be typing these brand names into a search box?
If these brands are so central to the business, why should any customer have to search for them? They should be front and center on the home page and every page. There should be "Famous Brands" and "Featured Products" links and lists and icons everywhere you look. All of these hot-button items should be one click away ... not something that customers will have to manually spell out and then hit "Go".
If we haven't put those features and shortcuts in place, (but we mostly have, as well as effective facet filtering *), then all of our time and energy should be on fixing that deficiency. Not fiddling with the search engine.
Let the search engine do its thing and return lots of branded parts and compatible parts for brands. Parts are hard to find; parts require searching. Parts are where you make your margin. ("Give away the razor; make a bundle on the blades.") Let's not take a chance on breaking that before the real users have had a chance to make their habits known.
* You can generally filter a result set in the 1,000's down to less than 50 items, usually under 25, in about two or three screens.
Labels:
key word search,
search,
user experience,
user research usability,
UX
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