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Online stores and product catalogs need a search function so that customers can bypass any hierarchical navigation and find the things they want to buy. It's a form of customer service, like having a knowledgeable sales person who can answer questions accurately.
Many online stores have no search engine or an inadequate one: when customers can't find what they want, they may well leave and never return.
- Accept multiword keyword searches, without requiring SQL commands or Boolean operators.
- Find matches on some or all words as keywords, as well as phrases
- Better to find something than nothing.
- Allow customers to enter product codes and product brand names as well as general topics.
- Make repeat customers happy
- Default to searching all the product information, but recognize a few special fields, such as size, color and price (see faceted metadata search)
- Include synonyms, so a search for "red sweater" will find scarlet cardigans and magenta crew-necks.
- Include site information, such as order status and return processing.
- Index extensive product information, even if it's stored in back-end databases
- Few database search engines are both easy to use and flexible, see the SearchTools Report on Database vs. Full-Text Search.
- Sort results so the most likely to be relevant items come first.
- Perform user testing to learn what relevance means to customers
- Analyze your search logs to find out what people ask for and where they go
- Adjust the search indexing to include everything that's useful
- Format results listings to show the most valuable information:
- Emphasize the matching text using bold or colors, so it's clear why the item was found.
- For physical products, such as clothes or groceries, show pictures.
- Show the most important elements, such as price, size, brand name or compatibility information.
- Include inventory status, so it's clear what's available and what must be backordered.
- For searches which don't find any matches, provide a clear and helpful error page.
- See the SearchTools Report on Search Failure and the report on No-Matches Pages
- Generate a search log, which store operators can consult for free market research:
- what's popular
- what's trending down
- what customers look for that you don't carry
- what misspellings and typos they commonly make.
Recommendations include building a vocabulary and synonym listings so that searches for a specific term will find pages with all variants and equivalent terms, improving content management, and implementing good user interfaces to the search engine. They even have a section on the benefits of fixing search, showing how it makes bottom-line sense.
Cost of search, mainly for e-commerce sites, is given at $150,000 for a search engine, $150,000 to integrate with existing databases and $60,000 for user interface and testing, along with an estimate of $4 per page or item for page titles, descriptions, removing duplicates and creating a controlled vocabulary.
SearchTools Analysis of the Forrester Report
I like this report a lot: it's clear on how important site search is and how traditional algorithms fail to retrieve and sort the results well. However, they don't emphasize the special issues that may arise in searching structured data (such as product catalogs), and they mix up retrieving relevant items with ranking (so that the relevant items appear on the first page). In addition, they don't understand how much people like a simple search field -- it's a Web convention that is now inescapable. And the cost is appropriate for a large e-commerce site, rather than a smaller or simpler site, such as an online magazine, small store, or corporate site.
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