Classifying Searchers – What Really Counts?

I continue to be impressed by the new ways in which enterprise search companies differentiate and package their software for specialized uses. This is a good thing because it underscores their understanding of different search audiences. Just as important is recognition that search happens in a context, for example:

• Personal interest (enlightenment or entertainment)
• Product selection (evaluations by independent analysts vs. direct purchasing information)
• Work enhancement (finding data or learning a new system, process or product)
• High-level professional activities (e-discovery to strategic planning)

Vendors understand that there is a limited market for a product or suite of products that will satisfy every budget, search context and the enterprise’s hierarchy of search requirements. Those who are the best focus on the technological strengths of their search tools to deliver products packaged for a niche in which they can excel.

However, for any market niche excellence begins with six basics:

• Customer relationship cultivation, including good listening
• Professional customer support and services
• Ease of system installation, implementation, tuning and administration
• Out-of-the box integration with complementary technologies that will improve search
• Simple pricing for licensing and support packages
• Ease of doing business, contracting and licensing, deliveries and upgrades

While any mature and worthy company will have continually improved on these attributes, there are contextual differentiators that you should seek in your vertical market:

• Vendor subject matter expertise
• Vendor industry expertise
• Vendor knowledge of how professional specialists perform their work functions
• Vendor understanding of retrieval and content types that contribute the highest value

At a recent client discussion the application of a highly specialized taxonomy was the topic. Their target content will be made available on a public facing web site and also to internal staff. We began by discussing the various categories of terminology already extracted from a pre-existing system.

As we differentiated how internal staff needed to access content for research purposes and how the public is expected to search, patterns emerged for how differently content needs to be packaged for each constituency. For you who have specialized collections to be used by highly diverse audiences, this is no surprise. Before proceeding with decisions about term curation and determining the granularity of their metadata vocabulary, what has become a high priority is how the search mechanisms will work for different audiences.

For this institution, internal users must have pinpoint precision in retrieval on multiple facets of content to get to exactly the right record. They will be coming to search with knowledge of the collection and more certainty about what they can expect to find. They will also want to find their target(s) quickly. On the other hand, the public facing audience needs to be guided in a way that leads them on a path of discovery, navigating through a map of terms that takes them from their “key term” query through related possibilities without demanding arcane Boolean operations or lengthy explanations for advanced searching.

There is a clear lesson here for seeking enterprise search solutions. Systems that favor one audience over another will always be problematic. Therefore, establishing who needs what and how each goes about searching needs to be answered, and then matched to the product that can provide for all target groups.

We are in the season for conferences; there are a few next month that will be featuring various search and content technologies. After many years of walking exhibit halls and formulating strategies for systematic research and avoiding a swamp of technology overload, I try now to have specific questions formulated that will discover the “must have” functions and features for any particular client requirement. If you do the same, describing a search user scenario to each candidate vendor, you can then proceed to ask: Is this a search problem your product will handle? What other technologies (e.g. CMS, vocabulary management) need to be in place to ensure quality search results? Can you demonstrate something similar? What would you estimate the implementation schedule to look like? What integration services are recommended?

These are starting points for a discussion and will enable you to begin to know whether this vendor meets the fundamental criteria laid out earlier in this post. It will also give you a sense of whether the vendor views all searchers and their searches as generic equivalents or knows that different functions and features are needed for special groups.

Look for vendors for enterprise search and search related technologies to interview at the following upcoming meetings:

Enterprise Search Summit, New York, May 10 – 11 […where you will learn strategies and build the skill sets you need to make your organization’s content not only searchable but “findable” and actionable so that it delivers value to the bottom line.] This is the largest seasonal conference dedicated to enterprise search. The sessions are preceded by separate workshops with in-depth tutorials related to search. During the conference, focus on case studies of enterprises similar to yours for better understanding of issues, which you may need to address.

Text Analytics Summit, Boston, May 18 – 19 I spoke with Seth Grimes, who kicks off the meeting with a keynote, asking whether he sees a change in emphasis this year from straight text mining and text analytics. You’ll have to attend to get his full speech but Seth shared that he see a newfound recognition that “Big Data” is coming to grips with text source information as an asset that has special requirements (and value). He also noted that unstructured document complexities can benefit from text analytics to create semantic understanding that improves search, and that text analytics products are rising to challenge for providing dynamic semantic analysis, particularly around massive amounts of social textual content.

Lucene Revolution, San Francisco, May 23 – 24 […hear from … the foremost experts on open source search technology to a broad cross-section of users that have implemented Lucene, Solr, or LucidWorks Enterprise to improve search application performance, scalability, flexibility, and relevance, while lowering their costs.] I attended this new meeting last year when it was in Boston. For any enterprise considering or leaning toward implementing open source search, particularly Lucene or Solr, this meeting will set you on a path for understanding what that journey entails.