Enterprise Search

Poor data quality gives search a bad rap

If you’re involved in managing the enterprise search instance at your company, there’s a good chance that you’ve experienced at least some users complain about the poor results they see. 

The common lament search teams hear is “Why didn’t we use Google?” when in fact, sites that implemented the GSA but don’t utilize the Google logo and look, we’ve seen the same complaints.

We're often asked to come in and recommend a solution. Sometimes the problem is simply using the wrong search platform: not every platform handles every user case and requirement equally well. Occasionally, the problem is a poorly or misconfigured search, or simply an instance that hasn’t been managed properly. Even the renowned Google public search engine doesn’t happen by itself, but even that is a poor example: in recent years, the Google search has become less of a search platform and more of a big data analytics engine.

Over the years, we’ve been helping clients select, implement, and manage Intranet search. In my opinion, the problem with search is elsewhere: Poor data quality. 

Enterprise data isn’t created with search in mind. There is little incentive for content authors to attach quality metadata in the properties fields of Adobe PDF Maker, Microsoft Office, and other document publishing tools. To make matters worse, there may be several versions of a given document as it goes through creation, editing, reviews, and updates. And often the early drafts, as well as the final version, are in the same directory or file share. Very rarely does a public facing web site content have such issues.

Sometimes content management systems make it easy to implement what is really ‘search engine optimization’ or SEO; but it seems all too often that the optimization is left to the enterprise search platform to work out.

We have an updated two-part series on data quality and search, starting here. We hope you find it helpful; let us know if you have any questions!

Gartner MQ 2014 for Search: Surprise!

Funny, just last week I tweeted about how late the Gartner Magic Quadrant for Enterprise Search is this year. Usually it's out in March, and here it is, July.

Well, it's out - and boy does it have some surprises! My first take:

Coveo, a great search platform that runs on Windows only, is in the Leaders quadrant, and best overall in the "Completeness of Vision". Don't get me wrong, it's a great search platform; but I guess completeness of vision does not include completeness of platform. Linux your flavor? Sorry.

HP/Autonomy IDOL is in the upper right quadrant as well, back strong as the top in 'Ability to Execute' and in the top three on 'Completeness of Vision'. IDOL has always reminded me of the reliable old Douglas DC-3, described by aviation enthusiasts as 'a collection of parts flying in loose formation', but it really does offer everything enterprise search needs. And, because it loves big hardware, everything that HP loves to sell.

BA Insight surprised me with their Knowledge Integration Platform at the top of the Visionaries quadrant. It enhances Microsoft SharePoint Search, or runs with a stand-alone version of Lucene. It's very cool, yes. But I sure don't think of it as a search engine. Do you? More on this later.

Attivio comes in solid in the lower right 'Visionaries' quadrant. I'd really expected to see them further along on both measures, so I'm surprised.

I'm really quite disappointed that Gartner places my former employer Lucidworks solidly in the lower left 'Niche players' quadrant. I think Lucidworks has a very good vision of where they want to go, and I think most enterprises will find it compelling once they take a look. I don’t think I'm biased when I say that this may be Gartner's big miss this year. And OK, I understand that, like BA Insight's Knowledge product, Lucidworks needs a search engine to run, but it feels more like a true search platform.

Big surprise: IHS, which I have always thought as a publisher, has made it to the Gartner Niche quadrant as a search platform. Odd.

Other surprises: IBM in the Niche market quadrant, based on 'Ability to Execute'. Back at Verity, then CEO Philippe Courtot got the Gartner folks to admit that the big component of Ability to Execute was really about how long you could fund the project and I have to confess I figured IBM (and Google) as the MQ companies with the best cash position.

If you're not a Gartner client, I'm sorry you won't get the report or the insights Whit Andrews (@WhitAndrews _), a long time search analyst who knows his stuff. You can still find the report from several vendors happy to let you download the Gartner MQ Search from them. Search Google and find the link you most prefer, or call your vendor for a full copy.

/s/Miles

Webinar: What users want from enterprise search in 2012

If you ask the average enterprise user what he or she wants from their internal search platform, chances are good that they will tell you they want search 'just like Google'. After all, people are born with the ability to use Google; why should they need to learn how to use their internal search?

The problem is that web search works so well because, at the sheer scale of the internet, search can take advantage of methodologies that are not directly applicable to the intranet. Yet many of the things that make the public web experience so good can, in fact, be adapted in the enterprise. Our opinion is that, beyond a base level, the success of any enterprise search platform depends on how it is implemented and managed rather than on the core technology.

In this webinar we'll talk about what users want, and how you can address the specific challenges of enterprise content and still deliver a satisfying and successful enterprise search experience inside the firewall.

Register today for our first webinar of the new year scheduled for January 25 : What enterprise users want from search in 2012.

 

 

 

 

 

 

Are you spending too much on enterprise search?

If your organization uses enterprise search, or if you are in the market for a new search platform, you may want to attend our webinar next week "Are you spending too much for search?". The one hour session will address:

• What do users expect?
• Why not just use Google?
• How much search do you need?
• Is an RFI a waste of time?   

Date: Wednesday, November 16 2011

Time: 11AM Pacific Standard Time / 1900 UTC

Register today!

Content owners don't care about metadata

Or do they?

Our recent post about Booz & Company's 'men named Sarah' highlights just how important good metadata can be in order to provide a great search experience for employees and customers.

One of our customers who spoke at the recent ESS 2011 in New York provided some great insights into the problems organizations have getting employee content creators to include good metadata with their documents.

During the ESS talk, they report that content owners don't really seem motivated when asked to help improve the overall intranet site by improving document metadata. However - and this is a big one - when a sub-site owner sees poor results on their own site, they are willing to invest the time to provide really good metadata.

[A bit of background: This customer provides a way to individual site owners within the organization to add search to their 'sub site' pretty much automatically - sort of a 'search as a service' within the enterprise.]

So if you've been thinking of adding the ability to search-enable sub-sites within your organization, but solving the relevance problem is your first task, you might reconsider your priorities!

/s/Miles

Sixty guys named Sarah

We're always on the lookout for anecdotes to use at trade shows, with our customers and prospects, and of course here in the blog, so I have to report that we heard a great one last week at Enterprise Search Summit in New York.

The folks from Booz & Company, a spinoff from Booz Allen Hamilton, did a presentation on their experience comparing two well respected mainstream search products. They report that, at one point, one of the presenters was looking for a woman she knew named Sarah - but she was having trouble remembering Sarah's last name. The presenter told of searching one of the engines under evaluation and finding that most of the top 60 people returned from the search were... men. None were named 'Sue'; and apparently none were named Sarah either. The other engine returned records for a number of women named Sarah; and, as it turns out, for a few men as well.

After some frustration, they finally got to the root of the problem. It turns out that all of the Booz & Company employees have their resumes indexed as part of their profiles. Would you like to guess the name of the person who authored the original resume template? Yep - Sarah.

One of the search platforms ranks document metadata very high, without much ability to tune the weighting algorithms. The other provides a way to tune the relevance; but it also tends to rank people relevance a bit differently - probably stressing documents about people less than the individual people profiles. The presentation was a bit vague about whether any actual tuning that might impact these differences on either platform.

The fact that one of the engines did well, and one did not, is not the big story here - although it is something for you to consider if you're evaluating enterprise search platforms. The real lesson here is that poor metadata makes even the best of search platforms perform poorly in some - if not most - cases.

 

Make your search engine seem psychic

People tell us that Google just seems to know what they want - it's almost psychic sometimes. If only every search engine could be like Google. Well, maybe it can.

Over the years, the functions performed by the actual 'search engine' have grown. At first, it was simply a search for an exact match - probably using punch card input. Then, over time, new and expanded capabilities were added, including stemming... synonyms... expanded query languages... weighting based on fields and metadata.. and more. But no matter what the search technology provided, really demanding search consumers pushed the technology, often by wrapping extra processing both at index time and at query time. This let the most innovative search driven organizations stay ahead of the competition. Two great examples today: LexisNexis and Factiva.

In fact, the magic that makes public Google search so good - and so much better than even the Google Search Appliance - is the armies of specialists analyzing query activity and adding specialized actions 'above' the search engine. 

One example of this many of us know well: enter a 12 digit number. if the format of the number matches the algorithm used by FedEx in creating tracking numbers, Google will offer to let you track that package directly from FedEx. For example, search for 796579057470 and you see a delivery record; change that last 1 to a zero, and you get no hits. How do they know?

The folks at Google must have noticed lots of 12 digit numbers as queries; and being smart, they realized that many were FedEx tracking numbers. I imagine, working in conjunction with FedEx, Google implemented the algorithm - what makes a valid FedEx tracking number - and boosted that as a 'best bet'.

Why is this important to you? Well, first it shows that Google.com is great in part because of the army of humans who review search activity, likely on a daily basis. Oh, sure, they have automated tools to help them out - with maybe 100 million queries every day, you'd need to automate too. They look for interesting trends and search behavior that lets them provide better answers.

Secondly, you can do the same sort of thing at your organization. Autonomy, Exalead, Microsoft, Lucene, and even the Google Search Appliance, can all be improved with some custom code after the user query but before the results show up. Did the user type what looks like a name? Check the employee directory and suggest a phone number or an email address. Is the query a product name? Suggest the product page. You can make your search psychic.

Finally, does the query return no hits? You can tell what form the user was on when the search was submitted - rather than a generic 'No Hits' page. Was the query more than a single term? Look for any of the words, rather than all; make a guess at what the user wanted, based on the search form, pervious searches, or whatever context you can find.

So how do you make your search engine seem psychic? Learn about query tuning and result list pre-processing; we've written a number of articles about query tuning in our newsletter alone.

But most importantly: mimic Google: work hard at it every day.

/s/Miles

 

 

 

 

Enterprise Search Engine Optimization: eSEO

Last week at the Gilbane Conference in San Francisco, I participated in a panel "Search Survival Guide: Delivering Great Results" moderated by Hadley Reynolds of IDC. In the presentation, I offered a new view on improving enterprise search engine relevancy that I call eSEO.

The term SEO is well understood by - and widely practiced in - the corporate world.  The concept of SEO, as summarized by one of the Gilbane talks, states that "Key to the value of any Web content is the ability for people to find it”. In the SEO world this is done by combining organic results and keyword placement - advertising - to improve placement, maintain ranking, and monitor search engine position - results- over time.

While we've been helping our customers improve their enterprise search results, it's hard to convince them that search results are not a problem they can solve once. I've decided to apply a new term to this process - Enterprise Search Engine Optimization, or eSEO. To paraphrase the role of SEO, eSEO is the process of combining organic results and best bets to deliver correct, relevant, timely content to enterprise search users - employees, customers, partners, investors, and others.

For both organic and best bets, the first step is to identify what we call the "top 100" queries. Start by creating a histogram that shows the top terms from your search engine. I hope you'll agree that if the top queries - whether 100, 50, or even 20 - deliver great results, you're on your way to having happy users. Talk to your content owners as you review the histogram, and ask them to identify the best result for each.

Once you have a list of queries and results, start the two step process: tune the search engine using its native query tuning capabilities. This will impact the shape of the histogram, and over time should start delivering better results. The bad news is tuning like this doesn't position all of your top terms, and it would be silly to try to micro-manage the results for each. That's why search engines have best bets.

When you feel pretty good about the curve through query tuning, it' time to start setting up best bets - the "ad words" of eSEO. Limit the number of bests bets to one or two at most - but remember that you can use other real-estate like the rightmost column of the screen to suggest additional content. Some guidelines for best bets:

• Use one or at most two best bets
• Don't repeat a document already at the top of the organic results
• Make sure your best bets respect security

Once you have tuned your search engine, and set up best bets for the most timely and actionable result, you're ready to roll it out. But then the ongoing part comes in: you need to review your search activity and best bets periodically. Usually, we'd suggest once a month for a while, then perhaps quarterly thereafter. You may find seasonal variations, and if you're not watching you'll miss a golden opportunity.

In Summary

1. eSEO is just as critical as SEO

• Lost time and revenue
• Legal exposure

2. Watch for trends over time: Search is not "fire and forget"

3. Make sure SEO doesn't impact your eSEO

• Use fielded data that web search engines ignore for your tuning (i.e., 'Abstract' rather than 'Description'.

This will get you started; but because your queries and your content changes over time, it's a never-ending story. Some companies - ours included - have tools that can help. But no matter what, hang in there!

s/Miles

Updated List of Free, Open Source and Low Cost Search Engines

Over at our partner site:
www.searchcomponentsonline.com/free-open-source-and-low-cost.html

Search Quality: You Can't Improve What You Don't Measure

In our latest survey of new newsletter subscribers we found that 29% had no formal metrics for measuring quality of search results.  Search metrics allow you to keep search on the right track and can be a powerful tool for managing your systems.  They are a wonderful source for insights and trends.  We thought we would share a couple that we think work well. Many of these are covered in greater depth in Interpreting Your Search Activity Reports in the Enterprise Search newsletter.

• Count the number of people who use search  
• Count the total number of searches  
• Count the number of zero search results  
• User feedback on top 100 searches  
• Track email complaints about search  
• Measure number of clicks on navigators (navigation menu items)  
• Business Goals  
•    
  • Reduce call volume (normallized for growth in customer base) by enabling self-service from search: results are good enough to reduce calls.
  • Reduce e-mail volume (again adjusted for growth in customer base) by enabling self-service from search: results are good enough to reduce e-mails. 
  • Revenue       
  • Add-on revenue