What are organisations planning to focus on to impove Search and Findability?

This year’s Search and Findability survey gave us a good indication of upcoming trends on the market. The activities and technologies that organisations are planning to start working with, are all connected to improving effectiveness. By using technology to automatically perform tasks, and by understanding the users’ needs and giving them a tailored search experience, there is a lot of potential to save time and effort. 

Top 5 activities organisations will focus in:

  • Natural language search interface, e.g. Query aid or chatbots (29%)
  • Personalisation e.g. tailored search experience (27%)
  • Automatic content tagging (24%)
  • Natural Language Processing, NLP (22%)
  • Machine Learning (20%)

The respondents planning to start working with one of these areas are more likely to be interested in, or are already working with, the other areas in the top 5. For example, out of the respondents saying that they are planning to use a natural language search interface, 44% are planning to start with personalisation as well. If you were to add the respondents already working with personalisation to that amount, it would increase by 75%. This might not be a big surprise since the different areas are much related to one another. A natural language search interface can support a tailored search experience, in other words – lead to personalisation. Automatic content tagging can be enabled by using techniques such as NLP and Machine Learning.

A Natural Language Search interface is a way of trying to find targeted answers to user questions. Instead of search based on keywords, the goal is to understand the question and generate answers with a higher relevancy. Since a large amount of the questions asked in an organisation are similar, you could save a lot of time by clustering and/or providing answers automatically using conversational UI. Learn more about Conversational UI.

One way to improve the Natural Language Search interface is by using Natural Language Processing (NLP). The aim with NLP is to improve a computer’s speech recognition for example by interpreting synonyms and spelling mistakes. NLP started out as a rule-based technique which was manually coded, but the introduction of Machine Learning (ML) improved the technology further. By using statistical techniques, ML makes it possible to learn from data without having to manually program the computer system.  Read more about improving search with NLP.

Automatic content tagging is a trend that we see within the area of Information Management. Instead of relying on user created tags (of various quality) the tags are created automatically based on different patterns. The advantage of using automatic content tagging is that the metadata will be consistent and that the data will be easier to analyse.

Personalisation e.g. tailored search experience is a way to sort out information based on the user profile. Basically, search results are adapted to the user needs, for example by not showing things that the user do not have access to and promoting search results that the user frequently looks for. Our findings in this year’s survey, show that respondents saying they are currently working with personalisation consider that users on both the internal and extern site find information easier. Users that find the information they search for easily, tend to be more satisfied with the search solution.

Results from this year’s survey indicates that organisations are working with or planning to working with, AI and Cognitive-related techniques. The percentage doing so has grown compared to previous surveys.

Do you want to learn more about cognitive search

Author: Angelica Lahti, Findability Business Consultant

High Expectations to Googlify the Company = Findability Problem?

It is not a coincidence that the verb “to google” has been added to several renowned dictionaries, such as those from Oxford and Merriam-Webster. Search has been the de facto gateway to the Web for some years now. But when employees turn to Google on the Web to find information about the company they work for, your alarm bells should be ringing. Do you have a Findability problem within the firewall?

The Google Effect on User Expectations

“Give us something like Google or better.”


“Compared to Google, our Intranet search is almost unusable.”


“Most of the time it is easier to find enterprise information by using Google.”

The citations above come from a study Findwise conducted during 2008-2009 for a customer, who was on the verge of taking the first steps towards a real Enterprise Search application. The old Intranet search tool had become obsolete, providing access to a limited set of information sources only and ranking outdated information over the relevant documents that were in fact available. To put it short, search was causing frustration and lots of it.

However, the executives at this company were wise enough to act on the problem. The goal was set pretty high: Everybody should be able to find the corporate information they need faster and more accurately than before. To accomplish this, an extensive Enterprise Search project was launched.

This is where the contradiction comes into play. Today users are so accustomed to using search as the main gateway to the Web, that the look and feel of Google is often seen as equal to the type of information access solution you need behind the firewall as well. The reasons are obvious; on the Web, Google is fast and it is relevant. But can you—and more importantly should you—without question adopt a solution from the Web within the firewall as well?

Enterprise Search and Web Search are different

  1. Within the firewall, information is stored in various proprietary information systems, databases and applications, on various file shares, in a myriad of formats and with sophisticated security and version control issues to take into account. On the Web, what your web crawler can find is what it indexes.
  2. Within the firewall, you know every single logged in user, the main information access needs she has, the people she knows, the projects she is taking part in and the documents she has written. On the Web, you have less precise knowledge about the context the user is in.
  3. Within the firewall, you have less links and other clear inter-document dependencies that you can use for ranking search results. On the Web, everything is linked together providing an excellent starting point for algorithms such as Google’s PageRank.

Clearly, the settings differ as do user needs. Therefore, the internal search application will be different from a search service on the web; at least if you want it to really work as intended.

Start by Setting up a Findability Strategy

When you know where you are and where you want to be in terms of Findability—i.e. when you have a Findability strategy—you can design and implement your search solution using the search platform that best fits the needs of your company. It might well be Google’s Search Appliance. Just do not forget, the GSA is a totally different beast compared to the Google your users are accustomed to on the Web!