Category Archives: Findability

Why search and Findability is critical for the customer experience and NPS on websites

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To achieve a high NPS, Net Promoter Score, the customer experience (cx) is crucial and a critical factor behind a positive customer experience is the ease of doing business. For companies who interact with their customers through the web (which ought to be almost every company these days) this of course implies a need to have good Findability and search on the website in order for visitors to be able to find what they are looking for without effort.

The concept of NPS was created by Fred Reichheld and his colleagues of Bain and Co who had an increasing recognition that measuring customer satisfaction on its own wasn’t enough to make conclusions of customer loyalty. After some research together with Satmetrix they came up with a single question that they deemed to be the only relevant one for predicting business success “How likely are you to recommend company X to a friend or colleague.” Depending upon the answer to that single question, using a scale of 0 to 10, the respondent would be considered one of the following:

net-promoter

The Net Promoter Score model

The idea is that Promoters—the loyal, enthusiastic customers who love doing business with you—are worth far more to your company than passive customers or detractors. To obtain the actual NPS score the percentage of Detractors is deducted from the percentage of Promoters.

How the customer experience drives NPS

Several studies indicate four main drivers behind NPS:

  • Brand relationship
  • Experience of / satisfaction with product offerings (features; relevance; pricing)
  • Ease of doing business (simplicity; efficiency; reliability)
  • Touch point experience (the degree of warmth and understanding conveyed by front-line employees)

According to ‘voice of the customer’ research conducted by British customer experience consultancy Cape Consulting the ease of doing business and the touch point experience accounts for 60 % of the Net Promoter Score, with some variations between different industry sectors. Both factors are directly correlated to how easy it is for customers to find what they are looking for on the web and how easily front-line employees can find the right information to help and guide the customer.

Successful companies devote much attention to user experience on their website but when trying to figure out how most visitors will behave website owners tend to overlook the search function. Hence visitors who are unfamiliar with the design struggle to find the product or information they are looking for causing unnecessary frustration and quite possibly the customer/potential customer runs out of patience with the company.

Ideally, Findability on a company website or ecommerce site is a state where desired content is displayed immediately without any effort at all. Product recommendations based on the behavior of previous visitors is an example but it has limitations and requires a large set of data to be accurate. When a visitor has a very specific query, a long tail search, the accuracy becomes even more important because there will be no such thing as a close enough answer. Imagine a visitor to a logistics company website looking for information about delivery times from one city to another, an ecommerce site where the visitor has found the right product but wants to know the company’s return policy before making a purchase or a visitor to a hospital’s website looking for contact details to a specific department. Examples like these are situations where there is only one correct answer and failure to deliver that answer in a simple and reliable manner will negatively impact the customer experience and probably create a frustrated visitor who might leave the site and look at the competition instead.

Investing in search have positive impacts on NPS and the bottom line 

Google has taught people how to search and what to expect from a search function. Step one is to create a user friendly search function on your website but then you must actively maintain the master data, business rules, relevance models and the zero-results hits to make sure the customer experience is aligned. Also, take a look at the keywords and phrases your visitors use when searching. This is useful business intelligence about your customers and it can also indicate what type of information you should highlight on your website. Achieving good Findability on your website requires more than just the right technology and modern website design. It is an ongoing process that successfully managed can have a huge impact on the customer experience and your NPS which means your investment in search will generate positive results on your bottom line.

More posts on this topic will follow.

/Olof Belfrage

Query Rules in SharePoint 2013

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Leaving both the SharePoint Conference in Las Vegas and the recent European SharePoint Conference in Copenhagen behind, Findwise continues sharing impressions about the new search in SharePoint 2013! We have previously given an overview of what is new in search in SharePoint 2013 and discussed Microsoft’s focus areas for the release. In this post, we focus more on the ranking of the search results using the query rules.

Understanding user intent in search is one of the key developments in the new release. The screenshots below, showing out-of-the-box functionality on some sample content, exemplify how the search engine adapts to the user query. Keywords such as ‘deck’, ‘expert’, or ‘video’ can express the user’s needs and expectations for different search results and information types, and what the search engine does in this case is promoting those results that have a higher probability to be relevant to the user’s search.

Query rules

Source: Microsoft

 

The adaptability of the search results can seem remarkable, as we see in these examples, aiming to provide more relevant search results through a better understanding of the user intent. Actually, this is powered by a new feature in SharePoint 2013 called query rules. Even more interesting maybe is that you can define your own custom query rules matching your specific needs without writing any code!

The simplest query rule would be to promote a specific result for a given search query. For example, you can promote a product’s instruction manual when the users search for that product name. Previously, in SharePoint 2010, you were able to define such promoted results (or “best bets”) using the Search Keywords. The query rules in SharePoint 2013 extend this functionality, providing an easy way to create powerful search experiences that adapt to user intent and business needs.

When defining a query rule, there are two main things to consider: conditions and corresponding actions. The conditions specify when the rule will be applied and the actions specify what to do when the rule is matched. There are six different condition types and three action types that can be defined.

For example, a query condition can be that a query keyword matches a specified phrase or a term from a dictionary (such as ‘picture’, ‘download’ or a product name from the term store), or that the query is more popular for a certain result type (such as images when for example searching for ‘cameras’), or that it matches a given regular expression (useful for matching phone numbers for example). The correlated actions can consist of promoting individual results on top of the ranked search results (promoting for example the image library), promoting a group of search results (such as image results, or search results federated from a web search engine), or changing the ranking of the search results by modifying the query (by changing the sorting of results or filtering on a content type). Another thing to consider is where you define the rule. Query rules can be created at Search Service Application, Site Collection, or Site level. The rules are inherited by default but you can remove, add, configure and change the order of query rules at each level. Fortunately, it also allows you to test a query and see which rules will fire.

There is one more thing though that you need to take into account: some features of query rules are limited in some of the licensing plans. Some plans only allow you to add the promoted results, and the more advanced actions on query rules are disabled. Check TechNet for guidelines on managing query rules and a list of features available across different licensing plans.

With the query rules, you have the freedom and power to change the search experience and adapt it to your needs. Defining the right keywords to be matched on the user queries and mapping the conditions with the relevant actions is easy but the process must undoubtedly be well managed. The management of the query rules should definitely be part of your SharePoint 2013 search governance strategy.

Let’s have a chat about how you can create great search experiences that match your specific users and business needs!

SLTC 2012 in retrospect – two cutting-edge components

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The 4th Swedish Language Technology Conference (SLTC) was held in Lund on 24-26 October 2012.
It is a biennial event organized by prominent research centres in Sweden.
The conference is, therefore, an excellent venue to exchange ideas with Swedish researchers in the field of Natural Language Processing (NLP), as well as present own research and be updated of the state-of-the-art in most of the areas of Text Analytics (TA).

This year Findwise participated in two tracks – in a workshop and in the main conference.
As the area of Search Analytics (SA) is very important to us, we decided to be proactive and sent an application to organize a workshop on the topic of “Exploratory Query Log Analysis” in connection with the main conference. The application was granted and the workshop was very successful. It gathered researchers who work in the area of SA from very different perspective – from utilizing deep Machine Learning to discover users’ intent,  to looking at query logs as a totally new genre. I will do a follow-up on that in another post. All the contributions to the workshop will also be uploaded on our research page.

As for the main conference, we had two papers accepted for presentation. The first one dealt with the topic of document summarization – both single and multidocument summarization
(http://www.slideshare.net/findwise/extractive-document-summarization-an-unsupervised-approach).
The second paper was about detecting Named Enities in Swedish
(http://www.slideshare.net/findwise/identification-of-entities-in-swedish).

These two papers presented de facto state-of-the-art results for Swedish both when it comes to document summarization and Named Entity Recognition (NER). As for the former task, there is neither a standard corpus for evaluation of summarization systems, nor many previous results and just few other systems which made it unfeasible to compare our own system with. Thus, we have contributed two things to the research in document summarization – a Swedish corpus based on featured Wikipedia articles to be used for evaluation and a system based on unsupervised Machine Learning, which by relying on domain boosting achieves state-of-the-art results for English and Swedish. Our system can be further improved by relying on our enhanced NER and Coreference resolution modules.

As for the NER paper, our Entity recognition system for Swedish achieves 74.0% F-score, which is 4% higher than another study presented simultaneously at SLTC (http://www.ling.su.se/english/nlp/tools/stagger). Both systems were evaluated on the same corpus, which is considered a de facto standard for evaluation of different NLP resources for Swedish. The unlabelled score (i.e. no fine-grained division of classes but just entity vs non-entity) of our system achieved 91.3% F-score (93.1% Precision and 89.6% Recall). When identifying people, the Findwise NER system achieves 78.1% Precision and 90.5% Recall (83.9% F-score).

So, what did we take home from the conference? We were really happy to see that the tools we develop for our customers are not something mediocre but rather something that is of very high quality and is the state-of-the-art in Swedish NLP. We actively share our results and our corpora for research perposes. Findwise showed keen interest in cooperating with other researchers in developing better tools and systems in the area of NLP and Text Analytics. And this I think is a huge bonus to all our current and prospective customers – we actively follow the current trends in the research community and cooperate with researchers, and our products do incorporate the latest findings in the field, which make us leverage both high quality and cutting-edge technology.

As we continuously improve our products, we have also released a Polish NER and some work has been initiated on Danish and Norwegian ones. More NLP components will be soon available for demo and testing on our research page.

Enterprise search case study: Vårdaktörsportalen makes reliable information easy to find for health professionals

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Vårdaktörsportalen (VAP) is a portal for health care providers made by Västra Götalandsregionen (VGR). This portal makes information from a number of reliable and authorised sources findable and accessible for the people who need it in their daily work. This stretches from doctors and nurses to medical secretaries primarily located in the region of Västra Götaland, Sweden. The site and most of its features and information is also accesible (in Swedish) to anyone through http://vap.vgregion.se. In November 2012 the first version of this site went live and Findwise had a big role in the creation of this search centric site. The main source of information for VAP is the regional guidelines found in a document repository within VGR but some other external sources are also included. These include trustworthy authorities like

  • Socialstyrelsen
  • Läkemedelsverket
  • SBU
  • TLV
  • 1177 - the public health care information site for citizens

This search solution is built around the open source search engine Apache Solr and our common tools for processing and indexing. For this site we have also implemented a rather unique metadata enhancement service that automatically extracts keywords from the document to index and attaches it as metadata. The keyword extraction is based on information from the medical term database SweMeSH. More information (in Swedish) can be found on Google Code. We also include synonyms to keywords to increase recall, making it easier to find documents regardless of what synonym used.

The metadata enhancement service was included because the quality of metadata on the external sites was not very good. VGR will work with the above mentioned authorities to try and make them understand that they would benefit if they improved their data. The source 1177 stands out with very good meta data and overall good quality texts.

We have conducted a user study to see how this first version is able to satisfy user demands. The result of that study shows that some local sources are missing, but a general positive feedback on the idea and the graphical design was collected.

Findwise is looking forward to continue working on VAP with VGR in the future to make it an even better tool.

Related links:

Enterprise Search in Practice: A Presentation of Survey Results and Areas for Expert Guidance

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Enterprise search in practice presentation has two main focuses. First, to present some interesting and sometimes rather contradicting findings from the Enterprise Search and Findability survey 2012. Second, to introduce an holistic approach to implementing search technology involving five different aspects that are all important to succeed and to reach findability rather than just the ability to search.

Presented at Gilbane Conference 2012 in Boston USA on the 28th of November by Mattias Ellison.

Presentation: Enterprise Search and Findability in 2013

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This was presented 8 November at J. Boye 2012 Conference in Aarhus, Denmark, by Kristian Norling.

Presentation Summary

There is a lot of talk about social, big data, cloud, digital workplace and semantic web. But what about search, is there anything interesting happening within enterprise search and findability? Or is enterprise search dead?

In the spring of 2012,  we conducted a global survey on Enterprise Search and Findability. The resulting report based on the answers from survey tells us what the leading practitioners are doing and gives guidance for what you can do to make your organisation’s enterprise search and findability better in 2013.

This presentation will give you a sneak peak into the near future and trends of enterprise search, based on data form the survey and what the leaders that are satisfied with their search solutions do.

Topics on Enterprise Search

  •  Help me! Content overload!
  • The importance of context
  • Digging for gold with search analytics
  • What has trust to do with enterprise search?
  • Social search? Are you serious?
  • Oh, and that mobile thing

Tutorial: Optimising Your Content for Findability

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This tutorial was done on the 6th of November at J. Boye 2012 conference in Aarhus Denmark. Tutorial was done by Kristian Norling.

Findability and Your Content

As the amount of content continues to increase, new approaches are required to provide good user experiences. Findability has been introduced as a new term among content strategists and information architects and is most easily explained as:

“A state where all information is findable and an approach to reaching that state.”

Search technology is readily used to make information findable, but as many have realized technology alone is unfortunately not enough. To achieve findability additional activities across several important dimensions such as business, user, information and organisation are needed.

Search engine optimisation is one aspect of findability and many of the principles from SEO works in a intranet or website search context. This is sometimes called Enterprise Search Engine Optimisation (ESEO). Getting findability to work well for your website or intranet is a difficult task, that needs continuos work. It requires stamina, persistence, endurance, patience and of course time and money (resources).

Tutorial Topics

In this tutorial you will take a deep dive into the many aspects of findability, with some good practices on how to improve findability:

  • Enterprise Search Engines vs Web Search
  • Governance
  • Organisation
  • User involvement
  • Optimise content for findability
  • Metadata
  • Search Analytics

Brief Outline

We will start some very brief theory and then use real examples and also talk about what organisations that are most satisfied with their findability do.

Experience level

Participants should have some intranet/website experience. A basic understanding of HTML, with some previous work with content management will make your tutorial experience even better. A bonus if you have done some Search Engine Optimisation (SEO) for public websites.

Approaches for Building a Business Case for Enterprise Search

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Approaches for Identifying Information Access Needs and to Build a Business Case for Enterprise Search and Findability

We have defined a number of alternative approaches to identify the need and value of search-driven findability to support an organisation or a specific process. In other words, different methods to build a business case for enterprise search in a specific organization or process.

Task oriented

Analysing information access needs in relation to specific work task within a business process (by utilizing e.g. the method developed by Byström/Strindberg or the Customer Carewords method).

Process oriented

Mapping the process flow of sequential and dependent (value-adding) activities and the related information access needs, Analysing the dependencies/accessibility of information systems in the different activities (e.g. by using some kind of Business Process Modeling, like the Astrakan-method).

Decision oriented

Identifying and analysing the decision points and the related information access needs within a process.

Risk oriented

Analysing situations within a process or for decision points where the right information was not available. Or even worse if there only was old and unvalid information available? What would have been the outcome of the situation if the desired/needed information had been available? How can we avoid for this scenario to be repeated? Inspired by Lynda Moulton at LWM Technology Services and Martin White of IntranetFocus.

Effect oriented

Determine the desired effects from search-driven findability and define measuring point to follow up the effects over time. Includes also identification of the related target groups/personas and their information access needs to be fulfilled for the effects to be reached (based on the InUse method and previous work at Ericsson (Case Study) and Forsmark (Case Study). An enhanced variant of this method is currently being developed in a project at Chalmers.

Our ambition is to use these methods to help organisations identify information access needs and findability barriers and to help motivate search investments. The analysis could for example be performed by our Findability Business Consultants as part of an in-depth findability review focusing on either an existing application or a specific business process.

Presentation: The Why and How of Findability

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“The Why and How of Findability” presented by Kristian Norling at the ScanJour Kundeseminar in Copenhagen, 6 September 2012. We can make information findable with good metadata. The metadata makes it possible to create browsable, structured and highly findable information. We can make findability (and enterprise search) better by looking at findability in five different dimensions.

Five dimensions of Findability

1. BUSINESS - Build solutions to support your business processes and goals

2. INFORMATION - Prepare information to make it findable

3. USERS - Build usable solutions based on user needs

4. ORGANISATION - Govern and improve your solution over time

5. SEARCH TECHNOLOGY - Build solutions based on state-of-the-art search technology

Enterprise Search and Findability discussions at World Cafe in Oslo

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Yesterday we (Kristian Hjelseth and Kristian Norling) participated in a great World Cafe event arranged by Steria in Norway. We did a Pecha Kucha inspired presentation (scroll down to the bottom of this blog post for the presentation) to introduce the subject of Enterprise Search and Findability and how to work more efficiently with the help of enterprise search. Afterwards there was a set of three round-table workshop with practitioners, where search related issues were discussed. We found the discussions very interesting, so we thought we should share some of the topics with a broader audience.

The attendees had answered a survey before coming to the World Cafe. In which 83,3% stated that finding the right information was critical for their business goals. But only 20,3% were satisfied with their current search solution, because 75% said it was hard or very hard to find the right information. More stats from a global survey on enterprise search that asked the same questions.

Unified Search

To have all the information that you would like to find in the same search was deemed very important for findability by the participants. The experience of search is that the users don’t know what to search for, but to make it even worse, they do not know where to look for the information! This is also confirmed by the Enterprise Search and Findability Survey that was done earlier this year. The report is available for download.

Trust

Google web search always comes up as an example of what “just works”. And it does work because they found a clever algorithm, PageRank, that basically measures the trustworthiness of information. Since PageRank is heavily dependent on inbound links this way of measuring trust is probably not going to work on an intranet where cross-referencing is not as common based on our experience. Most of the time it is not even possible to link stuff on the intranet, since the information is not accessible through http. Read more about it in this great in-depth article series on the difference between web search and enterprise search by Mark Bennet.

So how can we make search inside the firewall as good as web search? I think by connecting the information to the author. Trust builds between people based on their views of others. Simply put, someone has the authority over her peers either through rank (=organisation chart) or through trust. The trustworthiness can be based on the persons ability to connect to other people (we all probably know someone who knows “everyone”) or we trust someone based on the persons knowledge. More reading on the importance of trust in organisations. How to do this in practice? Some ideas in this post by BIll Ives. Also a good read: “How social is Enterprise Search?” by Jed Cawthorne. And finally another good post to read.

Metadata

By adding relevant metadata to information, we can make it more findable. There was discussions on the importance of strict and controlled metadata and how to handle user tagging. For an idea on how to think about metadata, read a blog post on how VGR used metadata by Kristian Norling.

Search Analytics

Before you start to do any major work with your current enterprise search solution, look at the search log files and analyze the data. You might be surprised in what you find. Search analytics is great if you want insight into what the user expects to find when they search. Watch this video for an introduction to Search Analytics in Practice.

Other subjects

  • Access control and transparency
  • Who owns search?
  • Who owns the information?
  • Personalization of search results
All these subjects and many more were discussed at the workshops, but that will have to wait for another blog post!
As always, your thoughts and comments are most welcome!