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

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

Big Data is a Big Challenge

Big Data is also a Big Challenge for a number of companies that would like to be ahead of the competition. I think Findwise can help a lot with both technical expertise in text analytics and search technology but also with how to put Big Data to use in a business.

During the last days of February I had the pleasure to attend IDG Big Data conference in Warsaw, Poland. It brought plenty of people from both vendors and industry that shared interesting insights on the topic. In general, big vendors that try to be associated with Big Data dominated the conference. IBM, SAS, SAP, Teradata has provided massive marketing information on software products and capabilities around Big Data. Interestingly every single presentation had its own definition on what Big Data is. This is probably caused by the fact that everybody tries to find the best definitions for fitting own products into it.

From my perspective it was very nice to hear that everyone agrees text analytics and search components are of big importance in any Big Data solution. In multiple applications analysis (both predictive and deductive) and for mass social media one must use advanced linguistic techniques for retrieving and structuring the data streams. This sounded especially strong in IBM and SAS presentations.

A couple of companies revealed what they have already achieved in so called Big Data. Orange and T-Mobile presented their approach of extending traditional business intelligence to harness Big Data. They want to go beyond standard data collected in transaction databases and open up for all the information they have from calls (picked and non-answered), SMS, data transmission logs, etc. Telecom companies consider this kind of information to be a good source for data about their clients.

But the most interesting sessions were held by companies that openly shared their experience about evolution of their Big Data solutions based mainly on open source software. In this way Adam Kawa from Spotify showed how they based their platform on Hadoop cluster starting from a single server to a few hundreds nowadays. To me that seems like a good way to grow and adapt easily to changing business needs and altering external conditions.

Nasza Klasa – a Polish Facebook competitor had a very good presentation on several dimensions connected to challenges in Big Data solutions that might be used for summarisation of this post:

  1. Lack of legal regulations – Currently there are no clear regulations on how the data might be used and how to make money out of it. It is especially important for social portals where all our personal information might be used for different kinds of analysis and sold in aggregated or non-aggregated form. But the laws might be changed soon, thus changing the business too.
  2. Big Data is a bit like research – it is hard to predict return on investment on Big Data as it is a novelty but also a very powerful tool. For many who are looking into this the challenge is internal, to convince executives to invest in something that is still rather vague.
  3. Lack of data scientists – even if there are tools for operating on Big Data, there is a huge lack of skilled people – Big Data operators. These are not IT people nor developers but rather open-minded people with a good mathematical background able to understand and find patterns in a constantly growing stream of various structured and unstructured information.

As I stated at the beginning of this post, Big Data is also a Big Challenge for a number of companies that would like to be ahead of the competition. I truly believe we at Findwise can help a lot within this area, we have both the technical expertise and experience on how to put Big Data to use in a business.

Analyzing the Voice of Customers with Text Analytics

Understanding what your customer thinks about your company, your products and your service can be done in many different ways. Today companies regularly analyze sales statistics, customer surveys and conduct market analysis. But to get the whole picture of the voice of customer, we need to consider the information that is not captured in a structured way in databases or questionnaires.

I attended the Text Analytics Summit earlier this year in London and was introduced to several real-life implementations of how text analytics tools and techniques are used to analyze text in different ways. There were applications for text analytics within pharmaceutical industry, defense and intelligence as well as other industries, but most common at the conference were the case studies within customer analytics.

For a few years now, the social media space has boomed as platforms of all kinds of human interaction and communication, and analyzing this unstructured information found on Twitter and Facebook can give corporations deeper insight into how their customers experience their products and services. But there’s also plenty of text-based information within an organization, that holds valuable insights about their customers, for instance notes being taken in customer service centers, as well as emails sent from customers. By combining both social media information with the internally available information, a company can get a more detailed understanding of their customers.

In its most basic form, the text analytics tools can analyze how different products are perceived in different customer groups. With sentiment analysis a marketing or product development department can understand if the products are retrieved in a positive, negative or just neutral manner. But the analysis could also be combined with other data, such as marketing campaign data, where traditional structured analysis would be combined with the textual analysis.

At the text analytics conference, several exciting solutions where presented, for example an European telecom company that used voice of customer analysis to listen in on the customer ‘buzz’ about their broadband internet services, and would get early warnings when customers where annoyed with the performance of the service, before customers started phoning the customer service. This analysis had become a part of the Quality of Service work at the company.

With the emergence of social media, and where more and more communication is done digitally, the tools and techniques for text analytics has improved and we now start to see very real business cases outside the universities. This is very promising for the adaptation of text analytics within the commercial industries.

Analytics and Big Data at IBM Information On Demand 2011

The big trend these days are in Big Data and how you can analyze large amounts of information in order to gain important insights, and from those insights be able to take the right action. This trend was a hot topic at the IBM Information On Demand (IOD) conference in Las Vegas earlier this year. IBM has a very strong position in this field, it’s hard to have missed how their computer system Watson challenged the top players of all time in Jeopardy recently, and won! Read more about Watson

Now IBM has taken the technology behind Watson and started to apply it in their different analytics products, where one specific area that is being targeted is healthcare. For this area IBM released a new product during IOD called IBM Content and Predictive Analytics for Healthcare, which can for example be used as a tool for physicians to support them in their diagnosis of patients.

In April this year IBM merged two of their products, their search engine OmniFind and their product for analyzing large amounts of unstructured information, Content Analytics. The new product is called IBM Content analytics with Enterprise search and it too is based on much of the same technology that is used in Watson, more specifically it utilizes the same Natural Language Processing techniques. This means that it has the ability to understand text on a level just as sophisticated as that of Watson.

Content Analytics with enterprise search scales very well to many millions of documents. However, when there is a need for analyzing really enormous data sets, in the magnitude of petabytes or even exabytes, IBM has developed what they call their BigData platform. This platform mainly revolves around two products, InfoSphere Streams and InfoSphere BigInsights, and it builds on a foundation of open source software, such as Apache Hadoop and Apache Lucene. InfoSphere Streams is used for real time analysis of information in motion. This helps you understand what’s happening right at this moment in your organization and supports you in taking appropriate action as things are happening. InfoSphere BigInsights on the other hand lets you analyze and draw insight from massive amounts of already existing data.

Studies have shown how organizations that fall short in this area are overtaken by those who understand how to use the power of analytics.

IBM has surely chosen an interesting path when merging Analytics with Findability.

Search Conferences 2011

During 2011 a large number of search conferences will take place all over the world. Some of them are dedicated to search, whereas others discuss the topic related to specific products, information management, usability etc.

Here are a few that might be of interest for those of you looking to be inspired and broaden your knowledge. Within a few weeks we will compile all the research related conferences – there are quite a few of them out there!
If there is anything you miss, please post a comment.

March
IntraTeam Event Copenhagen 2011
Main focus: Social intranets, SharePoint and Enterprise Search
March 1, 2 and 3, 2011, Copenhagen, Denmark

Webcoast
Main focus: A web event that is an unconference, meaning that the attendees themselves create the program by presenting on topics of their own expertise and interest.
March 18-20 , Gothenburg, Sweden

Info360
Main focus: Business productivity, Enterprise Content Management, SharePoint 2010
March 21-24, Walter E. Washington Convention Center, Washington, USA

April
International Search Summit Munich
Main focus: International search and social media.
4th April 2011, Hilton Munich Park Hotel, Germany

ECIR 2011: European Conference on Information Retrieval
Main focus: Presentation of new research results in the field of Information Retrieval
April18-21, Dublin, Ireland

May
Enterprise Search Summit Spring 2011
Main focus: Develop, implement and enhance cutting-edge internal search capabilities
May 10-11, New York, USA

International Search Summit: London
Main focus: International search and social media
May 18th, Millennium Gloucester Hotel, London, England

Lucene Revolution
Main focus: The world’s largest conference dedicated to open source search.
May 25-26, San Francisco Airport Hyatt Regency, USA

SharePoint Fest – Denver 2011
Main focus: In search track: Enterprise Search, Search & Records Management, & FAST for SharePoint
May 19-20, Colorado Convention Center, USA

June
International Search Summit Seattle
Main focus: International search and social media
June 9th, Bell Harbor Conference Center, Seattle, USA

2011 Semantic Technology Conference
Main focus: Semantic technologies – including Search, Content Management, Business Intelligence
June 5-9, Hilton Union Square, San Francisco, USA

October
SharePoint Conference 2011
Main focus: SharePoint and related technologies
October 3-6, Anaheim, California, USA

November
Enterprise Search Summit Fall Nov 1-3
Main focus: How to implement, manage, and enhance search in your organization
Integrated with the KMWorld Conference, SharePoint Symposium and Taxonomy Bootcamp,

KM-world
(Co-locating with Enterprise Search Summit Fall, Taxonomy Boot Camp and Sharepoint Symposium)
Main focus: Knowledge creation, publishing, sharing, finding, mining, reuse etc
November 1 – 3, Washington Marriott Wardman Park, Washington DC, USA

Gilbane group Boston
Main focus: Within search: semantic, mobile, SharePoint, social search
November 29 – December 1, Boston, USA

Findability Blog: Wrapping up the 2010 posts

Christmas is finally here and at Findwise we are taking a few days off to spend time with family and friends.

During 2010 we’ve delivered more than 25 successful projects, arranged breakfast seminars to talk about customer solutions (based on Microsoft, IBM, Autonomy and Open source), meet-ups in a number of cities as well as networking meetings for profound Findability discussions and moving in parties for our new offices.

At our Findability blog we have been discussing technology and vendor solutions (Microsoft and FAST, Autonomy, IBM, Google and open source), researchconferences, customized solutions and how to find a balance between technology and people.

Some of our posts have resulted in discussions, both on our own blog and in other forums. Please get involved in some of the previous ongoing discussions on “Solr Processing Pipeline”,  “Search and Business Intelligence” or “If a piece of content is never read, does it exist?”  if you have thoughts to share.

Findability blog is taking a break and we will be back with new posts is January.

If you have some spare time during the vacation some of customers run their own blogs, and good reading tips within Findability are the blogs driven by Kristian Norling (VGR) and Alexandra Larsson (Swedish armed forces).

Merry Christmas and a Happy New Year to you all!

Enterprise Search and Business Intelligence?

Business Intelligence (BI) and Enterprise Search is a never ending story

A number of years ago Gartner coined “Biggle” – which was an expression for BI meeting Google. Back then a number of BI vendors, among them Cognos and SAS, claimed that they were working with enterprise search strategically (e.g. became Google One-box partners). Search vendors, like FAST, Autonomy and IBM also started to cooperate with companies such as Cognos. “The Adaptive Warehouse” and “BI for the masses” soon became buzzwords that spread in the industry.

The skeptics claimed that enterprise search never would be good at numbers and that BI would never be good with text.

Since then a lot a lot has happened and today the major vendors within Enterprise Search all claim to have BI solutions that can be fully integrated (and the other way around – BI solutions that can integrate with enterprise search).

The aim is the same now as back then:  to provide unified access to both structured (database) and unstructured (content) corporate information. As FAST wrote in a number of ‘Special Focus’:

“Users should have access to a wide variety of data from just one, simple search interface, covering reports, analysis, scorecards, dashboards and other information from the BI side, along with documents, e-mail and other forms of unstructured information.”

And of course, this seems appealing to customers. But does access to all information really make us more likely to take the right decisions in terms of Business Intelligence. Gartner is in doubt.

Nigel Rayner, research vice president at Gartner Inc, says that:

”The problem isn’t that they (users) don’t have access to information or tools; they already have too much information, and that’s just in the structured BI world. Now you want to couple it with unstructured data? That’s a whole load of garbage coming from the outside world”.

But he also states that search can be used as one part of BI:

“Part of the problem with traditional BI is that it’s very focused on structured information. Search can help with getting access to the vast amount of structured information you have”

Looking at the discussions going on in forums, in blogs and in the research domain most people seem to agree with Gartner’s view: enterprise search and business intelligence makes a powerful combination, but the integrations needs to be made with a number of things in mind:

Data quality

As mentioned before, if one wants to make unstructured and structured information available as a complement to BI it needs to be of a good quality. Knowing that the information found is the latest copy and written by someone with knowledge of the area is essential. Bad information quality is a threat to an Enterprise Search solution, to a combined BI- and search solution it can be devastating. Having Content Lifecycles in place (reviewing, deleting, archiving etc) is a fundamental prerequisite.

Data analysis

Business Intelligence in traditionally built on pre-thought ideas of what data the users need, whereas search gives access to all information in an ad-hoc manner. To combine these two requires a structured way of analyzing the data. If the unstructured information is taken out of its context there is a risk that decisions are built on assumptions and not fact.

BI for the masses?

The old buzzwords are still alive, but the question mark remains. If one wants to give everyone access to BI-data it has to be clear what the purpose is. Giving people a context, for example combining the latest sales statistics with searches for information about the ongoing marketing activities serves a purpose and improves findability. Just making numbers available does not.

enterprise search and business intelligence dashboard

Business intelligence and enterprise search in a combined dashboard – vision or reality within a near future?

So, to conclude: Gartner’s vision of “Biggle” is not yet fulfilled. There are a number of interesting opportunities for the business to create findability solutions that combines business intelligence and enterprise search, but the strategies for adopting it needs to be developed in order to create the really interesting cases.

Have you come across any successful enterprise search and business intelligence integrations? What is your vision? Do you think the integration between the two is a likely scenario?

Please let us know by posting your comments.

It’s soon time for us to go on summer vacation.

If you are Swedish, Nicklas Lundblad from Google had an interesting program about search (Sommar i P1) the other day, which is available as a podcast.

Have a nice summer all of you!

Search in SharePoint 2010

This week there has been a lot of buzz about Microsoft’s launch of SharePoint 2010 and Office 2010. Since SharePoint 2007 has been the quickest growing server product in the history of Microsoft, the expectations on SharePoint 2010 are tremendous. And also great expectations for search in Sharepoint 2010

Apart from a great deal of possibilities when it comes to content creation, collaboration and networking, easy business intelligence etc. the launch also holds another promise: that of even better capabilities for search in Sharepoint 2010 (with the integration of FAST).

Since Microsoft acquired FAST in 2008, there have been a lot of speculations about what the future SharePoint versions may include in terms of search. And since Microsoft announced that they will drop their Linux and UNIX versions in order to focus on higher innovation speed, Microsoft customer are expecting something more than the regular. In an early phase it was also clear that Microsoft is eager to take market shares from the growing market in internet business.

So, simply put, the solutions that Microsoft now provide in terms of search is solutions for Business productivity (where the truly sophisticated search capabilities are available if you have Enterprise CAL-licenses, i.e. you pay for the number of users you have) and Internet Sites (where the pricing is based on the number of servers). These can then be used in a number of scenarios, all dependent on the business and end-user needs.
Microsoft has chosen to describe it like this:

  • Foundation” is, briefly put, basic SharePoint search (Site Search).
  • Standard” adds collaboration features to the “Foundation” edition and allows it to tie into repositories outside of SharePoint.
  • Enterprise ” adds a number of capabilities, previously only available through FAST licenses, such as contextual search (recognition of departments, names, geographies etc), ability to tag meta data to unstructured content, more scalability etc.

I’m not going to go into detail, rather just conclude that the more Microsoft technology the company or organization already use, the more benefits it will gain from investing in SharePoint search capabilities.

And just to be clear:  non-SharePoint versions (stand-alone) of FAST are still available, even though they are not promoted as intense as the SharePoint ones.

Apart from Microsoft’s overview above, Microsoft Technet provides a more deepdrawing description of the features and functionality from both an end-user and administrator point of view.

We look forward describing the features and functions in more detail in our upcoming customer cases. If you have any questions to our SharePoint or FAST search specialist, don’t hesitate to post them here on the blog. We’ll make sure you get all the answers.

Findwise in Cooperation with Borås University College Receives Research Grant

In recent decades Swedish and Western industry have had to adapt to the new paradigm. Moving from classical production industry organizations towards knowledge companies in which sales of services and knowledge are often bundled with a product – resulting in a complete solution. This change is vital for the survival of the Western world’s economy which previously has been built upon organizations of heavy industrial giants optimizing production processes and factory outputs by reducing overheads and increasing quality.

The threat to the industry from low cost countries, which no longer only compete just on low cost, but also with high quality and competence, forces Western organizations to develop new strategies to sustain their growth and competitive advantage. Cutting margins in order to compete with low cost countries is a downward spiral. Instead changing the model, to be able to provide knowledge and holistic understanding of customers needs and the ability to rapidly deliver a complete solution is now becoming the key competitive advantage. This however requires investment in IT and knowledge exchange tools. By moving away from selling physical products and components to solutions higher margins are possible because more business value is exchanged in the transactions.

The organizations adapting to this change, are identifiable by the fact that they consider knowledge and information as corporate assets – treated and cared for as any other asset. One example is the Swedish company SKF Group whose new vision is the “Knowledge Engineering Company” where the company going through a change from component supplier to a holistic supplier of both products and services.

A key success factor in this transformation from products to solutions is that the supply of knowledge and information to the employees is effective, easy to use and complete. The organization succeeds in providing that extra value, thereby allowing higher margins. Historical key performing indicators (KPIs) such as factory output, reduction of defects and increasing of quality, are dealing with physical production efficiency to ensure as little cost per unit manufactured and as high quality as possible. Individuals are used to measuring these KPIs and provide a way to manage the operational production processes. The turnover and efficiency of information and knowledge exchange lacks these models and measurement tools, thereby not allowing them to be managed. What you can’t measure, you can’t manage, or improve.

One technical solution which has the capabilities to enable complete, rapid and reduced turnover time for knowledge and information exchange, is Enterprise Search. This has been recognized by the Swedish Foundation for Strategic Research, which granted Findwise AB research funds to tackle this problem in cooperation with the College University of Borås in the Strategic Mobility program. The funded project will study the usefulness and value of a well functioning search engine for work-related information use. It will also identify performing indicators for information and knowledge exchange through search and to achieve results that systematically will illustrate the quantitative direct effects together with soft indirect effects.

The project will start early 2010 and run through the entire year. As part of the project, Dr. Katriina Byström will join Findwise and work together with Findwise employees in this joint research project. Findwise customers are invited to participate in the project and will have the availability to influence its direction. For more information on research at Findwise contact Henrik Strindberg.

About Dr. Katriina Byström
Dr. Katriina Byström is an associate professor in the Swedish School of Library and Information Science at the University College of Borås & Goteborg University, Sweden. She is one of initiators and director of the IA bachelor’s programme at Swedish School of Library and Information Science, and she is a chair for the programme with teaching involvement broadly across the curricula. Furthermore , Katriina is associate editor and co-founder at the Journal of Information Architecture. Katriina’s degree is in information studies, and her research focus on task-based information seeking, information retrieval and information architecture.

The Business Case for Enterprise Search

1. Achieve higher employee efficiency levels by providing company-wide, swift access to relevant information

Every business day, employees need to access information stored in various enterprise applications and databases. Enterprise Search addresses this need by providing your co-workers with swift access to relevant information and by consolidating, ranking and presenting it properly. The value proposition of enterprise search is thus to promote core business by enabling co-workers to work more efficiently, to avoid redoing work done elsewhere and to produce better quality as the information they need can be found through one single search solution.

2. Make more money by providing revenue-driving business processes with tailored means to access and act on information

The larger the corporation, the more different information access needs. Besides providing large user groups with general access to corporate information, an Enterprise Search solution can be tailored to meet the specific needs of revenue-driving business processes such as solution sales, business intelligence, patent management and mergers and acquisitions. There might not be that many people working in these areas, but the outcome of their work can have a tremendous impact on the bottom line of your company.

3. Leverage the hidden value of existing IT investments

The return on investment of Enterprise Search is not only a matter of getting your money’s worth for the license and deployment costs of the Enterprise Search solution. As the solution makes all the information hidden in document repositories findable through one search solution, the Enterprise Search solution will in fact help you get a return on investment on content management investments already made.

4. Lower your IT costs by centralizing access to information

Reduce your license, maintenance and support costs by providing one centralized Enterprise Search platform to handle all information access requests. Most companies store information in various information systems such as intranets and web sites, collaboration portals, document management systems, CRM and ERP systems and many other enterprise applications and databases. A typical set-up is to have separate search tools for each of these systems. By using your Enterprise Search platform as a service, you can replace these siloed search functions with one centrally monitored platform that provides search to each of these applications. In this way, you can reduce the annual costs on licenses, maintenance and support for separate search applications.