Category Archives: Customer Experience

Posts about customer experience

The amazing deeds of text analytics superheroes

In the last few years, the explosion of user-generated content in social media (networks, forums, communities, etc.) has significantly increased the need to extract information from unstructured content. Oddly enough, text analytics superheroes, wondrous as their achievements are, are just average guys who figured out what they could do with the right technology.

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Customer experience, a win-win in restaurants

 BLT sandwich, buttered or not?

 

Do you know if your customers prefer buttered toast in your BLT sandwich? Don’t worry; MeaningCloud is the kitchen helper you need to suit your dinner guest. Customer experience is the ingredient you need. Surfing the Internet you find hundreds of websites and apps to give feedback on restaurants. You could find by chance people talk about yours. Can you imagine people disparaging your BLT sandwich? For your information, I’d rather have it buttered.
blt-sandwich

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Net Promoter Score (NPS) via Voice of the Customer (VoC)

More and more companies have come to understand that to grow profitably in competitive scenarios, satisfied customers are the key to success. And they know that employees have a fundamental role in achieving a better customer experience.

In this challenge to improve customer loyalty, companies must be able to listen to their customers and understand what they are saying. It is what we call the Voice of the Customer (VoC).

However, a mission — such as customer satisfaction — that lacks a precise measure of success (or failure) is just hot air. Quoting Lord Kelvin, “If you can not measure it, you can not improve it.”

The Net Promoter Score (NPS) has become, for a number of companies, the key metric for measuring customer satisfaction. By the same standard, the mission to get motivated and happy people in an organization also has its key metric: the eNPS (Employee NPS).

As discussed below, in order to improve customer and employee experience, both the NPS and the eNPS need to find the reason that justifies the score given.

When asked What is the primary reason for your score? the NPS and the eNPS collect and analyze the open answers of thousands of customers and employees. Here is where the linguistic technology of Meaning Cloud intervenes.
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An Introduction to Sentiment Analysis (Opinion Mining)

In the last decade, sentiment analysis (SA), also known as opinion mining, has attracted an increasing interest. It is a hard challenge for language technologies, and achieving good results is much more difficult than some people think. The task of automatically classifying a text written in a natural language into a positive or negative feeling, opinion or subjectivity (Pang and Lee, 2008), is sometimes so complicated that even different human annotators disagree on the classification to be assigned to a given text. Personal interpretation by an individual is different from others, and this is also affected by cultural factors and each person’s experience. And the shorter the text, and the worse written, the more difficult the task becomes, as in the case of messages on social networks like Twitter or Facebook.

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Voice of the Customer Analysis and Benefits

 

What is the Voice of the Customer?

Social MediaHave you ever wondered why certain products or services undergo radical changes or even disappear from the market (and sometimes return with another trade name)? Does it depend only on the volume of sales or other factors come into play? To answer these questions, we should introduce the concept of “Voice of the Customer Analysis” and find out what it means. This term refers to all those practices which enable to understand what a (real or potential) customer thinks about a product or service. But it is not limited to a simple reading of comments or opinions written upon request -e.g. an online survey-, the issue is much more complex.

In recent years, the types of channels through which customers and users express their opinions, complaints, suggestions or congratulations (yes, these are also important, then we will see why) have multiplied exponentially. Only a decade ago, the channels that permitted the interaction with the business world were significantly fewer, among them we may recall the telephone or pre-compiled polls often sent by traditional mail. In addition, most of the exchanges between customer and company responded to a specific need of the second; in other words, they were requested.

 

How has it changed?

Today, the picture has radically changed.Voice of the Customer Analysis The communication channels are numerous and also allow to interact in different ways through various media (images, audio, video, etc.). And what matters most to us is that this interaction

  • is constant: 24 hours a day, 365 days a year;
  • most of the times is multilingual;
  • does not always follow predefined patterns (many times, it doesn’t even comply with the most basic spelling rules);
  • is unstructured: it is not stored in a traditional database nor organized according to predefined criteria.

There is no doubt that, from a corporate perspective, this enormous amount of information can be highly beneficial!
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Improve your Customer Experience Management with Text Analytics (recorded webinar)

Last June 10th we presented our webinar “Discover the WHY behind your Customer Scores – Improve your Customer Experience Management with Text Analytics”, featuring industry expert Seth Grimes.

The goal of the webinar was to ensure you are getting the most from your Customer Experience / Voice of the Customer initiatives, using text analytics to understand massive amounts of unsolicited, unstructured customer feedback in real time.

User Profiling and Segmentation

The agenda, with contributions from Seth and members of the MeaningCloud team, was:

  • Text analytics in Customer Experience (CX) management. Why is it important?
  • How text analytics complements/amplifies “traditional” CX? What specific benefits does it bring: understanding the reason behind the scores, extending to new, untapped feedback sources, analyzing CX in big data contexts … What new applications does it enable?
  • What text analytics techniques are applicable: text classification, information extraction, sentiment analysis, user profiling…
  • Analysis of some real scenarios/projects: survey analysis, contact center interaction, market research, social media analysis.
  • How to implement this easily with MeaningCloud: APIs, personalization tools, add-in for Excel.

For those of you interested, below you can find the webinar’s slides and recording.

And, if you want to give MeaningCloud a try and see how it can take your customer feedback analysis to the next level, register and use it for free here.

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Voice of the Customer in the banking industry

The Voice of the Customer (VoC) is a market research technique that produces a detailed set of customer wants and needs, organized into a hierarchical structure, and then prioritized in terms of relative importance and satisfaction with current alternatives.

Voice of the Customer (VoC)

The Voice of the Customer (VoC) is not a new concept. In one way or another, it’s been included in quality assurance processes for years, and yet, its full integration in the workflow is a pending tasks for many companies. The Voice of the Customer allows you to listen, interpret and react to what’s being said, and then monitor the impact your actions have over time.

The current challenge companies are facing comes from the volume of data available. In this digital age, feedback is ever-growing and not just limited to the periodic surveys sent to clients. Word-of-mouth has gone digital and has become more relevant than ever: everyone with a Twitter or a Facebook account has an opinion, and more often than not, it’s about the products and services they consume.

A typical client

A client

As so many other sectors, banking needs to figure out how to translate this first-hand source of knowledge their clients are providing into something useful, something that can be used in the company’s decision-making process.

Voice of the Customer combines two key aspects of information extraction: the need to know in detail what the customer is talking about and to interpret correctly his feelings about it. The former gives a quantitative view of the feedback obtained while the latter gives a more qualitative analysis, measuring what clients think a company is doing right or wrong.

The banking domain has the added difficulty of providing an extremely wide array of products and services, each one of them with very specific subcategories and received through completely different channels.

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The Role of Text Mining in the Insurance Industry

What can insurance companies do to exploit all their unstructured information?

A typical big data scenario

Insurance companies collect huge volumes of text on a daily basis and through multiple channels (their agents, customer care centers, emails, social networks, web in general). The information collected includes policies, expert and health reports, claims and complaints, results of surveys, relevant interactions between customers and no-customers in social networks, etc. It is impossible to handle, classify, interpret or extract the essential information from all that material.

The Insurance Industry is among the ones that most can benefit from the application of technologies for the intelligent analysis of free text (known as Text Analytics, Text Mining or Natural Language Processing).

Insurance companies have to cope also with the challenge of combining the results of the analysis of these textual contents with structured data (stored in conventional databases) to improve decision-making. In this sense, industry analysts consider essential the use of multiple technologies based on Artificial Intelligence (intelligent systems), Machine Learning (data mining) and Natural Language Processing (both statistical and symbolic or semantic).

Most promising areas of text analytics in the Insurance Sector

Fraud detection

Detección de Fraude

According to Accenture, in a report released in 2013, it is estimated that in Europe insurance companies lose between 8,000 and 12,000 million euros per year due to fraudulent claims, with an increasing trend. Additionally, the industry estimates that between 5% and 10% of the compensations paid by the companies in the previous year were due to fraudulent reasons, which could not be detected due to the lack of predictive analytic tools.

According to the specialized publication “Health Data Management”, Medicare’s fraud prevention system in the United States, which is based on predictive algorithms that analyze patterns in the providers’ billing, in 2013 saved more than 200 million dollars in rejected payments.

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The Analysis of Customer Experience, Touchstone in the Evolution of the Market of Language Technologies

The LT-Innovate 2014 Conference has just been held in Brussels. LT-Innovate is a forum and association of European companies in the sector of language technologies. To get an idea of the meaning and the importance of this market, suffice it to say that in Europe some 450 companies (mainly innovative SMEs) are part of it, and are responsible for 0.12% of European GDP. Daedalus is one of the fifteen European companies (and the only one from Spain) formally members of LT-Innovate Ltd. since its formation as an association, with headquarters in the United Kingdom, in 2012.

LTI_Manifesto_2014

LT-Innovate Innovation Manifesto 2014

In this 2014 edition, the document “LT-Innovate Innovation Manifesto:” Unleashing the Promise of the Language Technology Industry for a Language-Neutral Digital Single Market” has been published. I had the honor of being part of the round table which opened the conference. The main subject of my speech was the qualitative change experienced in recent times by the role of our technologies in the markets in which we operate. For years we have been incorporating our systems to solve in very limited areas the specific problems of our more or less visionary or innovative customers. This situation has already changed completely: language technologies now play a central role in a growing number of businesses.

Language Technologies in the Media Sector

In a recent post, I referred to this same issue with regard to the media sector. If before we would incorporate a solution to automate the annotation of file contents, now we deploy solutions that affect most aspects of the publishing business: we tag semantically pieces of news to improve the search experience on any channel (web, mobile, tablets), to recommend related content or additional one according to the interest profile of a specific reader, to facilitate findability and indexing by search engines (SEO, Search Engine Optimization), to place advertising related to the news context or the reader’s intention, to help monetize content in new forms, etc.

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Analyzing the Voice of the Customer channels at the Sentiment Analysis Symposium

Sentiment Analysis Symposium 2014

A few days ago we did a presentation at the Sentiment Analysis Symposium of New York. In our talk, we explained how to use text analysis technologies to listen to the different Voice of the Customer channels and get customer insights.

Textalytics at Sentiment Analysis Symposium 2014

For companies is vital to understand the opinions that their actual and potential customers express in new channels that are much more spontaneous and less structured than the traditional surveys (e.g. answers in questionnaires, interactions with contact centers, conversations in social media). The reach, the immediacy and the “emotional“aspect of these channels make them an impressive source of raw materials for obtaining valuable insights.

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