Category Archives: Sentiment Analysis

Posts about Sentiment Analysis

Obtain deep customer insights with MeaningCloud

Companies need to analyze the feedback that customers provide to them through a variety of unstructured channels: surveys, interviews, contact center, social media. However, the text analytics solutions available are limited to a shallow analysis of the feedback. In this post we show you how to use deep analytics to get a complete picture of customer opinions, perceptions, emotions and intentions.

Companies need to become customer-focused in order to understand the needs and opinions of their customers and thus, define the proverbial “segment of 1”. This forces us to implement Voice of Customer (VoC) analysis initiatives that go far beyond the typical periodic satisfaction survey with numerical scores, to look for new sources of insights.

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Recorded webinar: Deep text analytics to transform customer feedback into action

Last April 29th we delivered our webinar “Leverage deep text analytics to transform customer feedback into action”. Thank you all for your interest.

In it we explained how to use Meaning Cloud’s products in a synergic way to analyze your customer feedback through surveys, contact center interactions and social media, and level up your customer insights.

During the session we covered these items:

  • Leveraging unstructured customer feedback: benefits and challenges
  • Text analytics to the rescue… but with limitations
  • How to use deep text analytics to extract more actionable insights
    • Pre-made Insights
    • Adaptation
    • Development
  • understand the opinions, perceptions, emotions and intentions of your customers.

Interested? Here you have the presentation and the recording of the webinar.

(También presentamos este webinar en español. Tenéis la grabación aquí.)

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Communication during the Coronavirus (I): Thematic analysis in Spanish digital news media

While it is obvious that the priority during this pandemic is to cure the sick, to prevent new cases from surfacing and to ensure there are economic and social measures in place to help the people and businesses most afflicted overcome the current situation; without a doubt, in the near future, the analysis of content related to the coronavirus that has been generated by the media and social network users will be the object of research for numerous disciplines such as sociology, philology, linguistics, audio-visual communication, and politics, to name a few.

At MeaningCloud we want to do our bit in this area, by applying our experience and our Text Analytics solutions to analyze the enormous volume of information in natural language, in Spanish and in other languages, in Spain and in other countries, given that, unfortunately, this is a global crisis.

This first article in the series centers on the thematic analysis of content that has been generated in Spanish by digital media platforms in Spain over the last month, how it has evolved during this period of time and the informative positioning of the main media platforms in Spain.

These other articles (only available, at the moment, in Spanish) analyse conversation topics on Twitter in Spain (both from the hashtags and general topics perspective and also applying a specific thematic categorization) and the linguistic analysis of presidential speeches related to this crisis.

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Leverage deep text analytics to transform customer feedback into action (webinar)

Customer FeedbackOne of MeaningCloud’s goals is providing you with the best text analytics technology to help you better understand your customers and in recent times we have been launching products in this area: Voice of the Customer, Emotion Recognition, Intention Analysis.

But maybe you haven’t thought about how to use these products in a synergic way to analyze your customers’ feedback through surveys, contact center interactions and social media, and transform that feedback into action.

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Use case: VoC program for retail

Voice of the Customer (VoC) programs have become an established path for retailers to deliver enhanced customer experiences.

Consumer behavior, nevertheless, is always changing. Retailers are rarely able to anticipate these behavioral changes or adapt quickly enough to preserve or grow their market share.

In 2018, a regional supermarket brand with over 800 hundred stores wanted to understand customer experience at every touchpoint in order to identify potential areas of customer frustration.

The company undertook a strategic Voice of the Customer (VoC) program with the aim of systematically and consistently capturing insights from the customer experience.

The program is still running. It comprises of around 23,000 surveys per month, completed by customers at various branches of the supermarket chain.

In retail, listening to the Voice of the Customer to identify the strengths and weaknesses of business is fundamental. Competition is fierce. Given that the scale of information to be analyzed is immense, the company decided to work with MeaningCloud to process the literal answers to the open-ended questions of the surveys, so they need not worry about the amount or the time needed to process them.
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Invoking the MeaningCloud Sentiment Analysis API from Minsait’s Onesait Platform

Minsait’s Onesait Platform is an IoT & Big Data Platform designed to facilitate and accelerate the construction of new systems and digital solutions and thus achieve the transformation and disruption of business. Minsait is a brand of Indra: its business unit addressing the challenges posed by digital transformation to companies and institutions.

Minsait has published a post about the procedure to invoke an external API from the integrated flow engine of the Onesait Platform (formerly known as Sofia2).

MeaningCloud integrated with Minsait Onesait Platform

The post titled HOW TO INVOKE AN EXTERNAL REST API FROM THE SOFIA2 FLOW ENGINE? uses as an example the integration of MeaningCloud Sentiment Analysis API (in Spanish).

The article illustrates one of the strengths of MeaningCloud: how easy it is to integrate its APIs into any system or process.


MeaningCloud Release: Sentiment + Nordic Pack

Not long ago we published the first of our Language Packs: the Nordic pack, which includes several text analytics tasks in Swedish, Danish, Norwegian and Finnish.

Among the text analytics tasks supported, there’s one that was missed by many of you: Sentiment Analysis API. Well, no more!

We are happy to announce that from now on you can also analyze sentiment in the four languages included in the Nordic pack. And what’s more, for those of you that are already subscribed to the pack, it has been automatically included and so you can start using it right away without any change in pricing.

MeaningCloud release

For those of you that are not subscribed to the Nordic pack, remember that you can test all our packs full functionality by requesting a 30 day period trial. It’s super easy!

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Voice of the Employee Dashboard

Voice of the Employee gathers the needs, wishes, hopes, and preferences of all employees within an organization. The VoE takes into account both explicit needs, such as salaries, career, health, and retirement, as well as tacit needs such as job satisfaction and the respect of co-workers and supervisors. This post follows the line of Voice of the Customer in Excel: creating a dashboard. We are creating another dashboard, this time for the Voice of the Employee.

Text-based data sources are a key factor for any organization that wants to understand the “whys”.

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Meaningful Voice of the Patient at ePharma 2018 – New York

MeaningCloud sponsors the E-pharma 2018 which is taking place in New York, March 21-23. MeaningCloud’s value proposition for the conference can be summarized as AI-based Voice of the Patient analysis for Patient Experience.

ePharma 2018 is about patient-centricity and engaging with patients with digital marketing.For pharmaceutical companies, it is vital to understand the feedback that their customers, both current and potential, express through all types of channels and contact points.

Text Analytics technologies automatically process and analyze textual content and provide valuable insights, transforming text-based “raw” data into structured, usable information.

 

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