Author Archives: Eduardo Valencia

About Eduardo Valencia

Data-driven by instinct and by learning. I began my career as a linguist. Some things stay with you to the grave. Since 1995, I have been leading teams and companies that have successfully developed and distributed hundreds of successful data, analytics and ICT projects.

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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Introducing the Demo for VoC Retail

Illustration showing a group of shops. Voc Retail

At MeaningCloud, we know how important unstructured data is for  Voice of the Customer Analysis; so we’ve defined a model that will allow you to characterize any feedback, focusing on the retail domain, in detail that you receive from your customers.

Our experience in Voice of the Customer Analysis has shown us that to obtain useful results when consolidating or reorienting a business strategy the detection of peculiarities of a specific domain is vital, as much in a linguistic way as a conceptual way, taking into account the identifying characteristics of the brand to be analyzed. For this reason, we have not only developed an analysis model focused on the retail trade, but we have also adapted analytical tools towards the sale of groceries, personal care and homecare in the retail sector.

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How Artificial Intelligence makes RPA smarter: two use cases

RPA-automation-computer-robot-tools and statistics

Artificial Intelligence and RPA

Many organizations could be gaining huge operational efficiencies if they combined Artificial Intelligence and RPA (Robotic Process Automation).

In a previous post (The leading role of Natural Language Processing in Robotic Process Automation) we introduced the subject of NLP in RPA. In this post, we are seeing two use cases where Natural Language Processing (also known as Text Analytics) integrated with RPA/BPM software suites, is mature enough to solve typical insight extraction problems, conveniently and cost-effectively.

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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.

Case study on the voice of the patient for the Pharma industry

Pharmaceutical companies are extending their Voice of the Patient projects to include social media: comments on web forums, surveys, Twitter, and more.

The goal of the proof of concept ordered by one particular pharmaceutical company in Spain was to: ” Collect and analyze the voice of the patient, both quantitatively and qualitatively, from the channels where it is expressed”, including social networks like web forums, Facebook, Twitter, and other systems.

For the pharma industry, it is essential to listen and understand the feedback that their current and potential customers communicate through various means and touchpoints.

Web forums, for instance, gather millions of posts, and function as a meeting point for patients where support, experiences, and wisdom are shared with peers, family members, and friends.

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Web scraping and text analytics

Text analytics projects are often dependent on Internet-based public sources such as the World Wide Web. These projects usually begin by extracting data from a variety of websites. We call this process “web scraping” (or “web harvesting”). While users can handle web scraping manually, the term often refers to automated methods executed utilizing a web crawler.

Examples of projects that offer a valuable wealth of information include customer experience (in the same way as patient experience or employee experience), dynamic pricing and revenue optimization, competitor monitoring, or compliance checking. Continue reading →

People Analytics: MeaningCloud book on Amazon!

People Analytics. Data and Text Analytics for Human Resources

People Analytics. Data and Text Analytics for Human Resources. This MeaningCloud book is available on Amazon.

In People Analytics, and in this book, we use the evidence that the data provides to respond to several questions:

  • Which candidate will be high-performing, effective, loyal, and aligned with the corporate culture?
  • How can we measure the economic impact of a training program?
  • How can I segment the workforce to make their actions more effective?
  • Which people are considering leaving the organization?
  • What net benefit will employees contribute throughout time in a particular position?
  • How does employee commitment affect productivity and economic outcomes?
  • How can I design a study that is statistically and mathematically valid?

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Contact center: 6 ways to leverage text and speech analytics

Contact center. Ilustration

At contact centers, text analytics technology provides an unprecedented opportunity to convert customer interactions into business opportunities. We can improve customer experience, boost sales, reduce customer churn and streamline the efficiency of the processes.

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Pharmacovigilance: Monitoring the Voice of the Patient

Pharmacovigilance: Voice of the Patient

For the pharmaceutical industry, it is essential to listen and understand the feedback that their current and potential patients communicate through all sorts of channels and touchpoints.

Although there is a protocol that requires any identified Adverse Drug Reactions (ADRs) to be disclosed to the authorities, only 5–20% of them are reported. Fortunately, discussions regarding drugs, symptoms, conditions, and diseases can be analyzed to learn more about said branches of pharmaceutics. Artificial Intelligence significantly contributes in monitoring adverse episodes and understanding their impact in every phase of development.

Patient narratives of medicines and their adverse effects on social media represent an extra data source for drug safety monitoring.

At MeaningCloud, we have developed a platform to automate the process of monitoring ADRs on social media.

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