What are the pros and cons of human text analysis – Part 2

Published on — Written by Wonderflow

pros and cons of human text analysis part 2 - wonderflow

In the previous video, our CEO Riccardo Osti explained the pros of human text analysis, which can be summarised into ease of getting started, the ease to reach good quality and our ability to identify irony and other anomalies.

Now let’s talk about the limitations that humans have when analysing texts:

#1 Consistency

This is one of the biggest problems that we have. In fact, as humans we have emotions, and we evaluate things differently, following our mood. It’s clear that we will hardly derive any scientific result from manual analysis.

#2 Memory

Dictionaries can become very specific, especially when we need to analyze data about different products in various industries. I have seen dictionaries with more than one hundred topics, and you can imagine how difficult would be to remember all of them, and their description while we go through the records. This task, that is clearly difficult for us, is instead simple for a machine, that can potentially remember infinite ontologies.

#3 Speed

Human analysis can be very slow. Well…that’s pretty straightforward, in fact, humans can analyze 10 to 12 records per hour on average. Machines, once configured can process millions of records in the same amount of time.

So what is the conclusion? Having humans is a good exercise to understand what your customers say about you and your products, however, as soon as we grow the complexity or the volume of the analysis, all kinds of limitations arise.

The lack of consistency in our behavior, but also our limited memory, and our low speed make the automated analysis more attractive, especially for brands that intend to do text analysis seriously, at scale.

We look forward to hearing your point of view about human text analysis.

About Wonderflow

Wonderflow empowers businesses with quick and impactful decision-making because it helps automate and deliver in-depth consumer and competitor insights. All within one place, results are simplified for professionals across any high-UGC organization, and department to access, understand, and share easily. Compared to hiring more analysts, Wonderflow’s AI eliminates the need for human-led setup and analysis, resulting in thousands of structured and unstructured reviews analyzed within a matter of weeks and with up to 50% or more accurate data. The system sources relevant private and public consumer feedback from over 200 channels, including emails, forums, call center logs, chat rooms, social media, and e-commerce. What’s most unique is that its AI is the first ever to help recommend personalized business actions and predict the impact of those actions on key outcomes. Wonderflow is leveraged by high-grade customers like Philips, DHL, Beko, Lavazza, Colgate-Palmolive, GSK, Delonghi, and more.

Start making winning decisions based on customer feedback todayGet a free demo

Business · Dec 12, 2018

Review of the week: Polar watch Vantage V

You’ve probably heard the term sentiment analysis before but never really took much notice of how important it can be for your company. Wonderflow offers many tools that help brands discover the “why” behind customer feedback (ex. Why do customer dislike X feature?). This is because the language people are using can be mined to discover their true emotions and the intent in their sentences. With this information, you can gain a real understanding of…

wonderflow image

Press · Apr 22, 2020

Wonderflow supports companies with free employee feedback analysis tool WonderWork

Wonderflow supports companies with free employee feedback analysis tool WonderWork WonderWork extracts actionable insights from employee feedback using artificial intelligence, aiming to help companies support new ways of working, as well as monitor and improve employee well-being.   Amsterdam (NL) and Trento (IT), April 23, 2020 – Wonderflow, a leader in artificial…

wonderflow image

Business · Mar 02, 2020

Video: What is the biggest limit of data science teams in an enterprise?

If we think about innovation today, the first thing that comes to our mind is probably related to information technology, complex software, and hardware. If we think about the word “innovation” inside a company, we are therefore pushed to think about the IT department, and we sometimes believe that all the new good…