Listening to the voice of the customer
Giving people what they want has always been the ultimate goal of a business, since the beginning of the modern era. In order to do so, many resources have been deployed to catch the voice of the customer, understanding their needs and tailoring the offer accordingly.
However, the voice of the customer has never been so loud before. Since the digital revolution, there is no shortage of feedback, reviews, social media casual comments from customers and clients. People are online every day, talking about their passions and their interests, often addressing directly the products they buy, elaborating on them in the public sphere and leaving an ocean of words for everyone to read. There are plenty of them, maybe too many.
The challenge the industry is facing is finding the most efficient way to process and analyse these raw data and convert them into actionable insights.
To better understand the future of our industry, we have taken into account two recent reports about last year trends in processing the voice of the customer and analysing the customer sentiment.
A glimpse into the future: the widespread adoption of Text Analysis
The first report we examined is the annual GreenBook Research Industry Trends Report (GRIT Report) which is a leading voice in the market research and consumer insights space.
The report goes in great length discussing how 2020 has been a pivotal year for the industry due to the COVID-19 crisis. The global situation had caused a sensible acceleration to the digitalization process in any kind of business.
Emerging methods of analysis of the voice of the customer saw widespread adoption in order to adapt to the “new normal”. As you can see in the picture below, methods such as mobile-first surveys and text analysis are rapidly rising to hegemony.
Are these emerging methods just a transitory trend or an actual “new normal”, here to stay? The educated guess of the GreenBook researchers, argued over one hundred pages of the report, is the latter one.
Following their study, we need to take a closer look at the growth of text analysis in particular, and how new approaches to it can change the way we collect customer sentiment.
The good old dilemma about Customers Sentiment: Quantitative vs. Qualitative
Our field is always debating about the pros and the cons of Quantitative Methods and Qualitative ones respectively. While a quantitative approach has force in numbers and can be easily automated, it lacks the accuracy of qualitative ways of analysis. Accurate text analysis falls in the latter category but its deeper look into customer sentiment comes with the price of more time spent and more human resources deployed to the task.
Researchers historically are able to spend days, weeks, or even months conducting studies to cleaning the data and coding the verbatim in a meaningful way.
But does it have to be this way?
What if we can blur the distinction between quantitative and qualitative methods with the help of new technologies?
Ultimately, the goal of technology should be to reduce or eliminate time spent on simple and repetitive tasks, allowing human beings to spend more time on complex tasks. This is what we do at Wonderflow, regarding a particular type of text we find online: the reviews.
Reviews Analysis matters and here’s why:
One of the richest and most relevant text we must focus our effort into are online reviews. The centrality of reviews analysis is stressed out in the second report we took into consideration, carried out by the prestigious Spiegel Research Center.
According to the SRC Report, nearly 95% of shoppers are reading online reviews before making a purchase, transforming forever the way consumers make purchase decisions. Can be obvious that having reviews help the selling, but the magnitude of the edge is surprising: the purchase likelihood for a product with five reviews is 270% greater than the purchase likelihood of a product with no reviews.
Other counterintuitive and interesting factors are enlighted by the report. For example, negative reviews can have a positive impact because they establish credibility and authenticity and five stars ones are perceived as “Too Good to be True”.
Although the Spiegel study is mostly quantitative, it shows the importance of reviews as a whole and how the “mixed messages” ones are the most valuable. Here the customer sentiment is articulated in a precise but often deceiving manner. The natural language can be so complex that we taught that processing it in-depth will always be a human-task.
We were wrong.
The edge of Wonderflow
Wonderflow uses a top-notch artificial intelligence technology to perform reviews analysis, achieving a deep comprehension of what people care about.
Thanks to advanced Artificial Intelligence programmed by our team of highly experienced linguists, Wonderflow works within the semantics of natural languages just as a human researcher would do. But spending a fraction of the time normally required.
As you can read in this case study, our A.I. is able to understand customer sentiment better than the customers themselves!
After collecting a lot of feedback from a variety of public data sources, such as ratings and reviews on e-commerce websites and Youtube comments; the A.I. is able to isolate linguistic patterns and recognizing what people really mean and really feel when using recurring terms and expressions regarding certain topics.
In other words, Wonderflow has the numbers and the speed of quantitative methods of analysis but the accuracy of qualitative ones.
Developing new strategies is mandatory for every business that wants to keep up the pace with this fast-changing world. While the internet is more central than ever in everyone life, innovative technologies able to search the web in a fast and meaningful way will be the standard in the digital marketing industry.
The voice of the customer is already there, scattered all around the net, telling us all we need to know to refining our products and selling the best experience possible.
We just need the right tool to collect and analyse it. Wonderflow is the right tool.
Leader of reviews analysis