Automotive company uses VoC analytics to improve mobility experience


Learn how a transportation brand used data analytics to raise rider engagement (143%) and much more, driving the customer mobility experience forward.

  • 26% increase in driver CTR

  • 79% increase in driver engagement

  • 67% increase in rider CTR

  • 143% increase in rider engagement


We will share another success story from one of our clients, company N. This company deals in creating navigators for all transportation methods. Their primary focus is to generate the greatest available detail, accuracy, and real-time updates for their customers.

The company aims to provide the best available navigation systems. To research what more they could be doing for their clients, company N approached Wonderflow.

Main Problem

Before working with Wonderflow’s all-in-one solution, they handled their customer feedback analysis by collecting specific data from a few sources and analyzing them manually. Although it gave certain insights, this wasn’t enough to truly understand their customer’s goals. After a pilot program, where Wonderflow analyzed and reported on a set amount of reviews, the results were satisfying to company N.

However, that was just the beginning. In the case of the Wonderboard, the more you use it, the better it gets. The AI behind the data collection and analysis improves with each use, providing better reports and insights regarding quantity, quality, and accuracy. Before long, Wonderflow collected, analyzed, and reported on more than 112,000 reviews for 41 products, from 11 channels, in 6 different languages.

With all this data, the analysis generated crucial insights for company N. The most significant change was that Wonderflow segmented the reviewers based on which vehicle they were using. Company N already knew that their navigator users were split into two main categories: drivers (cars) and riders (motorcycles). The reviewers, though, did not identify themselves as either by themselves.

Through the Wonderboard’s Emotion Analysis, we segmented the reviewers based on how they felt when reviewing the navigators. For example, I liked it most because it could plan interesting routes for me to go out for a joyride. It meant that I discovered new places and new ways to go that were great fun. Hands down, this is my favorite part.

The above would be a review by a rider. More than 75% of riders-reviewers used words like “joyride, interesting, discover, tour,” which described a sense of adventure. It is safe to assume that riders were interested in using their motorbikes for more than commuting. Moreover, riders were analyzed to have long-winded reviews (average length of 280 words) since they are eager to share their emotions and a sense of adventure.

Finally, riders used strong, emotional adjectives, like “significantly, excellent, fantastic.” Riders were proven to be more romantic and sensitive in their reviews. Most of them were eager to use the navigator to take on adventures of all kinds with their bikes. Traveling while going through beautiful scenery or taking an exciting route was more critical for them than how long the ride would take.

On the other hand, we have this review: I now use my N daily on my commute to work just in case there are road works or an accident I can divert. You can already guess that it belongs to a driver. More than 82% of the driver-reviewers used words like “business miles, guide, road closures, plan a route.”

These words are used primarily to describe day-to-day processes (i.e., daily commute). Drivers were found to be more pragmatic and concise than the riders. Their reviews had an average of 200 words, significantly different from the riders’ average review length.

Finally, driver reviewers used unemotional phrases and neutral adjectives, like “simple to use, accurate directions” and “it works ok.” With that being said, the main aspects that they cared about were the ease of use and the best way to commute.

Main Solution

How to apply this analysis for MARCOM?

Having this kind of information and acting upon it, in a way that will be beneficial are two different things. The Wonderboard prompted through actionable insights that those words can be used in Marketing Communications (MARCOM).

That way, the wording from the analysis can increase CTR (click-through rate) and Engagement. Here’s how: before company N puts money behind campaigns and advertising, they test and experiment.

“You can always have an opinion about a headline and visual, but if you haven’t tested it with your audience, you don’t know how it will be perceived. In order to test you need different variations and here the Wonderflow analysis gives our copywriter great input by recommending which words and tone of voice to use.”, said Sophie, N’s Head of Marketing.

A proof of concept, however, is always necessary. For this reason, they created three Facebook ad variations for both groups: same visual, but different messaging. One of them was the copy they used in previous campaigns, and the other two were based on the wording from the analysis.

The outcome proved their assumption: the engagement with the ads was significantly higher for the new text. More specifically, Click Through Rates increased by 26% for drivers and 67% for riders.

Main Results

Overall, the analysis done by Wonderflow helped company N to dive deeper into their customers’ needs. They were able to identify their customers’ personas enabling them to provide products that will be more accurate to their needs.

After a new marketing campaign with different messages targeting both riders and drivers, company N was able to present some impressive results. More specifically:

Driver Results:

  • +26% CTR
  • +79% Engagement

Rider Results:

  • +67% CTR
    +143% Engagement

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.

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