Consumer Electronics (CE)

A Fortune 500 consumer electronics firm improved ratings by 6%, sales by 4%, and saved €500K

Learn how a global consumer electronics brand saved the launch of its new male razor by pinpointing the exact issue, thus improving average star ratings, e-commerce sales, and while saving on RnD costs.

6% improvement in average star ratings

4% increase in online sales

€500K was saved in RnD costs

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In this case study, we show how a Fortune 500 consumer electronics (CE) company saved a new product launch, an electric grooming razor for men, by pinpointing the exact issue that led to unexpectedly low sales. 

The team invested thousands of euros into its design and development, all tests successfully run, and they were confident the product would be a smash hit. As a result of this specific situation related to their male electric razor, our client saw a shockingly low ROI while star average ratings dropped across many e-commerce sites, and return and refund costs rose significantly. Plus, their customer service desks saw an abnormally high volume of calls complaints about the razor.

The client took immediate action by adopting a unified AI-based text mining solution, resulting in a 6% improvement in their razor’s average ratings and a 4% increase in recovery sales, while estimating that they saved €500,000 in damage control.

Wonderflow respects the client’s wish to remain anonymous and share limited information in this case. 

 

As Lotte, the firm’s product manager helped explained to introduce the problem better:

In the first weeks of release, the results were disheartening. We had done all the tests, and we couldn’t imagine what the reason behind such low scores was.

Lotte, Product Manager

Main Problem

Finding exactly why there's low sales in many ratings & reviews

It all happened when our client RnD department of a world-leading health-tech brand noticed a significant drop in both the average star rating and conversion rate of their recently launched electric facial razor for men.

Three different groups were mainly affected by the failed new product launch. So, we examine our client’s situation through the lens of the product manager, the customer service manager, and the consumer.

The Product Manager

As a product manager, Lotte has worked for our client for nearly eight years and was mainly responsible for overseeing the design and development of the new electric razor. 

Lotte first noticed the steep decline in the razor’s online ratings when monitoring its sales performance and actively scanning through its Amazon reviews. According to most online reviewers, the razor did not seem to work immediately for them right after purchase and unboxing it.

“Ok, but why? Lotte thought. With the help of her team, they scoured dozens of online customer feedback across multiple e-commerce platforms to try and find similar issues. After nearly three weeks, the manual analysis was beginning to look discouraging for the team. They couldn’t produce enough valuable insights into why razor sales were lower than expected. 

The Customer Service Manger

As our client’s customer service manager, Rebecca was experiencing higher volumes of customer emails than usual, plus chat support requests and calls. Most of them were complaints surrounding the new electric razor.

Customers mainly reported how the razor wouldn’t turn on for a while after they first unboxed it. Some got it to work after some hours, but most had to reach out due to instant frustration and asked the support agents to walk them through the product’s “messy” instruction pamphlet. 

Funny enough, many of the operators reported having very little knowledge about the new razor because, like the RnD team, they were also initially confident about the razor’s success.  So, not only were many employees slightly taken aback by the increasing complaints but generally had insufficient knowledge about the particular razor, leading most of them to feel unprepared in resolving the razor-related issues. Consequently, this significantly lowered our client’s overall customer satisfaction score.

The Customer

Another group affected by our client’s new razor launch is, of course, the end-users. In particular, our client believed they had found the possible source of the problem through Gijs, one of their new razor buyers. Gijs had emailed in his negative feedback to Rebecca regarding the product while at the same time detailing his situation enough to help the teams make valuable interpretations.

Gijs reported his excitement in unpackaging the new product only to find out that it “wasn’t doing anything.” However, unlike many other customers who bought the razor (as they shared in their reviews), Gijs reported not to have been immediately frustrated.

Instead, he simply realized afterward that the razor needed first to be plugged in and be set to ‘fully-charged mode before actual use. Its initial charge time took about an hour and a half, according to Gijs. He also mentioned that the user instructions were rather lengthy and unclear, demotivating him to read through it entirely. Gijs had to figure out how to turn on the razor on his own, which took him “several hours” out of his day.

And like Gijs, many other users left their negative feedback on similar issues. For instance, Michael, another of our client’s customers who bought the new razor, reviewed:

 

Main Solution

Global consumer electronics brand leverages Wonderflow: Getting to the heart of the problem

Our client instantly knew then that the best place to identify the source of the problem was their customer feedback data, which mainly drove the online sales of all their consumer electronic products.  So, Lotte’s team was tasked with finding a new text mining software that would allow them to uncover deeper consumer insights that they otherwise wouldn’t know. That was when our client approached Wonderflow, a unified customer-feedback analysis tool that utilizes artificial intelligence technology.

The program features that mainly benefited our client were (but are not limited to) the following:

On top of the above user benefits, our client also eliminated the need to hire new consumer insights analysts, thus saving more on acquisition costs. Compared to technologies requiring human input, our AI-enabled solution would be able to analyze the entire dataset, giving our client the full explanation of why customers were unhappy with the razor. Also, it collected only unbiased opinions, all at a more efficient speed.

Using a special technique called natural language processing, our AI accomplished the following main tasks:

  • Aggregated and processed our client’s customer feedback data across 80 different online channels (e.g., popular sources were contact center chats and call transcripts (both public and private, e-commerce review sites, retailers, etc.)
  • Performed an in-depth competitor analysis of the consumer electronics market, comparing our client against other similar competitors and granting them a full overview of the market
  • Automatically detected the customer sentiment behind each feedback source, categorizing them into several “aspects” or most talked-about topics

With the wealth of insights, our system automatically translated the results and presented them more comprehensively for most users to understand – all within a single dashboard called the Wonderboard. The client identified whether specific new-razor-related problems were brand-related or industry-related.

Moreover, our data revealed that many consumers simply felt misinformed about using the new razor right after purchase and opening. Thus, becoming dissatisfied with the product and brand. It’s generally known that many people don’t really read instructions. The razor’s user manual made it even harder for most users because it was lengthy and unclear.

Main Results

Improved ratings, sales, customer service, and overall satisfaction

What would have taken months for our client to extract the insights to take effective actions, Wonderflow did it within two weeks, including set up time. So, not only was our client happy with the quick access to insights, but they were also pleased with their ability to act quickly based on the data.

While we focused on analysis, our client prioritized their focus on fixing the actual problem. They decided to issue a second product rollout, introducing new packaging stickers explaining the brand’s reasoning behind the new (cordless) electric razor design. The labels also explicitly indicated that users must ensure the razor is fully charged right after purchase and opening.

The client modified their online product description as well and the razor’s user manual to be clearer and shorter. All in all, the solution was surprisingly more simple than everyone thought.

consumer electronics

After the two weeks that it took Wonderflow to perform the analysis and report its finding,  our client immediately began planning the second rollout in week three. By week four, they distributed the razor with its modified packaging and instructions and saw instant results within four days.

There was a steady increase in the product’s average star ratings, from 3.6 to 4.2 or up by 6%. Most of the revenue losses from the initial launch were recovered. Sales increased by 4% in the third quarter since the initial rollout. Lotte reported that her company saved an estimated €500,000 in research and development costs. On top of that, our client also saved on packaging and customer service costs.

Additionally, the customer service team reported a significantly lowered volume of customer complaints related to the razor. Therefore, allowing the department to redirect their attention to more pressing matters. After observing the improvements for a few months, Lotte shared:

In this [the electric razor] case, we received a quick response from the voice of the consumer and were able to save time, money and get back on track. We’ll have to keep a closer eye on consumer feedback from now on.

Lotte, Product Manager
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