Use case: Product launch

Quick feedback after launch

All too often, companies develop, built and launch a new product based on the wrong assumptions. Even with all the research done beforehand, the voice of the ‘real’ customer is often not heard. The result is the loss of development costs, advertising costs and damage to the reputation of the brand.

Why should you read this case study?

Are you dealing with product launches as marketer or product developer for FMCG? And do you want to have the tools that help you minimizing the risks? Please read this great example of a use case where your peers used customer feedback analysis to find out something they would have never found out otherwise.

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80

of product launches fail after one year

3

is the average cost of a product launch in consumer goods

75

of young parents check their baby every night

Your customers tell you what the problem is

In this case, Wonderflow helped a large consumer care company to find out why their highly innovative baby product did not meet the buyers’ expectations.

The product in this case is a band-aid/plaster with a sensor, which measures the temperature of the baby. The sensor is connected to a phone through a dedicated application. Parents are notified through the app if and when the temperature of their baby is going up or down.

After the product launch, with a big marketing campaign to support it, sales started to increase but soon after it came to a halt. 

The challenges we faced:

  • Key question: find out what went ‘wrong’ with the product launch
  • Focus on the technical aspects of the product, rather than the user
  • Find out what data to collect and to analyse

Your most unhappy customers are your greatest source of learning

Many products were sold online, giving Wonderflow the opportunity to collect valuable feedback from the e-commerce platform. Furthermore, feedback on several blogs for young parents was analysed and all structured in one database.

By analyzing the customer feedback data by using the AI-based NLP engine of Wonderflow, it came to light that the product had one big omission. It would only notify parents in case of the temperature of their baby changed, yet it did not tell them if all was still the same (no news is good news). Worried parents wanted constant updates, so had to get out of bed in the middle of the night to double-check the baby’s temperature. Their assumption was that the app wasn’t working, as it didn’t tell them anything.

Cause: It turned out the none of the product developers were parents themselves and therefore didn’t identify with this feeling – assuming that no updates was a positive feature. However, the lack of feedback (when there was no change in temperature) was perceived as bad news by the parents.

After this issue came to light through the analysis done with Wonderflow, the following actions were taken:

  • A modification on the app: continuous feedback about the baby was added
  • The communication and packaging information were changed
  • The company ran an influencer campaign for damage control

Result:In only a timespan of 3 weeks, Wonderflow was able to provide in-depth analysis for over 500 customer reviews gathered on different platforms. After the modifications were made, sales of the product picked up again.

Conclusion

In just a very short time-span after the launch, Wonderflow was able to identify the problem. Gathering and analysing a few thousand records of customer feedback. Preventing the company from spending more on advertising or canceling this highly innovative product.

The information in this case study is confidential. Brands and company names are anonymized.

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