Customer feedback analytics and ticket classification make for a successful wearable technology product launch. Read the full case study here.
Story
A global consumer electronics company was on the verge of releasing a brand new wearable product. Given such a high-profile launch, the company needed to be ready to resolve any issues that might crop up — and much more quickly than traditional methodologies could handle.
Challenge
They needed a solution that could detect issues automatically, allowing them to instantly prioritize and route incoming support tickets with ease. The problem was that most natural language vendors relied on a keyword-based approach. This meant they’d have to manually build and maintain a list of ontologies to tell the system what to look for.
The weeks to months-long setup time for this approach would not work with the company’s product launch schedule. In addition, consultants would have to regularly update and maintain the ontology, adding to the time and cost of the overall solution. Most concerning was the fact that any unexpected issues, for which a keyword had not been programmed, could be missed entirely.
Solution
The company decided to work with Luminoso because of our foundation in artificial intelligence and natural language understanding. Instead of scanning text-based feedback for matching words or terms, Luminoso’s solutions focus on understanding the underlying concepts in data – no matter which specific words are used to describe that content.
Results
As early as 24 hours after the product launch, the company began reaping benefits.
Fast Time to Insight: It took less than ten minutes to set up and Luminoso’s software, in contrast to the weeks to months it would have taken with another technology. The company was able to begin analyzing incoming support tickets and finding insights right away.
Multilingual Capabilities: Luminoso supports 14 languages, all of which are included in the software. No extra time, training, or work was required to get Luminoso’s solution up and running in the five major languages in which the company was receiving feedback.
Identify & Categorize Intent: Luminoso accomplished this in near-real-time and at a high level of accuracy.
Uncover Unexpected Insights: Within 24 hours, Luminoso’s software surfaced several unexpected insights. For example, Luminoso uncovered a subset of complaints related to a “scratched” or “cracked” screen. While the matching label – “Repairs and Physical Damage” – seemed obvious, the underlying cause of the issue was unexpected. Rather than being due to user damage, the technology was arriving with already-cracked or otherwise damaged screens. Determining the root cause of this issue enabled the company to take appropriate action and resolve the issue.
In addition, Luminoso’s software was able to uncover entirely unanticipated issues that would have gone unnoticed using a keyword-based approach. One such issue was a dial on the product that was
critical to the use of the device but which users reported as “sticking” or being entirely “unresponsive.” Even for consumers who had no issues using the dial, many found that the direction the dial turned was counterintuitive. Because this issue was quickly surfaced and isolated, the support team could take immediate action.Monitor Trends: Luminoso’s software monitored the prevalence of assigned labels and produced easily digestible reports, which the company’s analysts could use to quickly identify emerging issues. Key issues were monitored to see if they were trending upwards or downwards, enabling the support team to prioritize which problems were most pressing.
With Luminoso’s software, the global technology company was able to analyze and monitor their support processes in a more accurate, rapid, and streamlined way. The findings uncovered in the weeks following the product launch were critical in helping the technology company smoothly and successfully introduce its new product to market.
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