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Leveraging Social Data to Mitigate Risk and Lower Recall/Warranty Costs
The sooner you are aware of a vehicle quality issue, the more money you save on warranty and recall expenses by capping the scale of the problem. Join the presentation and discussion to learn new ways for garnering early vehicle quality feedback.

Industry stakeholders are harnessing and distilling millions and millions of weekly social posts and enhanced government data to identify quality "needles in the haystack" on their applicable vehicles and vehicles systems. An organized industry data model curates the steam of data for:
• Each and every in-market Make and Model (ICE and BEVs)
• Vehicle Platforms (example, GM T1XX) and Market Segments
(example, Large SUV)
• 45+ vehicle systems
• Engineering Failure and Noise-Vibration-Harshness (NVH)
• Positive/Negative Comment Sentiment

These new methods often yield problems not detected by black box and DTC codes such as leaky sunroofs, driver-side wind noise, safety camera blackout, crackling audio, loosening hardware, etc. The data can also be additive to black box data and DTC codes, often providing additional vehicle owner context to more accurately determine the issue.

Feedback is timely, actionable and efficient. Social and government data is turned around daily as it is detected, with a unique ability to link to original social posts, extended discussion threads and an opportunity to reach end vehicle owners for feedback. Push notifications can be configured via the data model per user-defined categories to deliver relevant issues to user's inbox (Example: “Send me data on leaks of vehicle exteriors for GM and Toyota vehicles” or “Alert me of battery fires on any battery electric vehicle” or “Send me any Failure or NVH issue detected on my vehicle program”)

Sep 22, 2022 12:00 PM in Eastern Time (US and Canada)

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