Audience platform Lucid has announced an independent, third-party verified quality assurance and measurement programme for market research sample.
The 10 Most Compelling Rio Olympics Ads, According to Facial-Tracking Technology Hershey wins gold with Simone Biles
Based on the feed from a web cam, Realeyes, working with audience platform Lucid, used machine learning and artificial intelligence to track the movements of 49 key facial points on 4,500 people to understand what each person thought and felt after watching dozens of Olympics ads. The data was then analyzed with an algorithm to understand which emotions were most prevalent and to rank the most compelling ads.
As the summer comes to a close, it is time to say goodbye to our intern class. At Lucid, our interns aren’t an adjunct to our team; they become part of it, and part of our culture. The hard work that they put in this summer is priceless – we hope to them as well as to us! Over the last few months, all eight of our interns have been working hard on projects to help our company grow. Let’s see what everyone was up to this summer!
Sample blending (using sample from multiple sources) broadens your reach while collecting data, and allows you to get more information faster because answers are coming from multiple sources instead of one, overall increasing the quality of your study. The concept of blending keeps the sample mix consistent over time because you are able to more accurately represent and monitor a specific target audience, making your data reliable. Get the most out of sample blending with these tips:
Emel Mohammadally has joined Lucid as executive director of business development, EMEA.
If you haven’t heard of it, you’re not alone. Nextdoor functions like a Facebook-Twitter hybrid that is made up of private neighborhood groups. With exclusive access to Lucid’s platform, Nextdoor was able to gain insight into the power of personal recommendation of neighborhood businesses and use that information to help advance its platform.
Do you ever wonder how great research comes together? In today’s 24/7 world of online sample, respondent engagement and perceived quality are critical metrics of success for all clients. How do you determine “bad” respondents? And more importantly, how do you ensure all respondents are engaged and providing the most accurate responses? Enter: red herrings.
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