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5 Best Practices for Drawing Insights from Consumer and Market Data

About this event

Time is money, yet unstructured data coupled with a vast variety of sources can halt even the most seasoned analysts. 

The good news is, by leveraging artificial intelligence (AI), you can avoid sifting through mountains of data to gain useful insights for your research project. In fact, 52% of business executives agree that AI boosted their productivity in 2021.

So the question is, what solutions will you leverage to save time on your own analyses in 2022? 

Join Sarah Flagg, Manager of Onboarding and Integrations, and Harvey Rañola, Global Head of Media Intelligence at NetBase Quid, for an incredible discussion about how to leverage AI to build processes that will ensure your research is conducted quickly, allowing you to run a much more comprehensive and nuanced analysis.

Explore real-world case studies from Tesla, Starbucks, and the hard-hit supply chain industry to improve your research, extract more meaningful data, and gain faster, more reliable results. Then discover how to save time by replicating your multi-hour analysis in just 10 minutes with NetBase Quid’s Artificial Intelligence platform.

3 Major Keys to Improving Your Research Productivity

  • Essential AI Techniques: Learn best practices for leveraging AI and drawing faster insights
  • Bias Prevention: Reduce and eliminate biased algorithms in your artificial intelligence
  • Data Structuring: How to share intelligence (and data) across your organization

Hosted by

  • Guest speaker
    Harvey Rañola Global Head of Media Intelligence @ NetBase Quid

    Harvey has been developing and executing marketing and revenue operations strategies for more than 10 years. He also has a background in journalism and multimedia production.

  • Guest speaker
    Sarah Flagg Manager of Onboarding and Integrations @ Netbase Quid

    Sarah has been with NetBase Quid for more than three years. With agency experience in client services, brand strategy, PR, and social media analytics, Sarah understands the importance of bringing multiple data sets together to inform "what’s next".


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