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Research papers

Trends change, motivations do not

How to build age-less marketing campaigns that are relevant to the consumers? Revealing the impact of 'motivations' on sales in the brand echoverse using linguistic inquiry and machine learning.

Catalogue: Fusion 2019
Authors: Ezgi Akpinar, Serkan Ceran, Ilker Sermen, Merve Yigit Yontar
Companies: Ipsos MRBI, The Coca-Cola Company
November 10, 2019
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Citation

Akpinar, Ceran, Sermen and Yontar (2019a, November 10). Trends change, motivations do not. ANA - ESOMAR. Retrieved April 27, 2024, from


https://ana.esomar.org/documents/trends-change-motivations-do-not


Videos

iFactor

Using CRM data to harness clients' irritating experiences feedback thanks to machine learning enrich outcomes with a social data deep dive into customers' pain points and related emotions.

Catalogue: Fusion 2019
Authors: Charlotte Zaepfel, Mathilde Guinaudeau
Company: Ipsos MRBI
November 10, 2019
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Citation

Zaepfel and Guinaudeau (2019a, November 10). iFactor. ANA - ESOMAR. Retrieved April 27, 2024, from


https://ana.esomar.org/documents/ifactor-10852


Research papers

A practical fusion of qualitative and social data

In this guide, we will mostly be talking about how yo set up a search on the social listening tools and analyze the data that comes out, but we will also touch on how to get the most out of tools, such as Google Trends that are free for the public...

Catalogue: Fusion 2019
Authors: Ellie Osborne, Sarah de Caux, Jillian Ney
Companies: Join the Dots InSites Consulting, The Social Intelligence Lab
November 10, 2019
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Citation

Osborne, de Caux and Ney (2019a, November 10). A practical fusion of qualitative and social data. ANA - ESOMAR. Retrieved April 27, 2024, from


https://ana.esomar.org/documents/a-practical-fusion-of-qualitative-and-social-data


Videos

Future-proof data quality using AI

This presentation details the exploration of various machine learning algorithms/models, which are tested on different market research studies collected using face-to-face (F2F) data collection in East African markets. The supervised machine learning...

Catalogue: Fusion 2019
Author: Dharmendra Jain
Company: Kantar
November 10, 2019
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Citation

Jain, D. (2019a, November 10). Future-proof data quality using AI. ANA - ESOMAR. Retrieved April 27, 2024, from


https://ana.esomar.org/documents/future-proof-data-quality-using-ai-10848


Research papers

Future-proof data quality using AI

p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 10.0px Helvetica}This paper details the exploration of various machine learning algorithms/models, which are tested on different market research studies collected using face-to-face (F2F) data collection...

Catalogue: Fusion 2019
Author: Dharmendra Jain
Company: Kantar
November 10, 2019
×

Citation

Jain, D. (2019a, November 10). Future-proof data quality using AI. ANA - ESOMAR. Retrieved April 27, 2024, from


https://ana.esomar.org/documents/future-proof-data-quality-using-ai


Videos

Machine learning and privacy

Machine Learning algorithms are born as a solution to a problem. Once we feel comfortable with a prototype, there is still a long path to its deployment...and it is rarely a smooth one. We would like to share our experience transiting that path.

Catalogue: Fusion 2019
Author: Anna Bellido
Company: Netquest
November 10, 2019
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Citation

Bellido, A. (2019a, November 10). Machine learning and privacy. ANA - ESOMAR. Retrieved April 27, 2024, from


https://ana.esomar.org/documents/machine-learning-and-privacy-10847


Videos

Can machines be emotional?

We know emotions play an important role in consumer decision making but how do we access them at scale? SKIM and J&J teamed up to investigate!

Catalogue: Fusion 2019
Author: Marcel Slavenburg
Company: SKIM
November 10, 2019
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Citation

Slavenburg, M. (2019a, November 10). Can machines be emotional?. ANA - ESOMAR. Retrieved April 27, 2024, from


https://ana.esomar.org/documents/can-machines-be-emotional--10853


Research papers

Machine learning and privacy

Machine Learning algorithms are born as a solution to a problem. Once we feel comfortable with a prototype, there is still a long path to its deployment...and it is rarely a smooth one. We would like to share our experience transiting that path.

Catalogue: Fusion 2019
Authors: Marcello Frattini, Anna Bellido, Joaquin Casino
Company: Netquest
November 10, 2019
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Citation

Frattini, Bellido and Casino (2019a, November 10). Machine learning and privacy. ANA - ESOMAR. Retrieved April 27, 2024, from


https://ana.esomar.org/documents/machine-learning-and-privacy


Research papers

Rapid impact

p.p1 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px 'Helvetica Neue'}p.p2 {margin: 0.0px 0.0px 0.0px 0.0px; font: 12.0px 'Helvetica Neue'; min-height: 14.0px}Making a new product a market leader in one year through machine learning, psychology, and...

Catalogue: Congress 2019: The Global Data & Insights Summit
Authors: Genevieve Hall, Vivek Banerji, Daniel Rayner, Alessandro D'Angelo, Dan Atkins
Companies: Insight Dojo, Shionogi
September 8, 2019
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Citation

Hall, Banerji, Rayner, D'Angelo and Atkins (2019a, September 08). Rapid impact. ANA - ESOMAR. Retrieved April 27, 2024, from


https://ana.esomar.org/documents/rapid-impact