Based on the insights from two customers in India, the innovative UI design for improving new customer registration was first launched in India. As a result, we witnessed a 6% increase in new account creation, which in itself is a big win given the Indian population. In the following months, the same design was adopted by the worldwide team, and was launched across all marketplaces. This resulted in 10s of Million$ win worldwide to Amazon. More importantly, it drove comfort with the idea that even qualitative research in India can deliver gains as big as big data worldwide.
Based on the insights from two customers in India, the innovative UI design for improving new customer registration was first launched in India. As a result, we witnessed a 6% increase in new account creation, which in itself is a big win given the Indian population. In the following months, the same design was adopted by the worldwide team, and was launched across all marketplaces. This resulted in 10s of Million$ win worldwide to Amazon. More importantly, it drove comfort with the idea that even qualitative research in India can deliver gains as big as big data worldwide.
Up to 85% of brand generated social media posts are wasted. With digital advertising approaching 50% of all advertising expenditure, we need to go beyond clicks and likes as a measure of ROI on social media expenditure. Through machine learning, a brand can now see how many posts support their intended position, how many are off target, and how many are simply ambiguous. This presentation demonstrates how the AI tool works, highlights the role of archetypal alignment across touch points, delivers a practical framework where brands can specifically identify the nature of their optimal social media imagery, and concludes that understanding archetypal codes is the key to optimising ROI in Social Media.
A brand in crisis. A cut-throat category. No money to spend. How do you rebuild a brand after it has made headlines for all the wrong reasons? Oi used emotion and smart research to wipe out marketing waste and begin the climb back to happiness.
Developing successful communication is becoming more and more difficult every day, particularly because people are exposed to an exponential number of stimuli, which makes them block out everything they do not consider relevant for their survival and/or more intrinsic needs. However, in order to help brands and their communications succeed in their business objectives, new technologies and theories about how people make decisions are being developed. First of all is the neuroscience development allowing a better understanding of how the brain works. For example, exploring the now well-known brain systems, one intuitive (System 1) and the other deliberative (System 2), strong conclusions about the impact of emotions in advertising, and later in building valuable brands, are being made. On the other hand, facial expressions are recognized as a manifestation of the unconsciousness of our emotions and thanks to technology advancements, facial coding can be used in a scalable way to better understand how advertising impacts human emotions. Then again, facial coding should not exist as an isolated element of communication understanding; it is important to have a holistic understanding between emotions and deliberative responses using direct questions. Therefore, in order to demonstrate the power of holistic analysis with System 1 and System 2, this paper explores three real cases of creative development for one of the most important companies of FMCG in Latin America: Alicorp. These cases helped to build successful campaigns that positively impacted Alicorp's business and their brands.
A brand in crisis. A cut-throat category. No money to spend. How do you rebuild a brand after it has made headlines for all the wrong reasons? Oi used emotion and smart research to wipe out marketing waste and begin the climb back to happiness.
Whereas Market Intelligence is a well-known term, the expansion into Augmented Market Intelligence might need some explaining. The logic here is the fusion of it with Augmented Intelligence, a term coming from the Artificial Intelligence / Machine Learning framework. In that context, what is augmented is originally meant to be the human intelligence, via automated analytics that are able to learn from training data. In our discussion here the scope is actually bidirectional. Certainly we are talking about some of the means that can be used to enhance and make more scalable human analytics and judgement, but it can also be viewed as a way to improve the quality of Artificial Intelligence. So in this talk we will be talking about the synergies and interaction of both human and automated analytics in the specific domain of Market Intelligence.
Whereas Market Intelligence is a well-known term, the expansion into Augmented Market Intelligence might need some explaining. The logic here is the fusion of it with Augmented Intelligence, a term coming from the Artificial Intelligence / Machine Learning framework. In that context, what is augmented is originally meant to be the human intelligence, via automated analytics that are able to learn from training data. In our discussion here the scope is actually bidirectional. Certainly we are talking about some of the means that can be used to enhance and make more scalable human analytics and judgement, but it can also be viewed as a way to improve the quality of Artificial Intelligence. So in this talk we will be talking about the synergies and interaction of both human and automated analytics in the specific domain of Market Intelligence.
Insights and strategies for different channels and touch points are usually considered in isolation... But how do these different channels and touch points influence and convert an individual shopper in the same Path to Purchase?
This paper is a case study involving a client with a successfully performing brand of fabric conditioner who has acquired another brand in the Australian market. The business strategy was to relaunch both brands with revised fragrance ranges that clearly define the essence of each brand and thus differentiate the two. The brand, fragrance descriptor and fragrance evaluation results were integrated to produce the optimum and most brand suitable fragrance range for each brand of Fabric Conditioner. In addition, the overall reach (in terms of appeal) of candidate sets of fragrance descriptors both within each brand were determined.