Nextatlas and Mondelez transformed foresight from best guess and periodic reports to real science accessible in real-time using Artificial Intelligence, Big Data from multiple social media sources, and precise algorithms.This helped Mondelez to make accurate predictions about future consumer behaviours and preferences.This session, tailored for heads of insights, strategists, heads of marketing and innovation, will unfold the journey that Nextatlas and Mondelez teams did to make an already successful and unique platform such as Nextatlas even more relevant and essential for its business clients.In the session you will be able to:Understand how can your business benefit from foresight as scienceWhat are the key metrics essential to make precise predictionsWhat makes Nextatlas technology unique and relevant for brandsHow Nextatlas data can be integrated into your digital infrastructure and accessible to your organisations.During the sessions, there will be plenty of time for questions and to see examples of how Nextatlas technology has been applied in different industries.
We are now less than 100 days before U.S. voters go to the polls to decide whether to stick with Donald Trump for four more years or make a change and elect Joe Biden. In this webinar, five North American pollsters will share their views on where the race stands, what seems to be the central issues, and how it's all likely to turn out.
Doctor When will see you now. The time traveler's guide to consumer insights: How to foretell your consumer's destiny accurately with big & small data.
Our journey to better understand the impact of advertising dollars on sales beyond the short run. Operating on a hunch, we ventured to harness the wealth of customer perception data and the best of existing statistical models at Microsoft to deliver measurement of advertising's long-term impact. The value this exercise would deliver to the business, however, was unprecedented.
Opinion polls and electoral polls were subject to intense scrutiny and criticism in the wake of the 2016 experience, followed by renewed confidence in the first months of 2017. Polling firms are facing up to the current challenges and reports of the death of quantitative electoral forecasts are "greatly exaggerated".
We set ourselves the challenge of forecasting the future for our insights engine, asking ourselves a series of questions about how we conceive insights across Unilever as a whole, how the field of insights is evolving, and about the needs and expectations of the new generation of insight experts who will power our engine in the next few years. Find out what we learnt.
We set ourselves the challenge of forecasting the future for our insights engine, asking ourselves a series of questions about how we conceive insights across Unilever as a whole, how the field of insights is evolving, and about the needs and expectations of the new generation of insight experts who will power our engine in the next few years. Find out what we learnt.
Projections about future developments, delivering expectations, indicating trends and making predictions, are activities that do attract attention. And of course, carefully formed opinions about what will happen in the future are indispensable to the planning process. But just how reliable are these forecasts? It seems that predicting the future has become a business in itself - with huge financial interests - in which mostly self-appointed gurus and trend watchers have developed a lucrative trade in prognoses and prophecies. Are they really any different from the seers and clairvoyants that through the ages provided decision makers with their visions? Not to forget the multitude of âvoodoo pollsâ, on-line political polls and analyses by the media that often go just skin deep. Predicting is fine - but ultimately it is not just about making predictions about the future. Timing is also crucial: to what particular point in time do the estimates relate and just how accurate are they? Best guesses might be welcome, but are not always sufficient. Much more preferable are systematic, independent and rigorous approaches on a continual basis - at least then the contribution of research can be more solid. Not that the aspiration is for research to bring universal happiness, but standards of professionalism should be respected. We have been looking ahead in Research World since the beginning of this year. In this issue we will explore the predictive quality of research from different angles. To avoid the myopia of the chronic emphasis on the short term, we will focus on long term developments and changes in areas that affect us all, such as the biomedical world and technology. We will focus on scenario planning and look at trends and hypes. We will try in particular to get a picture of the role of research. Can research help companies to pleasantly surprise consumers? Or make existing products obsolete, as people have said so insistently in the past? What can modern research do? Can it deliver photos, snapshots or reliable forecasts?
Customers are increasingly demanding, and successful companies need to design and introduce new ways to offer customer value. However, the process is not complete until they design control systems, provide a support decision tool able to identify and distinguish customer behaviour profiles according to their loyalty, and help marketers to readapt relationship marketing strategies in order to increase efficiency. LAMDA (Learning Algorithm Machine for Data Analysis), an artificial intelligence technique software tool enabling forecasting and identification of customer behaviour, is based on a self-learning classifying technique that relies on the generalizing power of Fuzzy Logic and the interpolation capability of logical hybrid connectives. This paper specifically examines the efficiency of the LAMDA classifier in identifying and distinguishing between the various degrees of customer loyalty. The study carried out in this project is based on data gathered from the customer loyalty cards of a Spanish grocer, Supermercats Pujol, S.A.
The paper discusses the application of sales prediction techniques to new product development in Latin America. It shows that in packaged goods product fields, both of the two mainstream methodologies, the Laboratory Test Market exemplified by SENSOR, and the concept/product test exemplified by MicroTest, deliver very similar consumer responses in the Latin American context as those found in other markets, notably Europe. This gives confidence in the validity of the consumer data. The problems lie more is obtaining accurate measures of market size, distribution and consumer purchasing due to the incomplete coverage of retail audit and consumer panel services. The extension of prediction techniques to durables and services, implications for the Latin America context, are also discussed.