Big Data, Social Listening and AI firms pop up every day. Whilst they are strong in aggregating large volumes of data, why is it that organisations can struggle to derive commercial implications and turn this data into impact? What's often missing is the cultural insight that makes human sense out of the numbers. Quilt.AI leaves the tech jargon at the door to help teams really get to the truth when it comes to how people think and behave. In this session, we'll bring our blend of data and insight to the topic of Sustainability. We already know Sustainability is high on everyone's agenda, for good reason, but we also know that what people say and what people do in this arena can be very different.Our mission is to bridge this gap by combining all the data sources you need, both at a public (e.g. Instagram) and private (e.g. Google) level with smart, industry/expert thinking, and to help organisations engage with consumers to really drive the Sustainability agenda at the corporate and brand level. Key takeaways:- Understand the gap between stated/claimed and real human behaviour in elements such as purchase decision making- Understand the impact of COVID on the perceived importance of Sustainability- Meet your potential consumer segments and learn how to size them- Uncover the key cultural codes/ criteria of Sustainability, and how they can be tracked over time.
With 2021 around the corner, the new realities of remote testing are here to stay. Everything seems to be changing, so we need a fresh perspective and new ways to cope- and this extends to market research. Contextual virtual shopping provides a unique potential for optimizing all touchpoints in the path to purchase- be they online or offline. This holds especially true for companies who until now relied on in-person research. How do you adjust your omnichannel strategy to plan for the unexpected but not back down on the quality of insights? Join Jonathan Asher and young research experts from EyeSee in discussing cutting-edge online research environments- and how to use them for making consumer-centric decisions:-How we help clients who are unsure about taking a leap with a new behavioral methodology that will add value to their research toolkit;-Why the new generation of rookie researchers might have an unexpected edge over experts in solving research problems, and how to nurture innovation in-house;-Why social media best practice studies and e-commerce researches are the bread and butter of 2021;-How new shopper touchpoints, such as click & collect or curbside pickups, can be recreated in virtual contexts.
Internet/Digital is no longer a question; it's a fact: Mobile and social aren't emerging, but merging through consumers who have become part-time marketers, who understand and expect brands to be honest and fast. For shopsumers speed, knowledge personalization and co-creation are basic and they expect brands to react to them within the hour, and not with any answer, but one that's personal and offers a solution. The shopsumers don't want to repeat themselves, they want companies and brands to know them and provide them with clear and sophisticated reasons to go from undecided to decided in brief: to shop!
Beauty marketers today are seeking information on how beauty is being discovered and purchased in LATAM- on who buys what products and on which platforms. With this study we aim to help marketers understand how best to reach the modern beauty buyer. We look at modern beauty buyer's priorities and their relationship with beauty. We also study how social media channels- specifically Facebook and Instagram- are playing a distinct role in purchase cycle.
The paper describes an in-depth segmentation analysis of online and offline shopper activity and explores the demographic and cybergraphic similarities and differences among the various segments. In addition, key driver analysis provided us with a deeper understanding of what drives consumers to spend and make purchases online. This type of research will be of use to retailers both online and traditional to improve their marketing and retailing strategies by gaining a better understanding of their customers' online and offline behavior.
In France, over the last five years, consumer purchasing trends have undergone immense changes and have therefore been thrown back into question. With regard to marketing practices, this has led to increased difficulty in understanding the consumers purchasing decision process. There also have been far reaching changes in the supply of consumer goods. Manufacturers are carrying out structural and organisational modifications in order to adapt their brand management to these challenges, but they will also need to set up information systems to evaluate the new operations. The authors present a new information system for brand management called Prometheus.
The current paper describes the development of purchasing and income panel survey from a basic households economic information source to a complex, model-based test panel. Great importance has been attached to the advantages of a households panel survey in the stage of the societys rapid development and the situation where the system of registers as a source of information has not fully formed yet. The second part of the paper presents examples of how the data from the panel survey can be used.
As the specialist practitioners of market modelling worldwide, NOVACTION's learning curve extends over fifteen years. Today, our history of marketing experimentation on test product mixes and consumer response benchmarks is computerised in a global databank. This paper discusses how DESIGNOR SYSTEM - its models and its databank - can support the marketing mission to develop profitable new brands through systematic understanding of consumer values.
This paper shows how RBL responded to marketing managements' changed needs by adapting mini-testing methodology to reduce the time necessary for testing in a way which preserved the extended observation of the repeat buying behaviour of panellists as the basis for forecasting stable repeat purchasing rates. The standard set for the new methodology in terms of its success was the ability to provide predictions comparable with standard 20-24 week Mini-Test Market estimates of volume potential. This paper describes how the examination of Mini-Test Market data was used to build a model using the negative exponential, and how this model was shown to be capable of predicting the long term repeat purchase rate of FMCG products on the basis of 12 elapsed weeks observation of repeat purchasing data comparable with estimates achieved in the standard 20-24 week Mini-Test.
A micro-behavioral marketing model provides the conceptual framework to explain free choice decision making among consumers who purchase our products or services. Since it is a micro model, it portrays the decision making of each individual respondent, one at a time. The underlying structure of the model is a highly simplified representation of the extremely complicated cognitive processes which actually take place when a consumer decides to choose or not choose a particular product or service. The simplifying assumption is that we are "creatures of satisfaction." We tend to make decisions, within acceptable economic and social constraints, which favour the things we like the most and derive the most satisfaction from possessing.