This project is a first step to driving predictive diagnostics to enhance some elements of brand health tracking. We created a 360° view of brand health by looking at customer and non-customerâs relationships with telecom brands through social media conversation. Key pain points were diagnosed and opportunities for action highlighted. The model and underlying data can now be accessed through an interactive dashboard enabling rapid visual analysis.
This project is a first step to driving predictive diagnostics to enhance some elements of brand health tracking. We created a 360° view of brand health by looking at customer and non-customerâs relationships with telecom brands through social media conversation. Key pain points were diagnosed and opportunities for action highlighted. The model and underlying data can now be accessed through an interactive dashboard enabling rapid visual analysis.
How healthy is your survey? Are all the questions in your survey working efficiently? Is your survey performing above or below benchmark standards? In this session Steve Wigmore and Alex Wheatley will discuss 10 diagnostic techniques which everybody in research can undertake to check the health of their surveys and give some tips on better ways to ask questions, resolve common data problems and improve the performance of their surveys.
The temporality of sensations has been acknowledged in the food industry and for a long time as a potential key driver of liking. However, no practical method was available until now for tracking down such a temporal sensory signal simultaneously on a number of attributes. TDS fills this gap. We illustrate our methodology by a study on fragrances produced by Body Washes. We were interested in knowing which concrete stimuli emanating from the product's features are perceived as dominant and when.
This paper addresses the need for an in-depth understanding of medical practitioners and the different profiles that can be detected among them. We will also see how we can get in touch with the deeper motivations that are the real drives behind behavior. The benefits this approach offers in developing a marketing strategy that deals with the complexity of pharmaceutical marketing are reviewed. In conclusion, a case of doctors treating sleeping disorders is provided. It will show that the personal sleeping experience of the doctor profoundly influences the way in which he deals with his patients' insomnia.
Implicit Theory principally addresses the marketerâs need for diagnostic problem-solving. It explains why people behave as they do, at different times in different situations on different occasions, in order to satisfy different need states. Also, in the hands of a creative researcher, implicit theory provides some guidance in anticipating needs that consumers might not know they have. The start-out position is the belief that consumer behaviour is not random (not even impulse buying). Rather, it is driven by systematic, dynamic forces within the consumer, that are embodied in human behaviour and human society. There are implicit reasons that drive consumer behaviour. Consumers may not be consciously aware of them. These reasons may not be and, often are not rational. Or, indeed, they may be a mixture of the rational and the irrational or emotional. They result from an internal, dynamic energy that is implicit. In other words, it is inherent and continuously present in human behaviour and in consumer behaviour.
This paper serves as an introduction to the use of a comprehensive model for managers engaged with direct marketing and the use of market systems in B-t-B marketing. The DialogueWheel was first presented to six Scandinavian companies and has been tested in two Scandinavian companies. The results of the research show that the model is working as assumed, both as a diagnostic tool and as a strategic guideline for further development. First of ail, the model - or the concept - provides guidelines for what the marketing manager should consider as necessary functions in order to gain the customers confidence. Secondly, the "DialogiieWheef' is a guidance for the user as to which functions to keep in-house and which to source out. The four dimensional model consists of 108 decision cells from which the marketing managers make analysis, describe their present position and forecast their strategic possibilities. The initial step is to read this article and have a clockwise "tour" of the model. Get acquainted with the terminology and mark of those areas of the model in which you are active. Understand the rings, and position yourself according to what you do in-house and which parts of the direct marketing work is processed outside your company. Try to fathom your company's position in the three-step planning process within each cell, and you are starting to realize where your company is positioned in direct marketing, and which options you have to consider for future development.
This manuscript discusses the development of the Canadian Media Directors Council (CMDC) Television Commercial Awareness Model. The CMDC model allows advertisers to estimate the awareness levels that are generated from television advertising media schedules. Software has been created that will allow the user to generate "what- if" scenarios to determine which media schedule generates the highest levels of awareness. The CMDC model represents a significant advancement in advertising media planning. The model provides greater predictive accuracy and diagnostic ability than available models by incorporating more influential variables and focusing on individual product categories. Specifically, the model uses GRP levels, the impact of daypart distribution, media schedule, commercial length and quality of the creative execution as input variables. The model can be used with mature brands because it examines recall of specific television commercials/campaigns instead of brand awareness. The model that was developed was based on a modification of Broadbent's ADSTOCK model. This is a distributed lag approach which assumes that advertising in past periods continues to have an effect, but at a diminishing rate. The model that was developed produced error rates from 2.4% - 5.3%. Analysis of the data raised questions regarding one of the most prominent debates in the academic literature: the shape of the advertising response curve. While the literature suggests S-shaped and concave downward response curves, these shapes failed to appear in the CMDC database.