This paper shares the experience of a pilot set up by Intel and Ipsos to build an ongoing framework for instant insights that can aid different stakeholders to explore rapid activation with micro-targets, sitting within the company ecosystemâ and not as an external truth. This paper shares the journey of how we got there.
This paper shares the experience of a pilot set up by Intel and Ipsos to build an ongoing framework for instant insights that can aid different stakeholders to explore rapid activation with micro-targets, sitting within the company ecosystem and not as an external truth. This paper shares the journey of how we got there.
This paper discusses a large research project conducted to investigate factors impacting on the relationship between banks and their business clients in Australia. A survey was conducted during February - March 1999 with 276 executives and financial managers on their firms relationship with banks. Factor and regression analyses were used to identify the underlying factors of close and long-lasting relationships between banks and their business customers. The insight gained through the data analysis guided the process of model building using a structural equation modelling techniques. The model shows that the measure of trust is crucial to understanding bank-business customer relationship.
The first part of this paper deals with the complexities associated with definition of FMCG (Fast Moving Consumer Good) retail outlets and their classification in India. It outlines the changes in outlet type and stocking patterns over time and elaborates on the methodology used for efficient stratification. The results are based on retail census studies conducted periodically by Operations Research Group, the latest being, CORE 95 (Census On Retail Environment 95). In the second part of this paper the authors suggest a model building exercise to capture the dynamics in the retailing universe. The proposed model will help to predict the rate of growth of retail outlets, for various outlet types and turnover categories. The model facilitates the updating of the universe even at the monthly level. This in turn would mean more accurate and meaningful off take estimates.
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.
I have been asked to sum up the learnings of this session and to provide some feedback to the presenting institutes on the future perspectives of the various instruments designed for testing marketing alternatives.
The purpose of this paper is to critically examine the above four distinct attributes of marketing models from the perspective of model building activities in social sciences, and to examine what contributions the consumer theory has made in building better marketing models. In the process, we will examine the crucial question as to whether consumer theory is sufficiently developed to be modelable and useful to marketing management.
The result of this examination of the formation of range and assortment policies is to emphasise the variety of the factors that may be involved. There is a danger of advancing too fast to the stage of model-building. Where the problem is not a matter of routine, these factors should be surveyed fairly systematically, and where it is a matter of routine, the existence of a complicated background should at least be kept in mind.
In this paper we examine a number of issues concerning the validation of two types of macro models: Aggregate response models, and aggregate flow models. The discussion is preceded by some remarks about model construction. The validation process is considered to consist of two steps: model fit and model prediction. Model fit will mostly involve econometric techniques as far as aggregate response models are concerned, tracking or trial-and-error-estimation for aggregate flow models. We will emphasise the need for good data and will argue for increasing the frequency of observations. The second step, model prediction, is in many cases not carried out by lack of data. A brief discussion is given of an empirical study about the relationship between market share and outlet share for the gasoline market in a European country.
In this paper, then, we deal not only with belief importance but with wider aspects of consumer modelling. Firstly, for completeness, we briefly outline the major belief models discussed in the literature; secondly, we describe the threshold model in greater detail; thirdly we discuss how threshold and other models may be used by consumers in a combined and sequential manner; finally we outline case histories which shift the emphasis to a more operational and practical level, and which indicate the major role we currently see for threshold.