Automated online design and analysis of marketing research activity and data

#This invention relates to a method, system and program product for dynamic online automation of the design of Marketing Research activity, its deployment and the analysis and reporting of the data gathered from it. Marketing research may include one or more research approaches, e.g., marketing experiments, surveys, interviews, focus group discussions and the like.

#Marketing research initiates from the problem that the merchant is trying to answer. The information required to address the problem is determined, the existing information and the available techniques are examined and the information gap is analyzed. Thereafter, a research approach is designed based on available data and analytical techniques to collect the missing information. The drawback is that this process is mostly manual and off-line in nature.

#In the brick-and-mortar world, customer opinions and actions cannot be compared, since only aggregate data is available. Customers, whose opinions are collected, may not be contacted later to check whether they acted on the opinions expressed or if they behaved according to their disclosed preferences, and if they did not, what were the reasons. To overcome this problem, marketers have created panels of households who are paid regular incentives to disclose their preferences and product purchase information. The high cost of maintaining such a panel, however, limits the size and the scope of such studies.

#The invention will now be described with reference to the accompanying drawings:

#FIG. 1 is a flowchart giving an overview of Dynamic Online Marketing Research

#FIG. 2 is a flowchart describing the operation of the Information Requirement Analysis Tool.

#FIG. 1 represents an overview of Dynamic Online Marketing Research. The merchant specifies one or more objectives to be achieved by the system, using a Merchant objective specification tool (1.1). The information requirement analysis tool (1.2) takes as input the merchant objective(s), data analysis tool repository (1.3) and available secondary data (1.4), and determines the missing (primary) data to be gathered (1.5). The next step is to determine and design the approach to gather the primary data (1.6). This tool takes as input the repository of research designs (1.7). The research approach design tool outputs a set of approaches with associated incentive, utility and gain values. Merchant may be allowed to choose from this, or the system automatically chooses the approach that maximizes the total gain. Some part of the selected approach may be executed by the system in an on-line manner and the rest may be done by the merchant through off-line mechanism (1.8). The data collected is analyzed (1.9) and the findings (1.10) are presented to the merchant.

#For the purpose of online marketing research, the merchant specifies a plurality of objectives to be achieved by the system, with the help of Merchant Objective Specification Tool (1.1). The objective could be sales forecast for a product, service or category of products, product preference tests, advertisement campaign effectiveness study, new product acceptance and potential, pricing studies, study of business trends in a particular market, desired feature enhancements to a product, market share analysis, studies of coupons, marketing campaign design, market structure study to spot new product opportunities, etc. The tool, as shown in FIG. 1, provides a graphical user interface to the merchant to specify the objective. The graphical user interface asks merchant to select one of the predefined objectives or a combination of these objectives with an interface to define interrelationships between each of the sub-objectives. For example, the objective of launching a new product can be broken down in sub-objectives of new product design, identification of the market segment, and finding the target customers for the new product.

#The secondary data (1.4), as shown in FIG. 1, is the set of existing information from data banks, government publications, periodicals and books, third-party information resources, prior research reports, past transaction data, etc. It may comprise on-line as well as off-line data, for example, the secondary data may include one or more of the following: