Data, Methods, and Project Management Opportunities in Advanced Marketing Analytics
It is a good idea for organizations, academic institutes, and aspiring students to spot trends in analytics and predictive methods. This helps the analytics market place achieve efficiency in designing the right training, instituting the right hiring process and benefiting by the analysts skills.
The trends in data collection, availability of data, methods, and tools are heavily influenced by the fast changing market response to the life-style dynamics of consumers. To quote an extreme example of challenge for companies, companies find it hard to adjust quickly to the multitude of channels of communication and real time engagement demands of consumers that are complicated by pervasiveness of the tablets and smart phones. These are changing the dynamics of data elements, data collection, privacy, methods of data analysis, and usability of analytics. The clients/companies are clamoring for consumer intelligence at their finger tips.
In this note, barring the detailed discussion on the above extreme example for now, I bring together some of the more immediately addressable opportunities for companies in acquiring data resources, and applying methods to derive powerful data intelligence for not only defending the company in the fierce competition but also thriving by being able to compete analytically.
These are common demands in advanced predictive modeling methods, specifically in marketing, but the availability of data are not wide spread, methods are not well understood or standardized, project management requirements can be challenging because the talents are hard to come by, and academic circles are not well equipped with tools and also because of shortage of highly experienced faculties.
Because of the combinations of above factors, these analytical solutions require longer term commitment and more financial investments from companies/clients to get the best from these types of projects.
Availability of data is considered high, when the data are already harmonized, qualified with data quality levels, and immediately available for usage. These data assets are available either internally or sourced from third party.
The availability of methods are high when it is comparable to standard statistical, econometric, and computational methods with standard software such as SAS, R, and SPSS and academic training is widely available and solutions are common.
Time management is considered to be of ‘Low’, when the data management, analytical processes, and client communications are not well standardized requiring higher order analytical talents. So you can see why attribution modeling is ‘Low’ while Brand preference models are Medium and standard predictive models are ‘High’.
The resources are considered ‘Low’ when it is not easy to spot, hire, and train for high performance of the analysts to field a winning analytics team. I have also provided ‘Standard data and Methods’ for comparison purposes.