|
Optimal use of data, related indicators and tools for the implementation of marketing campaigns |
|||||
The value of Optimisation approaches Since the Nineties, European banks have focussed more on their retail market clients to better understand their financial needs and to recognise the clients which offer the most potential in terms of profitability. This resulted in the need to collect and analyse with a variety of methods a large amount of client data and information. On one side, there has been a widespread use of market research techniques aiming to assess customer satisfaction and customer retention. On the other side, there has been a more IT oriented approach based on the development of data warehouses that have been the cornerstone for complex and expensive CRM (Customer Relationship Management) projects. A third approach has been to analyse the huge amount of data available through data mining techniques that classify clients on the basis of their behaviour and characteristics, resulting in more targeted marketing campaigns. This is the area where the most statistically biased customer profiling models have been developed. Currently, the most widespread approach is to plan according to products and offerings. For each product clients to be targeted (prospects) are selected on the basis of their estimated probability in replying to an offer. This allows marketing campaigns to be planned on the basis of estimated costs, sales targets, returns and delivery channels characteristics. However, this often results in a loss of client focus, with prospects being targeted many times in a short period of time for different marketing campaigns. It is also difficult to assess the overall returns of the different marketing campaigns that are independent from each other. This often leads to poor use of marketing resources. Optimisation techniques allow companies to tackle more easily the complexity of marketing decisions with the more effective use of available data, related indicators and available delivery channels. This approach is particularly useful to identify the best “mix of actions” that result in the overall optimisation of a set of marketing campaigns, taking into consideration individual client characteristics and economic returns while satisfying constraints posed by targets, volumes that can be handled by each delivery channel and available budgets. An example objective of an optimisation analysis for marketing purposes would be to maximise the following function:Marketing action returns = (Average product profitability * Purchasing propensity) – Offer Cost The main benefit of using constrained optimisation techniques is the possibility to evaluate, before their actual implementation, the effects of alternative courses of action resulting in the choice of the most suitable one in terms of the desired objectives. This approach has been chosen by many leading financial institutions such as Alliance & Leicester and Barclays. Luciano Bruccola & Jeremy Williams - Experian Decision Analytics Contact us for further discussions about this article
This article originally featured in MK Magazine, May 2007 |
|||||
|
Top |
|||||
 |
|||||
|
|
Read more about Marketing Optimization