Measurement of direct response advertising in the financial services industry : a new metrics model

Abstract

Direct response advertising in the financial services industry in South Africa has become one of the most important tactics companies utilise to build and maintain market share. Ensuring that these advertising campaigns yield optimal return on investment numbers is the responsibility of marketing departments and their partners in the marketing and sales processes, such as the creative and media agencies, the distribution force, as well as the client service area that supports the client value proposition. The marketing executive therefore is accountable for the planning, budgeting and execution of direct response campaigns, which need to deliver sufficient results to support the company’s overall business objectives. The challenge all marketers face is the lack of a proven structured and scientific methodology to facilitate this planning, budgeting and execution process. It has always been a general view in the marketing fraternity that it is extremely difficult if not impossible to combine creative output measures, which are subjective in nature, with cost, sales and profit measures, which are objective in nature. This study aims to create a structured approach to marketing strategising and planning, by creating a marketing metrics model that enables the marketing practitioner to budget according to output needed to achieve the overarching business objectives of sales, cost management and profit. This marketing metrics model therefore unpacks the business drivers in detail, but through a marketing effort lense, to link the various factors underlying successful marketing output, to the bigger business objectives. This is done by incorporating both objective (verifiable data, such as cost per sale) and subjective variables (qualitative factors, such as creative quality) into a single model, which enables the marketing practitioner to identify areas of underperformance, which can then be managed, tweaked or discontinued in order to optimise marketing return on investment. Although many marketing metrics models and variables exist, there is a gap in the combination of objective and subjective factors in a single model, such as the proposed model, which will give the marketer a single tool to plan, analyse and manage the output in relation to pre-determined performance benchmarks.