What is marketing analytics?
While analytics has been incorporated in different organisations, from technical fields such as software mining to more business-oriented ones such as product mix optimisation, analytics has actually been adopted since its early primitive form in the marketing field. The term marketing analytics could be dated back to the first day of the Digital Age when the advance of Web 2.0 sites created completely new media for marketers to reach out to potential customers. Until then, marketing was typically considered an art more than a science by incumbents whereby marketing decisions were less data-driven but more intuition-based. Since the invention of Internet, user-generated contents have provided the tools and facilities to marketers and other stakeholders to make marketing more efficient and effective, targeted to the right customers for the right products in a time- and cost-sensitive manner. On the other hands, instant connection to the world bring about a new generation of highly informed customers who receive information from a wide variety of channels, from subscribing emails to social media posts. It is hence empirical for incumbents to undertake a data-driven approach to understand customer behaviour and allocate marketing resources to achieve optimal product mix and brand identity. In this context, marketing analytics is more than just compiling customer data and reporting product margins but has advanced into scientific use of marketing-related econometrics to derive marketing strategies.
The below displays the evolution of marketing analytics which can be dated back to the first online ad in October 1994 by AT&T.
The Resource Allocation Framework
The ultimate purpose of marketing analytics is to achieve better use of business resources to achieve higher growth through effective marketing campaigns. This process has to be carefully scrutinised and cultivated by inter-department personnel, from the C-suite management to Finance, Engineering, and Product teams. In Cutting-edge Marketing Analytics, Venkatesan, Farris, and Wilcox derived the Resource Allocation Framework as a general guide for incumbents to refer to during this process. The framework consists of 4 key steps:
- Determine the objective function:
- What is the performance metric the company wants to set as its marketing goal? It can be market share, profit margin, customer lifetime value, etc.
- Connect the marketing inputs to the objective resource allocation
- What are the attributes of the business that contribute to the objective function? Are the relationship between the various attributes empirical (best guess or prediction) or computational (direct and certain)?
- Estimate the best weights for the empirical relationships identified in the second step
- What is the econometric or regression model of the empirical relationship? For example, the regression model could be a function of price, ads rate, sales calls, etc.
- Identify the optimal value of the marketing inputs to maximise the objective function
- Resource Allocation is an iterative and continuous improvement process in which organisations constantly look at the current internal and external markets and customise the marketing strategy to induce new business growth
Categories of Marketing Analytics
Marketing analytics entail different areas in which marketers can make use of corresponding third-party tools to focus on:
- Clickstream analysis: analysis of user clicks activities while browsing on webs or other online platforms
- Tools: Yahoo! Web Analytics, Google Analytics, Bing Webmaster Tools
- Outcome analysis: analysis of factors and experiences associated with some predefined outcome
- Mongoose Metrics, LivePerson
- Voice of customer: market research on consumer profiles and needs
- Bounce, Google Consumer Survey
- Competitive intelligence: analysis data about products, customers, competitors, and any related factors needed to support management making strategic decisions for an organisation
- Adwords Keyword Tool
- Google Trends
- Google Correlate