Analytics

Monday, 22 October 2012

Agent-Based Modeling | Marketing Mix Optimization Whitepaper

Fundamental shifts in the consumer marketing landscape have created a demand for better ways to understand both consumers and the marketing used to influence them. Historically, firms have used a variety of statistical techniques to build mathematical representations of the relationship between marketing spend and the resulting outcomes, typically some measure of sales. And in the past when there were fewer options on how to spend marketing dollars, these techniques fit the requirement well. Today, the number of options available to connect with consumers has exploded – each with unique measurements, resulting in a general lack of confidence in the effectiveness of traditional statistical modeling tools.

Tuesday, 4 September 2012

Data-Driven Marketing: How to Integrate Analytics & Technology

Free AMA Webcast

With the increased pace of change in technology and regulations coupled with demographic shifts and evolving digital lifestyles, the marketplace facing the financial services industry has become much more complex. In the past year alone, more than 10 million new users accessed financial services from mobile devices.

Thursday, 26 July 2012

ThinkVines Article on Fobes: Big Data? Try Smart Data

The recent article in Forbes by Kimberly Whitler entitled The CEO/CMO Dilemma: So Much Data, So Little Impact is right on target. The Sloan paper it mentions goes on to say, “Organizations traditionally are tempted to start by gathering all available data before beginning their analysis. 

Wednesday, 11 April 2012

Shift from Data-Intensive Planning to Smarter Marketing

As the author pointed out in the article If User-Level Data is Too Costly, Look into Alternatives, we live in a highly connected world where real-time access to news, data, and information has transformed the way both people and businesses make decisions. 

Thursday, 23 February 2012

Current State of Marketing Mix Modeling

Please note: this blog post is the first in a series of posts on the current state of marketing mix modeling.

The current tools for marketing mix models include a range of time series, traditional regression, and specialized regression models that attempt to explain the impact of the marketing mix on sales performance. They vary in breadth and granularity, but all of these models have one important flaw – they ignore the most important “P” in marketing: People.