Measuring Marketing ROI with Big Data

Cameron Turner Cameron Turner
October 26, 2016 AI & Machine Learning

The main objective of marketing analytics is to measure the effectiveness, or the ROI, of various marketing channels used to position a product or service. Given the increasing variety and complexity of marketing channels—reaching this objective is a serious challenge. A recent research from Crain’s BtoB Magazine casts serious doubts on the impact of digital marketing mix and demands a systematic investigation of its measurable worth!

The history

During the Crain’s BtoB Magazine’s poll in 2012, while 60 percent or more of the respondents expressed that their biggest challenge was generating sufficient leads, a solid 63 percent confessed that their marketing mix was either inadequate in terms of sales goals, or did not assure effective results. Interestingly enough, almost 40 percent of the respondents felt that the accurate measurement and attribution of online conversions was still missing from their digital marketing model. At least two major polls conducted in 2012 suggested  that a mere 11-19 percent of the respondents were using big data to measure or optimize their digital marketing strategies. The marketers’ world has made great strides since then; and they have moved towards a more integrated digital marketing strategy to drive a creative reinvention of digital marketing plan. Here are some sample findings reported in Era of Big Data: The 2012 BRITE/NYAMA Marketing in Transition Study by David Rogers and Don Sexton, in which 253 corporate marketing decision makers (director-level and above), were surveyed online between January 27 and February 8, 2012.

  1. 91% of senior corporate marketers reported that they relied on customer data to drive marketing decisions.
  2. But, among those 91%, 39% reported that their own company’s data was either infrequent or dead data.
  3. 51% of the respondents reported that a lack of sharing of customer data within their own organization was a serious roadblock in measuring their marketing ROI
  4. Among the large firms, only 19% are collecting new forms of digital data like mobile data; while 74% are collecting traditional customer survey data such as demographics, and 54% are collecting attitude.
  5. 85% of the respondents reported that large corporations use social media such as  Facebook, Twitter, or Google+ as their marketing channels.
  6. 65% of the respondents confessed that comparing the effectiveness of marketing mix is a major challenge for their business
  7. 37% of the respondents did not correlate marketing ROI to any kind of desired financial outcome.
  8. 57% of the respondents admitted that marketing budgets were not based on any ROI analysis
  9. 22% of the respondents reported that brand awareness was the sole measure for evaluating the existing marketing spends.

If you are curious to know more about this survey, you can access the downloadable copy of the full research report.

Don Sexton on Marketing ROI in the Era of Big Data 

This same study contains the two following tables that may be helpful.  The first Table shows the use of traditional vs. digital metrics in measuring the overall effectiveness of marketing channels in 2012: TABLE-4

The second Table shows the key drivers and barriers to effective measurement of marketing ROI: TABLE-6

The transition

In 2013, the emergence of Marketing Mix Modeling (MMM) provided a blueprint for developing analytics-guided marketing strategy. In an era where TV, print, or online marketing channels are  no longer stand-alone platforms but rather a well-integrated digital entity enabling consumers to quickly hop from one channel to another, marketing analytics played a significant role. During this period, it was noted that businesses that embraced big data analytics showed 15-20 percent higher results than those who did not. Traditional MMM data got frequently reinforced with advanced customer-behavior forecasting techniques. Sophisticated tools such as Regression analysis based on detailed customer surveys, or brand tracker surveys, or focus groups revealed consumer sentiments at different points in their decision journey across multiple channels.  This era also signaled that marketers and CMOs need to be involved in the analysis of customer data and insights to realize the full benefits of marketing analytics. You can view the full McKinsey report.

The current trends

More organizations today realize the importance of measuring marketing ROI for getting the full benefits of the marketing spend. They also realize that for an accurate measurement of marketing ROI, they need to utilize available big-data enabled analytics. As newer and more challenging digital marketing channels surface, organizations will have to execute the best practices defined here to be able to measure and optimize their marketing mix:

  1. Marketing data must be shared across departments and divisions within an organization.
  2. The marketing metrics must be aligned with finance goals
  3. The measurable data must be timely and actionable, and linked at the customer level.
  4. IT infrastructure like Hadoop and MapR should be integrated in the overall data marketing data centers
  5. Advanced analytics technologies like big data and predictive modeling must become commonplace in marketing data analysis.
  6. Visualization tools must be used to understand the complex inter-relationships between marketing metrics across channels
  7. Social feeds can be used to get real-time customer engagement data.

To learn more about the current marketing analytics trends and patterns, see Analytics Trends 2014, which was published by the trend-watching team at Deloitte.      

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