WHY MARKETING ANALYTICS HASN’T LIVED UP TO ITS PROMISE
Carl F. Mela
A very important topic and really worth going to the article for greater insight
We see a paradox in two important analytics trends. The most recent results from The CMO Survey conducted by Duke University’s Fuqua School of Business and sponsored by Deloitte LLP and the American Marketing Association reports that the percentage of marketing budgets companies plan to allocate to analytics over the next three years will increase from 5.8% to 17.3%—a whopping 198% increase. These increases are expected despite the fact that top marketers report that the effect of analytics on company-wide performance remains modest, with an average performance score of 4.1 on a seven-point scale, where 1=not at all effective and 7=highly effective. More importantly, this performance impact has shown little increase over the last five years, when it was rated 3.8 on the same scale.
How can it be that firms have not seen any increase in how analytics contribute to company performance, but are nonetheless planning to increase spending so dramatically? Based on our work with member companies at the Marketing Science Institute, two competing forces explain this discrepancy—the data used in analytics and the analyst talent producing it. We discuss how each force has inhibited organizations from realizing the full potential of marketing analytics and offer specific prescriptions to better align analytics outcomes with increased spending.
The Data ChallengeData are becoming ubiquitous, so at first blush it would appear that analytics should be able to deliver on its promise of value creation. However, data grows on its own terms, and this growth is often driven by IT investments, rather than by coherent marketing goals. As a result, data libraries often look like the proverbial cluttered closet, where it is hard to separate the insights from the junk.
In most companies, data is not integrated. Data collected by different systems is disjointed, lacking variables to match the data, and using different coding schemes……..What’s more, most companies have huge amounts of data, making it hard to process in a timely manner. Merging data across a vast number of customers and interactions involves “translating” code, systems, and dictionaries. Once cohered, vast amounts of information can overwhelm processing power and algorithms. Many approaches exist to scale analytics, but collecting data that cannot be analyzed is inefficient.An irony of having too much data is that you often have too little information
The Data Analyst ChallengeThe CMO Survey also found that only 1.9% of marketing leaders reported that their companies have the right talent to leverage marketing analytics. Good data analysts, like good data, are hard to find. Sadly, the overall rating on a seven-point scale, where 1 is “does not have the right talent” and 7 is “has the right talent,” has not changed between the first time the question was asked in 2013 (Mean 3.4, SD =1.7) and 2017 (Mean 3.7, SD =1.7)…
……In light of the exponential growth in customer, competitor, and marketplace information, companies face an unprecedented opportunity to delight their customers by delivering the right products and services to the right people at the right time and the right format, location, devices, and channels. Realizing that potential, however, requires a proactive and strategic approach to marketing analytics. Companies need to invest in the right mix of data, systems, and people to realize these gains