Predictive analytics: What are the challenges and opportunities? | 7wData

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In August 2016, Econsultancy published a report in association with IBM called The Secrets of Elite Analytics Practices.

Part of this wide ranging report seeks to discover just how Automation and AI have changed analytics in marketing.

Let's look at some of the talking points...

Time was identified as a business's most precious resource. Being able to streamline the marketing function through Automation and, in particular, the analytics portion, was something executives deemed hugely valuable.

But is automation driving out innovation and originality? With so much potentially determined by machines and algorithms, do brands risk losing the essence that made them unique and the innovation that could keep them alive?

Nearly 60% of respondents stated that their analytics solutions produced data-based insights without analyst involvement.

A further 80% of those stated it saved them significant time as a result. Either the analysts themselves could be redeployed to focus on trickier tasks or the insights generated pointed to opportunities elsewhere.

Hotel group IHG's head of CRM, Jim Sprigg, explains his position on automation thusly: "Automation and machine learning will be critical for the sort of thinking that requires many calculations done in a somewhat predictable way."

"It is definitely in our roadmap for broad use in predictive modeling which can drive, say, the assignment of offers and content in digital media based on individual customers' attributes, behaviors and transaction histories."

Dealing with the routine but complex

The idea of automation means different things to different people. For some organizations, particularly those that operate well on defined processes and rules-driven decision making, automation saves a great deal of time.

This is either because it can create a trickle down effect of automation allowing other systems to take appropriate action without human intervention, or alert business users when intervention is needed.

In complex, real time environments such as programmatic advertising, the automated processing of information into insights, and insights into action is viewed as essential to realizing opportunities before they pass brands by.

Danish AI-based media buying agency, Blackwood Seven, is expanding across Europe based on the success of its model that claims clients get a 25-50% improvement in the effect of their media (according to Campaign magazine) through using the company's AI technology.

The software analyzes 82 different data inputs (such as sales, YouGov data and weather info) to determine a media plan's likely outcome and optimizes in real time accordingly.

The advertising community is already looking at the question of whether or not automation and machine learning can actually create ad executions, not just supply humans with the insight with which to build their own creations.

However, the idea that AI would be integral to developing creative is still a pipedream. This begs the question, beyond a degree of grunt work or speedy number crunching to get the the right ads to the right audiences in real time, does automation have anything to contribute to the creative, innovative side of marketing.

In a discipline that has always been described as the marriage of art and science, can science begin to replicate (and replace) art?

There is a sense, however, that analytics will never fully be automated. The feeling persists that strong marketing is an intelligent marriage of art and science, even in today's data obsessed environment.

"Humans still have an advantage over computers," Sprigg insists. "We used to call these the big 'ah-ha' insights. The sort that come from intuition and highly synthesized recognition."

Sprigg gives the example of a time he showed the output from an automated learning process that suggested some offers landed differently with customers who came to the company via customer service than for those who used the web.