Home > Uncategorized > What Does AI Have to Do with Marketing?

What Does AI Have to Do with Marketing?

by Reggie Bradford, Oracle

Forbes (May 10 2016)

As a young brand manager at Miller Brewing Company in 1995, I crunched data using Excel spreadsheets, a process not so far away from what’s going on at a lot of companies today, I’d wager. But the tools that marketing teams use are about to get a lot more sophisticated with advances in a technology poised to reshape a variety of business areas: artificial intelligence (“AI”).

What does AI have to do with marketing – a human-to-human endeavor if there ever was one? Plenty.

Consider this noteworthy bullet point in Gartner’s “Top Predictions for IT Organizations and Users for 2016 and Beyond”.

 

By 2018, twenty percent of business content will be authored by machines.

 

When most people envision AI, they think of game show-playing computers, self-driving cars, or robot armies. Robotics is at one end of the AI spectrum; at the other is what’s referred to as “machine learning”, the ability to program a computer to recognize patterns and build models that let it make decisions or generate predictions.

Marketers are only just now starting to figure out where machine learning fits into their profession. The cutting edge is called “cognitive marketing” – research firm IDC expects that half of all companies will use this emerging generation of computer intelligence for their marketing and sales efforts by 2020.

Consider marketing’s call to action: right message, right place, right time. In the past that would have meant relying on the whims of an agency copywriter who’s trying to decide the best message that will resonate with thousands, or hundreds of thousands, of customers. Or, instead of a copywriter, a focus group or a panel of customers that is treated as indicative of all customers everywhere when they render their positives and negatives about a particular product or service.

The advantage of looking at consumer trends based on cultural, geographical, and historical data, as opposed to educated guesswork or extrapolation, is obvious. Today’s marketing environment calls for content that is personalized, delivered globally, across multiple channels – anywhere the consumer might connect with the brand. Machine-learning systems that correlate tens of thousands of data points are a great way to augment (not replace) creative marketing strategies.

Cognitive Content

For example, I’m on the board of a company called Persado, which describes its content-generating platform as “combining machine-learning algorithms with natural language processing to generate the precise combination of words, phrases, and images capable of motivating audiences at scale, and in real time”. The Persado platform can spin out its action-inspiring “cognitive content” for a variety of marketing channels, including display ads, email, Facebook, SMS, and websites.

By the way, Persado recently received $30 million in funding and counts among its customers American Express, Caesars Entertainment, Microsoft, and Verizon Wireless.

The marketing opportunities presented by machine learning are both wide and deep. Increasingly, Chief Marketing Officers (“CMOs”) are being called on to oversee “customer experience”, the totality of a customer’s interactions with a brand or organization. That oversight involves processing data, lots of it – and large amounts of data are what machine-learning algorithms use to spot patterns and make predictions.

Automated Marketing

One startup touts the ability of its automated customer relationship management system “to create a perfect customer record” and then apply its machine-learning system – incorporating third-party data – to ascertain how best to approach a customer. An even more ambitious machine-learning-based “automated marketing” system promises “true one-to-one personalization at scale”, according to a company vice president, which can result in three to five percent “incremental growth in customer revenue”.

What does my company, Oracle, have to do with this? First, Oracle incorporates machine-learning algorithms into many of its applications and systems, helping boost their effectiveness. For example, Oracle HCM Cloud employs such algorithms to help parse resumes, among other functions. And Oracle just announced that it’s acquiring a company to inject machine-learning capabilities into its data-as-a-service offerings.

At the same time, Oracle is the database company: We provide the technology to store and retrieve data in every form, including unstructured “big data”, easily and effectively. Our cloud services make our database technology accessible and cost-effective, and our platform-as-a-service tools can serve as building blocks for, or a means of enhancing, machine-learning systems.

The data channels marketing has available are only increasing. The ability to tap data streams in social media is expanding, and the Internet of Things promises whole new avenues of device-driven feedback.

To help leverage these myriad sources of consumer data, and target customers at the personal level they prefer, savvy CMOs should start building machine-learning-based “cognitive marketing” strategies right now.

_____

 

I’m Reggie Bradford, and I certify that this column was not written by a machine.

http://www.forbes.com/sites/oracle/2016/05/10/what-does-ai-have-to-do-with-marketing/

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