AI, Brand Strategy And Digital Marketing

From cars to healthcare, social media to finance, artificial intelligence (AI) is changing how business is done. Marketing is at the forefront of these sweeping changes -- Gartner predicts that 85 percent of customer interactions with companies in the US will be handled by machines by 2020. Other countries such as the U.K., Germany and Japan have similar estimates.

Machine Learning

How does AI handle the overwhelming data inputs available today? Machine learning is the answer -- granting computers access to data so they can teach themselves how to handle a task. The more data available for the computer to learn from, the more quickly and accurately it can complete a job or project. Deep learning, machine learning on huge datasets, facilitates automated identification of at risk customers, crafting of personal email messages and audience narrowing for custom campaigns. It also yields improved results with each iteration of a promotion, offer or campaign.

Engagement

At NVIDIA, a computer graphics processing unit (GPU) manufacturer, users generate large volumes of visual content (like video game screenshots) that are shared among the community and across social media. Detecting, classifying and managing this mountain of millions of images would be next to impossible for humans. The company uses machine learning to tag and store them to improve user engagement and interaction.

Personalization

We are moving from a world where brands broadcast a single message to millions of people to one where millions of individualized messages are delivered to specific customers at the same time. Further, while it's valuable to interact with thousands of users at the same time instantly, it is just as important that customers feel the interaction is authentic and personalized.

Awkward attempts at personalization are off-putting and create distance between users and brands. Taking the time to get personalization right is worth the effort, however. Harvard Business Review reports that proper personalization can create five to eight times return on marketing outlay, and build sales by more than 10 percent. The key is to constantly test innovative ideas with real clients and then quickly expanding successful efforts.

Rapid Testing & Iteration

Haven't marketers always tested new products, copy, and promotions before expanding to larger markets or national coverage? Generally speaking, yes; however, machine learning makes rapid testing and iteration of thousands of new concepts at the same time possible. One of the keys is the ability of machine learning to make predictions on how consumers will behave next. By analyzing tons of customer behaviors, artificial intelligence platforms like IBM's Watson helps marketers automatically discover how customer behaviors align with brand goals, predict future customer activities and suggest actions marketing executives can take to optimize customer engagement..

Predictive Analytics

Predictive analysis assigns score for a variety of customer behaviors like opting in to an email newsletter or purchasing a recent product promotion bundle. In designing a new campaign, marketers can segment customers lists to reach only those who meet certain scoring criteria -- perhaps those who have opted-in the last 30 days, or those who visited a specific product page more than 10 times but have not converted. Now it is much easier to test copy elements, delivery windows, channel mix, and price points to rapidly narrow down the best options.

Unlock New Opportunities

Marketing professionals, advertising professionals and commerce experts can join thousands of customers one-on-one simultaneously through the entire customer journey. Brand strategists can create a "marketing machine" that learns from every touchpoint with customers, and quickly spreads insight across the organization. Marketers can leverage platforms like IBM's Watson to anticipate customer needs, often before the customers themselves, facilitating new markets creation, reducing risk, optimizing marketing spend, driving growth and improving collaboration among teams and partners.