AI-based marketing is now indispensable for online businesses that want to stay ahead of the competition.  Today, companies must make timely decisions based on predictive analytics.  It has become necessary to automate this process, a feat that is made possible by harnessing the power of emerging technologies.

AI can augment the capacity of marketing teams by performing tasks–requiring less human intervention, thereby maximizing efficiency.  The idea is to procure an in-depth understanding of customer needs and preferences, and then act on that knowledge quickly and effectively.  Prior to incorporating AI technology into their outreach, marketing departments had to coordinate with data management teams to establish better processes for data harvesting and data curation.  This process is now taken care of by computers, thus streamlining what used to be an arduous, time-consuming, and expensive process.

AI tools prescribe the best actions to take when it comes to meeting specified benchmarks.  Those who generate business online are those who are most adept at discerning patterns in the online activity of target customers–distilling massive data-sets to uncover customer preferences.  The ability to make real-time, data-driven decisions has brought AI to the forefront.  AI-based platforms do this by evaluating profiles to learn how to best communicate with certain kinds of consumers, based on a profile of their online activity.

Machine learning enables the system to automatically tailor messages at the right time without the need of human intervention.  Marketing teams are thereby able to deliver personalized messages to customers at appropriate points in the consumer lifecycle.  AI can also identify at risk customers and target them with information that will get them to re-engage with the brand.

With a profusion of data to deal with, conventional marketing teams are having a difficult time gleaning insights from it.  This no longer needs to be an insurmountable obstacle.  AI learns customer preferences and pulls pieces from a gigantic reservoir of content to create customized emails or offers, which feature relevant images, videos, posts, or articles.  Enhanced UX ensures that online businesses more consistently engage customers, getting the most value out of each campaign (and not squandering limited resources on dead ends).

A problem that marketing teams tend to encounter is deciding when and where to place advertisements, and how to best focus messaging.  AI helps companies orchestrate effective campaigns based on user preferences, enabling them to alter the strategy in real time, recommending adjustments based on the latest consumer information.  This can be done via a savvy combination of personalized and programmatic advertising (that is: by combining micro-targeting and automation).  Programmatic buying–replete with judicious segmentation and personalization–exemplifies how machine learning can facilitate marketing flexibility–tailoring campaigns to meet customers as needs and interests evolve.

Moreover, “smart” platforms leverage machine learning to bid on ad space relevant to target audiences; and do so in real time.  Such bids are based on expressed interests, location, and purchase history.  This enables marketing teams to target the right channels in a timely fashion.

It is no secret that marketers need to have a vast amount of data at their disposal; as that’s what will train the AI in customer preferences, market trends, and other things that will impact the success of AI-enabled campaigns.  Hence the ongoing collection and analysis of data is required to train AI programs.

During this process, it is imperative to maintain a minimal degree of data quality.  As machine learning programs cull more information from the vast online ecosystem, they will learn how to make more and more effective decisions.  Yet if the data is errant, the recommendations it proffers could cause AI programs to make decisions that addle marketing campaigns.  Hence a well-executed marketing campaign requires data quality assurances.  Such information may be run through a sophisticated regime of CRM, taking into account the full array of factors that may contribute to a purchasing decision.  Efficiency means every deployment must be well-crafted and astutely targeted, a task that only an AI-powered system is equipped to carry out.

Selecting the right platform is necessary to get an AI marketing program off the ground.  Staying abreast of market trends requires capabilities that only MarketingMachine.AI can offer.  While AI is still new to the overall marketing space, it promises to only grow in popularity.  In the coming year, AI will replace many of the data analysts in marketing.  Marketing teams that fail to leverage the full power of AI will be transplanted by those who do.