Segmenting audiences means more message variants to be created, more campaigns, more automation workflows, the list goes on. The result? Marketers just simply cannot do it…or at least not to the level we expected of them. So, to combat this, e-commerce platforms try to motivate them. Solution providers create customer intelligence, augmenting contact data with smart data, making the segments more intelligent. These platforms show great analytics and reports, with scoring models and predictions, and even recommendations on the next best move, trying to guide and motivate the user to act. It helps, but not enough.

The marketer in the center can’t handle all the options. They don’t understand the decisions they need to make, and they don’t have time to create all these variants, not to mention optimizing them. They can’t handle the granularity of 1-to-1, and end up giving most of their attention to the same day-to-day routine they were doing before. At Emarsys, we realized that we need to release marketers from these tasks as it’s too much scope to handle. This is where AI comes into play.

Artificial intelligence Marketing needs to bridge the gap between data science and execution. And it’s not about fancy analytics, future revenue predictions, or scoring models. At Emarsys, we tend to think of AI as a robot that actually performs tasks, not simply tells the marketers what to do.

For digital marketers, the presence of Artificial Intelligence Marketing (AIM) is no longer the stuff of the future; the future is already here. AI marketing opens strategic doors that were previously closed to marketers and sets the stage for unprecedented levels of personalization in marketing.

Eliminating Manual Work

At Emarsys, when we place at our users’ fingertips product recommendations, incentive recommendations, send time optimization, and more AI capabilities that follow these principles, we finally start to see an increase in adoption of 1-to-1 communication. Why? Because we didn’t just make it smart, we also made it effortless. It’s the flick of a switch, which is no longer a nice to have for marketers, but a requirement in order for them to provide truly individualized personalization at scale.

Send Time Optimization is an AI marketing feature that follows these principles. Emarsys’ platform decides when to send the message to each contact according to the highest probability of engagement, it applies machine learning to actively search for new slot and adapt to the user behavior, and it is activated with the flick of a switch.

Utilizing AI marketing, marketers can now spend time creating high-level strategies and focusing on high-impact campaigns, instead of manually dealing with tedious data collection or granular segmentation. AI marketing solutions can even dig a layer deeper into data analysis than a human could, for better insights and visibility into consumer interactions and engagement, in turn leading to a more concrete strategy from the creative mind of the marketer.

Increasing Creative Output

For creative brains, there is nothing worse than being bogged down by the monotony of ‘numbers’. All marketers are faced with this dilemma; as much as many would love to create winning content all day long, it’s impossible to forge blindly ahead without the numbers to guide the direction.

With AI marketing taking this ‘numbers’ effort off marketer’s shoulders, more content can be created, and the quality of this creative output is heightened by increased data governing the direction and strategy, creating a positive feedback loop of continual refinement and ever-increasing scope. How is this possible? Product recommendations are a good example. With AI marketing, it’s decided on behalf of the marketer. For every contact, AI determines the products to present, how the content should be presented, and via which channel. All the marketer has to do in this scenario is place a black box widget in a website page or an email, and they automatically leverage machine learning to improve their results.

Product recommendations have solved a big challenge for marketers, one that was previously way beyond their scope to address. From the thousands of products in a given catalog, how can a marketer manually match, to each recipient, the products most likely to interest them? Even if they had all the website browsing data, in a form that could be segmented, they wouldn’t have the time and resources to sit and do this manual segment matching of people to products at 1-to-1 granularity. This was an impossible task that AI seamlessly solves without adding a second of additional workload for the marketer.

Final Thoughts

At the end of the day, AI marketing allows the marketer’s role to become more focused and streamlined. Less time is spent on manual processes and data analysis, and is instead spent doing what marketers do best: building high-impact strategies, creating winning content, and establishing topical messaging.