How AI’s Constant Learning Catalyses Omnichannel Growth

making a purchase, which means, they interact with a brand across multiple channels before they click the “buy” (73% of customers interact with multiple touchpoints before purchase!). Being aware of the customer’s actions at each of these interaction points is essential to understand their preference and intent. 

Real-time data integration and personalisation used to be a tough goal with traditional omnichannel strategies, owing to a lack of availability of real-time data and insights into customer behaviour. With the advent of AI, this is no more a hurdle—AI can quickly collect and analyse vast amounts of data, allowing brands to address customer needs in real-time. 

Omnichannel marketing is now synonymous with AI. By optimising and personalising the customer experience across all channels, AI unified data to inform marketing campaigns, automate tasks to help scale efforts, and identify channels where customers are most likely to convert. 

Five Key Roles for AI in Omnichannel Marketing

Automated Content Creation, Consistent Messaging

Connected customer journeys are an essential part of ensuring a customer doesn’t drop off from their browsing experience at any point. Due to a multitude of channels available to customers today, they might jump from one to another in the middle of their journey and a disconnect at any point can lead to cart abandonment. AI is adept at reading customer data like purchase history, browsing patterns, etc. and creating unique content tailored to every customer from this data. 

Further, a cohesive customer profile allows to maintain this messaging across any channel the customer might hop on to. AI offering by SAP Emarsys enables brands to enhance customer engagement using AI to generate content and deliver relevant, timely, channel-specific messages. The automation of content creation also frees up marketers to focus on other key omnichannel strategies requiring human input.

Personalisation at Scale

AI-powered recommendation engines improve the likelihood of conversion by analysing data across various channels. This could include the customer’s purchase history, browsing behaviour, and past interactions with the brand. With SAP Emarsys, for instance, brands can target customers with engaging offers based on status and expected behaviors, such as first-time buyers or those likely to convert. Automation offered by AI helps execute this at scale. 

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Real-Time Customer Support

Research shows that 73% of consumers are now open to AI-powered chatbots for customer service, indicating that they are becoming indispensable tools for real-time customer support. AI for customer service offers primarily two advantages—one, they can handle a variety of queries and concerns, simple or complex, presented by customers, and two, they can do this across different channels.

Further, AI-powered assistants are available 24/7 and besides answering FAQs, they go as far as assisting with the stages of purchase like product selection.  

Predictive Analytics, Targeted Campaigns

What sets artificial intelligence apart from other technologies is that the models develop and improve upon constant learning. By analysing past purchasing history and behaviour, AI uses predictive analytics to shift from a reactive to a proactive approach. For instance, AI optimises inventory management by predicting what a customer might be likely to add to their cart. Using tools like AI-personalisation from SAP Emarsys, brands can get a deep insight into campaign performance, including store metrics, return data, and lifecycle analytics.

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Seamless Channel Management

Juggling between diverse channels to keep a customer engagement can be a daunting task. Any disconnect can lead to dissatisfaction and cart abandonment. AI helps present all channel information in one place, on a single dashboard, making it convenient to act on consumer insights. Enabling seamless channel transitions also adds to the customer’s ease where pausing a conversation in one channel and continuing it elsewhere doesn’t give the preview of a broken customer experience.   

It is essential to remember that AI systems improve over time upon learning from new data. In order to best leverage AI to its complete potential, marketers must be mindful of continuously refining the AI models to keep up with evolving customer expectations and market trends. 

Marketers must also be mindful that AI, while smart and efficient, is not a magic wand. It can automate processes and offer insights but it needs to be fed on the right data from the right channels, unified into a single location, for it to be best utilised. AI, when supported with the right data, can be a marketer’s best tool for crafting omnichannel experiences.

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