3 Ways AI Can Help Marketers Uplift their Marketing Automation Strategy

Artificial Intelligence (AI) has emerged as a technological game-changer capable of disrupting industries. In today’s business environment, digital and mobile marketing is no exception to the application of AI. In fact, according to a study by MemSQL – the data warehousing giants – 61% of marketers say AI is the most important aspect of their data strategy.

The application of AI in marketing automation involves the use of customer and multi-channel campaign performance data – across platforms, devices, online, and offline sources – and computational concepts such as Machine Learning (ML) to predict customers’ digital actions or inactions across websites, mobile apps, marketing campaigns, social media ads, etc.

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Harnessing AI – marketing automation helps brands target the right customers with the right content, messages, offers, or recommendations across the right channel, and at just the right time.

And, all of this is aimed at improving customer engagement, monetization, and retention by achieving personalization at scale.

3 ways in which AI can be leveraged within the marketing automation ecosystem

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1. Campaign Subject Line Optimization

AI can recommend the use of high-conversion keywords (based on sentiment analysis) in email subject lines, campaign titles, and campaign messages – based on past interactions of customers with marketing communication.

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For instance, for an e-commerce flash sale; AI will recommend the use of the words “discount”, “sale”, “hurry”, or “limited time offer” in email subject lines for specific customer segments. These micro-segments that can then be targeted with personalized content based on previous products viewed, items added to cart, or purchased.

Higher the degree of personalization, the higher the chances of campaign success.

2. Campaign Send Time Optimization

Marketers also need to target the right customers at the right time. AI allows marketers to identify customer segments that respond to a particular campaign at specific times based on historical behavior.

This means that marketers can increase the degree of relevance to their multi-channel campaigns by delivering them when different customer segments are most likely to respond and act.

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“Does your customer check his email between 10 AM – 12 PM?” Or, “Is he more likely to respond to an app push notification between 4 PM – 6 PM?”

Building on the above example, the price drop campaign would have greater success if delivered to identified customer segments when they are most likely to respond positively in terms of purchase.

3. Product or Content Recommendations

Today, customers require a greater context. Greater relevance. They expect an end-to-end personalized customer experience, right from the first time that they land on the brand website or launch the mobile app.

Think of how giants like Amazon, Netflix, Spotify, and YouTube curate 1:1 recommendations to deliver a unique shopping or viewing experience – every single time. And, for that to happen,

AI needs to learn in real-time from customer data such as:

  • Demographic Data: Customer name, age, gender, etc.
  • Geolocation Data: Place from where the website is accessed, timezone, IP, etc.
  • Device-level Data: Device type and model, browser type, OS and version, etc.
  • Behavioral Data: Products searched for, viewed, added to cart, or purchased. Recency and frequency of window-shopping and purchase, preferred modes of payment, historical interactions with and responses to multi-channel marketing campaigns, etc.
  • Offline Data: Purchase history from physical stores, recency, and frequency of store purchase, customer category (based on loyalty programs), preferred modes of payment, etc.

AI can also help learn from both clickstream and customer eyeball data. Gaining visibility on what customers click is a must-have. But, also gaining visibility on products that customers “see-and-don’t click” and “don’t see-and-don’t click” provides invaluable intel on individual customer behavior.

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When marketers help customers discover products or content that are suited to their needs, intents, tastes, and preferences – the chances of purchase or content consumption increase significantly.

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Marketing automation allows marketers to extend these AI-led personalized recommendations beyond the website or mobile app – across channels such as email, app push notifications, SMS, social media ads, etc. This helps deliver personalized experiences at multiple digital touchpoints; across every stage of the customer lifecycle.

Hello from the AI Side!

The application of AI in marketing will continue to expand. Consider how fast voice assistants and chatbots are improving. Brands that carefully evaluate and embrace AI in an attempt to create an integrated, seamless, and personalized customer experience are more likely to reap the rewards of higher ROI, customer engagement, retention, and top-line growth.

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