Personalization at Scale: How AI Enhances Customer Engagement

As I hit the pavement for my morning run, my trusty running shoes were feeling a bit worn-out, reminding me it might be time for an upgrade. Just then, a notification popped up on my phone – an email from my favorite athletic store. I opened the email to find a personalized array of the latest models from my preferred shoe brand showcased. But it didn’t stop there. The store’s website greeted me with a curated selection of fitness gear tailored precisely to my needs, including essential accessories like Sweaty Bands to combat the Florida heat. As I browsed further, I was pleasantly surprised to see a list of upcoming races conveniently mapped out for me. It was as if the store knew exactly what I was looking for. In that moment, I realized the power of AI personalization – transforming my shopping experience into a seamless journey, where every recommendation felt uniquely tailored to my preferences and lifestyle.

Right message. Right time. Right place.

According to Salesforce, “Seventy-one percent of marketers say that meeting customer expectations is more difficult than a year ago.” Buyers have come to expectmore relevant messaging and content, and at the right time. McKinsey research shows “71% of consumers expect companies to deliver personalized interactions”, and “76% get frustrated when this doesn’t happen.” 

In order to achieve this level of connection, there’s a need to tap into AI’s vast potential, particularly in personalized campaigns, to boost customer engagement. 

Using my recent running experience as an example, AI served up a timely, tailored experience that ultimately drove sales. Let’s look at this scenario further and investigate how marketers can utilize AI to create meaningful engagements with potential and existing customers.

The Process

Data Collection

As marketers, we use a variety of sources, first-party data and marketing technology tools to build our customer profiles, segment and customize messages accordingly in an almost  modular fashion.

AI further elevates this data collection by gathering information from multiple online sources and analyzing text and images to unveil additional, relevant insights. This enables real-time analysis on a larger scale, providing deeper insights than ever before. CDPs, web scraping tools and social listening platforms have AI capabilities to collect and analyze data.

For example, AI can pull data from sources such as purchase history, GPS running stats, and online browsing habits, offering a comprehensive understanding of my behavior.

Data Analysis & Predictive Insights

Once the data is collected, AI uncovers hidden patterns and connections, a step previously non-existent but crucial for scaling personalization.

AI notices my brand loyalty and running frequency from GPS data and can predict my future needs. Understanding my loyalty to a specific brand and my running habits, AI anticipates when I require new shoes due to wear and tear from my typical mileage.

Personalized Recommendations

This is where I received the email suggesting the latest model of my favorite shoe, the store website adapted to showcase similar running gear and the pop-up highlighted upcoming races in Jacksonville.

Marketing Automation Platforms (MAPs) are beginning to build in ever increasing Generative AI capabilities around content personalization in emails and landing pages. Instead of segmenting the database based on fairly static attributes and creating variations of content pieces for the different segments, this is now able to be done at a much larger scale. Some MAPs even utilize AI to analyze performance and run A/B testing on content.

Strengthened Messaging through Advocates

AI helps businesses improve customer experience in many ways. Another use that intrigues me is gathering customer reviews and stories. AI scraping and sentiment tools can automatically collect this information from different sources, saving time and effort in what’s usually a lengthy process.These insights can be used to enhance marketing materials and may also help companies improve their products and services. 

Ok you got some new shoes, so what?

Yes, I love a good pair of new shoes. But the purpose of this post is to illustrate how marketers can use Generative AI to proactively send targeted communications to consumers and businesses about products and services before they may even realize they need them! And it’s not just a single email to me, it’s at a large scale! But to the prospect, on the B2B or B2C side don’t feel that, it feels personal.

One in 4 organizations have already implemented GenAI in marketing operations. And they’re seeing returns! “Early adopters are able to meet content demands 1.5x as often as companies with no plans to use GenAI, while saving the average content marketing employee 11.4 hours/week.”

Implementing personalization at scale is expected to free up employee time for strategic initiatives, increase engagement and boost conversion rates by providing prospects with what they need efficiently.

Getting Started

AI is a hot topic and is so transformative that it can be intimidating. Start by researching and exploring the tools you already have for AI functionality. Identify where you could use more support in creating personalized experiences. Remember, results depend on your data and models, so be patient. And don’t forget the human element—AI is a tool, not your replacement. 

Have you downloaded the SH/FT AI Readiness Guide? A great starting point in your journey to embrace AI, including a readiness assessment tool for your marketing team and the steps needed to implement an AI pilot program at your org. Need support along the way? SH/FT is here to help.