How AI Can Enhance Hyper-Personalization in Marketing

While I have tried to remain totally unbiased in all of my last articles, today, I must confess, I’m extremely excited by what’s happening with ChatGPT and Open AI and the implications it is having  and will continue to have in terms of hyper-personalization. OpenAI is a research organization founded with the goal of developing and promoting friendly artificial intelligence (AI)  for the benefit of humanity. OpenAI conducts cutting-edge research in areas such as machine learning, natural language processing, and robotics, with a focus on advancing the state-of-the-art in AI and making it accessible to a wide range of users.

In my past articles about hyper-personalization, I have stated some of the key elements needed and some of the barriers that companies are facing when it comes to implementing these kinds of strategies. AI technologies, such as OpenAI, are offering marketers new ways to engage with customers and create more personalized experiences. In this article, we will discuss the implications of OpenAI in key elements of personalization:

Customer Data Matching and Deduplication

One of the most significant challenges in personalization is matching customer data from multiple sources. Often, customer data is siloed within different databases, making it difficult to create a comprehensive view of the customer. This is where OpenAI can help. By using machine learning algorithms, OpenAI can identify patterns in customer data, enabling marketers to create a single, unified view of each customer. It can learn from local taxonomies where specific names could escape pre-established rules, just as happens in the southern part of Mexico where two-letter names and last names exist and are valid.

With OpenAI, marketers can identify duplicates, such as when a customer is entered into a system twice, and ensure that all data points are correctly associated with the right customer. This helps prevent confusion, ensuring that the right message is delivered to the right person. With accurate customer data matching and deduplication, marketers can create a more personalized experience that resonates with each individual customer.

Customer Insight

By analyzing large amounts of customer data, businesses can gain a deeper understanding of their audience and create more personalized marketing campaigns. OpenAI's machine learning algorithms are designed to sift through this data and identify patterns and trends that can help businesses segment their audience more effectively.

Segmentation is a crucial aspect of any marketing campaign, as it allows businesses to tailor their messaging to specific groups of customers. By using OpenAI's algorithms to analyze customer data, businesses can identify the characteristics and behaviors of different segments of their audience, and create messaging that is more relevant and engaging. This can help businesses build stronger connections with their customers, and ultimately drive more revenue.

Segment understanding is another area where OpenAI can help businesses improve their marketing personalization efforts. By gaining a deeper understanding of the needs and preferences of different customer segments, businesses can create more targeted marketing campaigns that are designed to resonate with their audience. OpenAI's algorithms can analyze customer data to identify the characteristics and behaviors of different segments, and use this information to create more personalized marketing campaigns.

It is in segmentation where OpenAI can explain in natural language a segment, so that marketers and the organization have a clearer understanding of the individuals aggregated in it.

Best Next Offer and Action

Once customer data has been deduplicated and matched, marketers can use OpenAI to determine the best next offer or action to take for each individual customer. OpenAI can analyze vast amounts of customer data and make predictions about what a customer is likely to be interested in next. This information can be used to create personalized recommendations for products or services, improving the customer experience and driving sales.

For example, a retailer can use OpenAI to analyze customer purchase history and determine that a customer is likely to be interested in a specific product. The retailer can then create a personalized recommendation for that product, which will be more likely to resonate with the customer than a generic offer. With OpenAI, marketers can create personalized recommendations that are tailored to each individual customer, improving engagement and conversion rates.

Imagine running this in real time and being able to deliver omnichannel personalization at scale, and having OpenAI create a specific campaign that traces the results of the same promotion it has offered in just one single step. Tracing back success rate and linking it back to the customer 360 view is one of the most time- and process-demanding activities in personalization, and now it can be done seamlessly.

Image Management for Visual Communications

Let’s imagine a world where you have installed the capability of delivering personalized offers to your customer base, but the problem you run into is that your Design and Art team is not able to create personalized content and art in your emails.

Visual communications, such as email and push notifications, are an essential part of any marketing strategy. However, creating personalized images that resonate with each individual customer can be a challenge. OpenAI can help by analyzing customer data and creating images that are tailored to each individual's interests and preferences.

For example, a retailer can use OpenAI to create a personalized email that includes an image of a product that the customer is likely to be interested in. The image can be customized based on the customer's purchase history, search history, and other data points. This level of personalization can significantly improve engagement rates, driving more sales and revenue.  

Now, each customer has a specific message and OpenAI can fetch something from the company's product assets (photos, videos, gifs) and place them where they are likely to have the most impact in the email, push, and others. 

It is hard to believe how this key element of hyper-personalization has advanced in a matter of weeks just because of the materialization of AI technologies.  Fast-adopting companies will benefit immediately from this technology and customers will be delighted.