Top 3 Generative AI use cases and tools for B2C in 2023

Unlike traditional AI engines that are designed to recognize patterns and to make predictions, Generative AI is designed to create new solutions or products on its own, without being explicitly programmed. In other words, generative AI creates new content such as images, text and media while learning from always-on large data sets.

Generative AI is a subset of artificial intelligence and uses a type of deep learning called GAN (Generative Adversarial Networks). This technology is already being used in a number of B2C sectors, such as ecommerce, travel, gaming and retail.

Let’s look at 3 B2C use cases explained and illustrated.

1. Hyper-Personalization

Personalization is a proven driver for customer engagement, and Generative AI is a key to unlocking its full potential. With its ability to identify key moments of truth in the customer journey and provide relevant content recommendations, Generative AI is already transforming the way marketers engage with their customers.

How Gen AI enables hyper-personalization

Generative AI also enables brands to personalize their marketing efforts more accurately, ensuring that they send relevant offers to potential customers and increasing their response rate. As shown in the graph, Gen AI let retailers or e-commerce websites go from regular ‘Push Marketing’ to Hyper-Personalization.

Here is an example of how Gen AI can add value to product recommendations.

Jane is a customer who is browsing your site looking for a pair of sneakers.

• Non-AI personalization engines:
  Hello Jane, I recommend you these discounted sneakers
  Push Marketing — Segmentation based, discounted offer push
• Traditional AI personalization engines:
  Hello Jane, I understand you are looking for comfortable blue sneakers
  Personalization — Behavior pattern, historical data, contextual & omnichannel recommendations
• Generative AI personalization engines:
  Hello Jane, I understand you are looking for sneakers that you can wear at work where the dress code is Business Casual. Also you would like your shoes to have soft soles because of your sensitive heel bone. You also have a preference for blue color
  Hyper-Personalization — Machine learning, real-time assimilation and predictive recommendations

Generative AI can make it easier to identify your customers expectations and keep them engaged, increasing loyalty and reducing churn. Customization at scale can now be achieved because of the high precision and accuracy of AI-generated content that becomes more engaging and relevant to a high volume of customers. We can now adapt the content in almost real-time which can factor in many elements such as location, culture, mood of the moment, and live events.
How come? Because it’s powered by a very large data set of behavioral interactions and continuously optimized by humans.

2. Content creation

AI-generated first drafts for content can save marketers significant time and resources while producing high-quality content. For example, Jasper or Writesonic can generate articles, product descriptions, and social media posts that can be used to populate marketing channels quickly, boosting your SEO and increasing engagement with your brand. You will also benefit from efficiency for your marketing teams: create faster, plagiarism-free content and minimum copyright hassle!

The content creation process goes as shown below. Inputs come in such as Trends, Contextual Data (e.g. a pandemic, a big sports event, etc.) , SEO Rules, and Content Parameters (tone of voice, keywords, length of text). As an output, most of the engine will first generate a draft that can be reviewed/edited by humans (online marketer, content editor, SEO specialist) before getting published.

Content creation with Gen AI to boost content marketing

While AI-powered tools can assist in content generation and optimization, it’s essential to ensure that the content produced aligns with your brand’s voice and values. Human oversight is crucial to fine-tune and maintain content quality and accuracy. Additionally, SEO success depends on various factors beyond content generation, such as website design, technical SEO, and link building. A comprehensive SEO strategy involves a combination of these elements.

3. Customer service & CRM

Generative AI can revolutionize CRM (Customer Relationship Management) and customer service for businesses in several ways. Here are three examples of how Gen AI can bring significant improvements.

Personalized and Contextual Conversations:

• Generative AI-powered chatbots can engage in natural language conversations with customers, offering personalized responses based on their preferences, purchase history, and browsing behavior.
• By understanding customer intent and context, these chatbots can provide more relevant product recommendations and support, enhancing the overall customer experience. They will also propose the next best action (NBA) to the customer or the next best offer (NBO)
• Customers feel valued and understood when they interact with a chatbot that can address their individual needs, leading to increased customer satisfaction and loyalty.

CRM with Gen AI

AI-Generated Content for customer communication:

• Generative AI can assist in creating personalized emails, newsletters, and promotional content tailored to each customer’s interests and behaviors.
• By dynamically generating content, businesses can maintain a regular and engaging flow with their customers, keeping them informed about new products, offers, and updates. Content can be SEO-friendly and plagiarism-free
• AI-generated content can also be used to craft compelling social media posts, further extending the reach and engagement with customers on different platforms.

Here is an interesting example of how Ssense, the fashion company, launched an AI-based personal stylist

Sentiment Analysis Intelligence to reduce Customer Churn:

• Generative AI can be employed to perform sentiment analysis on customer feedback, such as reviews, comments, and survey responses.
• This analysis allows businesses to quickly identify customer sentiments, preferences, and pain points, enabling them to address issues promptly and make data-driven improvements to products and services. This is linked to the next best action (NBA) and next best offer (NBO) mentioned above.
• By understanding customer sentiment, businesses can adapt their strategies and offerings to better align with customer needs, improving customer satisfaction and loyalty.

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Note: While Generative AI can provide significant advantages in CRM and customer service, it is essential to strike the right balance between automation and the human touch. Human oversight and intervention remain crucial to handling complex customer queries and situations that may require empathy and understanding beyond what AI can currently offer. Integrating Generative AI with human support can create a powerful and effective customer service ecosystem for B2C businesses.