Generative AI Use Cases for Marketing, Sales, and Customer Service

Leverage Gen AI technology to drive sales and retain customers by creating personalized content.

Analyst Perspective

Generative AI is as impactful as the internet. It will transform the way businesses and customers interact.

ChatGPT has created plenty of interest in AI. The service reached 100 million active monthly users just two months after it launched. The explosive popularity of generative AI (Gen AI) is thanks to its low barrier to entry. Anyone can access these large language models (LLMs) at any time from any place on Earth for free.

This accessibility can be attributed to the fact that LLM owners like OpenAI and Google have a symbiotic relationship with end users. Companies need consumers to use their service to improve their models while users leverage Gen AI services to help with their everyday workflow, creating new content like blog posts, emails, images, etc. LLMs are offered free of cost for individual users and at minimal cost to businesses.

Due to its relatively low cost, the promised benefits, and pressure from competitors, it is tempting for businesses to rush into using Gen AI tools without fully understanding the benefits and drawbacks of the technology. As popular as AI is, there is also anti-AI sentiment growing in some industries and audiences due to its threat of disruption to the workforce and the quality of products/services.

This report will help you quickly catch up on the use cases and drawbacks of Gen AI for marketing, sales, and customer service professionals.

Sai Krishna Rajaramagopalan
Research Specialist, Customer Experience & Application Insights
Info-Tech Research Group

Executive Summary

Info-Tech Insight

Gen AI offers incredible possibilities at a low cost. With the low cost, however, comes challenges like IP infringement, data security issues, and workplace transformation. It is important for organizations to understand both the capabilities and limitations of Gen AI.

Introduction to Gen AI

SECTION 1

Gen AI is an innovation in machine learning

Generative AI (Gen AI)

A form of machine learning whereby, in response to prompts, a Gen AI platform can generate new outputs based on the data it has been trained on. Depending on its foundational model, a Gen AI platform will provide different modalities and thereby use case applications.

Machine learning (ML) and deep learning

The AI system is instructed to search for patterns in a data set and then make predictions based on that set. With repeat searches, the system ‘learns’ to provide more accurate content over time. This requires a supervised intervention if the data is inaccurate. Deep learning is self-supervised and does not require intervention.

Artificial intelligence (AI)

A field of computer science that focuses on building systems to imitate human behavior. Not all AI systems have learning behavior – many of them operate on preset rules (e.g. customer service chatbots).

Info-Tech Insight

Many vendors have jumped on Gen AI as the latest marketing buzzword. When vendors claim to offer Gen AI functionality, pin down what exactly is generative about it. The solution must be able to induce new outputs from inputted data via self-supervision – not trained to produce certain outputs based on certain inputs.

Gen AI for marketing

Marketing

Gen AI can be extremely efficient in creating personalized content for marketing purposes. Gen AI can create all types of content like blogs, emails, pictures, and videos. Content creators like copywriters, bloggers, and artists may also use Gen AI simply for inspiration and not for heavy lifting.

According to research conducted by HubSpot in its State of AI survey, 88% of marketers who used AI claimed it was more effective than traditional methods. Gen AI also saved content creators an average of three hours in creating a single piece of content.

However, there is also concern among the marketers. Forty-three percent of participants who don’t use AI were afraid of over-reliance on using technology. Gen AI can also affect companies when it comes to plagiarism and copyright infringement. Since there is no proper regulation in the AI space, this is a major concern preventing the wider use of Gen AI for content creation.

Popular Gen AI use cases for marketers

Source: “The State of Generative AI,” HubSpot, 2023

Gen AI for customer service

Customer service

Gen AI allows customer service agents to be more productive, offer 24/7 support, and deepen and maintain relationships with customers.

Customer service professionals report saving an average of over two hours per day using chatbots and Gen AI to write responses to customer service quests. However, there are some concerns raised by professionals. Chatbots powered by Gen AI can be used to outsource customer service roles and potentially replace human workers. In a survey conducted by HubSpot, 39% of customer support specialists are concerned about AI replacing their job and 55% think Gen AI tools like ChatGPT sometimes offer inaccurate advice.

Fact-checking the results of Gen AI can be time consuming and detrimental to overall productivity. The two hours saved by being efficient can be consumed with fact-checking results.

Benefits of Gen AI anticipated by customer service professionals

Source: “The State of AI in Customer Service,” HubSpot, 2023

Gen AI for sales

Sales

Like marketers, sales professionals can use Gen AI for sales enablement materials like scripts, brochures, playbooks, and price quotations.

Content resource management (CRM) systems typically host a vast amount of customer data like emails, transaction history, customer personas, etc. This data can be used to train LLMs to create personalized materials to maintain customer engagement and satisfaction.

Salesforce has deployed the world’s first Gen AI CRM technology (Einstein GPT) that connects with the Salesforce cloud to generate AI-created content. Einstein GPT can generate and schedule personalized emails to send to customers, generate specific responses for customer service professionals to answer customer questions more quickly, schedule meetings and generate short summaries of previous meetings, and auto-generate code for developers.

Estimated impact of Gen AI by commercial leaders (% respondents)

Source: “AI-powered marketing,” McKinsey & Company, 2023

Use Cases for Marketing, Sales, and Customer Service

SECTION 2

Create marketing content customized for individual user preferences

Marketing content

• Gen AI can use large language and image models to automatically generate content such as blog posts, articles, summaries, social media posts, product descriptions, webpages, pictures, videos, etc.
• The quality of generated content can be equal to or better than that of human-produced content since the AI models can learn about different types of customers from a large data set and identify patterns.
• Companies are no longer limited to creating content that appeals to most of the audience. They can instead produce content that may resonate with all their audience.
• Creating personalized content helps businesses to convert an audience member into a customer. Users are more likely to read, watch, and appreciate content tailored to them and are more likely to make a purchase.

Adobe Firefly leverages Gen AI to create images.

Source: Adobe, 2023

Case study: Cadbury

INDUSTRY: Chocolate confectionery
SOURCE: The Verge, 2023

Cadbury

Cadbury is a British multinational confectionery company. Cadbury has a huge market in India grossing over US$9 billion in annual revenue in 2022.

The pandemic reduced chocolate sales since local stores were unable to operate. Local store owners also suffered from a lack of income since they could not sell any products. Cadbury started a marketing campaign to help local store owners across India.

Cadbury worked with Rephrase.AI to recreate Shah Rukh Khan's face and voice in a way that sounds like the actor is saying the local store or brand's name. Local owners would sign up to a dedicated website and share information about their business and brand. AI would then be used to recreate Khan's face and voice to make it appear as if the actor is saying the local store or brand's name.

Results

The solution allowed anyone to create an ad for their local store and use the face and voice of Khan to promote their brand without spending a penny on endorsements. The use of Gen AI reduced overall marketing costs by 10 to 20 times.

Source: Cadbury, 2021.

Case study: CarMax

INDUSTRY: Retail
SOURCE: Microsoft, 2022

CarMax

CarMax specializes in buying and selling used cars with over 40,000 cars in their inventory across 230 locations. CarMax

leverages GPT-3 language models that have been pretrained with trillions of words to build solutions for a wide variety

of use cases, such as writing assistance, code generation, and reasoning over data.

CarMax uses Gen AI to produce content for its car research webpages. For example, the 2018 Kia Sorento page contains several sections of AI-generated text, including the “New this year” and “2018 Kia Sorento trims” sections.

Customers often face difficulty reading through thousands of reviews for a single car they are interested in. CarMax leverages Gen AI to summarize thousands of car reviews into a few easily readable sentences at scale across their inventory.

Results

Using Gen AI, CarMax reduced the time required to create 5000 review summaries from 11 years of manual work to few months. Customers also appreciated the quality of the content, allowing the content to hit an 80% editorial approval rate.

80%

Gen AI produced 5000 review summaries with an 80% editorial approval rate.

Improve your customer support with conversational AI

Conversational AI

• Traditional chatbots have the limitation of only answering specific questions that have been preprogrammed. AI chatbots built with LLMs remove this limitation.
• AI chatbots can quickly respond to customer inquiries and provide personalized support in a more efficient way than traditional chatbots. The AI would also be able to respond to customers 24/7.
• Customers can ask questions about various issues and topics and get an accurate response within seconds. AI chatbots can have natural real-time conversations with customers from any geographical location in any language.
• Companies like Google have taken chatbots to the next level with voice input. Gen AI can be trained to have a voice and directly speak to customers, instead of only conversing with the AI via messages and chats.

Source: Google, 2023

Case study: Zammo.ai

INDUSTRY: Professional services
SOURCE: Microsoft, 2023

Zammo.ai

Zammo.ai is a no-code, voice-first, conversational AI solution. The startup aims to eliminate the need for any IT

expertise by providing a feature-rich platform and reducing the time it takes to build conversational content.

Using Zammo, any user without technical knowledge in an organization can publish, optimize, and convert existing content into conversational form within a day. The conversational content can be deployed across many channels like voice (IVR/telephones), websites, and social media in the form of chatbots.

In addition to saving time and resources, the solution gives customers full control of the technology to customize the user experience to their brand and use cases. Instead of hiring an outside engineering and development team or tasking internal employees with building a conversational AI solution from scratch, companies and government agencies can save time and money using Zammo.

Results

Zammo decreased the time it takes companies to build conversational AI content by 70%. The solution also aims to reduce the cost of staffing by 90%.

Source: Zammo.ai, 2024

Case study: Blip

INDUSTRY: Professional services
SOURCE: Microsoft, 2023

Blip

Blip (formerly Take Blip) is a platform for building, running, and evolving chatbots. It develops chatbots to help companies introduce their brands on standard messaging applications such as WhatsApp, SMS, etc.

Blip uses Microsoft Azure OpenAI Service to incorporate AI functionality into its platform. This allows it to leverage the GPT-4 language model, which is trending with its key customers.

Blip provides a personalized, fluid, and instantaneous conversation throughout the consumer journey on whichever channel the customer chooses using the GPT-4 language model.

Results

Blip’s first successful implementation involved bringing GPT-3 into one of Take Blip's chatbots using Azure OpenAI Service. The use case was a marketing campaign that helped customers write meaningful holiday messages. The campaign had an excellent result, with more than 15,000 users creating more than 18,000 messages in just a few days with an 83% approval rate.

83%

Gen AI is used to create thousands of holiday messages with an 83% approval rate.

Personalized sales outreach is the future of sales

Personalized sales outreach

• Gen AI can be trained by analyzing large amounts of customer data, such as demographics, past interactions, and purchase history to create customized outreach efforts.
• The sales team can address the specific pain points and needs of individual customers. The team can create customized large scale email campaigns with personalized subject lines, body content, and calls-to-action. Knowledge base articles like case notes and customized summaries of previous meetings can also be created to be sent to the customer or used by the agent.
• Gen AI allows sales teams to create dynamic sales presentations tailored to individual prospects and create personalized sales quotes based on customer information.
• Gen AI can be seamlessly integrated with existing CRMs. This allows the sales team to track and analyze the effectiveness of personalized outreach efforts and to measure metrics.

Source: Seismic, 2023.

Case study: Salesforce

INDUSTRY: Software services
SOURCE: “Revolutionizing Customer Experience with Salesforce’s Einstein GPT,” Salesforce, 2023

Salesforce

Salesforce have introduced their very own Einstein GPT, their Gen AI solution partnered with OpenAI that directly integrates with Salesforce Cloud.

Einstein GPT integrates public and private AI models with CRM data to help users make queries within Salesforce CRM. Users save time thanks to AI-generated content that continuously adjusts to changing client information and wants.

Einstein GPT can be used to create sales emails and meetings using Salesforce. Sales reps can easily edit content and adjust meetings with a few clicks to collaborate more efficiently. Knowledge base articles such as case notes and meeting summaries can easily be created.

Results

A recent survey of over 500 senior IT leaders found that 84% believe Gen AI will help them to better serve customers.

84%

A recent survey of over 500 senior IT leaders found that 84% believe Gen AI will help to better serve their customers.

Case study: IBM

INDUSTRY: Information Technology (IT)
SOURCE: IBM, 2023

IBM

IBM is working with Bouygues to implement Gen AI capabilities in their call center operations.

Due to the large volume of customer-agent conversations (around 8 million), agents could only capture small parts of information from conversations. As a result, valuable insights were missing from the captured information. Agents also had too little prep time to fully read automatic transcripts from previous calls.

Results

Bouygues Telecom worked with IBM consulting to leverage Gen AI to quickly and automatically summarize calls, extract topics, and update the CRM with actionable insights. This successful implementation of Gen AI has resulted in a 30% reduction in pre- and post-call operations and is projected to save over $5 million in yearly operational improvements.

30%

Gen AI is used to reduce call operations by 30% and save over $5 million annually.

Conclusion and Next Steps

SECTION 3

Risks and drawbacks of Gen AI

• Although generative models are powerful, they can create biased and even harmful outputs and incorrect facts (called hallucinations).
• AI developers have used publicly available content to train their Gen AI language models without the original creator’s consent. This creates the risk of IP infringement.
• Most industries and the government do not have clear rules or regulations for protecting AI generated content. There is still a debate on who owns AI generated content and whether the content is copyrightable if it is not created by a human.
• Companies working with highly sensitive information are concerned about divulging information to a language model they do not own or create.
• There is anti-AI sentiment in some fields such as visual arts – both artists and consumers are against the use of AI. In a survey conducted by HubSpot, 44% of customer service professionals state that customers prefer to interact with a human rather than an AI.
• Gen AI threatens to replace many human workers. Even if AI does not completely replace humans, it can still change their jobs and workers would be required to learn new skills.

Gen AI risks relevant to organizations

Source: "The State of AI in 2023," McKinsey & Company, 2023