10 proven Generative AI use cases to transform your CPG business

10 proven Generative AI use cases to transform your CPG business

<div class="insights_cta-component">In today's fast-paced CPG landscape, Generative AI is rapidly shifting from a buzzword to a business imperative. However, unlocking its true potential requires identifying the most practical and impactful use cases. This article delves into ten such applications, designed to deliver tangible value and streamline operations in your CPG enterprise.</div>

Table of contents

1. Automated call logging and summarization

Customer service & tele sales agents need to log and summarize many conversations. This can easily be automated - typically within just a few days of development time – by combining speech-to-text tooling like Deepgram, to generates the text transcript, and GenAI tooling like OpenAI, to summarize the transcript into any desired format. This use case reduces time spent on summarizing calls by up to 100%; proven to result in 10-15% efficiency gain at many clients. Furthermore, Gen AI call summarization also improves quality and consistency of summaries across agents, generating valuable data for further analysis.

2. Generated FAQ message replies

Customer service agents typically spend substantial amount of their time answering frequently asked questions. Many of these questions can be answered automatically by integrating Generative AI tooling with your company's customer service guidelines, FAQ pages, and internal documentation. This enables you to automatically generate responses to straightforward inquiries, such as order status questions. However, for niche questions, like tailored contract negotiations, you may prefer one of your sales members to personally review the generated answer. Agents can be kept in the loop and can have the ability to review & adapt Generative AI-drafted messages. This approach has already proven to significantly speed up response rates and reduce the time spent on answering FAQs by up to 90%.

3. Localized marketing content  

Marketing departments need to create a substantial amount of content, and local teams need to produce targeted local advertisements. Generative AI can facilitate the creation of marketing copy, visuals, and audio, as well as assist in analyses. Off-the-shelf tools can offer much of the functionality for basic tasks. As a next step, employing techniques such as few-shot prompting or fine-tuning your own models allows for customization with local insights, including language, tone, and imagery. This strategy not only boosts the efficiency of marketing departments but also empowers global teams to develop localized campaigns, significantly reducing the workload on local teams.

4. Automated product request processing

CPG players often supply products to others in the industry and spend considerable time deciphering inconsistent and extensive product requests from them. Generative AI can streamline this process by efficiently extracting crucial information from these varied requests. By utilizing Gen AI to identify specific types of information based on previous requests and defined criteria (such as key content related to taste), manufacturers can significantly improve their responsiveness. Past implementations of this technology have effectively demonstrated an increase in speed to market.

5. Automated identification of product trends

Food and beverage manufacturers invest considerable time in identifying & developing trendy products and sometimes even acquire expensive companies to stay ahead. Generative AI can proactively identify emerging trends by analyzing large volumes of data, including social media content. This approach ensures you are always informed about the latest trends, helping your products align with current market demands and preventing delays in market entry.

6. Personalized training for customer service & tele sales agents

Customer service managers and agents often lack the time to review all agent calls to learn how to improve conversations. Generative AI can automatically analyze conversations to pinpoint improvement areas for customer service agents, using speech-to-text and tailored AI tools with best practices, such as guides for handling upset customers.

Automatically highlighting areas for improvement and strengths of agent then enables managers to provide more precise and personalized coaching and training programs. Ultimately, this approach could lead to the development of an AI-powered training program. This use case not only enhances the quality of customer service with each interaction, but also reduces onboarding time, addressing high employee turnover in the customer service industry and enabling personalized trainings for customer service agents.

7. Automated local product compliance checks

Global companies often expend significant effort ensuring their products comply with various and ever-changing local regulations. Generative AI is highly effective at summarizing and examining large volumes of legal documentation, making it a valuable tool for quickly determining product compliance with local standards. By integrating Generative AI with legal documentation, legal departments can significantly save time, allowing them to concentrate on more strategic tasks.

8. Sales pitches for existing and new products

Sales representatives often struggle to create tailored sales pitches to increase conversion. Generative AI can generate customized sales pitches based on best practice guides, historic customer purchases, online customer information, or any other sources. This not only improves the quality of pitches, particularly for less experienced sales reps, but also accelerates their onboarding process by providing continuous guidance.

9. Sales assistant

Sales reps often find it time-consuming and challenging to retrieve customer-specific information. Besides that, it can be difficult to respond adequately during customer conversations. Combining Retrieval-Augmented Generation (RAG) with Generative AI tooling, and internal data sources (like best practice sales guides), can enable you to develop a personal assistant for sales representatives. This tool can provide immediate answers to queries about customer-specific deals (e.g., "What are the specific pricing agreements for customer X?") or offer advice on handling customer issues (e.g., "How should you respond to an upset customer due to late delivery?" or “Which additional products can I sell to this customer?”. This improves sales rep efficiency, customer satisfaction, and potentially revenue as well.

10. Automated market, competitor, and pricing reports

Many businesses struggle with accessing accurate market, competitor, and pricing data. Generative AI can assist by scraping and analyzing data from websites, reports, and other data sources. As an example, Gen AI could be used for daily pricing updates to your pricing team by automatically analyzing competitor prices. Additionally, you can ensure your innovation team is promptly updated whenever a competitor launches a new feature or product. This approach not only reduces external costs but also ensures the company remains well-informed about market trends, ultimately enhancing sales potential.

This list offers a starting point, but the possibilities with Generative AI are constantly evolving. The time to harness Generative AI's potential is now! Don't let your competition gain an insurmountable advantage - start exploring these use cases within your organization today.

If you'd like to discuss what's the best starting point for you, or how to develop a robust execution plan, reach out to us! Our team of experts are ready to guide you on your Generative AI journey.
Matti van Engelen
Associate partner | Practice Lead Data & AI

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