In this collection of use cases, you will discover smarter and more innovative strategies to effectively incorporate technology and human insights into your marketing strategy. Based on real-world examples from recognizable brands that have successfully implemented these tactics.

These 10 case studies highlight the diverse applications and significant benefits of data, machine learning and AI in enhancing marketing strategies including:

1. Tailored content and personalized product recommendations
2. Content creation with Generative AI
3. Dynamic customer segmentation
4. Seamless customer journey mapping
5. Email and SMS campaign optimization
6. Omni-channel marketing powered by technology and human insights
7. Leveraging the power of machine learning for Market basket analysis
8. Predictive AI and human insights fuels Starbucks marketing strategy
9. Leveraging data and AI algorithms to implement dynamic pricing at scale
10. Chatbots and virtual assistants

Let's dive in.

Tailored content and personalized product suggestions

Have you noticed content recommendations similar to the show or a film you are browsing on Netflix?

How it works

AI algorithms analyze customer browsing and viewership data to provide personalized product or service recommendations, resulting in higher levels of customer engagement and conversion rates.

The powerful Netflix Recommendation Engine utilizes a vast collection of viewership data, machine learning and AI to deepen their view of customer personalization.

Key results

• Everything is a recommendation
• Diversity  
• Distribution from 1 device to multiple devices
• Hyper-customer centric approach, a practice that they call "Consumer Data Science"
• Going international

Netflix has invested in extensive research and development in the areas of data, machine learning, predictive models and AI. This strategy has improved customer engagement and retention, saving the company over $1 billion in customer retention costs.

Read the full case study.

Content creation with Generative AI

Imagine being able to create personalized feedback surveys for every customer who makes a purchase at your restaurant or retail business, whether in-store or online. How amazing would that be?

With the right customer data, Artificial Intelligence and Generative AI tools, businesses can generate personalized content like emails, social media posts and blog articles that are tailored to that customer's preferences and experience with your brand.

How it works

BuzzFeed, a popular media company, has harnessed the power of AI and Generative AI to take personalization to a whole new level. By utilizing AI and Generative AI, BuzzFeed is able to create highly customized quizzes for their readers.

Key results

• A vast repository of reader data which includes information about their preferences, interests, and demographics.
• This data is then fed into machine algorithms and AI that analyze and process complex data sets.
• With the help of Generative AI, BuzzFeed can generate unique quiz questions and options based on each reader's individual profile.
• The result is highly entertaining quizzes and highly relevant to each reader's personal tastes and interests.

Read the full case study.

Dynamic customer segmentation fuels personalization strategy

Restaurants and retail businesses with limited resources can drive growth more effectively by implementing a simple yet dynamic customer segmentation approach in their email marketing, SMS campaigns, and loyalty programs.

How it works

Blue Oak BBQ, a growing quick service restaurant brand in the New Orleans and Alabama market is using dynamic customer segmentation that provides the owners with:

• Engaged local customers
• Engaged out-of-town customers
• Customers who purchase a daily special on a weekly basis
• Customers who purchase catering for special events

Key results

With limited resources, the business is able to seamlessly aggregate data from their stores using the guest Wi-Fi network, POS and website. The customer data personalizes their email marketing campaigns for their daily specials and catering programs.    

• More than half of Blue Oak BBQ's customer base actively engages with the brand through their inbox, demonstrating high levels of personal interest and connection.
• Dine-in service consistently outperforms every other sales channel by an impressive 30%.
• Email marketing campaigns are tracking at a 28% average open rate.

Read the full case study.

Seamless customer journey mapping

In today's rapidly evolving restaurant industry, businesses need to stay ahead of their audience's evolving behaviors.

How it works

• Varying age groups exhibit distinct eating habits.
• The market you serve comprises of individuals and families with diverse taste profiles and spending power.
• Differentiating between transient customers and residents.
• Gaining an understanding of the journey of every customer persona you serve is crucial in unlocking the full potential of your business.

Plnt Burger a growing vegan fast-casual brand in the East Coast needed to better understand the customer personas they serve and gain a visual map of their day-to-day journeys.  This is how they solved the challenge:

Key results

• Engaged GoGoGuest to help seamlessly gather all their customer data from Toast and AppFront.
• Established a consistent and complete view of their customers in a customer data platform (CDP)
• Identify the unique personas by market
• Understand the common journeys by each persona in each market

Read the full case study.

Email and SMS campaign optimization

Prior to the pandemic, many restaurateurs had a lackluster attitude towards email and SMS marketing. These communication channels were often perceived as "spammy" with the belief that consumers no longer open emails, and SMS being fraught with compliance issues.

That drastically changed during the pandemic when social gatherings in public spaces were disrupted, effectively limiting the ability of restaurateurs to attract foot traffic into their establishments.

Edley's BBQ and Pancho's & Lefty's were positioned well to respond to the pandemic with their early investments in data gathering and email marketing engagement.

How it works

• A guest WiFi captive portal was installed in each store location to enhance the customer experience and gather valuable data.
• Daily collection of customer data commenced eight months before the onset of the pandemic.
• Implemented automated email marketing campaigns that effectively engaged customers and activated their profiles.
• Effortlessly tagging local guests versus transient or out-of-town guests.

Key results

• In just eight months, Edley's and Pancho's achieved an extraordinary growth in their subscriber and active customer lists, increasing them from less than 1,000 unique subscribers to a remarkable 20 times that number.
• During the initial year of the pandemic, Edley's leveraged email marketing to boost sales for their delivery and pick-up services. As a result, the total revenue for that year witnessed a substantial increase of 20% compared to the previous year.
• Over the next 3 years, Edley's invested in a customer data platform and added SMS marketing to their marketing quiver.

Read the full case study.

Omni-channel powered by technology and human insights

A carefully curated technology stack can make a difference for any business. Meet Devocion Coffee, a New York City brand with roots in Colombia.

The growing multi-location coffee house uses omni-channel as a strategy to expand their sales channels to reach a wider consumer and wholesale audience.

How it works

• Devocion Coffee made a strategic investment in an appealing, mobile-friendly, and user-friendly eCommerce website powered by the trusted platform, Shopify.
• To elevate the customer engagement with online shoppers, Devocion invested in Klaviyo's comprehensive suite of data management tools, customer journey tracking features, automated processes, and effective email marketing strategies.
• To leverage their in-store data, Devocion Coffee made a strategic investment in GoGoGuest's guest Wi-Fi captive portals, which seamlessly integrate with Square and Klaviyo. This integration allowed them to expand their audience and effectively drive sales in their physical stores.

Key results

By meticulously selecting a complementary technology stack that functions as a cohesive ecosystem, Devocion Coffee has been able to enhance their physical store growth, boost the average revenue per guest Wi-Fi user, and maximize the potential of their eCommerce distribution channels.

• In-store customer growth by over 15,000 in less than 365 days
• Average purchase from guest Wi-Fi users increased to $70+ per month
• Active and engaged funnel in-store customers to online shoppers

The built-in data management, machine learning and AI from the collective technology ecosystem has empowered Devocion Coffee to successfully execute on a customer-centered marketing strategy.

Read the full case study.

Leveraging the power of machine learning for Market Basket Analysis

Marketing Basket Analysis (MBA) analyzes frequently purchased item combinations, even if they are unusual. For instance, it reveals if customers buy a summer salad with a lemon bar pastry. This helps understand the profitability, frequency, and revenue brought by such combinations.

The traditional process of generating an MBA report takes a significant amount of time and resources. It involves manual data collection from different sources, deep data analysis, and report generation. However, with the power of machine learning and predictive analytics, this process can be automated and simplified.

How it works

• GoGoGuest collects and captures your POS data to a customer data platform (CDP).
• GoGoGuest processes vast amounts of data using our proprietary MBA machine learning and predictive models.
• A quarterly MBA report is published every 90 days to our reporting engine.

Key results

Sweet Wheat Bakery, a beloved local establishment in the Redondo Beach market, leverages Market Basket Analysis to identify the most valuable offerings and develop effective promotions both in-store and online.

By utilizing a completely automated Market Basket Analysis reporting engine, which is generated through the power of machine learning and predictive analysis, Sweet Wheat Bakery was able to eliminate the time-consuming task of manually gathering data from multiple systems. This not only saved them hours of work but also resulted in significant cost savings, amounting to $10,000 per quarter.

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Predictive AI and human insights fuels Starbucks marketing strategy

Starbucks revolutionized its customer experience by implementing advanced predictive AI.

"In thinking about the two transformative elements of modern-day retail, it begins by creating unique and relevant experiences. If you can't create a customer experience in your brick-and-mortar store, an experience that goes beyond convenience, you're just another node in the supply chain. And that in-store experience must then be extended to a digital relationship."

Kevin Johnson, former CEO, COO and President, Starbucks

As of 2024, Starbucks has over 38,000 stores worldwide. This includes both company-operated and licensed stores.

Starbucks places great importance on the seamless integration of technology and human experiences, which is their guiding principle. To achieve this seamless integration, Starbucks has implemented advanced predictive analytics powered by AI. By leveraging customer data, machine learning algorithms, and AI, Starbucks is able to make accurate predictions about customer behavior, preferences, and purchasing patterns.

Read the full case study.

Leveraging data and AI algorithms to implement dynamic pricing at scale

Data, predictive analytics and AI algorithms is used to power Amazon's dynamic pricing strategy. The eCommerce marketplace automatically adjusts its pricing every 10 minutes.

How it works

• Amazon utilizes artificial intelligence and machine learning algorithms to analyze tons of customer data and market trends in real-time.
• The AI adjust prices dynamically based on factors such as demand, competition, and inventory levels.
• Amazon offers a dynamic pricing tool for sellers, enabling them to set a personalized dynamic pricing strategy.
• Amazon also automates email messages of similar products or  frequently bought products that meet a customer's preferences and buying price points.

This strategy helps Amazon maximize sales and profitability by offering competitive prices and personalized pricing strategies to different customer segments.

Key results

Dynamic pricing is a game-changer for Amazon, leading to:

• Increased revenue
• Improved customer retention
• Competitive advantage

By leveraging predictive analytics powered by data, machine learning, and AI, Amazon gains a competitive edge in adjusting prices in real-time according to market demand, stock levels, and user behavior. This data-driven approach allows Amazon to maximize sales and optimize revenue effectively.

Amazon's ability to adjust prices multiple times a day gives them a significant advantage in reminding shoppers about price changes for items in their basket that haven't been purchased yet. This proactive approach ensures that customers are aware of any price drops or increases, ultimately increasing the likelihood of completing the purchase.

Read the full case study.

Chatbots and virtual assistants

FedEx has successfully implemented AI-powered virtual assistants to enhance customer service and operational efficiency. Here are a few key examples:

FedEx's AI-Powered Virtual Assistant, Nina

FedEx has implemented an AI-powered virtual assistant named Nina across their global web pages. Nina is accessible in 15 languages and 79 countries and has successfully conducted over 6.7 million conversations in North America alone. With an outstanding first contact resolution rate of 80%-81%, Nina has made a significant impact on customer service by swiftly providing responses and efficiently managing routine inquiries.

Improving Customer Experience

FedEx's virtual assistant, Nina, is specifically designed to offer immediate support, minimizing wait times and enhancing customer satisfaction. Nina plays a pivotal role in assisting customers with a range of tasks, including package tracking, answering frequently asked questions, and offering valuable shipping advice. This proactive approach ensures that customers receive timely and valuable assistance.

Case Study Highlights

• Global Reach: Deployed across 79+ countries in 15 languages.
• High Interaction Volume: Handled over 6.7 million conversations in North America.
• Efficiency: Achieved an 80%-81% first contact resolution rate, enhancing customer satisfaction and reducing the burden on human agents​.

Read the full case study.

Conclusion

An increasing number of businesses are relying on the integration of extensive data, machine learning, predictive analytics, and AI algorithms to maintain a competitive edge. If you're still not convinced read Transformative Marketing research - the future of marketing.

Are you ready to dive in?

If any of these case studies have sparked inspiration and you would like to delve deeper into our data management, machine learning and predictive analytics offerings, we invite you to contact us.