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    Home»Development»Databases»Driving Retail Loyalty with MongoDB and Cognigy

    Driving Retail Loyalty with MongoDB and Cognigy

    April 10, 2025
    Driving Retail Loyalty with MongoDB and Cognigy

    Retail is one of the fastest moving industries, often the very first to leverage cutting-edge AI to create next-gen experiences for their customers. One of the latest areas we’re seeing retailers invest in is agentic AI: they are creating conversational chatbot “agents” that are pulling real-time information from their systems, using Natural Language processing to create conversational responses to customer queries, and then taking action- completing tasks and solving problems.

    In this race to stay ahead of their competition, retailers today are struggling to quickly bring to market these agents and don’t always have the AI skills in-house. Many are looking to the broad ecosystem of off-the-shelf solutions to leverage the best of what’s already out there—reducing time to market for their AI agents and leaving the AI models and integrations to the experts in the field.

    Some of the most successful retail conversational AI agents we’ve seen are built on Cognigy, a global leader in customer service solutions. With Cognigy, retailers are quickly spinning up conversational AI agents on top of their MongoDB data to create personalized conversational experiences that not only meet but anticipate customer expectations. Increasingly, whether or not retailers offer customers immediate, seamless interactions are key to retaining their loyalty.

    Illustration depicting a retail app

    Why next-gen conversational AI matters in retail

    Customer loyalty has been declining yearly, and customers are moving to retailers who can provide an elevated experience at every interaction. According to HubSpot’s 2024 annual customer service survey, 90% of customers expect an immediate response to their inquiries, highlighting how speed has become a critical factor in customer satisfaction. Additionally, 45.9% of business leaders prioritize improving customer experience over product and pricing, demonstrating that in retail, speed and personalization are no longer optional as they define whether a customer stays or moves on.

    The chatbots of the past that relied on simple rules-based engines and static data don’t meet these customers’ new expectations as they lack real-time business context, and can generate misleading answers as they’re not training on the retailer’s in-house data sets.

    This is where Cognigy’s AI agents can create a more compelling experience: These intelligent systems integrate real-time business data with the capabilities of LLMs, enabling AI-driven experiences that are not only personalized but also precise and controlled. Instead of leaving responses open to interpretation, retailers can customize interactions, guide users through processes, and ensure AI-driven recommendations align with actual inventory, customer history, and business rules. This level of contextual understanding and action creates trust-driven experiences that foster loyalty.

    Having quality data and the ability to harness it effectively is the only way to meet the strategic imperatives that customers demand today. This requires key factors such as being fast, flexible, and high-performing at the scale of your business operations, as winning companies must store and manage their information efficiently. This is where MongoDB, a general-purpose database, truly shines. It is designed to manage your constantly evolving business data, such as inventory, orders, transaction history, and user preferences. MongoDB’s document model stands out in the retail industry, offering the flexibility and scalability businesses need to thrive in today’s fast-paced environment.

    Cognigy can use this real-time operational data from MongoDB as a direct input to build, run, and deploy conversational AI agents at scale. With just a few clicks, businesses can create AI-driven chatbots and voice agents powered by large language models (LLMs), following their business workflows in a smooth and easy-to-implement way. These agents can seamlessly engage with customers across various phone lines as a major driver for customer interactions, including website chat, Facebook Messenger, and WhatsApp, offering personalized interactions. On the back end, Cognigy is built on MongoDB as its operational data store, taking full advantage of MongoDB’s scalability and high performance to ensure that its conversational AI systems can efficiently process and store large volumes of real-time data while maintaining high availability and reliability.

    The power of combining AI agents with real-time business data transforms personalization from a static concept into a dynamic ever-evolving experience that makes customers feel truly recognized and understood at every touchpoint. By harnessing these intelligent systems, retailers can go beyond generic interactions to deliver seamless, relevant, and engaging experiences that naturally strengthen customer relationships. Ultimately, true personalization isn’t just about efficiency; it’s about creating meaningful connections that drive lasting customer engagement and loyalty.

    Let’s look at how this looks in the Cognigy interface when you’re creating a flow for your chatbot:

    What’s happening behind the scenes?

    Figure 1 below shows an example customer journey, and demonstrates how Cognigy and MongoDB work together to use real-time data to give reliable and conversational responses to customer questions:

    Figure 1. An Agentic AI conversational flow with Cognigy pulling user and order data from MongoDB
    This image is a diagram showing an agentic AI conversation flow with Cognigy pulling user and order data from MongoDB. At the bottom left, step 1 is a user connecting to an application and asking when the delivery date will be. That request is sent to Cognigy AI, which pulls the order data from MongoDB. The order update is then confirmed with the distribution center, and then sent back to Cognigy AI. The AI then runs the prompt plus the answer through an LLM, which generates the response that is sent back to the user.

    This user’s journey starts when they make a purchase on a retailer’s ecommerce application. The platform securely stores the order details, including product information, customer data, and order status, in MongoDB.

    To coordinate the delivery, the user reaches out via a chatbot or phone conversation orchestrated by Cognigy AI agents, using advanced Large Language Models (LLMs) to understand the user’s inquiries and respond in a natural, conversational tone.

    The AI agent retrieves the necessary user information and order details from MongoDB, configured as the data source, taking real-time data that is always up to date. By understanding the user’s query, the agent retrieves the appropriate database information and is also able to update the database with any relevant information generated during the conversation, such as modifying a delivery appointment.

    As the user schedules their delivery, Cognigy updates the information directly in MongoDB, leveraging features like triggers and change streams to seamlessly synchronize real-time data with other key systems in the customer journey, such as inventory management and delivery providers. This ensures personalized user experiences at every interaction.

    Shaping the future of customer service with MongoDB and Cognigy

    Delivering responsive, personalized customer service is more essential than ever. By combining MongoDB’s flexible, versatile, and performant data management with Cognigy’s powerful conversational AI, businesses can create seamless, real-time interactions that keep customers engaged. The future of customer service is fast, dynamic, and seamlessly integrated into business operations.

    With MongoDB and Cognigy, organizations can harness the power of AI to automate and personalize customer interactions in real time, without the need for extensive development efforts. The MongoDB-Cognigy integration enables businesses to scale context-driven interactions, strengthen customer relationships, and exceed expectations while building lasting customer loyalty.

    Learn more about how Cognigy built a leading conversational AI solution with MongoDB on our customer story page.

    Needing a solution for your retail needs? Head over to our retail solutions page to learn how MongoDB supports retail innovation.

    Read our blog to learn how to enhance retail solutions with retrieval-augmented generation (RAG).

    Source: Read More

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