How do you make sure Seezar can understand and help different types of customers? What is the core of the product from a data perspective?<\/strong><\/p>\n\n\n\n Seezar works in two main ways. First, it acts as a smart assistant that understands each customer’s unique needs. When someone starts chatting with Seezar, it creates a profile of who they are and what they’re looking for. Then, using our recommendation engine, it suggests cars that best match their requirements.<\/p>\n\n\n\n But there’s more to Seezar than just chatting with customers. It also helps dealerships by gathering valuable information about potential buyers (leads) and providing insights about their car inventory. After each conversation, Seezar analyzes the interaction to help dealerships better understand their customers’ needs and manage their stock more effectively.<\/p>\n\n\n\n From a data perspective, the core of Seezar is built on two key components: our advanced recommendation engine that matches customers with the right vehicles, and our analytics system that processes conversation data to provide valuable insights to dealerships. These components work together to create a powerful tool that benefits both customers and dealers.<\/p>\n\n\n\n What information does Seezar use to respond to customers? What are the data sources that it uses, and how does it come up with the answers?<\/strong><\/p>\n\n\n\n Seezar processes customer inquiries using two primary data sources. First, it accesses a comprehensive inventory database that contains detailed information about all available vehicles. This allows Seezar to handle what we call “inventory queries” – questions about specific cars or requests for recommendations based on customer needs (like “I’m a family man with three kids and a dog, what car would suit me?”).<\/p>\n\n\n\n Second, Seezar maintains a sophisticated FAQ database containing information about dealership operations, locations, services, and policies. This handles what we call “generic queries” – standard questions about the dealership’s business operations.<\/p>\n\n\n\n To generate responses, Seezar employs a complex system of specialized agents and tools. When a customer asks a question, our natural language processing system first categorizes the query type. Then, it routes the question to the appropriate agent – either the inventory recommendation engine for car-related queries or the FAQ system for general information. For inventory queries, Seezar can create detailed responses with carousel displays of relevant vehicles, while FAQ queries receive clear and accurate responses based on the information Seezar has been trained with.<\/p>\n\n\n\n To ensure accuracy and continuous improvement, we’ve implemented a feedback system that tracks customer satisfaction with responses. This helps us refine our algorithms and improve the quality of Seezar’s interactions over time.<\/p>\n\n\n\n What kind of pain points does Seezar aim to solve?<\/p>\n\n\n\n Seezar solves three major pain points in the automotive industry. First, dealerships struggle with lead generation and management – Seezar helps by creating an efficient sales funnel that connects buyers with vehicles. Second, dealers face challenges with inventory management. When cars sit in stock for too long (3-4 months) or certain brands need more attention, Seezar can help prioritize these vehicles in recommendations, helping dealers move their inventory more strategically.<\/p>\n\n\n\n Third, customers often struggle to find the right car for their needs. Seezar addresses this by creating detailed customer personas from their conversations with the bot. By analyzing their interactions and preferences, we can match them with the most suitable vehicles, making the car-buying process more efficient for everyone involved. This creates an intelligent system where dealers can optimize their inventory while customers receive personalized, relevant recommendations – all while maintaining a natural, helpful interaction.<\/p>\n\n\n\n The car market changes pretty quickly\u2014how does Seezar keep up with all these changes? What happens when customer needs shifts, and there might be new offers by the dealerships?<\/strong><\/p>\n\n\n\n Seezar stays up-to-date with market changes in two main ways. First, whenever there are changes in dealership inventory – like when a car is sold or a new one is added – Seezar receives immediate notifications. This allows us to retrain the bot right away to ensure customers always get accurate information.<\/p>\n\n\n\n Second, we’ve developed a smart monitoring system that regularly checks dealership websites multiple times per day. When new offers appear (like during Ramadan) or when any information changes, our system detects these updates automatically. Even if dealers don’t directly inform us about changes, Seezar can spot updates in their FAQs and website content, ensuring customers always receive the most current information.<\/p>\n\n\n\n What were the biggest challenges you faced while developing Seezar, and what advice would you give to someone facing similar challenges?<\/strong><\/p>\n\n\n\n One of our biggest challenges was protecting Seezar from misuse. When developing an AI assistant, you need to be prepared for users who might try to use it for non-intended purposes. We solved this by implementing a smart classification system that identifies the type of questions being asked.<\/p>\n\n\n\n When Seezar detects a question that’s not related to automotive topics, it doesn’t process the request through its main system. Instead, it responds with a simple message explaining that it’s an automotive assistant and can only help with car-related queries. This approach has proven very effective in preventing what we call “prompt injection” – attempts to make the AI do things it wasn’t designed for.<\/p>\n\n\n\n My main advice for others facing similar challenges would be to implement these protective measures early in development. It’s much easier to build these safeguards from the start rather than adding them later. Also, having a robust system to classify different types of questions is crucial for maintaining the focus and effectiveness of your AI assistant.<\/p>\n\n\n\n How do you measure if Seezar is actually helping dealerships and their customers? What are some KPIs you look out for?<\/strong><\/p>\n\n\n\n We measure Seezar’s effectiveness through two main approaches. First, we collect direct user feedback through a simple thumbs-up\/down system. When users give a thumbs down, we provide them with structured options to tell us what went wrong – whether it was an accuracy issue, slow response time, or something else. This helps us continuously improve the service.<\/p>\n\n\n\n Second, we analyze conversation data to provide valuable insights to dealerships. For example, we track which types of vehicles customers are most interested in – if we notice a surge in SUV-related queries, we can advise dealers to adjust their inventory accordingly. We also monitor how many customers ask about services, dealership locations, and operating hours, giving dealers a clear picture of what information their customers need most. This combination of direct feedback and conversation analysis helps us ensure Seezar is delivering real value to both customers and dealerships while highlighting areas where we can make improvements.<\/p>\n\n\n\n As director of data, how do you balance technical data analysis with real-world business understanding? How do you combine data insights with customer and dealership needs?<\/strong><\/p>\n\n\n\n As Director of Data, my approach is to focus on making complex data insights simple and actionable for our clients. Instead of overwhelming them with technical details, we present information in ways that directly address their business needs. For example, we developed a “Car Attractiveness Score” that helps dealers understand how well each vehicle performs in their inventory. When we identify cars with lower attractiveness scores, we provide practical recommendations, such as adjusting advertising strategies to increase visibility and interest.<\/p>\n\n\n\n I encourage my team to think beyond just building technical solutions. We focus on solving real business challenges: helping dealers retain customers, optimize their inventory, attract more potential buyers, and ultimately sell more cars. This business-first mindset guides everything we do, from coding to presenting insights. Data analysis is most valuable when it translates into actionable business decisions. We regularly monitor key metrics like inventory turnover rates, customer engagement levels, and sales conversion rates. This data helps dealers make informed decisions about stock management, marketing strategies, and customer service improvements. <\/p>\n\n\n\n The key is maintaining a balance between technical excellence and practical application. While we use sophisticated data analysis tools and techniques behind the scenes, our focus is always on delivering insights that dealers can understand and act upon immediately to improve their business outcomes.<\/p>\n\n\n\n How do you balance AI capabilities with unique dealership needs, considering that different businesses require different insights and face different challenges?<\/strong><\/p>\n\n\n\n Customizing Seezar for different dealerships is now a seamless process. We offer multiple ways for dealers to personalize their experiences. Dealers can make basic customizations directly through their dashboard. They can provide specific instructions like “A: Promote SUVs more”, “B: Focus on luxury vehicles”, or “C: Highlight eco-friendly options” – either by working with our team or by programming the bot themselves.<\/p>\n\n\n\n We’ve also made Seezar more adaptable to local markets. Dealers can customize the bot’s name, personality, and communication style. For example, they can adjust how formal or casual the bot sounds, or even modify its accent to better connect with their target audience. This flexibility ensures that each dealership gets a virtual assistant that truly matches their brand and meets their unique business needs.<\/p>\n\n\n\n When Seezar works with different dealerships, how do you make sure it stays flexible while personalized customer experiences, while being able to understand different types of questions?<\/strong><\/p>\n\n\n\n We ensure Seezar remains flexible and personalized through three key approaches. First, we analyze historical data through post-processing to understand patterns in customer interactions. This helps us continuously improve the bot’s responses based on what has worked well in the past.<\/p>\n\n\n\n Second, we’ve developed “bot awareness” – which means Seezar always knows the current date and time. This is crucial for handling time-sensitive requests, like when a customer wants to schedule a service appointment several weeks in advance. Third, and most importantly, Seezar builds a detailed understanding of each customer through their conversations. As customers interact with the bot, it learns their preferences – such as their budget, preferred car types, and fuel preferences. This allows us to provide highly personalized recommendations and responses that truly match each customer’s needs.<\/p>\n\n\n\n What’s the biggest misconception people have about AI-powered tools like Seezar? Perhaps from a data POV?<\/strong><\/p>\n\n\n\n The biggest misconception about AI tools like Seezar is that they work like traditional chatbots with simple if-this-then-that decision trees. In reality, modern AI systems like Seezar use what we call Generative AI, which is much more sophisticated but also comes with its own challenges. Think of it this way: Generative AI is like advanced statistics that can understand and generate human-like responses. While this makes it very powerful, it also means the AI can sometimes “hallucinate” – providing information that isn’t entirely accurate. This is why we’ve put several safeguards in place.<\/p>\n\n\n\n We manage this challenge in three ways. First, we carefully control how creative the AI can be by adjusting settings like “temperature” which is a parameter used to adjust the output of the LLM (Large Language Model). Second, we always have backup systems in place in case our primary AI service has issues. Third, we use different LLMs depending on the task – simpler AI for basic questions like FAQs and more advanced AI for complex queries like finding specific cars with detailed criteria.<\/p>\n\n\n\n Looking ahead, what emerging technologies and innovations are you exploring to enhance Seezar’s capabilities, and what’s your vision for its future?<\/strong><\/p>\n\n\n\n We’re working on making Seezar more advanced and versatile in several exciting ways. First, we’re developing multimodal capabilities, which means Seezar will be able to understand and interact through both speech and visual inputs. This will make the experience more natural and user-friendly.<\/p>\n\n\n\n Beyond our current automotive focus, we’re also developing an innovative tool called the profit bot. This advanced system helps dealership executives analyze business performance without needing to consult a BI analyst. For example, executives can ask questions like “Which dealership had the highest profit margin last month?” or “How did our showrooms perform in terms of sales?” and get detailed answers with explanations.<\/p>\n\n\n\n Looking further ahead, our vision is to expand these capabilities beyond just data analysis. We’re working on features that will allow our AI to act more like a personal assistant – taking notes, handling various tasks, and providing support across different industries. The goal is to create a truly versatile AI assistant that can adapt to various business needs while maintaining the same level of expertise and efficiency we’ve achieved in the automotive sector.<\/p>\n\n\n\n What do you see the ecosystem evolving into? Many people are concerned about job security across industries. What impact do you think AI will have on the future?<\/strong><\/p>\n\n\n\n While there are valid concerns about AI’s impact on certain roles like BI analysts and data scientists, I believe AI is ultimately here to empower rather than replace workers. In my experience leading a data team, AI tools have actually made us more efficient – without them, we’d need about 20% more staff to handle our current workload. We’ve successfully integrated AI tools and modern coding capabilities to enhance our team’s effectiveness.<\/p>\n\n\n\n However, it’s important to note that AI has limitations. While it can help start projects and provide initial analysis, you still need human expertise to guide the process and make final decisions. The human element remains crucial for understanding context, making strategic decisions, and ensuring quality outcomes.<\/p>\n\n\n\n Looking ahead, I believe the next frontier in AI will be “agents” – AI systems that can handle complex, multi-step tasks. Unlike concepts like AGI (Artificial General Intelligence) or ASI (Artificial Super Intelligence), agents are practical tools that can already help with time-consuming tasks like web research or form filling. These capabilities are evolving rapidly, and I expect we’ll see significant advances in this area within the next six months and my answer will most likely change at that time.<\/p>\n\n\n\n What other industries do you think would benefit from something like Seezar?<\/strong><\/p>\n\n\n\n The great thing about Seezar’s technology is that it can be adapted for almost any industry. The core components – recommendation engine, virtual assistant, and data analysis tools – can be customized to serve different business needs. For example, the same technology that helps match customers with cars could help shoppers find the perfect furniture, or help patients find the right healthcare provider. The profit bot, which analyzes business performance, could be valuable for any industry that tracks profits and metrics. Whether it’s retail, healthcare, real estate, or education, any sector that involves customer service and data analysis could benefit from this type of AI solution.<\/p>\n\n\n\n Dimitri’s final \u2018brake\u2019 down:<\/strong><\/p>\n\n\n\n Looking back at our work with Seezar, I’m continually impressed by how we’ve revolutionized the car-buying experience through data-driven AI. What started as an experiment to create more meaningful customer interactions has now become a powerful tool that’s fundamentally changing the relationship between dealerships and their customers.<\/p>\n\n\n\n Seezar’s success comes from balancing advanced AI capabilities with practical business needs. Our system manages complex conversations, maintains brand integrity, and integrates seamlessly with dealer systems, making it an invaluable tool for both dealerships and customers.<\/p>\n\n\n\n Looking ahead, I’m excited to see how Seezar continues to enhance the human element in automotive retail, creating more efficient, personalized experiences that benefit the entire automotive ecosystem.<\/p>\n\n\n\nPart 2: How AI Chatbots Transform Information into Real-World Results<\/h2>\n\n\n\n
Part 3: How We Ensure Data Accuracy and Speed at Every Stage<\/h2>\n\n\n\n
Part 4: Future of AI Virtual Assistants: What to Expect?<\/h2>\n\n\n\n
\n\n\n\nWatch the full interview:<\/h5>\n\n\n\n