In this interview between CloudTweaks and Edwin Miller, CEO of Marchex, the discussion explores AI’s role in bridging data silos in multi-cloud environments to improve decision-making and customer engagement. Edwin highlights how cloud-enabled conversational intelligence scales AI insights, reduces operational bottlenecks, and enhances business agility. He also shares predictions on how AI advancements will reshape industries like healthcare, automotive, and SMBs by enabling smarter interactions and data-driven strategies. The interview offers valuable insights into the future of AI and cloud integration.
How is AI revolutionizing aspects of business today?
Conversational intelligence is transforming the way companies engage with their customers. By leveraging AI, businesses can better understand and enhance customer interactions, streamline processes, and simplify complex issues.
While AI provides deeper insights and automates many tasks, human involvement remains essential. For instance, instead of requiring a large team to listen to calls, AI can process and analyze those interactions, enabling a few individuals to focus on the key insights generated.
Although the technology is not fully mature yet, it is evolving rapidly. AI has the potential to make customer service interactions more natural and human-like. However, many people still prefer speaking directly to a person. For now, chatbots and AI-driven systems cannot completely replicate human interactions, but generative AI is on track to revolutionize these capabilities.
AI models are generally capable of handling a wide range of customer queries, generating personalized responses, and predicting some customer outcomes. However, for industries to truly benefit, it’s crucial to leverage AI solutions that have been trained on the nuances and data associated with each vertical market. This is where predictive and prescriptive analytics will best enhance customer interactions and improve experiences and outcomes. This is where Marchex excels.
How do you see the speed of business being affected by AI?
AI is accelerating the pace of business significantly. This evolution mirrors past technological advancements, such as transitioning from manual CRM systems to Web 1.0, 2.0, and now Web 3.0. Each step has made it easier to connect with others, and AI will continue this trend.
AI will influence who we connect with, how we connect, and interpret and respond to information. For example, during a call with a client, AI can provide real-time data and suggested responses, enhancing communication efficiency. While this reduces manual input, maintaining a human element remains vital for successful interactions.
AI’s ability to quickly analyze and serve relevant data is a game changer. Whether through typing or voice input, technology is bridging communication gaps. However, it is crucial to balance reliance on technology with personal skills like critical thinking and thoughtful communication.
Additionally, they ability to take unstructured data from a call, text, email, the web, and other areas, if the 1st party data harnesses AI to continually refine the Large Language Model, prescriptive analytics will become a reality.
Additional thoughts on AI and human potential?
AI can significantly enhance human capabilities, but over-reliance may weaken individual skills. For example, people who rely entirely on technology for writing or communication might lose their ability to express thoughts thoughtfully. Now, some would espouse that this is simply the evolution of technology that we have seen throughout the years. There needs to be a balance in this area.
AI is incredibly powerful—it processes and analyzes data at lightning speed, offering solutions humans may struggle to achieve. However, technology should be viewed as a tool to complement human abilities, not replace them.
To truly thrive in an AI-driven world, individuals must remain engaged and proactive, leveraging AI as a resource while continuing to develop their own expertise and leadership skills. Leaders who strike this balance will be better positioned for success in any industry.
What about the advancements? What about the advancements of that to customer experience and customer engagement? How?
AI is revolutionizing customer service and engagement. Its speed and ability to handle complex tasks allow businesses to streamline operations and improve efficiency. People in any role within a company will benefit from AI’s capacity to simplify and enhance processes, much like how athletes improve with better coaching and tools.
Take conversational AI as an example. It’s making interactions more natural and human-like. While the technology isn’t fully there yet, the advancements are undeniable. Today, customers often encounter chatbots on websites, which, while helpful, can’t always replace human interaction. If you manage to reach a human, your issue is typically resolved faster than with a chatbot.
For companies, chatbots save costs and handle a wide range of customer queries. They’re improving rapidly, learning from each interaction, and becoming more competent. However, they don’t always solve customer problems fully. AI’s predictive capabilities anticipate what might happen next and are a step ahead of reactive human responses. This evolution will eventually lead to improved customer satisfaction and engagement, though we’re not quite there yet.
How is AI helping streamline businesses to make more informed decisions based on their data to improve customer experience?
AI is breaking down silos and creating integrated data views that provide businesses with actionable insights. For example, AI and machine learning can analyze phone calls differently than humans. Instead of relying on manual CRM entries, AI can extract insights directly from conversations across various touchpoints in the customer journey.
Imagine a customer’s experience with a car dealership—from the first call to purchasing and servicing the car. AI can seamlessly analyze and connect these interactions. It validates data and provides a unified view, automating processes and enabling real-time insights. At Marchex, we call this “Marchex-as-a-service,” leveraging APIs, CRM, and CDP integrations to deliver unparalleled insights into customer journeys.
This approach allows businesses to understand their customers’ actions and anticipate future needs, improving customer experience in a highly efficient way. AI simplifies data analysis and ensures decisions are informed by accurate, comprehensive information.
Have you had organizations that are Marchex clients that see the data produced in this fashion and actually create new processes or change processes at the granular level?
Absolutely. Some of our Fortune 500 clients are leveraging AI to refine existing processes and develop new ones. Using AI models and LLMs, they can make prescriptive decisions and forecast scenarios for the next 18 to 36 months.
For example, in the EV market, clients analyze data to predict who will buy, in which territories, at what price, and what parts will be needed. On a granular level, they use AI insights to determine where to focus training efforts. For instance, if a dealership isn’t performing well, AI can analyze calls or text threads to identify specific issues and help trainers address them.
When I joined Marchex, we relied heavily on human listeners to analyze conversations. Now, with AI, much of that work is automated. Trainers can access best-in-class benchmarks faster and tailor their coaching to specific regions, territories, or dealerships.
What’s even more exciting is our move toward normalizing the data. Instead of having data silos tied to individual brands—like GM, Ford, or Audi—we’re creating benchmarks across the entire industry. This intelligent, normalized data allows us to deliver industry-wide insights and benchmarks in seconds, empowering our clients to make better, faster decisions.
How do organizations leverage cloud and multi-cloud platforms for conversational AI?
The shift from legacy systems to cloud platforms like Microsoft Azure underscores the revolutionary potential of modern cloud environments. Multi-cloud architectures, in particular, are redefining how organizations approach scalability, security, and compliance. These architectures enable rapid server deployment within minutes, a stark contrast to the delays of traditional setups.
By enhancing development speed and simplifying processes, multi-cloud platforms empower businesses to align with contemporary coding practices, accelerating the delivery of AI-driven solutions. Additionally, the distributed processing capabilities of multi-cloud setups support the efficient and rapid deployment of conversational AI technologies, ensuring seamless performance even in high-demand scenarios.
This approach modernizes infrastructure and enables organizations to stay agile, responsive, and innovative in the fast-evolving AI landscape.
What will the impact of conversational AI be in the healthcare and automotive sectors?
Conversational AI significantly improves customer interactions by enabling tailored recommendations, streamlining administrative tasks, and enhancing operational efficiency:
- Healthcare: Virtual health assistants facilitate quicker patient interactions and inform clinicians in real-time, reducing administrative burdens and improving care delivery.
- Automotive: Personalized recommendations guide customers’ journeys without human intervention, leveraging insights from millions of analyzed conversations to refine service delivery.
What are the key considerations for implementing conversational intelligence in regulated industries?
When deploying conversational intelligence, compliance, and data security are paramount:
- Regulatory Adherence: Ensuring alignment with industry and regional compliance frameworks is critical, especially in global markets.
- Data Privacy and Security: Protecting sensitive customer interactions demands robust cloud-based systems with secure configurations.
- Integration Challenges: Seamlessly integrating APIs and maintaining system integrity across platforms ensure consistent customer experiences.
Challenges like fragmented communication channels and limited system integration hinder scalability. Solutions include:
- Centralized Data Management: Ensuring all customer interactions, including unstructured conversational data, are captured and integrated into unified systems like CDPs.
- AI-Powered Insights: Leveraging AI to analyze and correlate data across regions and touchpoints, enabling actionable insights for dealerships and service providers.
- Workforce Enablement: Providing dealerships with intuitive tools and processes to bridge expertise gaps and deliver efficient service.
With consumer research cycles shortening dramatically (from 30 days to seven to eight days), businesses must adapt by deploying conversational intelligence that captures digital and unstructured data footprints. This readiness ensures competitive responsiveness, aligning business capabilities with empowered consumer behaviors.
Do you foresee legislation impacting conversational intelligence or AI development in the near future?
The focus will primarily be on ethics and responsible data use. Regulators will likely introduce audits to ensure ethical practices in capturing and leveraging conversational data. We could see parallels to Sarbanes-Oxley regulations, where compliance went overboard before settling into a balanced framework. Similarly, AI oversight must avoid overregulation but cannot leave critical aspects unchecked. Ensuring ethical AI practices will be a cornerstone of future frameworks.
Are specific sectors more likely to be affected?
Due to the sensitive nature of the data they handle, healthcare and finance are the most likely candidates for early and stringent regulations. However, companies adopting AI responsibly, like Marchex, are continuously optimizing their processes to stay ahead in compliance and efficiency. Striking the right balance in regulation is essential to protecting consumers while fostering innovation.
How will conversational AI shape personalized marketing and customer journeys?
Conversational AI drives deeper customer engagement and improves conversion rates by unlocking AI-driven insights. It enables businesses to view customer journeys better, not based on assumptions but on real data. This understanding empowers companies to optimize their marketing, operations, investments, and training strategies, bringing incredible precision to customer experience. We’re at a transformational moment where AI significantly accelerates this evolution, helping organizations act in milliseconds rather than months.
How are Marchex’s solutions leveraging AI to enhance customer experience?
Our customers frequently highlight the innovation we bring to the table. One example is our Sentiment Suite, which provides emotional analysis to understand nuanced customer dynamics better. Even in mixed-emotion scenarios, where a customer is upset with a product but satisfied with the service, our AI captures these complexities, offering actionable insights for training and operational improvements.
We go beyond just conversation analytics. Our solutions encompass the entire customer journey—integrating omnichannel data like Google ad clicks, Yelp reviews, web interactions, and phone calls. This real-time intelligence enables businesses to adapt quickly, from marketing to supply chain management, unlocking significant value across industries.
How is conversational intelligence changing business fundamentals?
Conversational intelligence fundamentally reshapes businesses, from the boardroom to the sales floor. For example, by capturing emotional and topical data early in customer interactions, companies can predict demand, adjust their supply chains in real time, and refine their marketing strategies.
With Marchex, this is not limited to call data—it spans omnichannel inputs, creating a holistic and actionable view of customer journeys. This is the future of intelligent business strategy, enabling companies to make daily decisions with precision rather than waiting for quarterly reports.
By Randy Ferguson