Joscha, would you mind sharing with us some insights into your professional journey and how you arrived at your current role as Head of Product at Connectly.ai?

My path to the tech industry and product management took a bit of an unconventional route. My introduction to product development started in the hair care sector, where I had the opportunity to dive deep into human needs and master the art of user-centric design. When I found myself looking for a more dynamic environment, I embarked on a nearly decade-long journey at Google.

I began in sales and gained invaluable insights into customer pain points and the intricacies of building relationships. This then laid the groundwork for my transition into a product role within the Ads organization at Google.

After my time at Google, I took a leap into the unknown and joined Connectly as the fourth employee—a decision fueled by the thrill of building something from the ground up.. Today, we have a global team of more than 50, we partner with category-defining customers, and we are pushing the boundaries of AI research and product development. I couldn’t be more excited about where we’re headed next.

How does RAG revolutionize customer interaction and business intelligence in sales, with a special emphasis on the critical aspects of accuracy and timeliness of information?

By combining a generative model with a retrieval system, Retrieval-Augmented Generation (RAG) enhances AI responses with accurate, current data. 

Large Language Models (LLMs) in a production environment are constrained by their static datasets, and often lack in accuracy and timeliness. However, RAG introduces a dynamic component that leverages real-time external databases. This ensures that every piece of information it provides or action it recommends is grounded in the latest available data.

As the Head of Product at Connectly.ai, how do you foresee integrating RAG technology into your product offerings to enhance customer experiences and sales effectiveness?

RAG is one part of a cohesive AI strategy. At Connectly we also found that we had to start training our own embeddings as well as models to help make our AI Sales Assistant efficient, fast and reliable.

Traditional AI models often encounter challenges with stale data sets and complex queries. How does RAG address these limitations, and what advantages does it bring to AI systems in terms of improving responsiveness and relevance of information?

Complex queries that would stump earlier AI models are now within reach with enhanced query resolution. By employing sophisticated retrieval systems to gather data from numerous sources, RAG can dissect and respond to multifaceted questions in a nuanced way that was previously unachieveable. 

Additionally, RAG has the capability to pull in and analyze data from diverse sources in real-time, which transforms it into a powerful tool for market analysis. This can then equip businesses and leaders with the agility to adapt to market shifts with insights derived from the most current data, offering a hard-to-match competitive edge.

Could you kindly elaborate on how Connectly.ai is leveraging RAG to enhance its AI sales assistants and provide more personalized and contextually relevant interactions for users?

Of course! RAG is one part of the AI sales assistant that we have built. Businesses share their product catalog with Connectly to inform our sales assistant. This product catalog can have many million products with different variants. The inventory and prices might change on a daily basis. In order to provide the end customer with real time and reliable data, we leverage RAG as part of our architecture.

In your esteemed experience, what key considerations or best practices should companies keep in mind when seeking to enhance their AI models with technologies like RAG to create better customer experiences?

I would recommend starting with a narrow use case first and learn from there. In our case we had to learn the hard way that, for example, offering a multi language product from the start came with many hurdles. Clothes sizing for example can be different from country to country. English makes up more than 40% of common crawl data, so language embeddings and foundational models will work better in English first.  

What personal strategies or approaches do you employ to stay informed about emerging technologies and industry trends, particularly in the realm of AI and customer interaction?

There is so much happening and the AI industry is moving at a crazy pace. I have gathered a list of people I follow on X to stay up to date with some of the latest trends and discussions. I’m also lucky to be living in San Francisco where you will overhear a conversation about AI just about anywhere you go. 

Drawing from your expertise, what valuable advice would you extend to our readers who are interested in implementing RAG or similar technologies to improve their own AI systems and customer interactions?

If you are incorporating AI into your business, I would always start with a design partner in mind who can provide you valuable feedback and insights and is willing to build with you. This can be an external stakeholder like a customer or an internal team. The external validation is extremely helpful and important to help solve actual problems and pain points. 

As we come to the end of our discussion, would you be open to sharing any final thoughts or insights regarding the future of RAG technology and its implications for sales and customer engagement?

There is a lot of interesting discussion around the future of memory in AI. If a sales assistant can remember and learn from all previous conversations it had with a customer, it will evolve into a true personal shopper. 

Finally, Joscha, could you provide us with some insight into what’s next for Connectly.ai and how RAG fits into your broader product roadmap for enhancing customer experiences?

We have a lot of exciting launches in the pipeline. We launched our sales assistant, Sofia AI, about 6 months ago and are already partnering with major global brands. One of the new features I am most excited about is our continued work on AI insights from the conversations customers are having with our sales assistant. These insights can be imported directly into a CRM and help our businesses truly understand their customers. Previously this would have only been possible by interviewing every member in the Sales staff.

Joscha Koepke

Head of Product at Connectly.ai

Joscha Koepke is Head of Product at Connectly. As part of the company’s founding team, he leads the product team in building and innovating its AI-powered conversational commerce platform, which enables businesses to operate the full flywheel – marketing, sales, transactions, customer experience – all within the customer’s thread of choice. Prior to Connectly, Joscha was a Global Product Lead for Google, leading the product & go-to-market strategy of emerging online-to-offline ad format products across Search, Display, YouTube, & Google Maps. 

The post AITech Interview with Joscha Koepke, Head of Product at Connectly.ai first appeared on AI-Tech Park.

Bernard, kindly brief us about Generative AI and its impact on various industries such as retail, healthcare, finance, education, manufacturing, marketing, entertainment, sports, coding, and more?

Generative AI (GenAI) is revolutionizing multiple sectors by enabling the creation of new, original content and insights. In retail, it’s personalizing shopping experiences; in healthcare, it’s accelerating drug discovery and patient care customization. Finance is seeing more accurate predictive models, while education benefits from tailored learning materials. Manufacturing, marketing, entertainment, sports, and coding are all experiencing unprecedented innovation and efficiency improvements, showcasing GenAI’s versatility and transformative potential.

Your latest book, “Generative AI in Practice,” is set to release soon. Could you share some key insights from the book, including how readers can implement GenAI, its differences from traditional AI, and the generative AI tools highlighted in the appendix?

In “Generative AI in Practice,” I explore how GenAI differs fundamentally from traditional AI by its ability to generate novel content and solutions. The book offers practical guidance on implementing GenAI, highlighting various tools and platforms in the appendix that can kickstart innovation in any organization. It’s designed to demystify GenAI and make it accessible to a broader audience.

With your extensive experience advising organizations like Amazon, Google, Microsoft, and others, what role do you see GenAI playing in transforming business strategies and performance?

It’s clear that Generative AI (GenAI) is poised to become a pivotal element in reshaping business strategies and boosting performance across industries. By leveraging GenAI, companies can gain a significant competitive advantage through the acceleration of innovation, the automation of complex and creative tasks, and the generation of actionable insights. This transformative technology enables businesses to refine their decision-making processes and enhance customer engagement in ways previously unimaginable. As we move forward, the integration of GenAI into core business operations will not only optimize efficiency but also open up new avenues for growth and value creation, marking a new era in the corporate landscape.

Why is Generative AI considered the most powerful technology humans have ever had access to, and what makes it stand out compared to other advancements in the tech industry?

Generative AI not only stands out as perhaps the most potent technology available today due to its capacity for creativity and innovation, surpassing prior tech advancements by enabling machines to understand, innovate, and create alongside humans, but it also offers a pathway to artificial general intelligence (AGI). This potential to achieve AGI, where machines could perform any intellectual task that a human can, marks a significant leap forward. It represents not just an evolution in specific capabilities, but a foundational shift towards creating systems that can learn, adapt, and potentially think with the breadth and depth of human intelligence. This aspect of generative AI not only differentiates it from other technological advancements but also underscores its transformative potential for the future of humanity.

GenAI brings forth unique risks and challenges. Can you discuss how businesses and individuals can navigate these challenges, especially in areas such as misinformation, disinformation, and deepfakes, particularly in an election year?

The unique risks and challenges presented by Generative AI, particularly in the realm of misinformation, disinformation, and the creation of deepfakes, demand a proactive and informed approach, especially during critical times such as election years. Businesses and individuals can navigate these challenges by adopting a commitment to ethical AI use, which includes the development and implementation of policies that emphasize accuracy and integrity. Additionally, investing in and utilizing advanced detection tools that can identify AI-generated misinformation or deepfakes is crucial. Equally important is the cultivation of GenAI literacy, ensuring that users can critically assess the information they encounter and understand its origins. This multi-pronged strategy is essential for safeguarding the informational ecosystem and maintaining public trust in digital content.

The impact of GenAI on the job market is a critical topic. What types of work do you anticipate being replaced or significantly altered by this groundbreaking technology, and how can individuals prepare for these changes?

The advent of Generative AI is set to significantly reshape the job market, introducing efficiencies that automate routine tasks, which could lead to the displacement of jobs in areas such as data entry, content creation, and customer service. Despite these disruptions, GenAI also promises the emergence of new job categories focused on AI supervision, ethical governance, and the creative industries, reflecting the technology’s dual impact on the workforce. To navigate this evolving landscape, individuals must prioritize lifelong learning and skill development, focusing on areas that AI is unlikely to replicate easily, such as creative problem-solving, emotional intelligence, and ethical decision-making. By adapting to the changes brought about by GenAI, workers can prepare for and thrive in the new job market dynamics it creates.

In your forthcoming book, you touch on how GenAI interacts with other transformative technologies. How do you foresee GenAI collaborating with gene editing, immersive internet, conventional AI, blockchain, quantum computing, etc., to create a world of hyper-innovation?

I explore the transformative potential of Generative AI (GenAI) as it intersects with groundbreaking technologies such as gene editing, the immersive internet, conventional AI, blockchain, and quantum computing, heralding a future of hyper-innovation. GenAI’s capability to produce novel content and solutions enhances gene editing for personalized medicine, enriches the immersive internet with dynamic virtual experiences, and augments conventional AI’s problem-solving abilities. In combination with blockchain, it promises more secure and efficient transaction systems, while its integration with quantum computing could revolutionize our approach to complex challenges, from material science to cryptography. This synergy across technologies suggests a paradigm shift towards a future where the acceleration of breakthroughs across fields from medicine to environmental science could vastly expand the horizons of human capability and knowledge.

Ethical concerns surrounding GenAI, including misinformation and deepfakes, are important considerations. What measures do you believe should be taken to address these concerns and ensure responsible use of Generative AI?

To effectively address the ethical concerns surrounding Generative AI, a multi-faceted approach is essential. This includes establishing transparency in AI development and deployment processes, adhering to rigorous ethical standards that are continuously updated to reflect emerging challenges, and actively engaging the public and stakeholders in discussions about AI’s societal impacts. Furthermore, the development of robust guidelines and regulatory frameworks for responsible AI use is critical, not only to mitigate risks like misinformation and deepfakes but also to foster trust and understanding among users. Such measures should aim to balance innovation with ethical considerations, ensuring GenAI serves the public good while minimizing potential harms.

Everyday activities are expected to be impacted by GenAI. Could you provide examples of how GenAI will influence tasks like searching for information, cooking, and travel in the near future?

Generative AI is poised to revolutionize everyday activities by enhancing efficiency and personalization. In the realm of information search, GenAI can provide more accurate and context-aware results, effectively understanding and anticipating user needs. For cooking, it could offer recipe customization based on dietary preferences, available ingredients, or desired cuisine, making meal planning simpler and more enjoyable. When it comes to travel, GenAI can tailor recommendations for destinations, accommodations, and activities to individual tastes and requirements, simplifying the planning process and enhancing the travel experience. These examples illustrate just a few ways GenAI will make everyday tasks more intuitive, enjoyable, and aligned with personal preferences.

In tracing the evolutionary blueprint of GenAI, from the 1950s to today, what key milestones and developments have played a significant role in shaping its current capabilities and applications?

The journey of Generative AI from its nascent stages in the 1950s to its current state has been marked by several pivotal milestones. The invention of neural networks laid the foundational architecture for AI to process information in a manner akin to the human brain. Subsequent advancements in machine learning algorithms have dramatically improved AI’s ability to learn from data, leading to more sophisticated and capable AI systems. The launch of platforms capable of generating human-like text and understanding natural language has significantly broadened GenAI’s applications, enabling it to write articles, compose music, develop code, and more. These key developments have not only advanced the capabilities of GenAI but also expanded its potential applications, setting the stage for its continued evolution and growing impact on society.

Bernard Marr

CEO and Founder of Bernard Marr & Co.

Bernard Marr is a world-renowned futurist, influencer and thought leader in the fields of business and technology, with a passion for using technology for the good of humanity.

He is a multi-award-winning and internationally best-selling author of over 20 books, writes a regular column for Forbes and advises and works with many of the world’s best-known organisations.

He has a combined following of 4 million people across his social media channels and newsletters and was ranked by LinkedIn as one of the top 5 business influencers in the world.

The post AITech Interview with Bernard Marr, CEO and Founder of Bernard Marr & Co. first appeared on AI-Tech Park.

Table of contents

Introduction
1. Reshaping Customer Engagement With Large Language Models
2. Importance of Knowledge Graphs for Complex Data
3. Embrace Web 3.0 For a Decentralized Future
4. Revolutionizing Business Operations With Virtual Assistants
Conclusion

Introduction

As we have stepped into the realm of 2024, the artificial intelligence and data landscape is growing up for further transformation, which will drive technological advancements and marketing trends and understand enterprises’ needs. The introduction of ChatGPT in 2022 has produced different types of primary and secondary effects on semantic technology, which is helping IT organizations understand the language and its underlying structure. 

For instance, the semantic web and natural language processing (NLP) are both forms of semantic technology, as each has different supportive rules in the data management process.

In this article, we will focus on the top four trends of 2024 that will change the IT landscape in the coming years.

1. Reshaping Customer Engagement With Large Language Models

The interest in large language models (LLMs) technology came to light after the release of ChatGPT in 2022. The current stage of LLMs is marked by the ability to understand and generate human-like text across different subjects and applications. The models are built by using advanced deep-learning (DL) techniques and a vast amount of trained data to provide better customer engagement, operational efficiency, and resource management. 

However, it is important to acknowledge that while these LLM models have a lot of unprecedented potential, ethical considerations such as data privacy and data bias must be addressed proactively.

2. Importance of Knowledge Graphs for Complex Data

The introduction of knowledge graphs (KGs) has become increasingly essential for managing complex data sets as they understand the relationship between different types of information and segregate it accordingly. The merging of LLMs and KGs will improve the abilities and understanding of artificial intelligence (AI) systems. This combination will help in preparing structured presentations that can be used to build more context-aware AI systems, eventually revolutionizing the way we interact with computers and access important information.

As KGs become increasingly digital, IT professionals must address the issues of security and compliance by implementing global data protection regulations and robust security strategies to eliminate the concerns.  

3. Embrace Web 3.0 For a Decentralized Future

The core of Web 3.0 (Web3) lies in three fundamentals: smart contracts, blockchain, and digital assets, which allow platform users to manage their authority and enable them to participate in the growth of the technological ecosystem. Web3 allows IT professionals to create, own, and manage their content and enjoy authority over their assets and data to safeguard them, as this technology eliminates third-party control and enhances the user’s experience by focusing on privacy, transparency, and security.

4. Revolutionizing Business Operations With Virtual Assistants

The concept of virtual assistance (VA) has transformed the way we work, interact, and communicate with technology, as it offers a myriad of benefits such as maximizing productivity, streamlining daily operations, and offering personalized customer experiences. The introduction of technological advancements such as AI, NLP, and DL has improved the VA’s intelligence and capabilities, allowing the VA application to address specific news and solve real-world issues. 

Conclusion 

The introduction of LLMs and semantic technologies has had a major impact on the AI-driven world, especially after the successful launch of ChatGPT, which has changed the way of communicating and also solved the problem of language translation.

However, with time, LLMs will be promoted as AI revolutionizes, and knowledge graphs will become more useful and recognizable platforms for data professionals. We also anticipate improvements in search engines and research, with Web3 taking the driver’s seat in changing the internet. 

Explore AITechPark for top AI, IoT, Cybersecurity advancements, And amplify your reach through guest posts and link collaboration.

The post The Top Four Semantic Technology Trends of 2024 first appeared on AI-Tech Park.

Table of Contents

Introduction

1. Five AI-smart Technologies That Will Transform This Holiday Season

1.1. Smart inventory management

1.2. Personalized shopping experiences

1.3. Efficient customer support with chatbots

1.4. Dynamic Pricing Strategies

1.5. Fraud Prevention and Security

2. Case Study

Macy’s Department Store

2.1. Challenge

2.2. Solutions

2.3. Results

Conclusion

Introduction

Retailers are compelling their customer service and supply chain systems to reach new limits with the anticipation of breaking the previous year’s record in spending during the holiday season. As the holiday season unfolds, it is a crucial time for retailers to maximize their sales and engage customers with the help of AI. We have witnessed in numerous situations how artificial intelligence (AI) has changed the game for the retail industry in our previous articles.

In this article, we will delve into how AI has taken center stage from the perspective of retailers and revolutionized the traditional way they used to approach the holiday season.  

1. Five AI-smart Technologies That Will Transform This Holiday Season

Here are five business functions in retail where AI will have a significant impact this holiday season:

1.1. Smart inventory management 

1.2. Personalized shopping experiences

AI-powered recommendation systems play an important role in personalized shopping experiences for customers. So, during this holiday season, retailers are leveraging these systems to suggest personalized gifts, discounts, ideas, and promotions based on individual preferences. This not only boosts customer engagement but also increases the likelihood of successful conversions, contributing significantly to holiday revenue.

1.3. Efficient customer support with chatbots

AI empowers retailers to implement dynamic pricing strategies during the holiday. By continuously analyzing market trends, competitor pricing, and customer behavior, AI automatically adjusts prices in real-time. This dynamic pricing approach helps retailers remain competitive, optimize revenue, respond swiftly to market fluctuations, and ensure a profitable holiday season.

1.5. Fraud Prevention and Security

With the increase in online transactions during the holidays, retailers prioritize cybersecurity. AI-powered fraud detection systems analyze transaction patterns, detect anomalies, and prevent potential threats in real-time. This not only protects retailers and customers from financial risks but also fosters trust in the online shopping experience.

2. Case Study

Macy’s Department Store

2.1. Challenge

Heightened competition in the retail sector, declining foot traffic in physical stores, and the need for a personalized customer experience for a more competitive edge.

2.2. Solutions

Adoption of AI technologies across numerous departments, including:

• Product recommendations

An AI algorithm analyzes customer browsing history, purchasing data, and demographic information to suggest relevant products and personalized gift recommendations.

• Virtual Try-On

AI-powered augmented reality (AR) tools allow customers to try on clothes and accessories, increasing purchase confidence and reducing returns.

• Omnichannel inventory management

AI optimizes inventory across online and physical stores to ensure products are readily available for customers, enhancing the shopping experience.

• Chatbot Assistance

AI-powered chatbots provide 24/7 customer support, answering questions, assisting with purchases, and improving customer satisfaction.

2.3. Results

• Increased Online Sales

Macy’s reported a 20% increase in online sales during the holiday season due to personalized shopping experiences.

• Improved Customer Satisfaction

Customers spent more time on the website and interacted more with product recommendations and AR features.

• Reduce the Return Rate.

Virtual technology led to a 14% decrease in clothing returns, saving Macy’s money and improving customer satisfaction.

2.4. Impact

Conclusion

To sum up, the integration of AI into retail operations during the holiday season marks a significant shift in how businesses approach this crucial period. From optimizing inventory and personalizing customer interactions to ensuring cybersecurity, AI is a key enabler of success for retailers. AI has also helped to level up the game for small retailers with advanced analytics and content creation capabilities. Industrialists believe that this technology leverages the transformative power of AI to make it easier for shoppers to shop and explore the extensive marketplace.

Visit AITechPark for cutting-edge Tech Trends around AI, ML, Cybersecurity, along with AITech News, and timely updates from industry professionals!

The post Transforming the Holiday Season with Smart AI Technologies first appeared on AI-Tech Park.

The Quadrant Knowledge Solutions SPARK Matrix provides competitive analysis & ranking of the leading customer loyalty solutions vendors 

Quadrant Knowledge Solutions announced today that it has named Salesforce as a Q2 2023 technology leader in the SPARK Matrix analysis of the global Customer Loyalty Solutions market. Salesforce was evaluated for its Loyalty Management solution.

The Quadrant Knowledge Solutions SPARK Matrix: Customer Loyalty Solutions, Q2, 2023, includes a detailed analysis of global market dynamics, major trends, vendor landscape, and competitive positioning. The study provides a competitive analysis and ranking of the leading customer loyalty solutions vendors in the form of the SPARK Matrix. It gives strategic information for users to evaluate different vendors’ capabilities, competitive differentiation, and market positions.

According to Preshit Parab, Analyst at Quadrant Knowledge Solutions, “Salesforce’s Loyalty Management platform leverages machine learning algorithms and predictive analytics, allowing brands to create personalized offers and rewards with targeted marketing campaigns. It offers comprehensive features, including the ability to create and manage loyalty programs, track customer engagement, and measure the ROI of loyalty initiatives. Salesforce Loyalty Management is integrated with Salesforce Customer 360, offering organizations a unified view of customers across various channels to deliver tailored loyalty offerings. Owing to its strong partner ecosystem, platform’s scalability and ease of use, robust analytical capabilities, and native cloud-based architecture, Salesforce has been positioned as a leader in the SPARK Matrix: Customer Loyalty Solutions, Q2, 2023.”

“We are pleased to be included as a Leader in this SPARK Matrix competitive evaluation. This prestigious industry recognition showcases our comprehensive and robust Loyalty Management solution and validates the incredible tool our team has built. Loyalty Management helps our customers deliver experiential programs to achieve higher customer lifetime value, leading to proven ROI, a strong zero and first party data strategy, and ultimately deliver better outcomes such as increased bottom-line revenue.” said Ram Machiraju, VP Product Management, Salesforce.

Additional Resources:

• For more information about Salesforce’s Customer Loyalty Solutions: https://www.salesforce.com/in/products/loyalty-management/overview/
• Complimentary download – Click Here 
• SPARK Matrix:Customer Loyalty Solutions, Q2 2023

Visit AITechPark for cutting-edge Tech Trends around AI, ML, Cybersecurity, along with AITech News, and timely updates from industry professionals!

The post Salesforce Leads in Customer Loyalty Solutions: Quadrant Report first appeared on AI-Tech Park.

Can you provide an overview of your role as the CTO at Calabrio and your responsibilities within the company?

I have the pleasure of overseeing our global technology and product management teams, ensuring that our development, cloud operations, information technology, security, product marketing, product management, and user experience (UX) development are in perfect sync. Together, we combine our customer-centric mindset and enterprise-grade true-cloud platform to deliver a product our customers know, trust, and love, as efficiently as possible.

How long have you been working at Calabrio, and what led you to pursue a career in technology and specifically in the field of customer engagement and workforce optimization?

I’ve been fortunate to be a part of the Calabrio family for a few months now, and I must say, the energy across teams is electric. My tech journey began long ago, fueled by a desire to unlock the untapped potential of innovation. The field of customer engagement and workforce optimization represents the intersection of human connection and technological prowess. It’s the perfect blend of art and science, where we can shape the way organizations engage with their customers and empower their workforce to reach new heights.

Calabrio is a leading provider of customer engagement and workforce optimization solutions. Could you elaborate on the key products and services offered by Calabrio and how they contribute to enhancing customer experiences?

Calabrio ONE is a workforce performance suite for customer-centric contact centers. A trusted ally for elevating and understanding human interactions, it empowers the contact center as a brand guardian. A true-cloud, fully integrated contact-center suite, Calabrio ONE’s core is workforce optimization (WFO), elevated with agent engagement and AI-fueled analytics tools using shared data from the entire suite and extending insights across the enterprise. Leveraging Calabrio ONE, our partners boost customer experiences, ensure agent success, simplify contact center operations, and support better decision-making.

In today’s rapidly evolving technological landscape, what are some of the major challenges that organizations face when it comes to customer engagement and workforce optimization? How does Calabrio address these challenges?

In the technological landscape, organizations face a multitude of challenges when it comes to customer engagement and workforce optimization. From managing interactions across various channels to maximizing agent performance and leveraging data intelligently, the opportunities are abundant but also so are the hurdles. Calabrio rises to the occasion by providing a unified platform that tackles these challenges head-on.

Our solutions empower brand guardians to harness the power of data, make informed decisions, and transform their customer engagement and workforce optimization strategies. Additionally, agents need to deliver the highest level of customer support instantly, so we continue to focus on the user experience to ensure they can easily absorb information and navigate workflows with ease.

Could you discuss any recent innovations or advancements in technology that have had a significant impact on customer engagement and workforce optimization? How is Calabrio leveraging these innovations to stay ahead in the market?

The advancements in AI technology have unleashed a world of possibilities for customer engagement and workforce optimization. These ground-breaking technologies have revolutionized data analysis, allowing organizations to unlock valuable insights and make real-time, data-driven decisions. Earlier this year, we announced a commercial integration with OpenAI, which accelerated our proprietary AI and ML capabilities and the framework of our workforce performance solutions. While others may look at AI’s potential to eliminate vital agent roles, we’re focused on leveraging employee engagement to augment the role of agents as brand guardians.

Data security and privacy are critical concerns for businesses, particularly when it comes to customer information. How does Calabrio prioritize and ensure data security for its customers’ sensitive information?

One of our core responsibilities lies in data security and privacy. We understand the gravity of safeguarding our customers’ sensitive information. That’s why we have robust security measures in place, adhering to industry best practices and complying with global data protection regulations. Our fortress of security includes stringent data access controls, regular security audits, and a relentless commitment to ensuring the highest level of data protection. Rest assured; our customers can trust Calabrio with their valuable data.

Can you share some examples of success stories or case studies where Calabrio’s solutions have helped organizations improve their customer engagement and workforce optimization strategies?

Last year, at our Calabrio Customer Connect (C3) event, we continued our annual tradition of recognizing and celebrating the most innovative and impactful uses of Calabrio’s analytics, speech-to-text, AI, and ML tools among our customers. These organizations dug into voice-of-the-customer intelligence and uncovered genuine insights to produce tangible results:

• Peckham drove an impressive $2.7 million in top-line revenue
• Idaho Central Credit Union eliminated 9,000 repeat calls
• Cummins recovered nearly $160k previously being lost to agent non-productivity

As technology continues to evolve, what do you see as the future trends and developments in the customer engagement and workforce optimization space? How is Calabrio preparing to adapt to these changes?

The future of customer experience lies in true-cloud solutions as the foundation for innovation and delivering AI-fueled solutions. The cloud enables faster product deployment, allowing our customers to receive updates and new features instantly. We also anticipate trends such as increased integration of AI and automation into operations, the rise of omnichannel customer engagement, and the growing importance of predictive analytics. Calabrio is proactively investing in research and development, fostering strategic partnerships, and continually enhancing our solutions. We are committed to staying ahead of the curve, anticipating customer needs, and providing innovative technologies that drive customer engagement and workforce optimization.

Collaboration and teamwork are essential for success in any organization. How does Calabrio foster a culture of collaboration and innovation within its teams?

Collaboration and innovation work hand in hand at Calabrio, creating an environment that nurtures brilliance through customer-driven innovation. We foster a culture of collaboration by encouraging open communication, cross-functional teamwork, and the sharing of knowledge. We provide our teams with the tools and resources they need to thrive, promoting a culture of continuous learning and personal growth. Each and every Calabrio team member is an innovator with a purpose to drive customer success.

Finally, what advice would you give to aspiring professionals who are interested in pursuing a career in technology, specifically in the areas of customer engagement and workforce optimization?

My advice to aspiring professionals interested in pursuing a career in technology, particularly in the areas of customer engagement and workforce optimization, is to embrace a growth mindset and continuously seek opportunities to expand your knowledge. Stay updated with the latest trends and technologies in the industry, develop a deep understanding of customer needs and pain points, and never stop learning. Seek out mentors, network with industry professionals, and be open to new challenges. Remember, technology is a powerful enabler, and by combining technical expertise with a passion for enhancing customer experiences and optimizing workforce performance, you can make a meaningful impact in this exciting field.

Joel Martins

Chief Technology Officer at Calabrio

Joel Martins, Chief Technology Officer, leads Calabrio’s company wide product, development, and technology teams. Joel has more than 20 years of experience driving innovation, growth, and operational excellence in software companies. Prior to joining Calabrio, Joel served as CTO at Apryse, Social Solutions, and MicroEdge. Successes in his tenures as CTO include completing a transaction to a new private equity owner, selling to a publicly traded company, creating, launching, and dramatic growth of new product lines, accelerating an existing product line to $1B, and securing a $59M investment from former Microsoft CEO Steve Ballmer, who joined the Social Solution’s Board of Directors.

Before becoming CTO at MicroEdge, Joel led global enterprise teams for 14 years at Symantec. He is also an Operating Advisor at Thoma Bravo. Joel graduated from the University of Minnesota with a BS degree in Computer Science and attended Luther Seminary in St. Paul post-graduate.

The post AITech Interview with Joel Martins, CTO at Calabrio first appeared on AI-Tech Park.

A recent McKinsey & Co. report found that over 70 percent of customers today expect personalized outreach from the companies they buy from. In fact, more than three out of four points to personalization as the factor most likely to turn them into a repeat customer that’s willing to recommend the product to friends and/or peers. This sends a clear message to companies; there’s no room for error when it comes to interacting with customers, whether the organizations are corporate giants or small-and-medium businesses all doing their best to survive. 

Consumers are less patient and far less forgiving than ever before. They no longer simply expect companies to cater to their every whim; they insist upon it and their loyalties are perpetually up for grabs because they’ll change their spending habits in a heartbeat if they sense that another brand understands them better and anticipates their needs more accurately and consistently. 

Leveraging AI Technology to Create a ‘Segment of One’

Consumers today feel let down when it comes to delivering a genuinely personalized experience because they’re not getting tailored messages and recommendations based on their needs and wants. As a result, sellers are looking to modern artificial intelligence (AI) technologies to provide the tools they need to master personalization and move beyond an older generation of marketing techniques that force customers into broad arbitrary categories. 

AI platforms, and machine learning in particular, are helping companies gain a thorough understanding of their customer’s behaviors, preferences, and goals. When armed with a vastly-improved understanding of these customers as individuals, companies can better leverage what they know to drive engagement. More importantly, they can apply AI to deliver the right message at just the right time. 

The value of personalization is clearest in its impact on profitability: companies that rely on AI to deliver “just the right experience” to “just the right customer” at ”just the right moment” consistently enjoy revenues that are 40 percent higher than those that don’t. As a result, getting personalization right is no longer optional. Unlike traditional market segmentation that forces unique individuals into broad-based categories on the basis of shared characteristics like age, gender, income, education, vocation, location, favored recreational activities, and spending habits, The concept of a Segment of One is about identifying what makes each and every customer tick. That knowledge is then used to engage with the customer at every stage of their shopping experience. 

Using a dynamic blend of AI, big data, and analytics – all boosted by automation – customers receive messages that are highly specific and highly contextualized. Promotions and offers are tied to specific aspects of the individual’s profile and real-time behavior that allows sellers to engage with the customer in a way that enhances their subjective experience of the brand and cultivates brand loyalty. 

AI: The Missing Link to Keeps Customers Happy (and Loyal)

Using AI-based systems, organizations are able to identify products and brands that the customer may want, but with a degree of specificity and confidence that goes well beyond what standard recommendation engines can deliver. This Segment of One approach leverages the advanced analytics provided by automated machine learning components that embrace a rules-based system and dispense with list-based constraints., Here, machine learning models trained on accurate, intelligently grouped customer data recommend a real-time, algorithm-generated “next best action” for the customer based on their specific journey. Dozens, or even hundreds, of variables and dimensions are brought together and analyzed almost instantly and outcomes are used to train the system so it  “earns over time as it gains access to more and more data. 

Customers who previously may have had a taste of personalization in their engagements with businesses are now demanding a vastly-improved experience with deeper personalization than ever before. They crave engagement that treats them as individuals, not as representatives of arbitrary marketing categories, and they’re rewarding companies that turn to AI to develop a comprehensive understanding of their unique tendencies, preferences, and goals. Customers respond better and more frequently when companies deliver offers, incentives, and messages that demonstrate a deep understanding of who they are and the nature of their experience as a customer. A blend of AI, data, analytics, and automation is enabling companies to engage with their customers as distinct, stand-alone entities, and customers are responding positively, even as (inevitably) they demand still more. Better yet, these cutting-edge technologies are getting better with time, and are ushering in a new era in which the wishes of the customer, not the manufacturer or retailer, are all that matter.

Visit AITechPark for cutting-edge Tech Trends around AI, ML, Cybersecurity, along with AITech News, and timely updates from industry professionals!

The post Segment of One: How the AI-Driven Revolution Is Super-charging Customer Engagement first appeared on AI-Tech Park.