1. Skydeo has been at the forefront of deterministic audience data for nearly a decade. Looking back at your journey as CEO, what has been the biggest lesson in balancing innovation, data accuracy, and ethical advertising?

Ethical responsibility and innovation have to come hand in hand. We have enhanced the usage of data to segment audiences, but user privacy and ethics should be the main priority, ensuring trust for future success. Ensuring a balance means adapting technology and policy to serve customers responsibly while remaining competitive.

The biggest lesson? Trust beats tech every time. You can build the most advanced audience data platform on the planet, but if you don’t operate with transparency and ethical responsibility, it won’t matter.

At Skydeo, we’ve had to push the boundaries of innovation while making sure our data is accurate, actionable, and compliant—because the second you lose accuracy, your insights become noise, and the second you lose trust, your platform becomes obsolete.

One of the biggest shifts is that brands now demand full transparency—they want to know where their data comes from, how it’s modeled, and how it’s used. We’ve leaned into that. Instead of black-box algorithms, we show exactly how predictive audience data works, helping brands cut waste, improve targeting, and do it in a privacy-safe way.

2. How has AI changed the way businesses approach audience segmentation and targeting in digital marketing?

AI has transformed audience segmentation as it allows companies to process large volumes of data and identify patterns that were not accessible before. It enables greater accuracy, making it possible to develop highly targeted campaigns. This implies that companies are no longer targeting demographics but behavioral and intent signals, which translates to improved ad performance and stronger customer relationships.

AI has flipped audience segmentation on its head. Five years ago, marketers were still using broad demographic buckets—“Men, 25-45, in urban areas.” That’s prehistoric by today’s standards. Now, AI enables hyper-personalized, real-time audience building based on behavior, intent, and predictive modeling. It’s not about static segments anymore—it’s about dynamic audiences that evolve as behaviors change.

For example, instead of just targeting “fitness enthusiasts,” AI can identify who’s actively looking for a gym membership versus who’s just casually watching home workout videos. That level of intent-based targeting is what makes AI a game-changer—it helps brands reach the right people at the right moment, not just the right general group.

3. How can predictive audience management improve personalization without compromising user privacy?

Predictive audience management utilizes anonymized data and machine learning to identify macro behavior and patterns, basically examining aggregated insight for personalization without invading user privacy. This approach can be further enhanced using privacy-first models like differential privacy.

Predictive audience management doesn’t need creepy tracking or third-party cookies to work. Instead, it looks at pattern-based behavior and anonymized signals to anticipate user needs.

Let’s say a consumer starts searching for baby strollers—they haven’t explicitly told a brand they’re expecting, but AI can recognize those signals and build a privacy-safe audience of “new parents.” The difference? No personal data is exposed—it’s just behavioral patterns at scale.

When done right, predictive audience management delivers better experiences for consumers while keeping brands on the right side of data privacy regulations.

4. What are the biggest challenges businesses face when leveraging customer data for AI-driven audience management?

A few of the most notable challenges include data quality, meeting strict privacy regulations, and ethics mapping of AI output. Some companies also find it difficult to integrate new AI solutions into their technology stack, which affects AI-based audience management adoption.

There are three big challenges:

Bad data = bad AI. AI is only as good as the data it’s trained on. If your audience data is inaccurate, outdated, or incomplete, AI won’t magically fix it—it’ll just make bad predictions faster. Brands need clean, verified data before they even think about AI.

Data silos kill efficiency. Too many brands still have disconnected data across marketing, sales, and customer service. If your AI can’t access the full customer journey, you’ll leave money on the table.

Privacy & compliance risks. AI can optimize targeting, but if brands aren’t respecting privacy laws (CCPA, GDPR), they could be setting themselves up for big legal headaches. The best AI solutions prioritize privacy-first modeling to stay compliant.

5. In what ways does AI-powered audience management improve ad spend efficiency and campaign performance?

AI-driven solutions quickly process data to recognize high-value segments, where ad budgets can be allocated to probable converters. Real-time optimizations enable dynamic campaign adjustments that minimize waste. Better targeting means relevant ads and improved performance in metrics like click-through rates and ROI.

AI saves marketers from themselves. A lot of brands still rely on gut instinct when building audiences. They assume they know their ideal customers, but AI proves otherwise.

AI delivers Higher ROAS, lower CPA, and smarter marketing decisions because it can:

Find high-intent users. AI identifies which customers are most likely to convert, so you’re not wasting money on broad targeting.

Predict lifetime value. Instead of chasing clicks, AI helps brands prioritize high-value customers that drive long-term ROI.

Optimize in real-time – AI doesn’t “set and forget”—it constantly adjusts targeting based on performance.

6. What are the key metrics businesses should track to measure the effectiveness of AI-driven audience segmentation?

Businesses must track conversion rates, CAC, LTV, and ROAS. Engagement metrics like CTR and bounce rates reflect the audience's resonance with the messaging. Analysis of accuracy of data and relevance of audience delivers greater insight into effectiveness.

If you’re running AI-driven audience segmentation, here’s what to track:

Conversion Rate (CVR). Are AI-powered audiences actually buying?

Customer Acquisition Cost (CAC). Are you spending less to acquire high-value customers?

Audience Match Rate. Is AI helping you reach more of the right customers?

Return on Ad Spend (ROAS). Is AI driving higher revenue per ad dollar spent?

Customer Lifetime Value (CLV). Are AI-targeted audiences sticking around longer?

Bottom line, if these aren’t improving, your AI audience segmentation isn’t working.

7. What ethical considerations should companies keep in mind when using AI for predictive audience targeting?

Companies must prioritize user consent and transparency when collecting and using data. Bias in AI models is another critical issue to address, as it can lead to unfair targeting. Additionally, businesses should ensure their methods remain compliant with privacy laws like GDPR or CCPA and consider implementing measures like anonymized data processing to uphold high ethical standards.

Ethical AI starts with three things:

Privacy-first modeling – Don’t use personally identifiable information (PII). Build models off behavioral insights without tracking individuals.

Bias detection. AI inherits human bias if it’s not trained properly. Brands need to audit AI models to ensure they’re not reinforcing stereotypes.

Transparency & opt-outs. Consumers should know how they’re being targeted and have the ability to opt-out. If you wouldn’t feel comfortable explaining your AI’s decision-making to a customer, it’s probably not ethical.

8. How do you see AI evolving in audience segmentation and predictive modeling over the next five years? 

AI for audience segmentation will be enhanced with better real-time data processing and deep learning. Predictive algorithms will power customer need forecasting, and hence hyper-personalized campaigns. More uses of AI models that deal with ethics and privacy are expected to be compliant with global regulations. NLP has the potential to enable greater understanding of nuanced customer interactions.

AI-driven audience segmentation is just getting started.  Here’s where we’re headed:

Real-time, adaptive segmentation. AI will continuously refine audiences in the moment based on new data.

Gen AI for audience creation. AI will automatically build custom audiences based on brand goals + real-time consumer behavior.

Predictive commerce. AI will anticipate what customers want before they search for it, making marketing proactive, not reactive.

Goodbye third-party cookies, hello AI-first data strategies. Brands will rely entirely on first-party data + AI models to personalize marketing without tracking users.

1. What strategies can be implemented to maintain the original tone and emotional depth of content during AI-powered translations?

Preserving tone and emotional depth in AI-powered localization goes beyond words alone. It’s about capturing the full human performance. Traditional dubbing often ignores pauses, inflections, and gestures, making speech feel unnatural or disconnected.

At Panjaya, BodyTalk ensures that voice, lip movements, and full-body gestures stay synchronized, preserving the authenticity of the speaker’s performance. This allows translated content to retain its natural rhythm and emotional impact, ensuring that audiences connect with it just as they would with the original.

Our latest innovation, Pod Pro, extends this to podcasts and interviews, where speech modulation and contextual adaptation help maintain the flow and nuance of spoken content. By using AI-driven adjustments, creators can ensure that translated versions sound as natural and compelling as the original, without the disconnected feel of traditional dubbing.

2. What are the technical considerations when implementing AI-powered dubbing solutions into existing content management systems?

For AI-powered dubbing to be scalable and effective, it needs to work seamlessly within existing content workflows, without adding complexity for creators. Traditional localization requires expensive, time-intensive studio recordings, but Panjaya eliminates these inefficiencies with an automation-driven approach that adapts to real-world content workflows.

Our solutions handle complex real-world scenarios like multi-speaker dialogues, shifting face angles, and even occlusions (e.g., microphones or hand gestures covering the mouth). This ensures that dubbed content stays synchronized and looks natural, even in dynamic video settings.

Additionally, human-in-the-loop precision tools give publishers the ability to fine-tune translations, adjust tone, and refine performance nuances, ensuring that localized content aligns with brand voice and audience expectations. Whether integrating into a corporate video platform, media library, or podcast workflow, Panjaya makes AI-powered localization effortless, scalable, and high-quality.

3. What metrics should be used to evaluate the effectiveness of AI-powered dubbing in maintaining content integrity across languages?

At Panjaya, we measure success through engagement, audience growth, and time and cost efficiencies.

Two key indicators of engagement are completion rates and share rates. TED saw a 2X increase in completion rates and a 30% increase in shares rates when switching from subtitles to Panjaya’s AI dubbing, proving that audiences prefer a natural, immersive experience over reading text on screen, and are far more likely to share that experience with others

Beyond retention, audience growth is another major measure of success. TED Talks localized with Panjaya saw a 115% increase in international viewership, proving that high-quality localization expands reach and strengthens audience connections.

Finally, time and cost efficiencies are critical metrics. Traditional dubbing takes weeks to months to complete, but our AI-powered solutions deliver high-quality translations in minutes to hours. This means enterprises can localize content at a fraction of the time it used to take. Additionally, our approach reduces costs significantly. Our AI dubbing solutions operate at around 1% of the cost of traditional dubbing methods, allowing companies to scale their multilingual content strategy without budget constraints.

4. How can AI dubbing solutions improve the localization of audio content to engage a global audience?

Expanding global reach requires more than just translation. It demands cultural and emotional resonance. Traditional subtitling and voice-actor dubbing often fail to capture the essence of the speaker, leading to disengagement from non-native audiences.

Panjaya solves this by ensuring that translated content retains the natural rhythm and delivery of the original. With multi-speaker support, adaptive speech modulation, and contextual adaptation, our AI makes translations feel just as engaging as the source material.

For example, 60% of Spotify’s podcast listeners are non-English speakers. That means podcast publishers relying only on English are missing a massive global audience. With Pod Pro, publishers can instantly translate episodes while preserving the speaker’s unique tone and storytelling style, allowing them to connect more deeply with international listeners.

By making content feel native in every language, AI-powered dubbing removes the barriers to global engagement.

5. How can reallocating resources from manual translation efforts to AI-powered solutions impact overall operational efficiency?

Manual dubbing is time-consuming, expensive, and difficult to scale. It requires studio time, professional voice actors, and intensive post-production work—all of which add costs and delays.

AI-powered solutions eliminate these inefficiencies by automating the dubbing process while still allowing human control where needed. Instead of taking weeks or months to localize content, organizations using AI-powered dubbing can generate high-quality translations in just minutes to hours. This time reduction translates directly into cost savings. Our AI-powered dubbing operates at just 1% of traditional dubbing expenses. For organizations like TED and JFrog, this shift has dramatically increased audience engagement while significantly lowering the cost of expanding their multilingual reach.

6. How can organizations balance the efficiency of AI translations with the need for human oversight to maintain content quality?

AI-powered dubbing is incredibly efficient, but human oversight remains essential for accuracy, cultural sensitivity, and maintaining brand voice. The key is to combine automation with human refinement, ensuring speed, scalability, and authenticity all at once.

At Panjaya, we believe the future of localization is a hybrid approach. AI delivers efficiency, while human oversight ensures accuracy, nuance, and cultural alignment. AI takes care of translation, lip-syncing, and body synchronization, while creators refine tone and style using precision tools.

This balance makes Panjaya’s solutions not just fast and scalable, but indistinguishable from native-language content, ensuring that every story is told authentically, no matter the language.

1. Your career spans industry giants like Accenture, Cisco, and now Five9. What drew you to the world of AI-powered CX, and how has your journey shaped your vision for the future?

I have had the opportunity to work with very talented people at some very influential companies. A common theme in my roles has been the power of partnerships, and Five9 really takes this to heart. The importance Five9 puts on doing the right thing and putting people first -- employees, customers, and partners -- was a big draw for me, along with the chance to work in an industry that so directly aFects everyday consumers.

I was also interested in working with a company that prioritized learning and nurtured innovation. AI is a great example. Five9 isn't just getting started there – we've been doing AI since 2018, and I wanted to be a part of bringing AI-elevated oFerings to the customer experience. While the industry has built a legacy of successful contact center solutions, the market is asking for modern capabilities to improve and deliver great customer experiences. Companies today need tighter integrated workflows and comprehensive capabilities that bring together the best of multiple platforms to future-proof their technology investments.

This leads me to the development of our global partner program. We believe that working with partners empowers our customers to do so much more – and do it all faster, better, and more eFectively. It's an exciting time to work with Five9!

2. You've led global partner strategies at top organizations. What's the secret to building partnerships that aren't just transactional but truly transformative—like Five9's with Google Cloud?

It always comes back to having a mutual and sincere desire to see customers succeed. It's that simple. When customer success is top of mind, you design solutions that address real customer needs, create processes focused on ease of doing business, and choose partners that share your values and drive for innovation and excellence. That's what guides us when we look for partnerships and, ultimately, what makes our partnership with Google so successful. 

3. Five9's launch on Google Cloud Marketplace simplifies access to AI-powered CX solutions. What makes this partnership a game-changer for enterprises worldwide?

The CX market is evolving at an incredibly rapid pace, with a big focus on AI. Ultimately, we strive to help our customers find success by providing hyper-personalized experiences that drive growth. We also recognize that customer organizations, including ourselves, around the world are increasingly engaging with Google Cloud & leveraging Google Cloud solutions to accelerate their growth. Five9's global availability on Google Cloud Marketplace means we are easy to find, purchase, and deploy for an even broader set of customers. This becomes a game changer for businesses looking to diFerentiate how they can serve their customers, potentially burn down some Google Cloud spend, and future-proof their technology stack for long-term scalability and innovation with a company that also is aligned to Google Cloud.

4. Five9 AI Agents are now globally accessible. How does this expansion empower businesses to scale AI-driven customer engagement effortlessly?

We launched AI Agents in November 2024, and it empowers businesses to create chat and voice bots that combine the conversational abilities of a human with the speed and extensive knowledge of AI -- and our recent announcement unveiled a new version of Five9 AI Agents specifically for Google Cloud. This stand-alone solution lets customers take advantage of the ease of Google Cloud Marketplace and utilize Google Cloud technology, coupled with Five9 AI-elevated CX, to create exceptional customer experiences. Designed to deliver the power of AI self-service for an elevated customer experience, we see the combination of the Five9 Intelligent CX Platform and the scalability and security of Google Cloud as a recipe for CX success.

5. The CX landscape is shifting rapidly. What's one customer expectation trend that businesses must adapt to in 2025 and beyond?

Without a doubt, AI is the biggest trend affecting all companies today, and CX is no exception. Its potential is endless, giving us the ability to help customers move confidently to a new era of CX. We believe in empowering everyone whose role can be supercharged by it. We harness AI to unlock organizational insights, making them accessible, actionable, and transformative.

In this AI-driven era, we believe that contact center agents will operate more like brand ambassadors. Armed with relevant and contextual business information, they will remain the backbone of customer relationships, fostering loyalty and trust. In terms of saying it as "one customer expectation": customers want real AI that delivers real outcomes, not just discussions.

6. AI is often measured by ROI and operational impact, but can you share a human-centric success story that highlights the real-world impact of Five9's AI solutions?

An AI-driven CX success story I love is US Radiology Specialists, one of the country's premier providers of diagnostic imaging services. But they aren't just a leader in diagnostic imaging - they're transforming patient care with tech.

With over 5,000 team members and more than 175 outpatient imaging centers across 13 states, their team conducts more than 7 million studies annually. They came to a place where they were experiencing significant wait times, misrouting calls, experiencing rising costs in their 10 contact centers, along with using outdated technology and ineFicient manual processes.

We were honored to partner with them, and they are now automating 75% of outbound calls and cutting call times by 4.5 minutes. With agents freed up for complex cases, conversion rates jumped by 24%, adding $4M in revenue.

But aside from great stats, the speed of getting through to a live person and getting the right treatment can make a real diFerence and save lives.

At Five9's recent annual sales & services kickoF, US Radiology shared a story about one of their physicians' family members experiencing severe head pain. They were worried about a hemorrhage. They called in, were routed to an agent, and they were able to schedule and see the patient within an hour to get a scan. Turns out it was indeed a brain hemorrhage – and they were able to bring the patient in for surgery, which ultimately saved that person's life. That's the kind of impact we are helping to enable – and you can't help but be inspired by that.

7. With Five9's centralized procurement through Google Cloud, how does this help companies stay agile, future-ready, and innovation-driven?

There are some very practical benefits to procurement of Five9 via Google Cloud Marketplace, including simplified billing and management and the ability to use existing Google Cloud budget and retire cloud-committed spend. The Google Cloud Marketplace model we deployed also makes Five9 an accessible solution for organizations of all sizes. At the end of the day, we want to be easy to access and easy to do business with to help drive innovation, collaboration, and sustainable value for our customers as the CX landscape continues to develop.

8. If you had to predict the next major breakthrough in AI-powered CX, what would it be—and how is Five9 positioned to lead that transformation?

We believe that we'll see the evolution from AI as primarily a chatbot or automation tool—to becoming a real-time assistant for human agents. We need to rethink AI—not as just a technology tool, but as a co-worker. Imagine if AI could sense tone, emotion, and frustration levels, allowing for human-like interactions. Analyzing voice and even facial expressions, what if AI could detect when a customer needs human escalation or when reassurance and tailored messaging could solve their concerns?

AI innovation is moving fast, and we believe that it can make the customer experience better. Five9 is taking that seriously by looking at the entire customer journey. We are one of the leaders redefining CX within and beyond the contact center and approach it with both practicality and 'sky-is-the-limit' ambition, remaining business-oriented in our innovations. As we look to the future, you will continue to see us invest heavily in our AI, our platform, and our people for success. 

1.       How do CDPs enhance customer segmentation and improve engagement across different channels?

The real power of CDPs lies in their ability to unify diverse data sources - from DMS and service records to digital interactions - creating a unified profile for each customer. What's particularly exciting about real-time platforms like Tealium is how they enable automotive businesses to segment and respond to customer behavior as it happens. For instance, when a customer is researching specific models on a website or approaching the end of their lease, the dealer can immediately tailor their approach. However, what really drives ROI is how CDPs orchestrate consistent messaging across all channels - whether a customer is receiving an email, seeing a digital ad, or walking into the dealership, they experience a cohesive journey allowing sales and marketing teams to engage proactively and significantly boost acquisition and retention rates.

2.                   What are the biggest challenges in integrating first-party, second-party, and third-party data within a CDP? 

For the automotive industry, the biggest challenges in integrating different data types stem primarily from data quality and standardization issues. This is because dealerships deal with multiple systems that often speak different languages - from dealership management systems to OEM databases, third-party sources, and more. 

Another challenge is privacy and compliance, particularly with regulations like CCPA and GDPR, as proper consent management and data handling is critical, all while maintaining complete transparency about how customer information is being used.

From a technical standpoint, most automotive companies struggle with legacy system integration and real-time data synchronization, which can impact their ability to deliver timely, personalized customer experiences. Equally challenging on the business side is the need to justify the significant investment in data integration while managing complex data-sharing agreements with manufacturers and partners. Finally, don’t overlook the organizational challenges - in my experience, getting different departments to break down their data silos and embrace a unified data strategy often requires significant change management and clear demonstration of ROI.

3.                   What strategies do you use to ensure customer data collected from various sources is unified and actionable? 

Tealium employs several key strategies that have proven highly effective for automotive clients. At the core is our real-time EventStream technology, which captures customer interactions across touchpoints and immediately makes them available for activation. What sets Tealium apart is our identity resolution framework that uses both deterministic and probabilistic matching to create a unified customer profile regardless of whether interactions happen on the website, mobile app, in the service department, or at the dealership.

Tealium’s data layer approach has been particularly valuable - it standardizes all incoming data into a consistent format before it enters our ecosystem, solving one of the biggest challenges in the automotive space where we're dealing with disparate systems like DMS, CRM, and digital platforms. Tealium's pre-built connectors to over 1,300 martech systems mean customers can quickly integrate new data sources without extensive development work.

Another powerful solution is Tealium’s server-side integration capabilities, which allow us to enrich customer profiles with additional data and execute complex segmentation rules before sending information to downstream systems. This ensures we're not just collecting data, but making it immediately actionable across our entire tech stack, enabling the personalized experiences our customers expect whether they're shopping online or visiting the dealership showroom.

4.                   How do you ensure that customer data collected and processed through a CDP complies with evolving privacy regulations? 

Privacy and consent are core tenets of Tealium’s value proposition. Our new Consent 2.0 Suite fundamentally changes how organizations manage privacy. With Consent 2.0, users get a new consent manager with granular preference controls and a zero-latency consent orchestration engine that automatically enforces preferences across all touchpoints. What’s unique is that consent validation and enforcement is executed real-time to minimize risk of non-compliance. We've embedded privacy-by-design into Tealium’s workflows by implementing data minimization principles and automatic purging procedures when data is no longer needed. 

5.                   What key performance indicators (KPIs) do you use to measure the success of a CDP-driven marketing strategy?

Our automotive customers have developed sophisticated KPI frameworks that demonstrate the true value of their CDP investments beyond traditional metrics. They measure acquisition efficiency through reduced cost-per-qualified-lead and improved source attribution. For engagement, our automotive clients closely track indicators like VDP (Vehicle Detail Page), view-to-lead ratios, and personalized offer response rates, which can increase significantly when leveraging real-time behavioral data. 

On the conversion side, they monitor sales cycle compression and multi-touch attribution across digital and in-dealership touchpoints, with many reporting significant improvements in attribution accuracy and faster closing times. Retention metrics reveal the most compelling ROI story, with service department utilization, lease renewal rates, and customer lifetime value showing how personalized experiences drive long-term loyalty. Finally, operational efficiency metrics demonstrate how our platform enables dealerships to execute sophisticated multi-channel campaigns without expanding their marketing teams.

6.                   How does your organization leverage CDPs to create more personalized and targeted marketing campaigns? 

Automotive brands use Tealium’s CDP to create highly-personalized and data-driven marketing campaigns and experiences. By unifying data from dealership websites, CRM systems, and offline interactions, Tealium clients can build 360-degree customer profiles that reveal buying intent and preferences. When a customer browses SUV models online, for example, Tealium can trigger real-time targeted ads or personalized emails showcasing relevant offers. AI-driven insights also help predict behaviors, such as when a customer may be ready for a trade-in, enabling proactive engagement. With seamless omnichannel execution, brands can synchronize messaging across email, social media, and paid ads, ensuring a consistent experience.  

One of our customers is a global luxury sports car and SUV manufacturer who uses the data collected from the online car configurator to build unique customer profiles for each visitor. Tealium collects and unifies all the first-party data that website visitors share - starting from the initial information they provide during the car configuration tool, and constantly updating the profile with future interactions and engagement with the manufacturer. These engagements can range from surveys, challenges, and even eBooks filled with information that is tailored to the individual customer.

1. In what ways can natural language processing capabilities in audience segmentation tools improve the efficiency of market research?

Natural language processing allows users to analyze and segment large datasets based on user intent in short periods of time, reducing the need for manually filtering audience attributes. NLP tools can generate complex audience expressions, saving marketers time while also improving precision and efficiency. This way, users can uncover consumer insights faster, leading to high-quality data-driven marketing strategies.

2. What are the implications of rapid audience segmentation on real-time marketing campaigns and customer outreach efforts?

By utilizing audience segmentation within seconds, marketing efforts become more agile with real-time data. Marketers are given the opportunity to react to rapidly changing consumer behaviors to launch more targeted campaigns and better align their messaging. The speed of the segmentation efforts allows brands to engage with the right audiences at the right time to encourage customer engagement.

3. How can organizations ensure the ethical use of AI-powered audience segmentation tools in their marketing practices?

Organizations need to prioritize data minimization, which uses only necessary data, pseudonymized and cached where possible, following compliance regulations, and maintaining some form of human oversight. When using AI-powered tools for marketing, transparency and consumer consent remains a key factor in data sourcing along with proper licensing to build trust. AI guardrails have been installed in the U.S. to prevent the misuse of personal data. Each state’s data privacy law is considering AI now as more organizations adopt these tools, so marketers need to leverage AI responsibly to avoid going down a slippery slope.

4. What training and skill development are necessary to effectively utilize AI-driven audience segmentation tools?

Building audiences can be extremely time-consuming and usually requires an understanding of Boolean terms and how to find exactly what you’re looking for using them. Ideally, AI-driven audience segmentation tools should be intuitive and simple to learn for marketers of all different skill levels. We made sure that Resonate’s rAI-powered Audience Builder gives users simple natural language prompts so that anyone can quickly and seamlessly create custom audience personas. Users can simply type in plain English what audience they want to create and rAI-powered Audience Builder will select the most appropriate attributes and build the Boolean logic-based audience expression for them with a single click.

5. What are the potential challenges and solutions in integrating AI-powered audience builders into existing data analytics frameworks?

General concerns about integrating AI-powered audience builders with existing data analytics frameworks include data compatibility, scalability and integration complexity – but all have simple solutions. For example, integration complexity can be reduced by using middleware or APIs to help facilitate communication between two different systems.

AI tools, including AI-powered audience builders, are only as strong as the data they are given. Resonate has been perfecting its AI-powered models for more than a decade to be able to predict and deliver the most comprehensive, updated understanding of consumer behavior. That’s why implementing practices like data minimization, hashing and pseudonymizing data are so important to start with. They lower levels of data bias and give marketers confidence in the ethical nature of the data they receive.

6. How can AI-powered audience segmentation tools be customized to meet the unique needs of different sectors?

The beauty of tools like rAI-powered Audience Builder is that it allows users to build complex, tailored audiences quickly and efficiently. Building complex audiences used to take hours, but rAI-powered Audience Builder creates them in seconds. This type of tool allows marketers across industries to dive deeper into strategy and the audiences they want to reach, creating potential to reach untapped or nuanced audiences and markets. It can also help find aspirational audiences to use in developing messaging strategy by using broad audience descriptors such as, “build an audience of people who like a lot of excitement in their lives.”

SurveyMonkey, the world’s most popular platform for surveys and forms, recently announced a series of updates to its market research solutions designed to help organizations of all sizes conduct more advanced research faster. We connected with Scott Monroe, SurveyMonkey’s Director of Product Marketing, to discuss how these newest advancements will help end-users make more informed, data-driven decisions:

1. How can organizations leverage expanded global survey panels to gain deeper insights into diverse consumer behaviors and preferences?

If organizations want to make smarter, more data-driven decisions, leveraging global survey panels is a great way to start. Getting feedback from the right people at the right time can help uncover market trends and nuances in customer buying habits or preferences. Additionally, broader audiences provide broader insights, which can help with building the right product, validating a new marketing strategy, or improving customer experiences online and in person.

2. How does access to a more extensive and diverse respondent pool impact the reliability and validity of market research findings?

When feedback is needed on an idea or concept, a larger, more diverse panel provides more trustworthy insights. A bigger audience means you’re hearing from a true mix of people, not just a small, skewed group. Plus, it helps reduce bias, so your results aren’t accidentally leaning too much in one direction. The bigger and more varied your sample, the clearer and more reliable your insights will be.

3. What strategies can businesses use to integrate enhanced market research capabilities into their decision-making processes?  

Sometimes feedback from a small sample, or even a hunch, can drive big, strategic decisions that impact business. Hunches are good, but bolstering them with data is better. Organizations can use market research to validate those new ideas and determine whether they are viable or not. Even if a company is already very data-driven, market research adds another level of insight that can inform building new products, creating new services, or better serving customers. 

4. What are the potential challenges and solutions in adopting new market research technologies within various organizational structures?

Anytime new technology is introduced to a company, some people may be slow to adopt–or even to use it at all. There may also be a preconception that it’s going to be slow and expensive. But it doesn’t have to be that way, because today’s market research is simpler to conduct and faster to insights. A solution to these potential challenges is to choose a market research provider that is easy to set up, intuitive to use, and able to provide powerful insights affordably. Ensure they have proven expertise and experience, as well as proof points to back it up.

5. What role does real-time data collection and analysis play in shaping marketing and product development strategies? 

Most marketing and product teams want feedback from target markets quickly, so timing is crucial. Marketing teams may be looking to launch a new campaign, and they want to validate a couple of different creative concepts to see what resonates. Having the ability to get close to real-time feedback like this helps them decide quickly on creative direction and get their campaign in the market faster.

6. How can businesses measure the return on investment (ROI) when implementing advanced market research solutions?

There are several metrics that can help determine the ROI of market research initiatives. Let’s say an organization conducted market research on a concept for a new product to add to its portfolio. And, in this case, the research validated the idea and indicated that consumers were willing to buy it. After the product is launched, there are some questions to answer that will provide insight into the ROI: How much new revenue was created from sales? Did the business improve market share? What was the customer satisfaction score for the new product? To truly measure the ROI of market research, organizations can also track results such as cost savings and revenue growth, as well as benefits like time-to-insights. 

Please tell us about your professional journey that led you to becoming the CEO of Amperity.

My journey began with a passion for innovative technology and data-driven decision-making. Before joining Amperity, I held leadership roles in various tech companies like Concur and Stripe, focusing on enhancing product capabilities and expanding global reach. In these positions, I gained a deep appreciation for the importance of data in making informed decisions, reducing risk, identifying trends, improving efficiencies and developing customer-centric strategies, among other things. These experiences paved the way for my role at Amperity, where we set new standards in customer data management.

It all started with my love for solving complex data challenges. Before joining the team at Amperity, I had the privilege of working with some amazing companies like Concur and Stripe. In those roles, I focused on making our products even better and helping the companies grow globally.

Through those experiences, I really came to understand just how critical data is in making smart decisions. I mean, when you have the right data, you can spot trends, reduce risks, boost efficiency, and create strategies that truly put the customer first. But it is only a game-changer if you are making decisions on a solid data foundation.

So, when the opportunity at Amperity came knocking, I knew it was the perfect fit. Here, we're not just unifying, managing and helping activate customer data; we're revolutionizing the way it's done for over 400 brands. It's an exciting time to be part of this team, and I can't wait to see how we continue to set new standards in the industry.

How do you think Customer Experience is changing the game in marketing? What role does data play in it?

Customer experience is transforming marketing by prioritizing personalized engagement at scale. In today’s digital landscape, the quality and accessibility of data are key to achieving this. Amperity ensures marketers have a solid data foundation, enabling them with high-quality data for precise personalization.

Amperity’s platform empowers brands to tailor experiences uniquely to each consumer by using advanced data capabilities and Generative AI. This approach allows for enhanced personalization, adapting to consumer behaviors and preferences in real time. The result is not just personalized marketing but personalization at the enterprise level, ensuring every customer interaction is impactful and relevant. By improving data quality and accessibility, Amperity helps marketers exceed the evolving expectations of their customers.

What trends will stand out in the retail industry? What role do AI and LLM play in the industry?

In the retail industry, trends like hyper-personalization, real-time customer engagement, and paid media activation are becoming increasingly prevalent due to consumers’ growing demand for customized shopping experiences that align closely with individual preferences and behaviors.

AI and large language models (LLM) are crucial for analyzing vast amounts of data and generating insights to predict consumer behavior. For instance, Amperity recently introduced AmpAi, a suite of generative AI capabilities, to add a critical intelligence layer to enable all technical and business users to get the most out of their customer data. The first two capabilities, AmpGPT and AI Assistant set a new benchmark in marketing and advertising technology. AmpGPT empowers marketers to interact with their data using natural language. Ai Assistant removes the barriers to creating SQL queries and fixing potential errors within those queries.

Can you share your perspective on how automation tools revolutionize the industry?

Automation tools are dramatically transforming industries by simplifying complex processes and delivering actionable insights within seconds. At Amperity, our automation capabilities streamline the unification and activation of customer data, freeing up marketing teams to concentrate on strategy and customer engagement rather than tedious data management tasks.

Amperity facilitates a seamless flow of insights across various platforms, such as CRMs and customer service tools. Consequently, these insights can be utilized to deliver precisely targeted messages at the right time, enhancing the effectiveness of communication strategies and improving overall customer experiences. This capability optimizes marketing efforts and scales personalized customer interactions across multiple touchpoints.

What advice would you like to impart regarding building customer relationships?

Building strong customer relationships starts with truly understanding your customers’ needs and preferences. Leveraging data effectively is critical. Ensure your data management tools, like our Lakehouse CDP, can share live data sets between a CDP and a lakehouse without maintaining ETLs or copying data in multiple places. This enables IT teams to optimize how data is stored and processed with any platform that uses a lakehouse’s open table formats to save time and lower costs. This composable, more secure flow of data ensures brands can fuel the data-intensive demands of Generative AI and 1:1 personalization with high-quality data.

Welcome, Sheila! Could you please share your marketing journey and how it influences your decision-making as the CMO at Coveo?

I started my career in 2000 at Procter & Gamble in the sales department. I worked there for 2 years and then joined L'Oréal for a position as the Assistant Product Manager for Garnier Fructis. I worked at L’Oréal from 2002 to 2014 in Montreal and Paris. I touched on many types of positions in marketing, sales, category management, trade marketing, brand, product creation, and more. I learned everything at L’Oréal. It's an incredible marketing school!

Then I worked for Danone for 3 years before joining Cirque du Soleil, first in brand and strategy, then as CMO (interim). I've been with Coveo since January 2021.

Because I've worked in several types of industries (CPG, Entertainment, Tech) and worked several jobs (marketing, sales, category management, trade marketing, brand, and product creation), I'm more of a generalist CMO. I can touch on anything and adapt to any situation very quickly. I'm used to working in fast-paced environments. I've always been motivated by growth and transformation. The status quo is not for me!

What has been the common uphill battle for CMOs of B2B organizations in the past year?

An important one was Digital Transformation. Before Covid, a lot of B2B business was done in person. During the pandemic, we searched for new ways to find leads to grow our pipeline without live events. Many B2B organizations are still grappling with the need to adapt to the new digital landscape effectively. This includes implementing digital marketing strategies, optimizing online sales funnels, and leveraging technology to better engage with customers.

Data and Analytics: We need to base our decisions on data. What messaging is working? What initiatives should we stop doing? What should we double down on? What is the return on our investment? The data exists. There's no reason to drive blindly anymore. This is something that's very important to me.

Account-Based Marketing (ABM): Some B2B organizations have adopted ABM strategies to target specific high-value accounts. Effectively implementing ABM requires aligning sales and marketing teams, account lists, personalized messaging, and account-specific campaigns. At Coveo, we started our ABM journey officially last year. We have embarked on a major transformation that will take several years to complete. The idea is to modernize the way we do B2B marketing so we don't get bogged down in forms to fill, MQLs, and leads.

SEO and Content Marketing: Creating compelling and relevant content for B2B audiences remains challenging. CMOs and their content teams have to develop content that addresses the specific pain points and needs of their target audience while showcasing the value of their products or services. This content needs to fit the SEO strategy so we can win from an organic standpoint. There are so many areas we need to cover — we need the right strategy, the right data, and the right prioritization. AI can also be a great help in creating this content.

Adapting to new technology and rapid changes in the market: This year, Large Language Models (LLMs) such as ChatGPT and alternatives have taken the world by storm. We had to react and react fast. Thanks to the fact that Coveo is very quick to adapt and was already very advanced in the field of LLMs — in addition to its 10 years of experience in AI — we were able to announce our generative AI offer very quickly. We like to say that we were the last to hype but the first to have a real product with real tangible results. We successfully changed our entire marketing plan over the course of 1 month.

How does Coveo enable businesses to “personalize everything” through its AI platform?

Large tech-enabled companies have been able to deliver remarkable, effortless, relevant experiences tailored specifically to the individual and designed for maximum consumer satisfaction.

Their tools are massive amounts of data, powerful artificial intelligence and machine learning, as well as armies of data scientists and engineers. 

The results? An understanding of who people are on an individual level. These companies know what we want and where we came from and can even predict where we’re going next. They use this rich understanding of us to deliver relevant, personalized digital experiences at scale. These experiences put people first, not products. They’re tailored for persons, not personas.

This is what we do at Coveo.

Because delivering relevance and personalization at scale absolutely requires AI.

Being relevant to one million individuals by manually writing rules is simply not humanly possible. But it is possible with AI. It is possible with Coveo AI.

The Coveo Relevance Cloud is a world-leading AI platform specifically built to make every digital experience delightful, relevant, and profitable. We do that through AI-powered advanced search, relevant recommendations, unrivaled personalization, and now relevant generative answering across Commerce, Service, Workplace, and Websites.

We are the intelligence layer behind many of the biggest global brand experiences.

What are the key elements of a successful marketing strategy, and how can marketers accomplish those with limited budget & resources?

Here are 3 simple steps for creating a successful marketing campaign:

1. Understand Your Target Audience: Conduct thorough research to understand your target audience's preferences, needs, and pain points.
2. Establish a Clear Value Proposition and Messaging: Determine what is unique about your brand, your offer, and your product/solution. Clearly communicate what sets your product or service apart from competitors and why it's valuable to the target audience. Use engaging and concise messaging in your go-to-market materials.
3. Then, you can Build Your Marketing Plan with Multi Tactics and Touch Points:

• • Events and Webinars: Participating in third-party events or creating your own.
  • Media: Paid Search and Paid Social
  • Organic traffic - Search Engine Optimization (SEO): Optimize your website and content to rank higher in search engine results.
  • Content: In B2B, content is key. You need to have insightful, valuable, and relevant content that educates, entertains, or solves problems for your audience.
  • PR and Social Media: Establish a strong presence on relevant social media platforms to engage with your audience directly. Make sure journalists and media are also engaging and talking about you.
  • Emails: Build an email list and use it to nurture relationships with potential and existing customers.

And more…

Remember, success in B2B marketing doesn't solely depend on the budget. It's about understanding your audience, being resourceful, and focusing on the channels and strategies that provide the most value for your specific business.

In this constantly evolving marketing landscape, what’s your drill to ensure you & your team are on top of trends?

The dynamic landscape of Business, Marketing, and Technology is undergoing rapid and constant change. Staying up to date in such an environment can be challenging at times. It takes a village (my full team) to stay up to date. You need to have curious people in your team, people hungry for new ways of doing things.

The way we do it at Coveo is through different practices:

Continuous Learning: Encourage a culture of curiosity and continuous learning within your team.

Marketing and Industry Publications: Keep a close eye on reputable marketing publications, blogs, and websites. Subscribe to newsletters and follow thought leaders in the industry.

Other industry best practices: We should also look at what other industries are doing. B2B can learn from B2C and vice-versa. Make-up brands can learn from the automotive industry, tech can learn from CPG, etc.

Competitor Analysis: Regularly analyze your competitors' marketing efforts to identify any new strategies they are implementing successfully.

Experimentation and Testing: Encourage a culture of experimentation within your team. For example, this year, the Coveo Marketing team launched its own 1000-tests initiative. We are learning tons.

Could you tell us about an innovative solution that Coveo is currently developing, which has the potential to set a new industry benchmark?

Large Language Models (LLMs) such as ChatGPT and alternatives have taken the world by storm. Despite their current shortcomings for enterprise-level adoption (misinformation, hallucinations, no personalization, expensive training costs, lack of privacy & security, and questionable ethics, among others), we see a huge demand for Generative AI question-answering experiences in customer service, workplace, website, and commerce. We believe that search and generative question-answering need to be integrated, coherent, and based on current sources of truth with compliance for security and privacy — providing relevant answers every time.

At Coveo, we just launched our GenAI solution, Coveo Relevance Generative Answering.

We have seen unprecedented customer interest in this enterprise-grade Generative Answering that brings factually accurate and contextually relevant question-answering combined with enterprise-grade security from multiple sources of enterprise content. Coveo Relevance Generative Answering brings Large Language Model (LLM) technology on top of the secure unified indexing and relevance capabilities of Coveo's market-leading Relevance Cloud AI platform. This makes generative answering using LLMs applicable within enterprise — where security, privacy, factuality, real-time sources of truth, relevance, and access to multiple sources of content are all key imperatives. This is more than a decade in the making, building on Coveo’s powerful Relevance Cloud AI Platform.

Coveo's Relevance Generative Answering capability is designed to solve eight critical GenAI challenges:

1. Vulnerable Environment – The Coveo Relevance Generative Answering solution is built on top of Coveo’s secure indexing at its core. Robust security measures protect valuable assets, ensuring data remains secure throughout the generative answering content generation process.
2. Lack of Confidentiality and Privacy – Coveo Relevance Generative Answering protects confidentiality and privacy, ensuring that valuable data remains secure within organizational boundaries and proprietary content is not shared with public engines or used in a generated answer.
3. Hallucinations or Lack of Accuracy – Leading brands cannot hallucinate. The Coveo Relevance Generative Answering capability maintains factual accuracy at scale without compromising a brand's credibility.
4. Outdated Facts and Answers – Coveo Relevance Generative Answering leverages real-time data sources from the unified index, enabling answers to be generated that are consistent with enterprise content.
5. Non-Compliancy and Validity – Coveo Relevance Generative Answering establishes seamless links with sources of truth, allowing users to verify and validate the accuracy and credibility of generated answers.
6. Content Decentralization – Coveo Relevance Generative Answering is built on the power of the Coveo unified secure indexing and enrichment of enterprise content using Coveo AI. By integrating multiple content sources securely, it enables exponential growth in generative AI capabilities.
7. Siloed Search and Chat Channels – Search and generative answering should not operate as separate silos; the future lies in their coherent integration. Coveo Relevance Generative Answering bridges the gap by delivering a unified and consistent user & veracity experience across all search and chat channels, as they are fed from the same unified index and relevance mechanisms.
8. Generative AI Chat Is Expensive – By leveraging advanced search and relevance algorithms combined with LLMs, Coveo eliminates the need for costly alternatives. With this approach, enterprises can get results for a fraction of the cost typically associated with generative AI, offsetting the fact that chat can be 100x to 1,000x more expensive than query-based search.

In your opinion, what do you think will be the next big trend in marketing that will surpass personalization in terms of industry buzz?

Personalization remains a cornerstone of strategic marketing.

In the B2B world, there is a big movement from traditional lead generation to ABM - Account-based marketing. MQL, leads, and form-fills are old ways of doing business that make our customer journey difficult and even painful. Some people are saying that MQLs are dead; they may not be dead, but when you think about it, they are not so relevant in a customer-centric go-to-market.

To explain ABM vs. Traditional Marketing, I often use the fishing metaphor.

Traditional Marketing can be compared to net fishing, where the goal is to cast a wide net and capture as many fish as possible. Then you can reject the ones you do not want and hope the best ones will stick.

On the other hand, Account-Based Marketing can be likened to spearfishing, which is much more targeted and precise. Instead of casting a wide net, ABM focuses on identifying specific high-value target accounts and decision-makers within those accounts. This approach is akin to a surgical strike, where the marketing and sales teams collaborate closely to tailor personalized experiences for each account.

The core of ABM lies in understanding the unique pain points, needs, and objectives of each target account. By gaining a deep understanding of the challenges faced by a particular company or organization, marketers can develop tailored content, messages, and marketing campaigns.

ABM and Personalization are not new, but the reality is that they will still be a priority for many marketing teams for the next 2-3 years.

What major goals do you aim to accomplish as a marketing leader over the next five years?

Growth. Growth. Growth. At Coveo, the potential ahead of us is truly exhilarating. We are fueled by excitement, and it’s crucial that we maintain our focus and momentum as we move forward.

In order to support and fuel this Growth, my aspiration is to continue to build the best B2B marketing team in the world. To realize this vision, our people will be at the core of our success. I want them to feel happy, motivated, and curious, as these attributes fuel creativity and innovation. Encouraging a culture of constant learning and development will enable us to remain at the forefront of marketing practices and technologies. To achieve greatness, we must be committed to "getting better at getting better." I want our team to embrace a culture of continuous analysis and improvement. Complacency is not an option. We must challenge the status quo and constantly seek ways to enhance our strategies, processes, and outcomes.

Moreover, I value a growth mindset. I want our team to approach challenges with tenacity and a willingness to take risks.

Ultimately, success will come not only from the brilliance of our technology but also from the passion, dedication, and collaboration of our people. Together, we can exceed our potential and make Coveo AI a beacon of innovation and excellence.