• Predictive AI can anticipate when a customer is most likely to churn and trigger retention campaigns before it happens.
• Generative AI can personalize email content, product recommendations, or even ad creative for each user at scale something manual teams could never achieve.
• Journey orchestration platforms infused with AI can adapt the next best action for a customer as their context changes, rather than locking them into a rigid funnel.

• Customer Data Platforms (CDPs) powered by AI can reconcile identities across multiple touchpoints, resolving fragmented profiles into a single source of truth.
• AI can also cleanse, enrich, and normalize messy legacy data turning previously unusable information into actionable insights.

• Data scientists and marketing technologists will become core to every team, bridging creative storytelling with analytical rigor.
• Copywriters will evolve into AI content strategists, leveraging generative tools to ideate and scale.
• Campaign managers will transition into journey architects, focusing on customer experience orchestration rather than one-off campaigns.

• Trust & Transparency: Customers want to know when they’re interacting with AI, and they expect responsible data usage. Clear disclosure and ethical guardrails are essential.
• Bias in Models: If AI is trained on biased data, it will deliver biased outcomes. Companies must actively monitor, audit, and retrain models to ensure fairness.
• Change Management: Marketers often resist AI adoption because it challenges familiar workflows. The answer is gradual integration, strong governance, and upskilling programs.

1. As demand for multi-gig broadband services grows, how are you helping customers align product innovation with infrastructure investment to ensure sustainable market expansion?

Today, broadband leaders need the operational agility to launch new products, packages and bundles in days, not months. As customers expect faster, more personalized experiences, organizations need the infrastructure flexibility to adapt to market trends in real time and bring tailored offerings to customers.

Mediacom comes to mind as a perfect example of a broadband leader that knows how to scale and innovate without leaving existing customers behind. As the demand for multi-gig broadband continues to accelerate, Mediacom is expanding one of rural America’s most robust 10G broadband platforms. While growing their customer base, they are swiftly bringing new innovations to the market, ensuring their existing customers can maximize the value of their services across cable television, internet and telephone.

CSG works with broadband leaders like Mediacom to create operational efficiencies and to secure customer loyalty with a personalized, timely experience.

2. How are you helping organizations integrate real-time customer data to drive personalization, reduce churn, and enhance customer loyalty?

Loyalty is more critical than ever for sustainable growth, as it leads to increased customer lifetime value, higher profit margins and more stable revenue streams.  In a crowded market, customers are more inclined to make decisions based on value and their experience with the brand, rather than service capabilities alone.

With that in mind, organizations need to prioritize clarity and personalization in every customer interaction.

First, they need to understand the customer. CSG helps organizations break down data silos to get a complete view of the customer across all lines of business. Second, they need to take action. With operational agility, organizations can use that data to deliver clear, contextual communications and quickly build new, personalized offerings that they know will resonate and drive loyalty.

3. What role do automation and proactive service delivery (e.g., proactive billing insights or order accuracy) play in your customer experience and operational efficiency roadmap?

Automation is crucial to deliver a proactive, timely customer experience at scale. But an automation strategy needs to be carefully scoped and designed with the customer in mind.

AI is not the answer to every problem. When approaching new AI use cases, organizations should focus on ones that positively impact their customers the most  – identifying and solving breaks in the customer experience, strengthening data security and ensuring order accuracy.

CSG Bill Explainer, for instance, is an AI-powered solution designed to solve bill confusion, a multi-million-dollar problem for subscription businesses and a driver for as much as 50% of contact center volume. Organizations use CSG Bill Explainer to proactively reach out to customers in their preferred channels to explain changes to their bill – before they need to ask. This customer-focused automation allows organizations to reduce billing-related inbound contact, increase on-time payments, reduce contact center volume and build trust with customers.

4. How do shared values and a people-first culture influence your choice of technology or service partners, and how do you evaluate the long-term impact of these relationships?

To me, being a people-first company means that we care deeply about our customers and the outcomes we deliver. We care about trust and authenticity, and we don’t overpromise.

We choose strategic partners that share those same values and help us solve real problems, not buzzy trends. Our partner ecosystem is designed to eliminate complexity, accelerate innovation and scale solutions for sustainable growth.

Those shared values are also what makes our customer relationships so enduring. Once again, our relationship with Mediacom is a prime example. With three decades of successful collaboration, our business relationship has been built on mutual trust, a shared commitment to customer-centric innovation and a focus on delivering intuitive experiences. United in our goal of creating clear, connected experiences, we’ve achieved serious value and positioned Mediacom to meet and exceed expectations today and in the future.

5. What criteria do you prioritize when extending long-term partnerships to ensure alignment with future business goals, customer needs, and technological evolution? 

Great question – because it really is about the future. When evaluating long-term partnerships, we focus not only in creating value today, but long term value. It’s never a one-and-done; it’s about helping our customers prepare for anything the future may hold.

Success to us is when our customers can move with total agility, responding to their customer needs in real time while planning for future customer expectations.

Take our expanded partnership with Amazon Web Services (AWS), which we’ve just announced. The fact is, organizations that don’t move to the cloud and embrace AI today will fall behind. In particular, telecom and financial services companies are under enormous pressure to modernize and innovate faster. We partnered with AWS to help our customers fast-track cloud transformation and gain access to advanced GenAI and agentic AI solutions, so they can innovate with confidence in the AI-driven future.

6. What emerging technologies are you exploring to enhance broadband delivery, reduce service friction, and create new revenue opportunities in a saturated market?

I’d be remiss not to bring up AI again. Broadband leaders are facing an ultra-competitive market, where customers have sky-high expectations for value. By applying AI to create faster, easier and more personal experiences, broadband providers can stand out and win.

As broadband and other organization leaders plan for the future, they will need to view AI not only as a way to cut costs, but as a tool for sustainable value-creation. We’re helping our customers identify the right AI applications and use cases for their businesses – ones with clearly defined scopes that actually solve a problem and generate value.

For example, when it comes to agentic AI, the opportunity is enormous – but so are the risks. A true agentic AI solution is completely autonomous, with the agency to remember, decide and execute. That means that it must be applied very thoughtfully, ideally layered over a platform that already understands the customer and the business. In fact, despite the amount of market chatter, right now there are only a handful of use cases where agentic AI works reliably. We’re helping organizations find the areas where they have the data, the system integration and the governance for agentic AI to be effective and trustworthy.

Get in touch with our MarTech Experts.

1. How does the ACE generative AI tool differ from traditional ad‑optimization tools, and what measurable impact has it made on advertiser ROI so far?

The ACE (Adaptive Content Engine) generative AI tool represents a step-change in creative optimization for performance marketing within the Rokt platform. Unlike traditional ad-optimization tools that rely heavily on manual A/B testing or rule-based systems, ACE leverages advanced generative AI models trained specifically on Rokt’s proprietary Transaction Moment dataset. This enables it to generate and adapt ad creatives in real time, tailored to highly specific transactional contexts and consumer intent signals.

Whereas traditional systems typically iterate on a limited set of static variants, ACE dynamically crafts new creative variations that reflect subtle but impactful differences in tone, format, copy, and visual elements. It uses natural language generation, machine learning, and experimental design to systematically find the wording that resonates best with each audience, often yielding substantial conversion lifts (on average ~21% lift in conversion rates). It does so with a deep contextual understanding of what performs best on Rokt.

Advertisers using ACE have seen measurable performance gains, with the tool consistently delivering improvements in click-through rates, conversion rates, and ultimately return on investment (ROI). In benchmark testing, ACE-generated creatives have outperformed legacy variants by +20% conversion rates across key verticals. These gains translate into more efficient customer acquisition and higher revenue per impression, particularly for brands focused on maximizing the impact of performance marketing budgets.

2. What synergies are you seeing post‑acquisition of Aftersell, particularly in terms of upsell opportunities during cart, checkout, and post‑purchase moments?

Aftersell’s native “Upsells” capability has already lifted average-order-value by 15 %+ for thousands of Shopify merchants. By merging that engine with the Rokt Brain, we’re now deploying the same bespoke cross-sell logic to enterprise-scale retailers on Rokt’s network, unlocking materially larger revenue pools. Integrating Rokt Thanks into Aftersell lets merchants convert what was once a passive confirmation page into a high-intent engagement surface, delivering fresh incremental profit while preserving a premium shopper experience. The enhanced commercial model from this gives us reinvestment firepower to keep building first-party tools that compound those gains for merchants.

And, with Aftersell anchoring us in the DTC ecosystem, Rokt Ads can now reach a new segment of brands while simultaneously giving the entire network access to a broader pool of high-quality advertisers. Ultimately, this leads to more ad demand diversification and better results for our ecommerce partners and advertisers. 

3. You grew revenue by 40 % YoY to reach $600 million. What were the key levers of that growth, and what does 2025 look like from a revenue‑strategy perspective?

In 2024, we drove a 40 % year-over-year lift to $600 million by landing a wave of new ecommerce partners—vastly expanding supply—and by unlocking higher spend from existing advertisers across the network. For 2025, our plan is to compound that momentum by focusing on four priorities: first, elevating relevancy so every impression shown to shoppers performs better; second, broadening demand by winning new client segments and verticals; third, rapidly scaling Rokt Pay+, which turns the payments page into a profit engine; and fourth, integrating mParticle to deepen our CDP capabilities. Alongside these initiatives, we will keep pushing both supply and demand growth aggressively, onboarding bigger brands and powering transactions at an even faster clip.

4. What are the most overlooked moments in the ecommerce transaction journey where you are delivering hidden value for clients?

Ecommerce teams usually fixate on acquisition and product pages, but the quiet profit is hiding in checkout. For example, Rokt turns what merchants see as a cost center (the payments step) into a revenue engine by letting payment providers and BNPL partners compete for a placement, so every click monetizes itself without adding friction. In other placements, such as the cart, our ML can surface in one-click add-ons that lift AOV before the order even finalizes, while the order-confirmation page surfaces premium first- or third-party offers that convert at engagement rates multiples above standard ads. By optimizing these moments, Rokt consistently unlocks incremental dollars per transaction and upgrades overall unit economics that most brands never realize are possible.

5. What advice would you give to ecommerce brands looking to drive more value at the point of transaction without compromising customer experience?

To drive more value at the point of transaction without compromising the customer experience, it’s critical to start by letting data guide every decision. Treat each checkout change as a hypothesis: instrument the funnel end-to-end, set clear success metrics such as incremental revenue per session or attachment-rate lift, and test relentlessly. Evidence-backed micro-optimizations always win over sweeping, unvalidated redesigns and protect the shopper experience while surfacing new revenue. Equally important, ensure strong foundations, especially identity resolution. When you can reliably recognize a shopper across devices and sessions, you can present tailored offers, payment methods, and loyalty nudges that feel helpful rather than intrusive, which ultimately drive more incremental revenue. A strong data foundation turns checkout into a moment of relevant value instead of an upsell that clutters the journey.

6. How does your recent appointment—and those of your fellow leaders—support Rokt’s broader goals for growth and innovation?

My role as CPO is to integrate our products—Rokt Ads, Pay+, Thanks, and Aftersell—into one cohesive, AI-powered platform that helps brands and retailers deliver more relevant experiences at the moment of transaction. It’s about turning our data and AI advantage into products that are simple to use, drive real results, and become essential to our partners.

Claire, as Chief AI Officer, is making sure our models continue to get smarter, faster. Her team is building the AI capabilities that power everything from relevance to creative generation—like our new ACE (Adaptive Content Engine) tool—and making sure that innovation is responsibly applied and easy to integrate into our products.

Pete, as SVP of Advertiser Partnerships, is focused on growing and strengthening our advertiser ecosystem. He’s helping us bring in new categories and deepen relationships with top brands, which feeds even more data and demand into the platform.

Together, we’re tightening the loop between product, AI, and partnerships—so Rokt can keep pushing the boundaries of real-time relevance and fuel the next phase of our growth.

Get in touch with our MarTech Experts.

1. How does the ‘4 Voices’ strategy you created influence the way you approach enterprise CX and research programs?  

The ‘4 Voices’ strategy—Customer, Partner, Employee, and Market—reflects my belief that there is no single pathway to truth in CX or research. Each voice offers a distinct perspective, and only by listening holistically can we uncover insights that are both grounding and surprising. This multi-perspective approach deepens our understanding, surfaces systemic patterns, and ensures that strategy and action are based on a more complete view of reality. In enterprise environments, this triangulation is essential—it aligns teams, clarifies priorities, and converts  fragmented feedback to focused, cross-functional execution.

2. How can organizations move beyond simply collecting feedback to activating it across business units?

Collecting high-quality feedback at scale is challenging—but without connecting it to business decisions, it becomes a pleasant commodity rather than a catalyst for change. Moving beyond collection means designing feedback programs with business outcomes in mind. Every metric should have a clear owner and a defined action if performance declines. This creates accountability and ensures that signals resonate with both customer needs and operational priorities. Metrics must be meaningful, not abstract —translating sentiment into tactical insight. Ultimately, activation happens when data is embedded in workflows, and teams see the clear link between feedback, action, and impact.

3. What methodologies do you recommend for aligning research insights with measurable business outcomes? 

To align research insights with measurable outcomes, I advocate for a mixed-method approach grounded in business impact. But outcomes don’t exist in a vacuum—customer sentiment, behavior, and intent are always relative: to the market, to competitors, and to past experiences. That’s why I recommend using relative metrics alongside standard KPI; they better reflect the customer’s context and decision-making lens. It’s equally important to model barriers to those outcomes—understanding not just what customers want, but what’s preventing them from getting there. When research accounts for both drivers and friction, it becomes a far more powerful tool for driving focused, ROI-positive action.

4. What role does action-first thinking play in closing the gap between customer feedback and business performance? 

Action-first thinking fundamentally reshapes how we approach feedback—it shifts the mindset from passive analysis to proactive readiness. Instead of waiting to interpret what feedback might mean, we design systems with predefined responses so that signals trigger action, not debate. This posture assumes that teams are ready to respond, and the data simply tells them when. Often, we don’t need four-decimal precision to intervene; where there’s smoke, there’s usually fire. The goal is to empower teams to act —autonomously and swiftly—to investigate, triage, and improve without waiting for perfect clarity. This is what closes the gap between listening and performance.

5. In your view, what differentiates companies that sustain long-term CX excellence from those that fall behind? 

Many companies aspire to be customer-centric but often settle for being merely customer-focused—responding to feedback without truly redefining their strategy around customer value. The key difference is that customer-centric organizations identify what truly creates value for their target personas and actively engineer strategies to deliver on those needs, even when it requires bold pivots. They don’t just improve the current experience—they reimagine it. These companies are also more discerning about whom they serve best and more deliberate in designing for those use cases. Crucially, they build innovation and adaptability into their core—developing the muscle memory to evolve as customer expectations shift. The ones who master 10x innovation are often better at 10% improvements, too, sustaining CX excellence over the long term.

6. How will your capabilities evolve to meet emerging demands around real-time CX, personalization, and predictive analytics?

We’re actively investing in capabilities across real-time CX, personalization, and predictive analytics—but just as critically, we’re focusing on preparing customers to embed these capabilities into their everyday routines. Measurement has come a long way—today we can detect a bad experience in real time, even before the customer leaves the parking lot. But that speed is meaningless without companion systems that empower employees to respond with equal agility. Personalization, often misunderstood, isn’t about treating every customer as entirely unique; it’s about recognizing archetypes and delivering mass-personalization that aligns with those distinct cohorts. On the analytics front, we’re extending from predictive to prescriptive—using models and knowledge bases to recommend the most probable high-impact actions. While humans will always make the final call, these tools de-risk decisions and help build the muscle for consistent, everyday experience-making at scale.

Get in touch with our MarTech Experts.

1. How can brands foster more emotional bonds with customers, and why is it so important to do so?

Emotional bonds aren't just "important" for businesses anymore — they're make or break. I think as consumers ourselves, we all understand that pretty well. I mean, when I connect with a brand personally, I don't just shop there occasionally…I become their unofficial ambassador.

The challenge is that building a brand customers love has typically been limited to delivering great products and great customer service. Because, let's face it, it was always much harder to achieve that with truly great marketing. Highly personalized, contextual marketing has been too hard for brands to achieve with the tools and technologies they had available to them.

AI is shattering these limitations – not incrementally, but completely. We're witnessing a radical shift where every single customer touchpoint can be uniquely tailored to each customer’s needs and context. When we use AI to personalize at human scale – making every email, push notification, or interaction feel like it came from someone who deeply understands you – customers don't just feel satisfied, they feel a genuine emotional connection.

2. How does a shift from transactional incentives to emotional drivers in marketing influence brands’ approach to customer loyalty?

We all know that coupon shoppers aren't loyal shoppers. They may provide a quick hit to your quarterly KPI, but they won't help you build a lasting brand. True loyalty only emerges when your brand means something deeper than the price tag.

And you really can’t make your brand mean something to a customer if you don’t understand your customer. So at the heart of the shift from transactional incentives to emotional drivers is a deep, connected understanding of customer data. Not siloed data living in disconnected systems, but a unified view that reveals who customers truly are and what genuinely motivates them.

3. What role does post-purchase engagement play in converting customers into brand advocates?

The post-purchase experience is where advocacy either solidifies or dies, but it’s really common for marketing teams to underestimate its importance! We obsess over acquisition but then revert to generic communication after purchase.

Of course, there are a lot of customer service-related actions that play a role in driving post-purchase loyalty… easy returns, for example (in a similar vein, our loyalty report with EMARKETER found that services like available customer support and free delivery are key to customer retention).

But don’t overlook the impact that genuine emotional connections and deep personalization can have in post-purchase, too. Personalized recommendations and follow up communications, reminding customers when it might be time for a product refill… these post-purchase, personalized touches can play a huge role in helping brands strengthen their relationship with customers.

4. How can brands ensure consistency in emotional engagement across various customer touchpoints and channels?

The fragmented, channel-by-channel approach to emotional engagement isn't just ineffective—it's actively damaging the connections we're trying to build with customers. When Monday's email feels deeply personal but Tuesday's push notification screams "generic discount," we're not just missing an opportunity; we're eroding trust.

This is where AI really makes a difference, particularly now as agentic AI is making marketing more autonomous. Brands can leverage agents to create this kind of message consistency across every channel —  from email and SMS to social media and in-app notifications — and can do that at scale for every customer. It lessens the manual burden of trying to create this kind of experience, and unlocks a level of scale that really hasn’t been possible until now. With AI, you can ensure that every customer is receiving a personalized, consistent experience with your brand, attuned to the emotional drivers they actually care about.

5. How can organizations address potential trust issues that may arise from negative customer experiences or brand missteps?

Trust isn't built through perfect execution. It’s built through authentic human response when things inevitably go wrong. It's how you handle the stumbles that defines your brand's emotional connection with customers. When missteps happen (and they will), transparency isn't just the ethical choice; it's the only strategy that preserves the emotional bonds we work so hard to create.

Along with that transparency, there needs to be clear value creation. If customers don't believe that sharing their data results in genuinely better experiences that matter to them personally, you’ll never build a strong relationship. We need to fundamentally reimagine the value exchange between brands and customers — transforming data collection from a transaction into a partnership where both sides clearly benefit from deeper, more meaningful connections.

Get in touch with our MarTech Experts.

1. How does an organization's social media strategy align with the finding that consumers primarily follow brands to stay informed about products/product updates?

Consumers primarily follow brands on social media to stay informed about products, but their expectations go beyond just updates. They’re looking for education, inspiration, and proof of product quality. That’s why an effective social strategy must deliver consistent, value-driven content that speaks to each of these needs. At Emplifi, we empower brands to scale this approach; enabling teams to collaborate across markets and product lines, supported by AI for scale, to deliver timely, relevant content and measure its impact. The brands that succeed are those that use social not just to promote, but to educate, engage, and build lasting trust.

2. With Instagram Reels and TikToks accounting for brand posts, are content strategies adapting to prioritize short-form video content? 

With Instagram Reels and TikTok videos now representing a significant portion of branded content, brands must evolve their content strategies to prioritize short-form video as a high-impact tool for reach and engagement. Consumers increasingly crave authenticity and fast, value-driven interactions. In fact, short, unpolished content is one of the top ways to win attention, according to recent findings.

To meet this demand, brands should focus on producing concise, visually compelling videos that highlight product features, showcase customer stories, share practical tips, and deliver data-informed insights. (Or finding these online with the help of AI based technology that can identify user generated content for you.) These formats are uniquely positioned to capture attention within seconds and convey clear value, making them highly effective across both B2C and time-constrained B2B audiences. By optimizing content for platforms like Reels and TikTok, brands can meet consumers where they spend time while maintaining the relevance and credibility today's audiences expect.

3. What initiatives are being implemented to increase audience engagement?

To increase audience engagement, brands should focus on creating content that sparks interaction, feels personal, and offers immediate value. Insights from our report show that consumers today want authenticity, entertainment, and a real sense of connection - not just polished marketing messages. This means moving away from one-size-fits-all messaging and tailoring content to what your audience actually wants to see, whether that’s quick how-to videos, behind-the-scenes looks, user-generated content, or timely, relevant conversations.

Since short, unpolished content wins attention, formats like short-form video, polls, questions, and stories often drive stronger engagement than static posts. Additionally, encouraging and sharing user-generated content builds trust and deepens audience connection. A/B testing different approaches can help uncover what resonates most.

Ultimately, the goal is to create content that invites participation, not just passive consumption. The more your audience feels seen, heard, and inspired to respond, the more meaningful your engagement will be.

4. The report indicates that 70% of consumers will abandon a brand after just two negative experiences, what strategies can brands have in place to monitor and improve customer interactions on social media?

The report highlights that 70% of consumers will abandon a brand after just two negative experiences, making it critical for brands to proactively monitor and improve customer interactions on social media. To address this, brands should implement real-time social listening to ensure no customer question, concern, or mention goes unnoticed. Leveraging AI-powered sentiment analysis helps detect shifts in customer mood early, enabling brands to flag potential issues and quickly escalate them to the right teams, whether for product improvements or crisis management. With technology it is possible to leave no stone unturned.

Brands can also benefit from streamlining social customer care through automation. Tools that support pre-populated responses for frequently asked questions and automated case management enable teams to respond faster, possibly achieving the ever allusive “first contact resolution”, and more consistently.

For example, Emplifi’s solutions have helped clients reduce handling times by over 80% and increase resolved cases more than tenfold, demonstrating how these strategies can translate into real business results. Adopting such approaches not only improves customer experience but also builds long-term loyalty by preventing negative interactions from escalating.

5. How should organizations calculate and interpret social media engagement rates to inform strategic decisions?

Engagement rate is ultimately a summary metric that aggregates many different interactions: likes, comments, shares, clicks - and serves as one piece of a larger puzzle. While it provides a quick snapshot of how content is performing, it’s important for brands to view it alongside deeper analysis of conversations and sentiment on social media. Together, these insights can guide strategic decisions beyond content creation, such as identifying emerging customer needs, uncovering potential product issues early, and inspiring innovation.

By interpreting engagement rates in context, brands can make more informed choices about where to focus marketing efforts, how to refine messaging, and when to pivot their strategy in response to audience feedback. This holistic approach ensures social media data drives smarter decisions across marketing, customer experience, and product development, helping brands build stronger connections and stay ahead of evolving consumer expectations.

6. What plans are in place to innovate your social media strategy to stay ahead of emerging trends and consumer behaviors in 2025?

Looking ahead, AI will play a crucial role in shaping social media strategies. As we move into 2025, brands will increasingly rely on AI to analyze audience behavior, identify trending topics, and predict the types of content that will resonate with specific segments. This technology will empower marketers to deliver hyper-targeted content, optimize posting times for maximum engagement, and create dynamic, personalized creatives. AI will also enhance customer interactions; whether through smarter product recommendations in DMs or AI-generated replies that maintain brand authenticity. Ultimately, AI will enable brands to engage at scale to meet the increasing demand without adding staff while keeping interactions personal and meaningful, making it the cornerstone of social media success in 2025.

At Emplifi, we’re already leading the way in providing the technology that enables marketers to leverage AI-driven insights, optimize content creation, and elevate customer engagement. Moving forward, we will continue to enhance our solutions, helping brands stay ahead of emerging trends and evolving consumer behaviors, while delivering even more personalized and impactful experiences for their audiences.

Get in touch with our MarTech Experts.