Interviews | Marketing Technologies | Marketing Technology Insights
GFG image

Interview

 Authentic Video Storytelling for Brand Trust

Authentic Video Storytelling for Brand Trust

marketing 12 Sep 2025

 

  1. How do you see organizations leveraging video formats (e.g., behind-the-scenes) to build trust with Gen Z and Millennial audiences?  

Video has evolved beyond a digital marketing tool to become a powerful force for human connection, especially among Gen Z and Millennial audiences. Social video is less about persuasion, as one might see with traditional advertising, and is more about entertaining and informing users: as iStock’s global research platform, VisualGPS, found, about half of Millennials (45%) and Gen Z (50%) say they use video‑first platforms for entertainment. Additionally, the VisualGPS research shows that 31% of people globally seek out videos on social media for inspiration and to learn something new. With these insights in mind, brands and SMBs should focus on video content that adds value to people’s lives to build interest in their brand by teaching viewers something new or sharing a personal story.

A staggering 98% of people say they value authenticity in the visuals they consume, which is one reason that behind-the-scenes content is becoming such a popular (and powerful) format. At a time when audiences are deeply skeptical of content they encounter online, video content that humanizes a business and comes from a place of authenticity is more likely to foster trust. To do so, businesses are adopting popular social video formats that mirror the content users are already looking for.

For example, a local bakery might work with one of their employees to create a “day in my life” video – a common lifestyle video format – to showcase the bakery from a behind-the-scenes perspective while giving audiences a personality to connect with. Meanwhile, a beauty brand might debut a new line of products with a “get ready with me” (GRWM) video–a format that is as much a vehicle for powerful personal storytelling as it is for showing the look and feel of a product. Our research shows that video-led personal journeys inspire empathy and engagement, and these first-person, narrative-focused formats are deeply compelling while fairly simple to produce 

All this to say, many small businesses don’t have the time or resources to produce 100% of their own content. They may also want to include visuals they can’t capture locally, or represent more diverse identities in their videos. To solve this, small businesses are utilizing stock footage to augment their video content. The right pre-shot imagery and footage can evoke a certain mood, heighten the impact of their message, and allow more audience groups to see themselves reflected in a brand’s content.

Overall, a combination of stock footage, smartphone video, and user-generated content will help brands and businesses to strike that coveted balance between authenticity and polish. 

  1. Which platforms are brands prioritizing in their video distribution strategy (e.g. Instagram, YouTube), and how do they adapt content formats to meet each platform's expectations? 

Brands are going where their audiences are going. Which social platforms they target will vary depending on which audiences that brands want to engage, where their brand social accounts already have a strong presence, and where they hope to grow. From there, brands are creating video content in line with the expectations of users on a certain platform. For example, TikTok content might play to a trending format or make use of a viral audio file to increase discoverability, while YouTube videos could be tailored for more intentional, appointment-style viewing.

A major trend of note is long-form content, which is gaining widespread popularity across platforms. It’s a shift that defies the reality of our shrinking attention spans and speaks to consumers’ appetite for valuable, authentic content. This is not to say that every brand should be churning out hours of video entertainment. Rather, the growth of long-form video gives brands more time and freedom to tell their stories.

  1. How effectively does video content reflect a brand’s personality—whether fun, premium, or purpose-driven?

If every piece of content is an opportunity to create a personal connection with a potential customer, then it’s best to portray your brand honestly and authentically. In engaging today’s consumers, personality and credibility go hand-in-hand. Video content that effectively showcases a brand’s personality is content that focuses on who the brand is, not just what it sells or how it operates.

Brands should also account for industry-specific nuances when creating content that expresses their personality. For example, health and wellness brands might consider showing how their products and services improve the lives of everyday people, rather than leveraging paid influencers, as 81% of people prefer to see real individuals actively improving their well‑being over aspirational imagery. Even sleeker, more “premium” brands can humanize their content by showing the passion and care that goes into the work. It’s all about leaning into personality in a way that compels audiences, but also feels truthful.

  1. Are SMBs using video to demonstrate products (e.g., unboxings, tutorials, testimonials) in ways that reduce buyer friction and increase conversions?

According to VisualGPS, 72% of consumers prefer video for product demonstrations, making them a crucial way for SMBs to help audiences understand their product and make informed purchasing decisions. Video allows for a 360-degree view that static online shopping doesn’t offer, as well as the injection of customer testimony or expert commentary from the seller. The more questions a business can answer about how their products look, feel, and function, the more likely they are to convert.

Fortunately for small businesses, these kinds of videos are not excessively expensive to produce, and audiences will value the authentic, realistic look at the product. These videos also offer another chance for SMBs to show off their personality, building further trust and amplifying the chance of conversion. 

  1. How do you quantify the impact of video storytelling on long-term customer loyalty and brand trust?

Our ongoing VisualGPS research looks at consumer sentiment over time, and our latest video insights reveal that approachable content told through diverse, creative formats are what resonate most with consumers, building loyalty and trust.

As for quantifying the impact of an individual campaign, each brand has its own specific metrics that matter most, but video content has been expressly linked to higher conversion rates, social engagement rates and improved SEO. SMBs and brands can also use UTMs to see if videos are driving web traffic and monitor for an uptick in product reviews, location check-ins, and social mentions.

And it’s not just quantity that matters: when posting visuals on social media, comments and direct messages from audiences can be valuable sources of qualitative feedback to help SMBs determine whether their video campaigns are resonating.

  1. How are you preparing your teams to scale video storytelling as part of a broader digital engagement strategy in a “video-first” environment?

Video content has been a core part of our offering at iStock, and we work with our content creators to produce compelling clips and footage that can be used for just about any project, whether it's for social media, paid ads, websites or digital banners. Creating and scaling original content, especially high-quality video content, can be cost-prohibitive for SMBs; stock footage enables businesses to create varied, personalized and more creative videos to engage a wider variety of audiences. With the variety of dynamic video options available to today’s businesses, it’s easy for them to find something that feels like a true fit for their brand and the story they’re trying to tell.

Scrolling and watching videos online is how so many people fill the downtime in their days, so brands and businesses want to enter these spaces without being invasive and overly advertorial. Video content that models what users are already seeking, while coming from a place of honesty and authenticity, is the ideal way in.

The secret to scaling storytelling is to mobilize your teams as storytellers. It’s important to look at the metrics and understand which content attracts which audiences, but the human element is what truly unlocks scalability without requiring a massive budget. Audiences have a keen sensibility for what’s real and what isn’t, and the best way to keep them engaged is through storytelling that feels honest.

Get in touch with our MarTech Experts.

 

 How Cleeng’s SRM® Model Redefines Subscriber Retention

How Cleeng’s SRM® Model Redefines Subscriber Retention

marketing 12 Sep 2025

When it comes to combating subscriber churn, nurturing long-term relationships is the key. Today, we sat down with Gilles Domartini, CEO and Founder of Cleeng, a subscriber retention management (SRM®) company to discuss strategies that can strengthen the subscriber engagement lifecycle and activate personalized, real-time approaches that can convert passive users into loyal subscribers.

1. You’ve described Cleeng as a “Subscriber Retention Management” company. How does that differ from traditional subscription platforms?

A Subscriber Retention Management (SRM®) system takes a more strategic approach to keeping subscribers engaged, reducing churn, and maximizing lifetime value. Our SRM® suite helps traditional subscription services optimize retention by leveraging data-driven insights, ensuring payment reliability, and providing robust customer support.

For example, our customers include traditional subscription platforms such as Univision, Volleyball World and Newsmax. By leveraging Cleeng, Newsmax gained over 150,000 paying subscribers within the first month and retained over 85% of those subscribers as part of the launch of Newsmax+, their OTT service that provides access to Newsmax for those without traditional cable subscriptions.

2. Can you share an example of how a small change in personalization led to a big impact on engagement or retention?

One example that comes to mind is our most recent work with Skyship Entertainment and how a simple change of streamlining their billing process to meet the demand for multi-channel offerings, led to impactful subscriber growth.

Skyship Entertainment is the company behind Super Simple Songs, one of the world’s most trusted educational brands for preschoolers, with 47 million Youtube subscribers. With an audience spanning millions of families worldwide, they wanted to scale their reach even further and offer a more premium, ad-free experience that children could use independently, with content parents could trust.

Specifically, parents wanted the ease and freedom to subscribe once and access the service across multiple devices, whether on iOS, Android, or Amazon tablets. By leveraging our multichannel billing solution, they were able to create a unified multi-channel experience, without making the experience complex for subscribers.

Over the past year alone, the platform’s subscriber base has grown by more than 140%, driven organically, by improving the onboarding flow, having seamless cross-device access, and increasing awareness through YouTube.

3. What’s one underrated metric companies should track more closely when it comes to churn prevention?

One underrated metric that companies should pay closer attention to is Time-to-Convert: the duration between when a user signs up and when they actually start a paid subscription.

While it happens at the very beginning of the customer journey, it can be a strong indicator of future churn risk. A long time-to-convert often signals friction in the onboarding process, a lack of perceived value early on, or hesitancy to commit. These are factors that can lead to weaker engagement and, ultimately, higher churn. Tracking this metric can help teams identify and address conversion bottlenecks before they turn into retention problems.

Yet, there are many more KPIs to succeed, like winback rate, cancellation rate, upgrade/downgrade, LTV. That’s the benefit of having a platform like Cleeng that helps you easily monitor those.

4. What are some UX mistakes you see platforms make that unintentionally drive users to churn?

One of the most common UX mistakes I see is not being transparent enough about trial periods and billing. When users aren’t sure when they’ll be charged or how to cancel, it creates mistrust and often leads to churn right after a free trial ends. A 65%+ conversion from free to paid is typically a good benchmark.

Another issue is making it difficult for subscribers to access their content across devices. If logging in or switching between devices isn’t seamless, users get frustrated and may give up on the service altogether. Nowadays, the web only accounts for 40% of connections (may vary substantially), and the vast majority of people connect on multiple devices.

But perhaps the most overlooked mistake is failing to support users when a payment fails. It represents between 30% to 50% of all churn. Many people churn involuntarily because their payment didn’t go through, not because they wanted to leave. If the platform doesn’t make it easy to resolve payment issues, you lose customers who actually intended to stay. Focusing on transparency, smooth access, and proactive payment support can make a real difference in keeping subscribers engaged.

5. How do you identify the “right moment” to deliver a specific message to a subscriber?

With D2C subscription models, brands are able to collect a significant amount of data from its subscribers, however the challenge that many of them face is efficiently extracting insights from the data and leveraging them to make impactful decisions. These data-driven decisions are crucial to identify that “right moment” to deliver messages to subscribers in order to stay competitive, maximize customer lifetime value.

Advanced AI tools can be beneficial to help streamline this process. With our ChurnIQ AI-ssistant, we help brands get precise answers from their data without the need for deep analytic expertise, which can be both costly and time consuming. Brands can leverage AI-ssistant by asking simple prompts, which will then quickly generate data visualizations, and uncover hidden trends and patterns from their subscriber dataset. These insights can then be used to send those specific messages, uplevel retention strategies, adapt to evolving customer needs and enhance user experiences.

6. If you could give one piece of advice to D2C leaders trying to improve retention, what would it be?

If I could offer one piece of advice to D2C leaders focused on improving retention, it would be to treat retention as a core discipline, not just a byproduct of great content. Retention success requires more than reactive strategies; it depends on having the right infrastructure to support seamless subscriber experiences across billing, offers, payments, customer care, and data analytics.

Too often, platforms rely on fragmented tools or internal builds that are hard to scale or adapt to changing needs. Instead, it's worth investing in solutions that are purpose-built for subscriber businesses. These should offer automation, actionable insights, and the flexibility to support multiple models such as subscriptions, pay-per-view, or seasonal passes.

What sets the most resilient platforms apart is their ability to respond quickly to churn signals, optimize the right levers, and experiment without being held back by complex systems or limited resources. In a competitive and fast-moving landscape, adaptability and operational precision are essential for long-term retention and growth.

Get in touch with our MarTech Experts.

 The Future of MarTech: AI, CX, and Personalization

The Future of MarTech: AI, CX, and Personalization

customer experience management 11 Sep 2025

1. From your perspective, what does “The Future of MarTech” mean, and why is AI at the center of this transformation?

The future of MarTech is about creating seamless, intelligent, and adaptive marketing ecosystems that move beyond campaign execution to real-time customer orchestration. AI sits at the center because it enables what traditional marketing tools could never fully achieve contextual personalization at scale. Instead of marketers pushing static messages, AI allows us to listen, learn, and respond dynamically to individual behaviors, preferences, and intents. It’s not just about automation; it’s about intelligence woven into every layer of the stack.
 
2. Can you share specific ways AI is enabling personalized customer journeys compared to traditional MarTech solutions?

Traditional MarTech relied heavily on rules-based segmentation, grouping customers by demographics or predefined personas. AI transforms this by leveraging machine learning models that analyze behavioral, transactional, and contextual data in real time. For example:
  • 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.
This level of personalization creates fluid, living customer journeys instead of static pathways.
 
3. Many organizations struggle with data silos and legacy systems. How can AI-driven MarTech help overcome these barriers?

AI thrives on integrating and harmonizing disparate data sources. Modern AI-driven MarTech platforms use natural language processing, entity resolution, and advanced data unification models to break down silos.
  • 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.
In short, AI doesn’t just sit on top of legacy infrastructure; it acts as the bridge that makes fragmented systems interoperable.
 
4. How do you see AI reshaping marketing team structures and skill sets in the next few years?

AI will redefine roles rather than replace them. Marketing teams will shift from execution-heavy functions to strategy, creativity, and oversight.
  • 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.
The key skill sets will be prompt engineering, AI ethics, data literacy, and cross-functional collaboration, alongside the timeless need for creativity and empathy. 
 
5. What do you see as the biggest challenges in AI adoption for customer engagement, and how can companies address them?

The biggest challenges are trust, bias, and change management:
  • 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.
Addressing these challenges requires a balanced approach equal parts technology, governance, and culture shift.
 
6. Do you believe AI will replace traditional marketing strategies, or will it serve as an enhancement to human creativity and strategy?

AI will augment, not replace. The essence of marketing lies in human insight, creativity, and empathy. Qualities that machines cannot replicate. AI will take over the repetitive and data-heavy tasks, freeing marketers to focus on strategy, storytelling, and innovation.
Think of AI as the co-pilot: it can analyze billions of signals, suggest the best path forward, and even create variations at scale but the vision, the brand voice, and the emotional connection must remain human-led.
The future of marketing is not man versus machine, but man with machine - a partnership where technology amplifies creativity.
 
Get in touch with our MarTech Experts.
 
 EDO’s Joshua Lee on Data-Driven TV Outcomes

EDO’s Joshua Lee on Data-Driven TV Outcomes

advertising 11 Sep 2025

Advertisers face rising pressure to prove the value of their TV investments, especially in a fragmented market and amid ongoing economic uncertainty. Traditional planning often forces a trade-off between broad reach and measurable outcomes — a compromise many marketers can't afford to make.

EDO, the TV outcomes company, uses predictive engagement data that correlates to future sales to help advertisers bridge that gap. With tools like Engaged Audience Planning, EDO enables brands to test investment scenarios within their existing workflows and identify strategies that deliver both scale and performance. Joshua Lee, EDO's Chief Technical Officer and Head of Product, shares how the company's approach is helping advertisers plan with greater confidence.

1. What does the setup and onboarding process look like for advertisers using Engaged Audience Planning for the first time?

Media planning today is complicated enough, so we’ve made onboarding to Engaged Audience Planning as easy as possible. This process doesn’t require a new workflow or integration; we align with advertisers’ existing planning tools, like those from Nielsen, Kantar Media, or VideoAmp. Clients can see which scenarios offer the best combination of reach, engagement, and cost efficiency — all before a dollar is spent.

Advertisers simply share their existing media plans — including scenarios and metrics like GRPs or CPMs — with EDO. From there, our team maps the plans to EDO’s cross-platform TV outcomes data, calculating engagement rates and outcome efficiency for each scenario. This provides a clear, side-by-side comparison that illustrates how different investment scenarios can result in various combinations of audience impressions and outcomes.

2. EDO has measured over 110 trillion cross-platform impressions — how does this dataset power the predictive models behind the solution?

EDO’s dataset spans every major linear network and a growing number of streamers, enabling us to model how different audiences respond to ads. Our predictive models analyze ad-driven behaviors, such as brand search, website visitation, and LLM chat engagements, which are proven indicators of consumer intent. Using vertical AI to analyze engagement across trillions of impressions and hundreds of industries, we surface meaningful patterns that predict future performance by program, daypart, genre, and more. This enables us to forecast engagement outcomes at scale and optimize our approach toward them before campaigns even begin.

3. Can advertisers using other platforms (e.g. Adobe, etc.) also integrate EDO’s data for unified planning?

Whether it’s Engaged Audience Planning or any other product in our suite, EDO data is designed to be interoperable. Whether a brand is using Nielsen, VideoAmp, Kantar, or agency planning tools from Dentsu, GroupM, or IPG, EDO’s outcome data can be layered onto existing plans with no disruption. We’ve structured Engaged Audience Planning to work flexibly within the tools clients already rely on, often using exported files to match and model engagement outcomes. There’s no need for a formal integration or technical relationship to get started.

4.  In what ways does Engaged Audience Planning support both brand awareness and performance marketing objectives simultaneously?

Traditional audience planning often forces a trade-off between brand reach and performance. With EDO’s data, advertisers no longer have to choose. Our solution helps brands identify plans that deliver both strong audience reach and measurable outcomes. That means marketers can optimize their investments for mid- and upper-funnel KPIs in tandem — a growing priority in convergent TV, where brand and demand goals increasingly overlap.

5. How do you see this tool fitting into or enhancing existing audience segmentation strategies used by brands?

Audience segmentation is essential, but advertisers don’t see the full picture unless they also know how viewers in each audience segment engage with the ads they see. By pairing outcome data with audience targets, EDO adds a crucial layer of intent to segmentation strategies, enabling advertisers to define their audiences and test which environments actually drive those segments to take action. This enables more effective media planning, where audiences are prioritized on both relevance and predicted performance.

6. What message would you give to brands still hesitant to fully embrace data-driven, outcome-optimized planning in a convergent TV world?

The media landscape is only getting more fragmented, and guesswork simply won’t cut it. Brands that embrace outcome-based planning gain a competitive edge — not just in efficiency, but in clarity. EDO helps advertisers make more confident decisions by connecting plans to real consumer behavior. If you’re still relying on audience reach alone, you may be missing the plans that deliver better results for the same or lower cost.

Get in touch with our MarTech Experts.

 AI-Powered Search & Personalization: Insights from Algolia

AI-Powered Search & Personalization: Insights from Algolia

ecommerce and mobile ecommerce 11 Sep 2025

1. In what ways does combining manual curation with algorithmic ranking influence your approach to customer experience and conversion optimization?

Combining manual curation with algorithmic ranking allows us to strike a balance between creativity and scale. Manual curation allows retailers to highlight seasonal trends, sponsors, editorially chosen features, and other considerations that may not be picked up from an automated algorithm. This is a great addition to the algorithmic ranking that supports the massive scale of infinite searches and the various ways customers express their needs, whether it's finding a specific product or getting help for a unique scenario. This hybrid approach enhances the customer experience by allowing retailers to solve their customers’ needs more accurately and quickly while also reducing the operational overhead of fully manual configurations. We can leverage AI to help us interpret both user intent and business goals, leading to more efficient and effective conversion optimization.

2. How are you addressing the challenge of managing large or frequently changing catalogs, and what operational improvements could you unlock for your business? 

Large, complex catalogs are where accurate and efficient search and discovery becomes really important. The first step in managing large catalogs is making sure they are fully complete and content rich. Every product must have images, descriptions, and translations, or they simply won’t be found or purchased. Next, Algolia focuses on how we can make the catalog better. For example, we can curate and personalize it for specific audiences. This includes layering in rich content such as guides, how-tos and comparisons. Since generating this content is time-consuming and costly, we have given retailers the ability to automatically generate descriptive content using GenAI. And then lastly, make sure everything is operational. We use AI to create and rank content products, create category pages rich in content, and apply image recognition to match products beyond simple metadata. These improvements significantly boost operational efficiency while still elevating the customer experience.

3. How does the ability to personalize search results and category layouts align with your broader personalization strategy across digital touchpoints?

Personalization is most effective when every touchpoint feels relevant and intuitive to the individual, and takes into account who the customer is, their current needs, and informed by recent behavior. By tailoring search results based on behavioral signals, retailers can reduce friction and add true value to a consumer’s shopping experience. Beyond search, personalizing category layouts continues to show a deep understanding of individual preferences. For example, recognizing that one shopper’s “summer look” inspiration will likely be influencing a “back-to-school” wishlist. Beyond making a sale, this personalization builds trust and loyalty in a brand.

4. How are you currently exploring retail media as a revenue stream, and how are you enabling brand placement, sponsored content, or inventory-based monetization? 

We work closely with many customers who are investing in retail media and promote their own brands through sponsored content and strategic placements. Customers also have additional revenue streams by hosting channels. Our approach blends manual input with AI optimization. Creatively, we support the manual curation to ensure that particular sponsors or content types are featured in appropriate locations based on brand relevance. At the same time, we leverage AI within our search systems to rank and feature the most optimal products and content driven by real-time customer behavior.

5. Which departments beyond merchandising—such as content, marketing, or media—could benefit most from a no-code, AI-driven content positioning tool, and how will it shape interdepartmental collaboration?

Beyond merchandising, marketing teams would benefit significantly from the combination of creative freedom and intelligent automation, allowing them to tailor campaigns and promotions while introducing them at scale. UX and customer service teams also benefit and could learn more about the content people consume.

6. How important is it to have a unified tool that supports consistent yet localized product and content presentation?

It is incredibly important. Customers are far more likely to engage with—and ultimately purchase—products and content that feel tailored to their needs, location, and preferences. By leveraging a single platform, retailers can maintain brand integrity and quality while also delivering localized, relevant experiences.

Get in touch with our MarTech Experts.
 AI Conversation Intelligence: Edwin Miller & Marchex

AI Conversation Intelligence: Edwin Miller & Marchex

customer engagement 11 Sep 2025

1. How is AI-powered conversation intelligence transforming customer interactions and engagement?  
 
AI-powered conversation intelligence is redefining what it means to “know your customer.” For a long time, businesses saw voice as a black box: calls came in, agents responded, and maybe a CRM was updated, but the actual content and emotional tone of those conversations disappeared when the call ended. AI has shattered that limitation. Today, every conversation can be transcribed, analyzed, and mined for insight. That is not just about listening better. It is about understanding at scale.  
 
The impact is multifaceted. First, it enables a level of personalization that would have been impossible before. Let’s say a customer calls to inquire about financing options for a home renovation. Even if they don’t convert on the first call, the AI can flag buying intent and trigger targeted outreach within hours, via text, email, or even a follow-up call tailored to their budget and timeline. This moves engagement from transactional to relational.  
 
But it’s not just about sales. AI listens for tone, sentiment, pace, interruptions, and other subtle cues that indicate customer emotion. It can detect when someone is confused, frustrated, or overwhelmed even when the words themselves are neutral. That kind of emotional intelligence allows companies to proactively resolve issues, often before the customer has voiced a complaint.  
 
One of the most transformative elements is how conversation intelligence creates feedback loops between the front lines and the C-suite. Executives can see patterns emerging across calls, trends in objections, product issues, and competitive threats and respond strategically. Suddenly, voice is not just a customer service tool. It’s a source of truth that informs marketing, product development, staffing, and brand strategy.  
 
AI is turning conversations into a strategic asset. The companies that win today are those that can listen deeply and respond quickly. Conversation intelligence makes that possible. It doesn’t replace human empathy, but it scales it and that’s a game-changer.  
  
2. What role does AI play in improving customer support and sales through conversation intelligence?  
 
AI plays a pivotal role in making customer support and sales teams smarter, faster, and more effective. At its core, conversation intelligence powered by AI turns every customer interaction into a moment of insight. For sales, this means understanding exactly what motivates a buyer, what objections are slowing them down, and which offers or phrases tend to close deals. For support, it means diagnosing pain points quickly, resolving issues efficiently, and turning frustrated customers into brand advocates.  
 
Let’s take sales first. In traditional call settings, success was often a matter of the individual rep’s skill and intuition. But AI levels the playing field. By analyzing top-performing calls, it identifies which questions build trust, which objections require deeper education, and when silence signals hesitation. That knowledge is then made available across the team. Reps don’t have to guess anymore; use data to coach them.  
 
Every customer, regardless of whom they speak with, receives a high-quality, personalized experience tailored to what has worked best across the organization.  
 
For support teams, AI acts as a real-time assistant. It flags when conversations are starting to veer off course, the customer sounds increasingly agitated, or the agent is speaking too quickly. As deployments of automated AI support agents increase, it’s more important than ever that they be monitored for effectiveness and measured against CSAT scores. 
 
Supervisors can intervene if needed, or post-call training can focus on specific moments that are particularly important. It’s no longer about judging performance after the fact, but about enhancing it while the conversation is happening.  
 
Crucially, AI helps teams prioritize. If 100 calls came in today, which 10 need follow-up right now? Which customers are on the verge of churn? Which sales leads are warmest? Without AI, that triage is a matter of guesswork. With it, it becomes a precision tool for growth.  
  
3. What are the key challenges in ensuring data privacy and regulatory compliance in AI-driven conversations?  
 
One of the most significant responsibilities associated with AI in customer communications is protecting privacy and ensuring compliance. As powerful as AI-driven conversation intelligence can be, it also introduces a new set of risks, especially when it comes to recording, transcribing, analyzing, and storing sensitive conversations. And with data regulations tightening worldwide, companies can’t afford to get this wrong.  
 
The first challenge is consent. Depending on the jurisdiction, recording a call may require single-party or dual-party consent. That alone introduces complexity for organizations operating across multiple states or countries. AI systems must be designed to recognize the origin of a call and apply the appropriate rules automatically, both to prevent violations and to establish trust with customers.  
 
Next is data retention. Voice data is extremely rich, but not all of it should be stored indefinitely. Organizations need clear policies regarding what is kept, for how long, and for what purpose. More importantly, customers need visibility and control over that process. Can they request deletion? Can they opt out of analysis? These questions are no longer theoretical; they’re becoming table stakes for customer trust.  
 
Then there’s the issue of data masking and redaction. AI tools must be trained to automatically identify and remove personally identifiable information (PII) from transcriptions, including Social Security numbers, addresses, and financial details. This isn’t just good practice; it’s often a legal requirement.  
Finally, there’s the question of transparency. Many customers are unaware their calls are being analyzed by AI, even if they’ve accepted a recording disclaimer. Companies need to be more transparent about how that data is being used not just for compliance, but also for ethical reasons. AI should augment human service, not replace it. And it should never become a “black box” that customers can’t understand or question.  
The companies that handle this approach privacy not as a barrier but as a design principle. They build trust into the system from day one, and they communicate that trust. It’s not just about staying out of trouble, but about building brand equity in a world where data sensitivity is the new norm.  
  
4. How can AI-driven conversation intelligence be integrated across various digital and offline touchpoints? 
 
The beauty of modern conversation intelligence is that it doesn’t have to live in a silo. Its value multiplies when it connects across channels. A customer might call on Monday, chat on Tuesday, and click on an email on Thursday yet still expect a unified, coherent experience. AI can make that possible by acting as the connective tissue between those moments.  
 
The integration begins with centralization. All conversation data, whether it comes from voice, chat, SMS, or web forms, needs to be routed through a common intelligence layer. This allows AI to build a comprehensive profile of each customer, drawing on tone, intent, history, and outcomes across every touchpoint. When done right, the profile updates dynamically and is accessible to any team engaging with that customer.  
 
Imagine a home services company where a customer calls in to request a quote for HVAC installation. The AI captures that request, notes the urgency in their tone, and logs it. Later that week, the customer chats with a rep about financing. Because the AI has stitched those interactions together, the sales team can now follow up with a personalized message referencing both the HVAC inquiry and the financing options without asking the customer to repeat themselves.  
 
This also works in reverse. A social media comment can prompt a follow-up voice call. An email campaign can be tailored based on the language the customer used in a past phone call. The possibilities are endless but they all depend on conversation intelligence being integrated across platforms, not isolated within departments.  
 
Offline matters, too. Many of our clients operate in industries such as automotive, healthcare, or home improvement -- areas where calls and in-person visits still predominate. By integrating voice analytics with their CRM and POS systems, they can create a loop where insights lead directly to action. For example, if multiple calls indicate confusion about a warranty policy, that insight can prompt an update to in-store signage or a new script for frontline staff.  
 
Integration is not just about plumbing but about experience design. AI doesn’t just connect systems but connects people, moments, and expectations. And when it works seamlessly, customers feel like they are being heard—not just once, but across their entire journey.  
  
5. How does AI help tailor responses and recommendations based on individual customer interactions?  
 
AI tailors its responses by listening not just to what customers say but to how they say it, what they’re asking between the lines, and what they have said before. In traditional systems, personalization means inserting a name into an email or referencing a past order. With AI-powered conversation intelligence, personalization goes much deeper.  
 
The AI listens to intent and emotion in real-time. Suppose a customer calls for the third time about a billing issue. In that case, the system recognizes this as a potentially high-frustration interaction and routes them to a more experienced representative or even escalates the issue before the call begins. If a customer asks about service tiers and sounds hesitant, AI can prompt the agent with context-specific offers, FAQs, or scripts proven to address those exact objections.  
 
It also works post-call. Based on what the customer said, the system can trigger a personalized follow-up: a message that references specific phrases from the call includes a relevant offer or even matches the tone of the conversation. That kind of nuance was not possible before. Now, it is becoming standard.  
 
Crucially, this tailoring is not just a reactive approach. AI is always learning. It tracks which messages get opened, which calls convert, and which ones correlate with satisfaction or churn. Over time, it refines its recommendations, becoming smarter with every interaction. This means businesses are not just responding better; they are learning faster.  
 
It is the difference between speaking to customers and speaking with them. AI gives businesses the ability to adapt in the moment, read the room, and demonstrate that they are not just listening but understanding.  
  
6. What emerging trends in AI-driven conversations are likely to shape business strategies in the coming years?  
 
Several trends are converging to reshape how companies think about conversations, not just as interactions, but as data assets, brand differentiators, and strategic levers.  
 
First is real-time adaptive conversation. We are moving toward AI systems that do not just analyze, but participate during the moment. They provide agents with live guidance, coach on tone or pacing, and even suggest offers or rebuttals based on the flow of conversation. This will shift the frontline experience from reactive to predictive.  
 
The second is multi-modal integration. Voice data is being paired with video, screen sharing, and physical behavior (such as in retail or automotive showrooms) to build a more comprehensive understanding of customer intent. We’re entering an era where AI listens with more than ears; it “sees” patterns and context across mediums.  
 
The third is explainability. Customers, regulators, and companies alike are demanding AI that can explain its logic. As trust becomes a competitive advantage, companies can not only say what their AI recommends but also explain why.  
 
Lastly, we are seeing a shift from “solution” to “ecosystem.” Conversation intelligence is no longer a feature, but it is a framework. It connects CRM, marketing automation, sales enablement, and analytics. That means CMOs, CROs, and CIOs are all rallying around the same insights drawn from the same source: the customer’s own words.  
 
In the years ahead, the winners will not be those who talk the most. They will be the ones who listen best and act the fastest. Conversation AI is giving them the solutions to precisely do that.
 
Get in touch with our MarTech Experts.
 Summer Thompson on Real-Time Personalization

Summer Thompson on Real-Time Personalization

marketing 10 Sep 2025

1. What does your approach to real-time personalization different from other CDPs or journey orchestration platforms?

Most CDPs and journey orchestration platforms limit how much data can be used for real-time personalization, often restricting brands to a narrow set of behavior signals and limited customer history. Hightouch removes those limits. Our approach is built around full data access and flexibility, enabling marketers to combine real-time behavioral signals with the complete depth of customer history from the data warehouse. With our new take on same-session personalization, we made it possible, for the first time, to react to in-session activity using the entire customer profile. Whether you're delivering an experience in under a second or orchestrating it over minutes, our real-time product suite is designed to meet the full range of real-time needs with no trade-offs between speed and data richness.

2. Same-Session Personalization is a bold claim. What was the core challenge in marketing that this feature is solving?

The core challenge is relevance in the moment. Without understanding current customer behavior, personalization efforts can create a disconnect between user intent and brand response. Same-session personalization solves this by allowing marketers to react to in-session signals, like product views, cart behavior, or site search, in less than a second. That means offers, messaging, and experiences can adapt as the customer is browsing, not after they've bounced. Our approach to same-session personalization goes one step further, and makes it possible to combine behavior signals with complete customer history in under a second. Brands can interact with their customers as a person, not just a set of digital behaviors.

3. Many CDPs force marketers to choose between speed or historical depth. How do you remove that trade-off?

Hightouch is uniquely positioned as a Composable CDP, which means we use the data warehouse as the source of truth for rich customer profiles, while also integrating real-time event streams. This approach means marketers don’t have to sacrifice depth for speed. You get the historical context of warehouse data and the in-the-moment context of behavioral events. It’s not about choosing between the past or the present. With Hightouch, you get both.

4. How do you handle identity resolution in same-session scenarios where the user might not yet be logged in?

We can use anonymous identifiers to stitch session activity to a profile. Whenever an anonymous user authenticates or provides identifying information, we can retroactively connect their session data to their historical profile in the warehouse, and be ready to address that user’s anonymous identifiers in the future as well. This enables persistent, privacy-safe personalization that respects user consent, while still delivering highly relevant experiences in the moment.

5. What’s your take on how AI and decisioning engines are collapsing the gap between insight and action?

AI is transforming marketing from reactive to predictive. With tools like Hightouch’s AI Decisioning, we’re enabling marketers to operationalize insights the moment they emerge. Rather than waiting for analysts to surface trends or build segments, AI models can evaluate user behavior and context in real-time. AI Decisioning constantly experiments and continuously improves delivery based on the results of each experiment. The result is personalization that’s not just fast, but smart—driven by data, governed by logic, and scaled through automation. Even with this rapid iteration, it’s also really important to surface key insights back to marketers, so they can improve their overall strategies and create more effective content and campaigns.

6. How do you envision yourself evolving to support marketers as zero-party and consent-driven data become the new norm?

Hightouch is built on privacy-first principles. As the industry shifts toward zero-party and consented data, our composable architecture gives brands full control over what data is collected, how it’s used, and where it’s activated. We’re also investing in features that help marketers surface and act on self-reported preferences in real time, whether that’s through consent banners, preference centers, or in-product feedback. The purpose of personalization is to create connections with people, and that starts with trust. With Hightouch, security, privacy, and trust are not an afterthought; they are core components of our architecture and company culture.

Get in touch with our MarTech Experts.

 Bryan on Data, AI & the Future of Marketing

Bryan on Data, AI & the Future of Marketing

data management 10 Sep 2025

1. How should enterprises evaluate the balance between data privacy and personalization when adopting new marketing technologies?

Enterprises must approach marketing technology adoption with privacy-first design as a foundational principle. Trust with customers is paramount, and without it, no advantage gained from marketing will make up for loss of trust. While enterprises do need to create the right internal policies and governance for marketing teams around how they should use AI-powered resources or generated content (including navigating the complexities of external regulatory requirements for data privacy), they can also integrate tools that are tailored to align with security needs. Databricks’ Data Intelligence for Marketing integrates Unity Catalog’s centralized governance and security with privacy and consent management — partnering with OneTrust — to ensure data is collected, unified, and activated responsibly with full respect for customer consent. This approach helps turn privacy from a compliance burden into a competitive advantage, helping enable personalized experiences at scale without sacrificing customer trust or regulatory compliance. 
 
2. How important is real-time data accessibility for marketers with varying technical skill levels in an organization?

Regardless of technical skill, the need for marketers to access real-time data is important to effectively respond to changing customer behavior and broader market dynamics. The time it takes to go from event to insight to action can mean the difference between an engaged or churned customer. Databricks empowers marketers of all technical skill levels through self-serve access to real-time insights using AI/BI Genie. Often, insights happen on the front line, but decisions happen at a leadership level. Self-serve access to insights can empower front line marketers to make more informed decisions, while leadership can more closely track progress and thereby give more independent decision making power to front line marketers. As a result, we see Databricks enabling both technical and non-technical marketers to make data-driven decisions, optimize campaigns in-flight, and personalize customer journeys effectively.
 
3. What operational efficiencies (e.g., time-to-market, cost reductions) do you expect from adopting integrated marketing data platforms? 

When marketers operate from a single source of truth that unifies customer and campaign data, the operational efficiencies are transformative. An integrated marketing data platform can break down silos across disparate systems, such as CRM, ad platforms, analytics, and content management, to enable consistent metrics and identifiers across channels. This unified data foundation eliminates delays caused by fragmented or inconsistent data, allowing marketers to trace and optimize customer journeys end-to-end with confidence. For example, since utilizing the Data Intelligence Platform, HSBC has seen a rapid increase in the speed at which they have data available for analysis,  and has  a number of jobs that used to take 6 hours and now take only 6 seconds.
 
4. How critical is unified customer and campaign data for enterprise marketing strategy and growth objectives?

One of the most critical challenges for marketers is getting a complete view of their customers and campaigns, because their data is scattered across different systems–and fragmented data leads to incomplete insights and reactive marketing. Building from a unified customer and campaign source of truth is no longer a nice to have, but necessary to compete and win in today’s data-driven business environment. Databricks unifies disparate data sources into a single source of truth, and then seamlessly integrates out-of-the-box with leading martech providers to empower marketers to deliver consistent, personalized experiences and measure campaign effectiveness with clarity and confidence.
 
5. How do improvements in metrics like click-through rates, cost-per-click, and return on ad spend influence organizational investment in marketing data solutions? 

Ultimately, any improvement seen in key metrics like click-through rates, cost-per-click, and return on ad spend help to directly validate the value of marketing data solutions. When organizations see tangible performance gains driven by data intelligence—enabled by real-time insights and AI-powered personalization—they are more likely to increase investment in these platforms to sustain competitive advantage and maximize marketing ROI.  For example, Databricks’ customer Sketchers has used the new access to data insights they’ve gained to create personalized customer journeys,  enhancing their ability to engage customers and achieve higher customer lifetime value. They’ve seen a 324% increase in click-through rates, a 68% decrease in cost-per-click, and a 28% increase in return on ad spend.
 
6. How do you envision the role of data intelligence evolving in enterprise marketing strategies over the next 3-5 years?

Over the next 3-5 years, we believe data intelligence will evolve from a supporting function to the core driver of marketing strategy across B2B and B2C organizations. Advances in AI automation, real-time and conversational analytics, and privacy-first data governance will enable marketers to anticipate customer needs, truly personalize experiences at scale, and orchestrate seamless omnichannel journeys. At Databricks, we believe in a future  where marketing decisions are data-informed, privacy-compliant, and can automatically adapt to changes in customer behavior.
 
Get in touch with our MarTech Experts.
   

Page 2 of 36

Most Recent

An Updated Look at the Enduring Value of Press Releases

Interview Of : Tony Miller Partner at Noteya Innovations

An Updated Look at the Enduring Value of Press Releases

PetAg & 5WPR: Science-Backed Pet Wellness

Interview Of : Marijana Gucunski

PetAg & 5WPR: Science-Backed Pet Wellness

Future of Intelligent Automation | Nintex

Interview Of : Niranjan Vijayaragavan

Future of Intelligent Automation | Nintex

Beyond Black Friday: Year-Round Retail

Interview Of : Anthony Capano

Beyond Black Friday: Year-Round Retail

B2B Social Data Meets Business Impact

Interview Of : Daniel Kushner

B2B Social Data Meets Business Impact