• The next-generation platform is designed to bridge the gap between social data and business action, surfacing real-time market signals from social to inform product development, customer care, and more.
• Trellis will be integrated across the Sprout ecosystem to uncover insights and improve workflows across Publishing, Listening, the Smart Inbox, and Reporting.
• Trellis Studio introduces customizable AI workflows that can be tailored to users’ unique goals and operational needs.

Sprout Social (Nasdaq: SPT) today announced the unveiling of its AI-powered social intelligence platform, designed to help organizations operationalize real-time, unfiltered market conversations at scale. Central to this launch is the upcoming expansion of Trellis, Sprout’s proprietary agentic AI engine. Purpose-built for social, Trellis will be integrated across the Sprout ecosystem — Publishing, Listening, the Smart Inbox, and Reporting — to help transform fragmented social data into organization-wide action.

Available to all customers in July, Trellis will evolve beyond Listening to become a conversational intelligence layer for the platform. By synthesizing social data across networks and combining it with insights from across Sprout, Trellis is designed to help teams ask complex questions and surface relevant, actionable insights faster.

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

This rollout also debuts Trellis Studio, a dedicated environment where organizations will be able to build bespoke AI workflows. Trellis Studio is designed to help teams streamline recurring workflows, so that social intelligence can be tailored to their unique KPIs and operational needs.

“Social is the fastest reflection of what people are thinking and feeling, yet most organizations lack the infrastructure to act on that data in real time,” said Scott Morris, CMO of Sprout Social. “What changes with social intelligence is not just access to more data, but the ability to turn that signal into strategic action across the business. When organizations can do that, social moves from a downstream function to the heart of how a business anticipates change and drives growth. In today’s market, failing to act on these signals can create a direct constraint on performance.”

Marketing Technology News: From MarTech Stack to MarTech Fabric: Weaving Brand, Content, and Conversion Into One Thread

The shift toward social-led strategy is fueled by a growing reliance on real-time insights for high-stakes decision-making. Sprout’s latest research reveals that 71% of marketing directors expect social data to surpass traditional market research in shaping enterprise strategy by 2029. However, this evolution demands more than just access to information. It requires a fundamental organizational capability to bridge the gap between insight and execution at a moment’s notice. With this launch, Sprout aims to close this gap, providing automation and agentic workflows built to turn signals into action faster across the business.

“AI is only as powerful as the data that informs it. Unlike general-purpose models, Trellis is uniquely valuable because of its access to real-time, native social data across multiple networks,” said Srinivas Somayajula, Chief Product Officer at Sprout Social. “When customer sentiment shifts or a competitive threat emerges, organizations cannot afford to miss the moment. Foundational models lack visibility into these signals in real time, but Trellis delivers, helping to transform network-native social data into decision-ready intelligence exactly when it matters most.”

Sprout’s AI-powered social intelligence platform focuses on four key pillars of value:

• Predictive Media Intelligence: Leveraging agentic AI to help detect shifts in industry narratives as they emerge, allowing brands to respond proactively.
• Full-Funnel Social Optimization: Helping bridge the gap between social engagement and ROI through AI-powered insights designed to align social performance with broader business goals.
• Scalable Social Support: Moving beyond reactive replies to proactive engagement. AI helps surface the highest-priority interactions, enabling teams to provide personalized service at a global scale.
• Authentic Brand Amplification: Identifying high-affinity advocates and creators through AI-driven recommendations to extend brand reach with authenticity.

These innovations, along with the findings of the 2026 Social Intelligence Report, will be showcased today during Breaking Ground, Sprout’s quarterly showcase of the company’s latest product updates and cutting-edge industry insights.

Keywords, search traffic, incoming and outgoing referrals, landing pages, and popular pages enhance Similarweb-grounded research for Manus Pro AI agents

• Nectar members can now spend points at over 20 Merlin attractions across the UK, including Alton Towers Resort, Thorpe Park, LEGOLAND® Windsor Resort, Chessington World of Adventures Resort, the London Eye and SEA LIFE aquariums

• Members can also double the value of their Nectar points on tickets; for example, swap £5 worth of points for £10 off

• To redeem, open the Nectar app, select the Merlin offer, then book via the dedicated booking page

Nectar has launched a new partnership with Merlin Entertainments, giving members a new way to save on days out across the UK. Customers can now spend their loyalty points to secure entry at more than 20 Merlin attractions when they book through the Nectar app.
The offer covers popular destinations across the UK, including LEGOLAND® Windsor Resort, Chessington World of Adventures Resort, Alton Towers Resort, Thorpe Park, the London Eye, SEA LIFE aquariums, Warwick Castle, Cadbury World and more.
For even greater value, Nectar and Merlin are giving customers the opportunity to double the value of their points. For example, by simply swapping £5 worth of Nectar points customers can save £10 off Merlin ticket prices.

From world famous theme park rides to immersive indoor experiences, the partnership offers Nectar members a new way to redeem their points, turning their everyday grocery shopping into opportunities for families to visit destinations, experiences and attractions across the UK. It’s quick and easy to redeem. Nectar members simply open the app, select the Merlin partner offer, book via the Merlin x Nectar website, choose how many points they want to use at the checkout and receive their tickets by email.

Mark Given, Sainsbury’s Chief Technology, Marketing and Data Officer, said: “We know our Nectar members want great value and real rewards. That’s why our partnership with Merlin matters. It’s all about giving families fun days out for less and making every point count towards something special.”

Amir Rasekh, Nectar360’s Managing Director, said: “Making it easy for customers to spend their points is really important. By stripping out unnecessary steps, we’ve created a faster, more intuitive redemption experience in partnership with Merlin – one that’s much better for our Nectar members.”

Marketing Technology News: MarTech Interview With Jay H. Lee, Chief Marketing and Growth Officer @ Five9

Stan Swinton, Merlin’s Chief Growth Officer, said: “With Nectar, we are able to offer even better access to days out and holidays for families across the UK. This partnership is another step in realising our ambition of providing affordable attractions that bring families close together through play. With Bluey the Ride: Here Come The Grannies at Alton Towers and World of PAW Patrol at Chessington World of Adventures, now is the best time for Nectar customers to enjoy the benefits of Merlin attractions and even more Nectar points.”

Nectar360 starts with the UK’s largest multi partner loyalty programme and ends with brands connecting to their customers in smarter, more meaningful ways.Working with over 900 brands, including Sainsbury’s, Argos, British Airways, Esso and American Express®, we use rich data and deep behavioural insight to understand who customers are, what they value, and how to reach them with relevance. With access to over 24 million members, we help brands, agencies and partners turn insight into loyalty — and loyalty into growth.We’re a full‑service, full‑strategy retail media network.

That means pairing data with creativity; using loyalty to fuel precision; and giving clients the clarity and confidence to plan (including CPG and General Merchandising brands like Unilever, Samsung and PepsiCo), activate and measure with impact. From omnichannel campaigns that move customers from social to shelf, to tools that unlock billions of real data points, we make every decision count.Since 2002, we’ve redefined what retail media can do – blending media, loyalty, data and insight to deliver outcomes for brands and better experiences for customers.

Merlin Entertainments is a world leader in branded entertainment destinations, offering a diverse portfolio of resort theme parks, city-centre gateway attractions and LEGOLAND Resorts which span across the UK, US, Western Europe, China and Asia Pacific. Dedicated to creating experiences that inspire joy and connection, Merlin welcomes more than 60 million guests annually to its diverse global estate in over 20 countries. An expert in bringing world-famous entertainment brands to life, Merlin works with partners including the LEGO Group, Sony Pictures Entertainment, Peppa Pig, DreamWorks and Ferrari to create destinations where guests can immerse themselves in a wide array of brand driven worlds, rides and uplifting learning experiences.

New FMP Upgrade Delivers Real-Time AI Campaign Auditing for Multi-Location Brands

AdMax Local (AML), a leading digital marketing partner for SMBs, franchises, and multi-location businesses, announced the next evolution of its proprietary Franchise Management Portal (FMP): AI Insights, a new capability delivering automated channel audits, campaign diagnostics, and data-driven recommendations within the platform franchise partners rely on daily.

The FMP was built to solve a persistent challenge in multi-location marketing: fragmented data and inconsistent visibility across dozens or hundreds of locations. It unifies reporting into a single source of truth, giving brands and franchisees clear insight into performance and opportunity.

Marketing Technology News: MarTech Interview with Stephen Howard-Sarin, MD of Retail Media, Americas @ Criteo

Through the FMP, franchisee clients can:

• Monitor KPIs like ROAS and lead generation across all locations in real time
• Review targeting strategies deployed on their behalf
• Communicate directly with the AdMax Local team
• Adjust targeting parameters such as zip code coverage
• Turn campaigns on/off or reallocate budgets by location

Marketing Technology News: From MarTech Stack to MarTech Fabric: Weaving Brand, Content, and Conversion Into One Thread

Introducing AI Insights: A Franchise Business Competitive Edge

AI Insights is an automated auditing engine that proactively analyzes campaigns to identify inefficiencies, flag risks, and recommend improvements. Monthly audits surface issues such as campaign and keyword bloat, cannibalization across keywords or locations, match type hygiene issues, and Quality Score challenges, then deliver prioritized recommendations both clients and the AML team can act on immediately.

“The franchise marketing landscape has never been more competitive, and the margin for wasted spend has never been smaller. With AI Insights built into the FMP, we’re giving clients and our team the ability to identify problems and act on opportunities faster than ever. This is what it looks like to put AI to work for our clients.”

— Melinda Schwartz-Oliver, Senior Director, Franchise Partnerships, AdMax Local

Brands relying on manual reviews are at a disadvantage to competitors using AI to continuously optimize. AI Insights empowers AdMax Local clients to stay ahead, a meaningful differentiator for multi-location systems where consistency and local performance both matter.

But the surfaces are noisy. Your prospect can scroll past the ad in their feed, filter the email, skip the pre-roll, or fast-forward through the podcast break. During my time at Meta, we told marketers they had three seconds before the scroll. That pressure hasn’t gotten easier. It’s compounded.

This is the gap TV fills. Not instead of the stack you’ve already built, but alongside it.

The Buyer Is Already Watching

The people approving vendor budgets and signing software contracts are the same people watching TV after work. Reaching them there isn’t a departure from B2B marketing logic. It’s an extension of it.

Streaming or CTV ads have made this practical in ways that weren’t possible five years ago. Audience-based buying, geo tests, frequency controls, survey attribution — the measurement mechanics B2B performance marketers already know map directly onto CTV. Relay, the fintech platform for small businesses, started on CTV because it offered tighter targeting and faster feedback loops than TV, with measurement they could actually explain to a CFO. Early results showed a direct lift in branded search and site traffic. That’s not a brand metric. That’s demand generation.

IAB data put CTV ad spend at $23.6 billion in 2024, up 16% year over year. The channel is no longer experimental. Most B2B marketers just haven’t caught up to that yet.

What TV Does That Digital Can’t

Search ads get six words. LinkedIn posts compete with every other hot take and humblebrag in the feed. A 30-second TV spot is unskippable. It gets the full screen and the viewer’s attention in a way that no digital format can guarantee. Your prospect can keep scrolling past your social ad. They can skip your pre-roll. They cannot skip the TV spot.

For B2B brands with complex products, that guaranteed attention is valuable. Gusto, the payroll and HR platform, builds its TV strategy around live tentpole moments, major sporting events and cultural moments, because that’s when their customers are most engaged and most likely to be thinking about the problems Gusto solves. It’s awareness-building timed to purchase intent.

One tactic that connects TV directly to the performance stack: CTV retargeting. Someone visits your pricing page on Tuesday. By Thursday, they’re seeing your ad in their living room, on a full screen, in an environment that carries more weight than another banner in a crowded feed. It closes the loop between your ABM motion and a channel your competitors almost certainly aren’t using against the same accounts.

Marketing Technology News: MarTech Interview With Jay H. Lee, Chief Marketing and Growth Officer @ Five9

TV Raises the Bar (and Maybe Your Next Round)

There’s a credibility effect to TV that doesn’t get discussed honestly enough in B2B circles. It isn’t just about awareness scores. It’s about what showing up on TV signals to the people evaluating you.

Consider the AI SDR space. Dozens of companies competing for the same accounts with near-identical pitches. If your brand has been on TV and your competitors haven’t, your prospect takes the call. You’re no longer one of many vendors in an inbox. You’re a company that operates at a different scale. That perception change happens before your sales team says a word, and it makes everything downstream more efficient.

The CMO is certainly focused on building brand awareness among their ICP, but corporate marketing is another area they own, one focused on raising the company’s profile within its industry and ultimately increasing its perceived value.

When a founder or board member sees their company’s ad during a live sporting event, their phone lights up. Fellow founders text. Investors notice. Raising a round is a different conversation when your brand has been on TV. Acquisition discussions go differently when the other side’s partners recognize your name. This rarely gets framed as marketing’s job. It is.

The Stack Is Good. It’s Just Missing a Layer.

The B2B marketers seeing the biggest results from TV aren’t treating it as a replacement for their performance programs. They’re using it as the layer those programs can’t provide: broad, credible, high-attention reach that introduces the brand to future buyers before they’re searching, and reinforces it with buyers already in your funnel.

Otter, the AI-powered meeting intelligence platform, found that well-crafted TV spots drive immediate engagement even for a complex multi-platform product. Viewers, particularly on mobile, check out the product right away. Top-of-funnel reach converting to bottom-of-funnel action. That’s the full motion.

Your ABM programs, your intent tools, your LinkedIn campaigns are all more effective when the buyer has already seen your brand somewhere that commanded their full attention. TV is that somewhere. The stack you’ve built is good. This is the layer it’s missing.

About Tatari

Tatari is building the infrastructure to modernize TV advertising for Brands, Agencies, and Publishers.

They are tuning it out.

Not because AI lacks value, but because the way it is being marketed often fails to align with what buyers actually prioritize. For organizations making high-stakes, long-term technology decisions, the fundamentals still matter most: engineering quality, technical expertise, reliable delivery, and reduced risk.

The growing disconnect between what vendors emphasize and what buyers need is creating friction in the buying process and, in some cases, eroding trust.

The AI Messaging Overload

Right now, nearly every platform, service, and solution touts some form of AI integration. While this proliferation reflects genuine advancements, it has also created a crowded and often confusing landscape.

For buyers, the challenge isn’t access to innovation—it is clarity.

When every vendor claims to be “AI-driven,” true differentiation actually becomes more difficult. Messaging starts to sound the same across the board, leaving buyers unsure what genuinely matters versus what’s just baseline capability. In this crowded landscape, bold AI claims without clear context or proof points don’t signal innovation, they blend into the noise.

To break through, marketers can’t rely on generic AI language alone. They need to be more technically fluent and deeply informed about emerging technologies, so they can engage increasingly sophisticated buyers and craft messaging that rises above vague, cookie-cutter AI narratives.

What Buyers Actually Prioritize

Despite the emphasis on AI, B2B buyers consistently return to a core set of priorities when evaluating solutions:

1. Engineering Quality

Buyers want to know that a product is well-built, scalable, and designed to perform under real-world conditions. According to recent BIXA research of 480+ business buyer decision-makers, quality of engineering and technical expertise are statistically tied for the most important attributes they look for in a vendor.

2. Technical Expertise

Beyond the product itself, buyers assess the depth of knowledge behind it. Research shows that technical expertise and guidance are tied as the most important attributes buyers look for in a vendor. They prioritize teams that understand their industry, technical challenges, and implementation complexities. For instance, 97% of buyers say it is important that a vendor both understands and uses AI technologies in their own processes.

Expertise ultimately signals credibility: 41% of tech leaders who augment their existing teams with external engineers say certified AI experts make a vendor stand out—and that credibility directly reduces perceived risk.

3. Reliable Delivery

Execution matters as much as vision. Buyers need confidence that timelines will be met, deployments will go smoothly, and ongoing support will be dependable. Efficient delivery is a top-five priority for buyers, and it is the single most important factor for 17% of UK-based decision-makers. Overpromising, particularly in emerging technologies, can quickly erode confidence when delivery does not keep pace. Buyers are also pragmatic about how to build that confidence quickly — 47% value paid workshops specifically because they accelerate project momentum. Buyers also increasingly expect AI to reinforce that reliability through faster code generation and automated code reviews.

4. Risk Reduction

At its core, every B2B purchase is a risk management decision. Whether it’s financial risk, operational disruption, or reputational impact, buyers are evaluating how a solution minimizes uncertainty. A bold guarantee is the top determining factor for buyers, carrying 40% of the relative importance in their decision-making process. In fact, 88% of buyers would choose a vendor offering a 100% bug-free guarantee even if their price was 30% higher than competitors. Clear documentation, proven use cases, and transparent communication, such as through de-risking workshops favored by 34% of buyers, all contribute to lowering the #1 hesitation in the market: concerns over code quality and security.

These priorities are not new. What has changed is how easily they can be overshadowed by trend-driven messaging.

The Cost of Misalignment

When marketing narratives focus on AI but ignore these foundational concerns, a gap forms between expectation and reality. This misalignment leads to clear consequences:

• Longer sales cycles, as buyers seek additional validation and clarity
• Increased skepticism, particularly toward bold or vague claims
• Missed opportunities, when solutions fail to resonate despite strong underlying value

In some cases, the emphasis on AI can even distract from a company’s true strengths. A well-engineered product with a track record of reliable delivery may be far more compelling than a newer, AI-heavy offering that lacks maturity. But if the messaging doesn’t reflect that strength, buyers may never fully recognize it.

Reframing the Narrative

The solution isn’t to move away from AI, it’s to stop pretending the tools are the transformation.

The teams winning with AI aren’t the ones with the most tools. They’re the ones that changed how their engineers work. This is a people and process problem, not a procurement decision—and most vendors avoid saying it because it’s harder to sell.

The shift in messaging is simple but demanding: stop leading with what the technology is and start with what it takes to make it work. That means structured workflows, validated output at every stage, and a clear acknowledgment that AI without governance doesn’t reduce costs—it increases them. AI usage is not free; it is metered in tokens and accumulates quickly.

There’s also a risk that almost no transformation partner raises: internal resistance. AI champions inside a client organization pull ahead. Resistors create drag. If you don’t address adoption at the engineer level from day one, the transformation fails at the people layer, not the technology layer. Buyers should be asking their vendors how they handle this. Most can’t answer.

Marketing Technology News: MarTech Interview With Jay H. Lee, Chief Marketing and Growth Officer @ Five9

Questions to challenge yourself and your teams:

• Is your AI architected well enough that the economics actually work?
• Do you have a structured methodology or just a capability?
• What happens when your engineers resist?

Building Trust Through Substance

Trust is the currency of B2B relationships. It is built through consistency, transparency, and proof. In a market saturated with AI claims, substance is the differentiator.

• That substance shows up in four ways:
• Clear, specific use cases that demonstrate real-world impact
• Technical depth that proves how solutions are built and maintained
• Evidence of reliability, backed by performance metrics and long-term customer outcomes
• Honest communication about capabilities and limitations

When buyers see that a company is willing to go beyond surface-level messaging, it signals confidence—and that confidence is often more persuasive than any single feature or capability.

The Opportunity Ahead

The current wave of AI enthusiasm is real, and so is the backlash forming underneath it. Buyers aren’t rejecting AI. They’re rejecting the version of AI that showed up late, overpromised, and left their teams holding the complexity.

The companies that will win this window aren’t the ones with the boldest AI narrative. They’re the ones who can answer the questions a sophisticated buyer will eventually ask: Is your AI architected well enough that the economics actually work? Do you have a structured methodology or just a capability? And what happens when our engineers resist?

Bad AI is expensive AI. Buyers are starting to do the math, and the vendors who can’t show their work are going to lose deals they don’t even know they’re losing.

The fundamentals haven’t changed. Proof, expertise, reliable delivery, and reduced risk. What’s changed is that AI has raised the stakes on all of them. The companies that understand that distinction – and can demonstrate it – are the ones that will eventually define this market.

About Vention

Vention is the premier global leader in software engineering, synonymous with technology designed for scale and the common denominator behind the world’s most successful tech-empowered enterprises, industry innovators, and startups.

LinearB, an engineering productivity platform for mid-market and enterprise software organizations, announced that Gartner has named it a Leader in the 2026 Gartner® Magic Quadrant for Developer Productivity Insight Platforms (DPIPs). LinearB was evaluated on both Ability to Execute and Completeness of Vision.

LinearB gives engineering leaders the visibility and tools to act on engineering productivity.

The market’s progression to growing executive demand for evidence-based measures of value delivery, the rapid adoption of AI coding tools, and the need to govern AI-enabled software delivery at scale. Gartner estimates the DPIP market at approximately $400 million with an average growth rate of over 40 percent, based on an assessment of global organizational spending on data-driven engineering analytics platforms.

Marketing Technology News: MarTech Interview With Jay H. Lee, Chief Marketing and Growth Officer @ Five9

LinearB gives engineering leaders the visibility and tools to act on engineering productivity. They explore their data through a natural-language interface, build a measurement framework across the full SDLC using unified metrics, benchmarks, and developer surveys. They act on what they find directly inside Git, where code governance policies and a code review agent analyze pull requests before merge, giving developers specific, actionable findings without requiring manual intervention.

“Engineering organizations are under real pressure to prove the impact of AI investment, and most of them are trying to do that with disconnected tools and incomplete data,” said Ori Keren, CEO and co-founder of LinearB. “Being named a Leader in the first Gartner Magic Quadrant for this category, we feel, reflects what our customers have been telling us for years, that measuring AI is not enough. The platforms that win will be the ones that turn engineering data into action, automatically and at scale, and that is where we have invested.”

Leaders demonstrate strong execution across multiple functional use cases and deliver meaningful business outcomes through enterprise-grade DPIP capabilities. Leaders also show consistent roadmap momentum, have a clear market vision, and have the operational maturity, CX and market presence to support cross-functional deployments at scale.

Retailers are sitting on more customer data than ever. Most of it is contradicting itself

Most organisations can agree on how many customers they have. Sometimes, the agreement ends there. Ask which channel best reaches a specific customer, what their lifetime value actually is, or whether they already own the product you are about to recommend, and you will get different answers from every team.

Retailers have invested heavily in omnichannel strategies, AI-powered customer experiences, and personalisation tools, yet many are building those capabilities on a foundation of data that does not align across systems. The investment is real. The unified view of the customer it depends on often is not.

Amperity’s recent expansion into the AWS Asia-Pacific (Sydney) and Asia-Pacific (Melbourne) regions brings that challenge into sharper focus for local enterprises, for whom data residency and governance are now operational requirements, not just strategic considerations.

Every team has their own version of customer data governance. Marketing deduplicates aggressively to maximise campaign reach. Analytics applies strict matching rules to avoid inflating customer counts. Operations relies on whatever the CRM says. Loyalty uses its own member ID. Each team’s logic is defensible in isolation.

However, when those conflicting views feed the same personalisation engine, the same AI models, or the same board report, the brand cannot deliver the experiences leadership is asking for.

The customer count might line up. But the loyalty programme cannot reconcile purchase history across channels because each channel defines “same customer” differently. And that is before you account for the customers who forget to scan their loyalty card, share an account with someone in their household, or never enrol in the programme at all despite being high-value repeat buyers.

Marketing sends reactivation campaigns to customers who are active in the loyalty programme but dormant in the email platform. The data is not wrong in any one system. It is wrong in aggregate.

One Amperity customer discovered that a single shopper appeared as four separate profiles in their system because they used email as their golden record. Each profile had a different lifetime value and different shopping preferences. None was a complete or accurate representation of the actual person. When that happens at scale, personalisation is not just imprecise. It is fiction.

Why customer data governance breaks down without identity resolution

Most companies govern data at the system level, and some agree on an overarching standard like email or loyalty ID. But no single identifier captures every customer interaction.

Each platform, be it email, point of sale, loyalty, support, or the data warehouse, still applies its own matching rules, its own thresholds, its own definition of what makes two records the same person. Over time, the gaps between those definitions add up.

This is the core challenge of customer data unification: not collecting more data, but connecting the data you already have into a unified customer profile that every team trusts.

Customer identity resolution connects fragmented records across systems, linking identifiers like email addresses, phone numbers, device IDs, loyalty accounts, and transactions into a single, accurate customer profile.

Identity resolution approaches fall on a spectrum. Deterministic matching links records through exact identifiers, such as a shared email address or login credential. Probabilistic and AI-based methods go further, evaluating patterns across data points to surface connections that exact matching misses, like when the same person uses different email addresses across channels or checks out as a guest in-store.

The most effective systems combine both, using deterministic rules as a foundation and machine learning to find the connections that rules alone cannot.

That gap compounds with every new tool and data source, each introducing its own governance logic. And when leadership asks the brand to personalise at scale, to recommend the right product on the right channel at the right time, the teams cannot deliver. Not because they lack the tools or the talent, but because no one has a complete picture of the customer to work from.

Try this thought experiment: pick a customer at random. How long would it take to gather enough detail to confidently send the right message, on the right channel, to drive their next purchase? Now imagine doing that for every customer.

How contextual identity graphs produce a unified customer profile

Before you can contextualise a customer, you need a complete picture. You cannot recommend the right product if you do not know what they have already purchased or returned.

You cannot choose between a discount code via SMS and an exclusive preview via email if you do not know which channel drives their purchases. You cannot calculate real lifetime value if the same person exists as four separate records.

That complete profile is the foundation. Contextual identity is what makes it useful.

Preferences change. A customer who never buys from a particular category might be shopping for a gift next week, or for someone else in their household. A full-price buyer exploring a new category for the first time might or might not respond to a promotional code.

Marketing Technology News: MarTech Interview With Jay H. Lee, Chief Marketing and Growth Officer @ Five9

A single, static customer identity graph cannot handle that complexity. It forces every team into the same rigid view, and someone is always compromising.

Amperity’s Customer Data Cloud takes a contextual identity approach: purpose-built identity graphs optimised for each use case, all constructed from the same resolved foundation using first-party identity resolution.

Marketing: maximise reach. Identity graphs tuned for broad audience coverage so campaigns connect with as many real customers as possible, without duplicates inflating the numbers.

Analytics: consistency. Identity graphs built for accurate customer counts, reliable lifetime value calculations, and reporting that holds up across teams and time periods.

Operations: precision. Identity graphs optimised for transactional accuracy, where matching the right record to the right person at the right moment matters most.

Every graph is built from your first-party data. IDs stay consistent day to day. When data changes, the system learns and adapts. Connections are transparent, rules are tuneable, and every decision is auditable. No black box. No third-party data spine. No vendor lock-in.

One resolved foundation. Multiple purpose-built views. Every team works from the same truth, expressed for their specific need.

Identity infrastructure is now a compliance requirement

Transparency in data handling carries legal weight. Organisations cannot make accurate disclosures about automated decision-making unless they have clear visibility into how personal data moves through their live systems.

Consent signals, data lineage, and access controls need to be built into the foundation of customer data infrastructure from the outset.

As mentioned, Amperity’s platform is available in the AWS Asia-Pacific (Sydney) and Asia-Pacific (Melbourne) regions, allowing organisations to keep customer data resident locally while supporting performance and scalability requirements for real-time customer intelligence.

Brands that treat identity resolution as a compliance exercise end up reacting to problems. Those that build it into their data infrastructure from the start solve them before they surface, with a governed, trusted customer view that serves marketing, analytics, operations, and regulators alike.

About Amperity

Amperity’s Customer Data Cloud empowers brands to transform raw customer data into strategic business assets with unprecedented speed and accuracy. Through AI-powered identity resolution, customisable data models, and intelligent automation, Amperity helps technologists eliminate data bottlenecks and accelerate business impact. More than 400 leading brands worldwide, including Accent Group, Alaska Airlines, DICK’S Sporting Goods, BECU, and Wyndham Hotels & Resorts, rely on Amperity to drive customer insights and revenue growth. Founded in 2016, Amperity operates globally with offices in Seattle, New York City, London, and Melbourne. For more information, visit amperity.com or follow us on LinkedIn, X, Facebook and Instagram.

This traditional approach was how marketing ecosystems used to work. Customer media consumption was more predictable and interactions with brands were more linear. But the digitalization of consumer behavior has changed this landscape fundamentally. Today’s consumers don’t interact with brands in isolated channels. They don’t just “visit” websites, mobile apps, social platforms, streaming services, marketplaces, physical stores, and connected devices. A customer might learn about a brand on social media, do their research using search engines, engage with an email campaign and ultimately make a purchase via a mobile app – all as part of the same journey.

That has led to a radical shift in customer expectations. They want brands to know their preferences and intent and to give them relevant interactions wherever they are in the engagement. You can’t just be on every platform anymore; it’s about relevance, timing, and context. Customers are judging brands less and less on individual campaigns and more and more on the consistency and quality of their overall experience.

This evolution has revealed the shortcomings of channel-centric marketing models. Traditional campaign planning often results in disconnected experiences, inconsistent messaging, and disjointed customer interactions.

Experience orchestration is a strategic necessity as journeys become non-linear. Customers move and switch unexpectedly between awareness, consideration, purchase and loyalty stages, and frequently interact across multiple touchpoints simultaneously. They want brands to react in real time, adapt to changing behaviors and deliver consistent experiences across the journey. The shift has forced companies to re-examine the place of technology in customer engagement.

Martech is at the heart of this transformation. Today’s martech is well beyond campaign automation and channel management. Martech is transitioning from its traditional function of executing marketing activities across different platforms to an orchestration layer that connects data, systems, teams and customer interactions into one experience ecosystem.

Brands are now creating engagement strategies based on moments and intent of customers, and not just channels. Instead of asking which platform to be focused on, organizations are looking at what the customer needs to know at any given time and how to deliver the most relevant experience. It is a big move from campaign-driven marketing to engagement that puts the experience first.

Ultimately, experience-first Martech allows organizations to deliver contextual, real-time, customer-centric interactions throughout the entire journey. Martech aids businesses in delivering seamless experiences aligned with how modern consumers actually engage through customer data, AI-driven insights, journey orchestration and automation. The future of marketing is no longer about isolated campaigns, it’s about connected experiences, centered around customer intent, timing and context.

What Is Experience-First Martech?

The marketing landscape is evolving rapidly as brands shift from isolated campaign execution to continuous customer engagement. The standard marketing strategies were primarily channel-centric, comprising email, social media, search and display advertising. But customers today don’t interact with brands in predictable, linear ways.

They move across multiple platforms, devices, and touchpoints while expecting seamless personalized experiences throughout the journey. This change has led to experience-first Martech, where engagement is designed around customer moments, intent and context, rather than just channels.

Definition of Experience-First Martech

Experience-first Martech: Marketing technology ecosystems built around customer experiences, not isolated campaigns. Rather than optimize individual channels separately, organizations use Martech to create connected, contextual interactions across the entire customer lifecycle.

Success in traditional marketing models was often measured by channel-specific metrics such as click-through rates, impressions or email opens. Experience-First Martech Changes: Prioritizing Engagement Continuity, Personalization, and Customer Satisfaction. The focus has shifted from simply transmitting messages to creating meaningful interactions that meet customer needs in real time.

This evolution is part of a larger shift from optimizing channels to optimizing moments. Brands are shifting from asking, “Which channel should we use?” to asking, “What experience does the customer need right now?” This view enables organizations to deliver more relevant and effective engagement strategies that are responsive to changing consumer behaviors.

Customer Intent and Context as the Foundation

A key feature of experience-first Martech is a focus on customer intent and context. Today’s customer wants brands to understand them, not just who they are, but what they need, when they need it and how they want to interact.

Browsing behavior, search activity, purchase history, and engagement patterns are all examples of intent signals that offer valuable insight into customer expectations. Martech platforms analyze these signals to determine the best next action. Context also matters — such as the type of device, location, timing, customer history and behavioral triggers.

Experience-first Martech uses intent and context to help organizations deliver interactions that feel personalized, timely and relevant. It builds deeper customer relationships, while reducing friction in the journey.

The Evolution of Martech

The rise of experience-first engagement is very much tied to the evolution of Martech. The first generation of Martech systems was fairly focused on automation and campaign execution. Organizations used technology to automate email campaigns, run advertising and optimize basic marketing workflows.

The rise of digital channels made the Martech ecosystem more sophisticated. To cope with the rising volume of customer interactions, customer data platforms, analytics systems, CRM technologies and automation tools were brought in. But many of these tools worked in silos, making it difficult to create unified customer experiences.

The next phase of Martech evolution has brought us capabilities like AI, predictive analytics and journey orchestration. These technologies could enable organizations to get beyond static campaigns and begin creating dynamic customer journeys. Real-time personalization, behavioral segmentation and automated engagement workflows took on added importance in helping brands respond more effectively to customers.

Today, martech is transforming into a connected orchestration layer that can orchestrate interactions across the entire customer lifecycle. Modern Martech ecosystems are not just disparate tools, they are a combination of data, automation, analytics and AI that supports ongoing engagement.

Growth of Journey-Based Engagement Systems

One of the biggest changes in Martech has been the emergence of journey-based engagement systems. Customer journeys today are very non-linear. Customers go back and forth between awareness, consideration, purchase and loyalty stages and across multiple touchpoints.

A journey-based system allows organizations to view interactions as a whole, not as individual events. Today, martech platforms track customer journeys, discover behavioral trends and launch personalized engagements based on real-time activity.

For instance, a customer looking at products on a site could receive personalized recommendations through email or mobile notifications at a later time. They can automatically trigger a follow-up engagement, based on behavioral triggers, if they leave a cart. This journey based way of working ensures consistency across interactions and improves the overall customer experience.

From Channels to Experience

Experience-first Martech is also part of a broader trend in how organizations think about channels. In traditional marketing models, strategy revolved around channels. Teams did email, social media, search, paid advertising and offline marketing themselves.

Channels are increasingly delivery mechanisms, not strategic silos, in today’s engagement models. The customer experience itself is the focal point. Brands no longer optimize individual platforms in isolation, but instead orchestrate interactions across channels to support unified customer journeys.

This switch is particularly crucial because customers don’t think in channels. They want brands to recognize their behavior and offer continuity no matter where there are interactions. A disjointed experience – think irrelevant or repetitive messages across platforms – can chip away at trust and engagement.

Experience-first Martech can help eliminate these inconsistencies by centralizing customer context and enabling coordinated engagement across all touchpoints.

Experience-First Marketing as a Competitive Differentiator

In an increasingly crowded marketplace and with customer expectations continuing to rise, the quality of experience is fast becoming a key competitive differentiator. It’s no longer enough to offer products and pricing to build lasting loyalty.

Customers are more and more choosing brands on the basis of the quality, relevance and consistency of their interactions. Experience-first Martech companies have a huge leg up in personalization, responsiveness and customer engagement. They can better anticipate customer needs, respond to evolving behaviors and deliver seamless experiences across the journey.

It also improves operational efficiency by reducing fragmented workflows and facilitating better coordination between marketing, sales, customer service and customer experience teams.

Experience-first Martech aligns engagement with how customers really engage with brands in today’s digital landscape. Martech allows organizations to move from siloed campaigns and channels to customer moments, intent and journey continuity, enabling them to deliver connected, contextual and real-time experiences that drive stronger relationships and long-term business value.

The Importance of Customer Moments in Experience-First Martech

Customer engagement today is not about campaigns and marketing channels in isolation. Today, consumers engage with brands in a sequence of fluid, intent-driven moments that happen across devices, platforms and environments. Such interactions are usually immediate, contextual and highly personalized, forcing organizations to rethink how they design engagement strategies. Martech is increasingly evolving around customer moments rather than around channels alone as a result.

Understanding Micro-Moments in Customer Journeys

Micro-moments are one of the most important concepts in modern engagement strategy. Micro-moments are intent-driven interactions when customers are actively looking for information, making decisions, solving problems or taking action. These moments often happen in a blink and are driven by customer needs at a given moment in time.

Micro-moments can occur at any stage in the customer journey. Examples are:

• A customer reading reviews before buying a product
• A shopper leaving a cart and reconsidering choices
• A user requesting support on a mobile app
• Customer looking for store locations or services near me

Each of these touchpoints may seem innocent enough on its own but together they all add to the customer experience. Modern Martech platforms are increasingly being built to identify, analyze, and respond to these moments in real time.

Micro-moment engagement is not a traditional campaign with a set schedule. Organizations need to know what customers are trying to accomplish in each interaction and deliver the most relevant experience right then. That’s why customer moments have become the focus of experience-first marketing strategies.

Why Intent Is More Important Than Channels?

Conventional marketing tactics optimized performance in silos, one channel at a time — email, search or social media. But customers don’t think in channels. They think in terms of goals, needs and outcomes.

For example, a customer looking for product information on a smartphone might continue the journey later on a desktop website or a social media interaction. The channel is less important than the intent of the customer. So, today’s Martech systems are designed to look for intent signals, not just channel activity.

Intent-based engagement allows brands to:

• Offer more related content
• Enhance timing & personalization
• Reduce friction through the journey
• Increase engagement & conversions

It’s a big step forward in how Martech is used to manage customer experiences.

a) Context Across Channel

Another important characteristic of experience-first engagement is the increasing significance of context. Today’s customers want brands to understand not just who they are, but the context of each interaction.

The context includes, for example:

• Time of day
• Device type
• Geographic location
• Browsing behaviour
• Purchase history
• Current purpose

Take a customer looking at your products on a mobile device while commuting, for example. They may need a different experience than a customer researching your products in depth on a desktop computer at home. Context-aware Martech systems can change messaging and recommendations on the fly based on these factors.

This contextual approach beats generic campaigns by a mile, because it engages with real customer needs at the moment. Instead of sending the same message to a broad audience, organizations can deliver highly relevant experiences that speak to each individual’s situation.

Modern Martech platforms are constantly assessing context and tuning interactions based on customer data, analytics, and AI-driven insights.

b) Emotional and Behavioral Triggers

Customer decisions are driven by more than just logic. How people engage with brands depends on emotions, urgency, convenience, trust, and situational factors. Understanding these emotional and behavioral triggers has become a mainstay of modern Martech strategies.

Behavioral signals are the strongest indicators of customer intent. Things like repeat product views, abandoned carts, support inquiries or interaction with specific content are indicators of what customers think and feel along the journey.

These signals are analyzed by sophisticated Martech platforms to personalize engagement strategies. For instance:

• Customers showing hesitation may receive reassurance-focused messaging
• High-intent users may receive promotional offers or product recommendations
• Returning customers may receive loyalty-focused experiences

Personalization that considers emotional and behavioral context helps organizations build trust and improve customer satisfaction. Martech enables brands to move away from a one-size-fits-all approach and instead build adaptive experiences that respond in real time to the needs of each individual customer.

The Rise of Real-Time Expectations

One of the biggest shifts in consumer behavior is immediacy. Customers expect brands to respond immediately and provide adaptive experiences in real time.

Static campaign schedules are less effective as customer needs are not static and are constantly changing. Waiting hours or even minutes to respond can cost you engagement opportunities.

Today’s Martech ecosystems enable real-time engagement by processing customer signals in real time and triggering automated responses. For example:

• Real-time product recommendations
• Automated cart recovery messages
• Dynamic website personalization
• Instant support interactions

Location-based offers and notifications

Continuous engagement models are replacing traditional scheduled campaigns. Brands are increasingly expected to operate as always-on engagement systems capable of adapting to customer behavior at any moment.

Continuous Engagement Across the Journey

Experience-first Martech is built to enable ongoing customer relationships rather than single campaign transactions. Organizations are moving away from treating each engagement in isolation and instead are looking at continuity across the entire customer journey.

This means that interactions should stay connected regardless of where and when they occur. “Customers expect brands to remember past interactions, understand the context of the moment, and anticipate what’s next.

Ongoing engagement leads to better:

• Customer’s Satisfaction
• Journey Uniformity
• Conversion rates
• Long-term loyalty

Martech allows organizations to orchestrate interactions across multiple touchpoints to deliver seamless and intelligent customer experiences.

Key Takeaway

Customer moments, not channels, define the opportunities for engagement today. As customer journeys become more dynamic and non-linear, it is vital for organizations to concentrate on real-time understanding of intent, context, emotions and behavior. With modern Martech, brands can move from executing static campaigns to executing contextual, ongoing, customer-centric engagement strategies that reflect how people really engage in the digital world.

Challenges of Channel-Based Campaigns

The traditional channel-based marketing model is becoming increasingly ineffective as customer expectations continue to evolve. The way campaigns were structured around individual channels like email, social media, paid advertising, search, web and offline marketing has been the way organizations have been doing it for years. Each channel was siloed with dedicated teams, technology, workflows and KPIs. This approach was aligned with the way consumers interacted with media in the past, but more dynamic and non-linear ways of interacting characterize today’s connected customers.

Today’s customer journeys flow across devices and touchpoints, making it difficult to maintain isolated campaign strategies. Customers expect seamless, contextual and personalized experiences wherever they engage. But channel-centric marketing often causes fragmentation, inconsistency and operational inefficiencies that prevent organizations from meeting these expectations. As a result, more companies are turning to Martech to move beyond channel management to unified experience orchestration.

a) Fragmented Customer Experiences

Fragmented customer experiences are one of the biggest disadvantages of channel-based campaigns. Traditional marketing structures often fail to connect messaging across platforms as each channel is run independently.

A customer might receive an email message, see different messaging on social media, and see unrelated offers on a website or mobile app. These inconsistencies lead to confusion and erode trust. Brands need to understand what consumers like, and give them a consistent experience across all touchpoints. Disparate systems make this difficult.

Channel-based marketing also causes repetitive engagement. Because platforms don’t share data effectively, customers may get duplicate promotions or communications that don’t apply to them. Companies cannot have a consistent view of customer behavior without integrated Martech systems.

Fragmentation is a particular problem in today’s omnichannel world where customer journeys are taking place across multiple touchpoints simultaneously. Rather than having a connected relationship with the brand, customers are met with disconnected campaigns that are not aligned with their true needs and intent.

b) Siloed Teams and Technologies

Traditional marketing organizations are usually organized around channels. Separate teams in silos manage email marketing, social media, paid advertising, content, web engagement and offline campaigns. Specialization increases channel expertise but it creates operational silos.

These siloed structures often result in disjointed strategies, inconsistent KPIs, and poor collaboration between teams. One department might optimize for clicks, another for impressions, and a third for engagement even if those goals don’t contribute to a cohesive customer journey.

Technology fragmentation adds to the problem. Many organizations have large Martech stacks that include specialized tools for specific channels. Email automation platforms, social media management tools, CRM systems, analytics platforms and advertising technologies are often siloed with limited integration.

Therefore, martech stacks are optimized for channel execution, not journey orchestration. Customer data remains trapped in silos across systems, preventing organizations from building a complete picture of customer interactions. Such fragmentation limits the ability to customize and diminishes the value of customer engagement strategies.

Operational complexity is also increased by the lack of integration. Teams spend so much time manually orchestrating campaigns, syncing data, and managing disconnected workflows. “Fragmented Martech environments tend to slow down execution and create inefficiencies, rather than enable agility.

c) Static Campaign Models

Another significant drawback of channel-based marketing is its dependence on static campaign structures. Traditional campaigns are planned weeks or months in advance, with fixed schedules, pre-determined messaging and little opportunity for responsiveness.

But customer behavior is changing fast today. Context, preferences, behavior, or outside events can change customer intent in a flash. Static campaigns are not meant to interact in real-time and thus cannot react to these dynamic interactions.

In traditional campaign models, slow response time is often an issue. If a customer abandons their cart, browses products or requests support, they may not receive relevant follow-up communication for hours or days. In many cases, these delays mean missed engagement opportunities.

Static campaign structures also offer little in the way of personalization. Instead of real-time behavioral signals, traditional segmentation models often depend on broad demographic categories. Many interactions are generic and not based on real customer intent because of this.

Modern Martech platforms are increasingly overcoming these limitations with adaptive and event-driven engagement models that respond in real-time to customer actions.

d) Lack Of Cross-Channel Visibility

The lack of visibility across the entire customer journey is one of the biggest challenges in channel-based marketing. Interactions span multiple systems and touchpoints, so organizations often don’t know how customers move between channels.

Without integrated Martech, it is extremely difficult to track end-to-end customer journeys. Marketers might be aware of performance in each channel but not know how touchpoints impact each other.

For example:

• A customer discovers a product on social media
• Search it on search engines
• Engage with email content
• Complete the purchase on a mobile app

These interactions are often studied independently in fragmented environments, rather than as part of a connected journey.

Attribution is difficult because there is no visibility. Modern customer behaviour is complex, and traditional attribution models often over- or undervalue specific channels because of this. Organizations struggle to understand which touchpoints actually affect conversion outcomes.

Advanced Martech ecosystems are helping businesses to overcome these challenges by centralizing customer data and offering unified journey analytics.

e) Channel Metrics vs Experience Metrics

Traditional marketing models focus on channel metrics like impressions, clicks, open rates, and engagement percentages. These KPIs are good for operational visibility but don’t always reflect the quality of the customer journey.

You may have a campaign that has good clickthrough rates but poor overall customer satisfaction because the interactions are inconsistent or irrelevant. This highlights one of the biggest weaknesses of channel-centric marketing: success is often measured at the campaign level, not at the experience level.

Modern businesses increasingly see journey-based measurement models as a necessity. Instead of solely looking at channel performance, organizations are considering:

• Customer satisfaction
• Journey continuity
• Retention rates
• Customer lifetime value
• Engagement quality

This transition requires more advanced Martech capabilities, which can connect the customer experience across the full lifecycle.

Experience metrics provide a more accurate picture of how customers feel about brand interactions. They also encourage organizations to optimize for long-term relationships, not just short-term campaign performance.

Hence, what modern connected customers are demanding is more than channel-based marketing can deliver. Fragmented experiences, siloed teams, static campaigns, poor visibility and outdated measurement models challenge organizations to deliver seamless and contextual engagement. As customer journeys become more dynamic, businesses need to move away from siloed campaign execution to more integrated, experience-first engagement strategies enabled by modern Martech.

Role of Martech in Experience-First Design

As organizations move away from disconnected, channel-centric approaches, Martech is becoming the backbone of experience-first engagement. Today’s Martech platforms are evolving past campaign execution and are becoming intelligent orchestration engines that coordinate customer experiences across the entire journey.

Design that begins with the experience demands that organizations understand the entire customer journey, respond in real time and deliver personalized interactions across multiple touchpoints. Martech is the catalyst of this transformation, integrating data, automation, AI, analytics and orchestration into a cohesive ecosystem.

a) Customer Data Platforms (CDPs)

Customer Data Platforms have become a critical part of today’s Martech ecosystems. CDPs aggregate behavioral, transactional and engagement data from multiple systems into a single customer profile.

Rather than storing information in disparate silos, CDPs consolidate customer intelligence in one location. This allows organizations to create a complete picture of customer behavior across channels and touchpoints.

Unified profiles improve personalization, segmentation and journey orchestration and eliminate inconsistencies in customer interactions.

b) Predictive Analytics and AI

Artificial Intelligence is reshaping the landscape of modern Marketing Technology. Data-driven AI analytics help businesses understand customer intent, identify behavioral patterns, and forecast future actions. Predictive models analyze engagement signals to determine:

• Purchase likelihood
• Churn risk
• Content preferences
• Next-best actions

This intelligence powers real-time personalization and recommendations in the context and intent of the customer.”

With AI, Martech systems are constantly optimizing engagement strategies based on customer behavior to improve relevance and responsiveness throughout the journey.

c) Journey Orchestration Platform

Journey orchestration platforms are used to orchestrate interactions across touchpoints to deliver seamless customer experiences. Instead of managing channels in isolation, orchestration systems allow organizations to:

• Map customer journeys
• Trigger personalized interactions
• Coordinate messaging across platforms
• Adapt engagement dynamically

Martech orchestration platforms today are capable of handling very dynamic customer journeys, where interactions are constantly changing based on behavior and context.

d) Automation and Trigger-Based Engagement

Automation is another core capability that enables experience-first Martech. Event-driven campaigns enable organizations to respond instantly to customer behaviors such as:

• Cart abandonment
• Product browsing
• Form submissions
• Support requests

Automated Martech workflows ignite real-time, personalized engagement instead of static schedules. That makes it more responsive, but with less manual effort to run it.

Trigger-based engagement also leads to more relevant and contextual engagements, improving customer experience and conversion performance.

e) Real-Time Data Processing

The speed and contextual responsiveness are very critical today for customer engagement. Martech platforms can analyze customer interactions on the fly and choose how to interact with them immediately because they can process data in real-time.

This capability allows:

• Dynamic personalization
• Instant recommendations
• Context-aware messaging
• Continuous optimization

Real time processing changes marketing from a scheduled campaign model into an adaptive engagement ecosystem that can respond continuously to customer behavior.

Positioning: Martech as a Smart Experience Orchestration Engine

The Martech space is changing fast. What used to be a collection of disconnected campaign tools is evolving into an intelligent experience orchestration engine that can link customer data, engagement workflows, AI-driven insights, and real-time interactions into one ecosystem.

Martech is helping organizations move beyond channel-centric marketing to seamless customer experiences built around moments, intent, and behavior. It enables journey-based engagement, contextual personalization, and continuous optimization.

Designing Campaigns Around Moments

Channels alone are not enough to drive modern customer engagement. Consumers interact with brands across multiple devices, platforms and touchpoints and demand a frictionless, relevant and personalized experience throughout their journey. This has prompted organizations to move from traditional campaign-centric strategies to moment-based engagement models that are centered around customer intent, timing and context. The change is being driven by next-gen Martech ecosystems that can orchestrate dynamic customer experiences in real time.

Experience-first marketing understands that customers don’t think in campaigns or channels. They live in moments, specific interactions where they gather information, make decisions, solve problems or build relationships with brands. Organizations need to rethink how they use Martech to understand customer behavior, personalize interactions, and orchestrate experiences throughout the entire lifecycle to build campaigns around these moments.

a) Identifying Critical Customer Moments

One of the most important steps in experience-first engagement is identifying critical customer moments across the journey. These moments are opportunities where customer intent, emotion and decision making are at a peak.

1. Awareness Moments

Awareness moments are the first time a customer sees a brand, product or service. These interactions can occur via social media, search engines, online reviews, advertising or recommendations. Typically, customers are in the mode of considering options and researching information, not actively buying, at this stage.

Modern Martech platforms help organizations identify awareness signals through behavioral tracking, engagement analytics and intent analysis. This enables brands to provide educational and relevant content that caters to the needs of early-stage customers.

2. Decision-Making Moments

Customers are researching products, comparing solutions or readying to transact at these decision-making moments. These moments are so powerful because customers are actively assessing value, trust, convenience and relevance.

These Martech systems allow organizations to track behavioral signals, including repeated views of products, visits to pricing pages, abandoned shopping carts, and frequency of engagement. These kinds of insights help brands deliver personalized offers, recommendations and messaging to assist with conversion decisions.

3. Retention and Loyalty Moments

Customer engagement doesn’t stop at conversion. Retention and loyalty moments are equally important because they build long-term customer relationships. Post-purchase experiences include follow-up communication, support interactions, loyalty rewards and personalized recommendations.

With advanced Martech ecosystems, organizations can ensure they keep these interactions going, so customers continue to get relevant engagement long after the initial purchase.

b) Mapping Intent Across the Journey

Designing campaigns around moments and not channels is where customer intent is key. Intent is what the customer is trying to do at a particular moment in their journey.

1. Behavioral Analysis and Engagement Statistics

Behavioral data is analyzed in real time by modern Martech platforms to determine intent of the customer. Engagement signals such as browsing patterns, search activity, purchase history, content interaction, and response behavior can offer valuable insights into customer interests and needs.

For example:

• Frequent product comparisons may indicate evaluation intent
• Repeated visits to support pages may indicate confusion or friction
• Increased engagement with promotional content may signal purchase readiness

With the study of these behaviors, organizations can be proactive and forecast customer needs with the use of Martech systems.

2. Understanding Customer Needs at Each Stage

Different stages of the customer journey require different types of engagement. Early-stage customers may need educational content, while social proof, offers and product recommendations may be more effective with customers closer to conversion.

Experience-first Martech allows organizations to personalize messaging in real-time, as customer intent changes. Brands also have the ability to personalize experiences based on the behavioural context and the stage of the journey and not treat all customers the same.

c) Building Contextual Engagement Strategies

Context has become one of the most important elements of contemporary engagement strategy. Brands need to provide interactions that are timely, relevant and personalized.

1. Delivering the Right Content at the Right Moment

Experience-first campaigns are very focused on delivering the right content at the right time. This means that organizations need to understand not only customer behaviour but the environmental and situational context as well. Modern Martech platforms leverage contextual data such as:

• Device type
• Time of day
• Geographic location
• Customer history
• Current browsing behavior

These insights help organizations tailor engagement dynamically to improve relevance, and effectiveness.

2. Adaptive Messaging Based on Customer Behavior

Adaptive messaging is another big benefit of experience-first Martech. Organizations can change engagement on the fly based on what customers are doing at that moment, rather than run fixed campaigns.

For example:

• A first-time visitor may receive introductory educational content
• A returning customer may receive loyalty rewards
• A customer abandoning a cart may receive follow-up recommendations

This flexibility enables you to improve the customer experience, boost engagement, and improve conversion performance.

d) Omnichannel Experience Coordination

Today’s customer journeys are multi-channel, multi-device. A customer might start searching for a product on a smartphone, continue on a desktop and make the purchase via an app or physical store. One of the key roles of modern Martech is to orchestrate those interactions.

1. Seamless Cross-Device, Cross-Platform Transitions

Customers expect continuity wherever interactions take place. “They don’t want to re-do actions, they don’t want to re-enter information, and they don’t want inconsistent messaging across platforms.”

Advanced Martech systems connect customer data across devices and touchpoints, helping organizations ensure smooth transitions throughout the journey. This leads to a more intuitive and frictionless customer experience.

2. Maintaining Continuity in Conversations

The key to building trust and engagement is continuity of experience. Frustration and reduced customer satisfaction are often the results of disconnected interactions.

Connecting customer interactions across Martech platforms is made possible by journey orchestration capabilities:

• Email
• Social media
• Mobile apps
• Websites
• Customer support channels
• Offline touchpoints

This coordinated approach turns isolated interactions into continuous relationships with customers.

e) Dynamic Content and Personalization

Personalization has emerged as a defining customer engagement trait in the modern age. But delivering personalized experiences at scale requires advanced Martech capabilities fueled by AI and real-time analytics.

1. AI-Driven Recommendations

Martech platforms can use artificial intelligence to provide personalized recommendations based on customer behavior and preferences and intent signals.

For instance:

• Product recommendations
• Personalized content suggestions
• Dynamic pricing offers
• Loyalty incentives

AI-powered personalization enables organizations to improve relevance and boost customer satisfaction and conversion performance.

2. Real-Time Customization of Experiences

Today’s consumers expect experiences that respond immediately to their actions and preferences. Real-time customization allows organizations to change content, messaging and interactions throughout engagement.

For example:

• Website experiences can change based on browsing history
• Email content can adapt to customer preferences
• Mobile apps can display personalized offers in real time

This allows Martech platforms to provide highly contextual, personalized experiences across all customer journey touchpoints.

KEY FINDINGS

Experience-first campaigns focus on timing, relevance and continuity not channel execution. Instead of isolated campaigns, organizations are leveraging Martech to build connected customer experiences around moments, intent and behavior.

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Business Impact of Experience-First Martech

Experience-first engagement is changing the way organizations build relationships with customers and how they define success in marketing. Businesses are transforming customer outcomes and operational performance through the use of Martech to provide seamless, personalized and contextual interactions.

a) Enhanced Customer Experience

One of the most immediate benefits of an experience-first Martech is a better customer experience. Customers expect brands to understand their needs and offer relevant, connected interactions more than ever before.

• More Seamless, Relevant Interactions

In the modern Martech ecosystem, organizations can personalize engagement based on context, behavior and preferences of customers. It provides a smoother, more intuitive experience throughout the customer journey.

• Increased Customer Satisfaction and Trust

Trust comes from being consistent and customized. Customers are more likely to engage with brands that recognize them and offer continuity between interactions.

b) Higher Engagement and Conversion

Experience-first engagement strategies also pay off for marketing performance.

• Improved Response Rates Through Contextual Marketing

Contextual messaging at the right time, is more relevant and delivers higher engagement. Customers prefer interactions that are aligned with their intent and behaviour.

• Reduced Friction Across Customer Journeys

Connected experiences help reduce confusion, duplicated interactions, and the unnecessary complexity that prevents customers from successfully completing desired actions.

c) Improved Customer Retention

Retention is now the main focus for long-term growth of organizations.

• Better Relationships Through Increased Personal Engagement

Brands can take advantage of personalized post-purchase experiences to build deeper relationships with customers over time.

• Increased Loyalty and Lifetime Value

Experience-first Martech drives customer lifetime value and repeat engagement through loyalty programs, targeted recommendations and retention campaigns.

d) Better Data and Insights

Unified MarTech ecosystems help organizations gain a more holistic view of customer behavior.

• Deep Understanding of Customer Behaviour

Businesses get better visibility into journey patterns, preferences and intent signals by unifying customer data across channels and touchpoints.

• Better Decision Making and Optimization

Organizations can continuously optimize customer experiences and engagement strategies through real-time analytics and AI-driven insights.

e) Operational Efficiency

Experience-first engagement also improves internal operating performance.

• Automation Cuts Manual Coordination

Martech platforms have automated features that reduce repetitive tasks and help to streamline workflows across teams.

• Unified Workflows for Teams and Channels

Integrated systems allow marketing, sales, customer support and customer experience functions to work together better.

Takeaway

Experience-first Martech drives better customer outcomes and better business performance. Martech is helping organizations move beyond siloed campaigns to intelligent, customer-centric engagement ecosystems, enabling contextual engagement, real-time personalization, journey orchestration and unified customer experiences.

Challenges in Implementing Experience-First Martech

As organizations shift from channel-centric marketing to experience-first engagement, Martech is playing a more strategic role than ever before. Today’s business world demands seamless, personalized, real-time interactions throughout increasingly complex customer journeys. But applying experience-first Martech is anything but simple. While the promise of connected customer experiences is alluring, many organizations are hamstrung by technological, operational and cultural barriers impeding their transformation efforts.

To achieve experience-first engagement, organizations need to rethink how they handle customer data, work together across teams and align technologies throughout the enterprise. It’s not just about launching new platforms, it’s a complete change in the way organizations interact with customers. As businesses seek to provide a unified customer experience across channels and touchpoints, some major challenges remain.

a) Data Fragmentation

Data fragmentation is one of the biggest barriers to experience-first Martech deployment. Modern customer journeys produce massive amounts of information from websites, mobile apps, CRM systems, social media platforms, advertising tools, customer support systems, and offline interactions. However, this data often resides in different environments in silos making it difficult to have a single customer view.

1. Customer Data Spread Across Systems

Most organizations have multiple systems that independently capture and store customer data. Transactional data in CRM platforms, engagement data in marketing automation systems and behavioral insights in analytics tools. When not properly integrated, these systems create data silos that limit insight across the customer journey.

Fragmented data presents a number of operational challenges:

• Duplicate customer records
• Inconsistent customer profiles
• Incomplete behavioral insights
• Disconnected personalization strategies

Many enterprises still struggle to fully integrate these data sources, despite efforts by modern Martech platforms to consolidate them.

2. Difficulty Creating Unified Profiles

The ability to create unified customer profiles is critical to experience-first engagement. Organizations need a comprehensive view of customer behavior, preferences, intent and history across all touchpoints.

But identity resolution is hard, because customers frequently move across:

• Devices
• Channels
• Platforms
• Online and offline environments

The absence of advanced Martech capabilities makes it difficult for businesses to consistently identify customers throughout the journey. This fragmentation limits the ability to personalize and diminishes the impact of experience orchestration strategies.

b) Organizational Silos

If organizations remain fragmented, technology alone cannot deliver unified experiences. Many companies still have siloed marketing functions organized around channels rather than journeys.

1. Teams Structured Around Channels

The traditional marketing department is often split into specialist groups that focus on:

• Email marketing
• Social media posts
• Paid advertising
• Web engagement
• Content marketing

Each team is independent with its own goals, processes and KPIs. This structure might increase channel expertise but it creates barriers to collaboration and customer journey continuity.

Martech with an experience-first focus necessitates that organizations move beyond channel-specific execution and embrace cross-functional collaboration models. This change can be difficult, because existing organizational structures are deeply embedded in many enterprises.

2. Resistance to Journey-Based Collaboration

Cultural resistance is one of the biggest challenges in Martech transformation. Teams accustomed to owning their own channels may resist broader engagement strategies that are journey-based and require shared accountability.

This resistance often appears in several forms:

• Lack of collaboration between departments
• Conflicting KPIs and performance models
• Reluctance to share customer data
• Difficulty aligning around customer-centric goals

So, organizations adopting an experience-first Martech will have to focus on change management and alignment of leadership along with technology modernization.

c) Technology Integration Complexity

Today’s organizations tend to run big, highly fragmented Martech ecosystems full of specialized tools. The individual platforms may be doing well but getting them all into a single experience infrastructure is very tricky.

1. All-in-One Marketing Technology Platforms

Many businesses use a variety of platforms for:

• CRM
• Analytics
• Automation
• Advertising
• Customer support
• Data management
• Content delivery

These tools are often built by different vendors on different architectures and data structures. It’s a huge effort to integrate them into a coherent ecosystem and requires ongoing maintenance.

In the absence of integration, customer interactions are isolated within systems, limiting the ability to provide seamless experiences.

2. Managing Interoperability

Interoperability is one of the most important priorities in modern Martech environments. What organizations need are platforms that can share data and coordinate workflows in real time.

However, interoperability is difficult to achieve because:

• Legacy systems may lack modern APIs
• Data formats may differ between platforms
• Integration workflows may require customization
• Real-time synchronization increases operational complexity

As Martech ecosystems grow, organizations need to balance flexibility with operational simplicity to prevent the creation of unmanageable technology stacks.

d) Compliance and Privacy

As customer engagement becomes more personalized, privacy and compliance concerns are increasing.

1. Balancing Personalization with Data Governance

Experience-first Martech uses customer data to offer relevant and contextual interactions. However, companies must make sure their personalization efforts are in line with privacy laws and ethical data practices.

Customers are also increasingly asking for transparency around:

• Data Gathering
• Consent administration
• Practices of personalization
• Exchange of information

As a result, organizations must balance their personalization capabilities with robust governance frameworks.

2. Issues with Consent Management

Current privacy laws require businesses to carefully manage customer consent across multiple touchpoints and systems.

This poses operational challenges such as:

• Consent management across platforms
• How to Manage Customer Preferences
• Worldwide regulatory compliance
• Maintaining transparency in data usage

Poor privacy management can damage customer trust and lead to legal risks. Hence why compliance is becoming a key part of modern Martech strategies.

e) Skills Gap

Another major obstacle in deploying experience-first Martech is the increasing scarcity of specialized skills.

1. Demand for AI, Analytics & Journey Orchestration Skills

Modern Martech ecosystems demand expertise in multiple disciplines, such as:

• Machine learning and AI
• Customer Analysis
• Journey orchestration
• Automation workflows
• Data integration
• Personalization strategy

But many organizations are struggling to find professionals who can manage these increasingly sophisticated environments.

The fast-changing nature of Martech technologies has resulted in major skill gaps across the industry. Often, businesses will adopt sophisticated platforms without the internal expertise to get the most value from them.

2. Complexity: strategic and operational

Experience-first engagement is more than technical know-how. Organizations need professionals who understand:

• Customer psychology
• Behavioral analysis
• Experience design
• Cross-functional collaboration

Martech transformation initiatives commonly fail to meet expectations without a blend of strategic and technical skills.

The Takeaway

Experience-first transformation is a technology and an organizational change. Advanced Martech platforms can assist with real-time personalization, journey orchestration, and customer intelligence, but the true transformation is also linked to data strategy, cross-functional collaboration, operational alignment, and cultural adaptation.

The Future of Experience-First Martech

The future of Martech is more and more about smart, connected and always-on customer engagement ecosystems. With customer expectations constantly changing, organizations are shifting from traditional campaigns to highly adaptive experiences powered by artificial intelligence, automation and real-time customer intelligence.

Experience-first engagement is no longer just a competitive advantage, but a business imperative. Future Martech ecosystems will move away from static customer journey mapping toward dynamic orchestration based on behavior, context and intent.

a) AI-Driven Experience Orchestration

Artificial intelligence is quickly emerging as one of the most revolutionary forces in modern Martech.

1. Autonomous Personalization Engines

Future Martech systems will be heavily dependent upon autonomous personalization engines that can:

• Analyzing customer behavior continuously
• Predicting intent in real time
• Adapting content dynamically
• Optimizing engagement automatically

These AI-based systems will dramatically reduce manual campaign management while improving the quality of personalization at scale.”

2. Predictive Engagement Models

Experience-first Martech strategies will increasingly revolve around predictive analytics. AI models will predict customer needs before they are articulated enabling organizations to provide proactive engagement experiences.

Predictive capabilities will allow:

• Next-best-action recommendations
• Churn prevention strategies
• Dynamic pricing models
• Personalized journey optimization

b) Real-Time Customer Intelligence

The future martech ecosystems will increasingly operate in real time.

1. Continuous Behavior Analysis

Organizations will continuously analyze customer behavior across channels, devices and interactions to identify intent signals that are evolving in real time.This real-time intelligence enables brands to respond instantly to customer actions, reducing friction and enhancing relevance.

2. Adaptive Customer Journeys

Customer journeys will be more fluid and responsive. “Future Martech systems will not run pre-defined campaign flows, but will dynamically adjust experiences based on customer behavior and contextual signals.

c) Hyper personalized experiences

Personalization will continue to evolve toward hyper-individualized engagement.

1. Individualized Engagement at Scale

Modern customers increasingly expect experiences designed specifically for their needs, preferences and context. Future Martech platforms will enable personalized interaction across:

• Web pages
• Apps mobile
• Promotion
• Customer service
• Business environments

2. Context-aware Recommendation

AI-powered recommendation engines will constantly adjust interactions based on:

• Behavioral history
• Real-time context
• Purchase intent
• Emotional signals

This degree of personalization will be a hallmark of future customer engagement strategies.

d) CX and Salestech Converge Martech

The lines between Martech, customer experience platforms and Salestech are starting to blur.

1. Unified Experience Ecosystems

More and more organizations are building unified ecosystems linking:

• Advertising
• Sales & marketing
• Customer support
• Sales operations
• Customer experience management

This convergence allows organizations to manage the entire customer lifecycle in a more cohesive manner.

2. Connected Customer Life Cycle Management

Future Martech environments will enable ongoing customer lifecycle management, not one-off campaign execution. Every interaction will be part of a connected experience ecosystem.

e) Experience as the Primary Competitive Differentiator

With products and services increasingly commoditized, the quality of the experience is becoming the primary competitive differentiator.

1. Brands Competing for Relevance and Responsiveness

Organizations will increasingly compete on:

• Personalization quality
• Response speed
• Journey continuity
• Customer understanding

Brands that can deliver seamless and intelligent experiences will have long-term competitive advantages.

2. Marketing Is Evolving to Continuous Experience Management

Marketing is moving from campaign execution to continuous experience management. Organizations will manage ongoing customer relationships powered by Martech orchestration systems rather than running isolated promotions.

Positioning

The future of Martech is experience, intelligence and always-on. As AI, automation and customer intelligence continue to evolve, Martech platforms will become increasingly connected engagement ecosystems that can deliver seamless, adaptive and highly personalized experiences across every touch point of the customer journey.

Conclusion: Marketing Goes Experience-Driven

Marketing is going through one of the biggest transformations in its history. Experience-first engagement strategies focused on customer moments, intent and contextual interactions are quickly replacing traditional, campaign-based models built around standalone channels. Today’s customers don’t think about email campaigns, social media channels or advertising platforms anymore. They think in experiences They want brands to understand what they need, to respond in real time, and to deliver seamless interactions no matter where they engage.

The change has fundamentally altered the role of martech. What began as a suite of tools for campaign management and automation is evolving into an intelligent orchestration layer that connects customer data, AI-driven insights, real-time analytics and cross-channel engagement into a single ecosystem. Martech is helping organizations to move beyond disjointed customer interactions and toward continuous, personalized and adaptive experiences.

Today’s journeys are anything but linear, and customer moments are becoming ever more important. Consumers move from device to device and across touch points expecting continuity across the entire lifecycle. Brands that don’t deliver connected experiences risk friction, inconsistency and disengagement. So, organizations are putting more emphasis on contextual engagement, not just channel execution.

The future of Martech is getting smarter and more predictive Meanwhile. AI-driven orchestration, hyper-personalization, real-time customer intelligence and unified experience ecosystems are changing how brands engage with their customers. Marketing is becoming a continuous engagement function where personalization, timing, responsiveness and relevance are the keys to success.

This change is also visible in the convergence of Martech, customer experience platforms and Salestech. “Organizations are no longer managing marketing, sales and support in silos. Instead, they are building connected engagement ecosystems around the entire customer lifecycle. Every interaction contributes to the total experience and every touchpoint becomes part of an ongoing relationship.

Ultimately, the future of marketing will not be defined by the number of channels brands use, but by the effectiveness of Martech to facilitate seamless, contextual and intelligent customer experiences across every moment of the journey. Brands that successfully adopt an experience-first approach to engagement will be better positioned to build trust, foster loyalty, improve operational efficiency and gain enduring competitive advantage in a more connected digital economy.

The world’s simplest and most powerful event scanner, now with AI-powered enrichment and conversation intelligence capabilities.

Captello, a leader in event technology solutions, is proud to introduce its latest breakthrough: the Intelligent Scanner, designed to revolutionize how organizations capture and enrich event data. This groundbreaking scanning solution is designed to streamline event data capture by offering unparalleled flexibility and intelligence. The Intelligent Scanner allows users to capture everything from event badges and business cards to QR codes, LinkedIn profiles, paper documents, and even live conversations, all with the simplicity of a single button.

Ryan Schefke, CEO of Captello, expressed his excitement about the new release: “We are thrilled to introduce the Intelligent Scanner, a game-changer for organizations of all types. This solution allows our users to gather valuable insights effortlessly and in real-time, all while maintaining privacy and accuracy. The Intelligent Scanner transforms how organizations capture leads, ensuring that no valuable data is ever missed.”

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A New Era in Lead Capture: One Button, Limitless Possibilities

The Intelligent Scanner’s true power lies in its versatility. It’s the first solution that combines cutting-edge AI-powered data enrichment with the simplicity of a single button, enabling users to capture virtually any type of data from event badges to handwritten notes instantly and effortlessly.

This feature ensures that no data is ever missed, whether it’s a note scribbled on a napkin during a networking moment, a printed resume handed to you at a conference, or a badge from an event that doesn’t offer an API integration. Once scanned, the information flows through Captello’s powerful multi-layered AI engine, which instantly enriches the data by pulling details such as email addresses, phone numbers, and company information from over 25 data sources. This ensures that all lead data is comprehensive, actionable, and ready for follow-up.

For Captello’s Chief Technology Officer, Nassir Jamal, the focus on innovation and user experience was paramount. “Our team has worked tirelessly to develop a solution that not only delivers on speed and functionality but also integrates cutting-edge AI to enrich the data we capture,” Jamal said. “The new scanner brings convenience and power to our users by automatically enriching scanned information. This is an essential step toward the future of event data management.”

The technology also boasts conversation intelligence capabilities, allowing users to record and transcribe live consent-based conversations at events. This unique feature provides a full transcript, action items, suggested next steps, and even identifies who said what during the conversation. This enriched content flows directly into the user’s CRM or marketing automation system, ensuring that no important details are lost in the hustle of a busy event.

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Seamless Integrations for Streamlined Workflows

Captello’s Intelligent Scanner integrates seamlessly with over 6,000 CRM and marketing automation platforms, as well as over 300 registration providers. This ensures that all captured data flows directly into your preferred systems, automating follow-up and enriching data without the need for manual entry. Whether you’re using Salesforce, HubSpot, Marketo, or any other leading CRM or marketing automation tool, Captello’s platform offers seamless connectivity, making it easier than ever to keep your leads organized and your follow-up processes running smoothly.

Capturing More Than Just Data: A Complete Event Intelligence Solution

Captello’s Intelligent Scanner is part of a broader suite of AI-powered event solutions, including engagement, digital networking, meeting management, enterprise-grade reporting, powerful automation, and workflow capabilities designed to optimize lead capture, accelerate follow-up, and prove event ROI.

“We’ve developed a platform that not only helps businesses capture leads but also provides the tools they need to convert those leads into real business opportunities,” said Aaron Karpaty, Senior Director of Strategic Growth. “With the Intelligent Scanner, we’re empowering organizations to make every interaction smarter, faster, and more valuable.”