Each week, I speak with business leaders who have invested significantly in AI and CRM, yet still see customers waiting on hold, repeating information, and leaving frustrated. Our latest research quantifies this: poor customer service in EMEA costs consumers 9.2 hours annually, more than a full working day. While AI can address these issues, applying it to fragmented systems only worsens the experience. The real solution is to rethink the systems supporting service, not just the technology layered on top.

Frontline customer service agents often lack the necessary tools and information, with only a third of organizations reporting their agents are truly empowered, according to ServiceNow’s annual CX Shift report. Despite investments in technologies like AI, many businesses undermine these efforts by failing to unify their organizations within a single CRM system.

Addressing this challenge requires a fundamental shift in CRM usage toward a connected enterprise, where departments share information effectively and CRM functions as a system of action across the business. Moving away from siloed approaches reduces customer frustration and repetition. Every customer interaction, whether proactive or reactive, can either build or erode loyalty.

The Cost of Disconnection

The research surveyed 17,335 executives, service representatives, and consumers across EMEA. It found that 47% of customers would switch brands after a single poor or slow service experience. Even in sectors where quick resolution is critical, such as banking and telecoms, issues can take three to four days to resolve.

A critical gap remains between insight and action, as businesses struggle to translate AI investments into improved customer relationships. Too often, organizations layer AI onto fragmented CRM systems, expecting a transformation that does not materialize. Siloed workflows and disparate data only accelerate negative customer experiences.

Half of the surveyed executives report deploying end-to-end CRM platforms that support the entire customer lifecycle. However, what is needed is an AI-driven service powered by CRM data, enabling seamless, efficient customer escalation.

Connected Enterprise Is the Foundation, Not Just a Goal

Notably, 76% of EMEA organizations expect progress in the next three years to result from a connected enterprise approach, compared to 51% who expect it from AI adoption alone. A truly connected CRM is increasingly viewed as the operational foundation for enhanced customer experience.

Traditional CRM systems, which most organizations have used, were designed primarily for the front office. They capture customer requests but often do not manage fulfillment, resolution, or back-office actions, which are handled by separate systems. This fragmentation forces customers to repeat themselves, as no single system provides a complete view.

Current expectations require a new approach. Sellers, service agents, field technicians, and back-office teams should operate on a unified AI-powered platform, sharing a single customer record in real time. Customer issues raised through chat should be tracked, escalated, fulfilled, and resolved without requiring the customer to repeat information.

When CRM is implemented in this manner, businesses experience stronger customer loyalty, increased agent productivity, and improved cost efficiency.

The Agent Experience Is Part of the Customer Experience

It is essential that agents have access to the right tools and data, which requires rethinking how information is shared across the organization. In most organizations, agents are hindered by fragmented systems and disconnected tools. The research found that 79% of EMEA service agents must log into three to five separate systems to resolve customer queries, and inconsistent data across these systems remains a significant challenge.

Service agents prefer to focus on complex customer issues where human assistance is essential, rather than compensating for fragmented systems. By adopting integrated systems, agents are freed from switching between platforms, administrative tasks, and searching for information across departments. Instead of investing in automation without a strategy, organizations should reimagine CRM as a connected engine that unites teams, data, and processes, enhancing the service agents provide.

When organizations implement CRM effectively, the benefits extend beyond improved service interactions. A connected, service-led CRM strategy saves time for both customers and employees, transforming fragmented touchpoints into cohesive journeys that foster trust and long-term loyalty. Customers are more likely to deepen relationships when they feel recognized and understood at every stage. Internally, teams gain shared data visibility, enabling faster decisions, more effective AI use, and meaningful human engagement where it matters most.

AI Delivers When the Plumbing Is Right

However, few organizations have integrated customer data across touchpoints to create a unified view. Only 43% of EMEA organizations surveyed have achieved this, and just 23% have broken down silos to enable seamless AI strategies that connect departments.

This highlights the need for an approach that connects data across cloud environments, departmental tools, and legacy systems, providing AI with a complete customer view before taking action. In this model, AI agents act autonomously, coordinate across departments, and operate continuously without waiting for human input.

This is the difference between AI that resolves a billing dispute at 2:00 AM without human intervention and AI that simply accelerates the same flawed experience customers already face.

Service as a Growth Engine

Organizations that implement connected CRM effectively are discovering what the cost-center perspective overlooks: when service has full visibility into the customer relationship, it becomes a revenue driver.

In practice, this allows service agents to identify upsell and cross-sell opportunities in real time. They can create quotes, manage renewals, and escalate commercial opportunities on the same platform used for service requests. Service and sales become integrated, enabling the agent who resolves an issue to also strengthen the customer relationship.

A connected, service-led CRM strategy not only reduces the nine hours EMEA consumers lose annually to resolution friction but also builds trust and encourages customers to strengthen their relationships rather than switch brands.

Curbing Repetition, for Good

When repetition is the issue, the solution can be straightforward. By establishing a connected enterprise where customer information is shared across all channels and applications, agents are empowered to deliver effective service. A single interface with a comprehensive information streamlines work. In this model, service becomes a growth driver by enhancing productivity, insight, and competitive advantage across the organization.

Investing in AI to accelerate flawed processes will not yield results. Business leaders should instead reimagine CRM as a system of action across all channels, ensuring agents can deliver, and customers no longer waste valuable time with each interaction.

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HubSpot’s Spring 2026 Spotlight arrived this week with a clear thesis: Raw data is no longer enough for artificial intelligence to be effective. As organic search traffic continues to fracture, the CRM giant is betting on “context”—the deep, historical knowledge of customer behavior—to power its next generation of growth tools.

“Most AI tools have access to data. What they don’t have is context,” said Duncan Lennox, Chief Product and Technology Officer at HubSpot. “If data is what happened, context is why. It’s the difference between generic output and real business outcomes.”

The company’s latest releases focus on three critical pillars of the modern enterprise: building awareness in an AI-first world, accelerating revenue through autonomous prospecting, and scaling support without inflating headcount.

Also Read: Clarity Is Marketing’s Most Valuable Asset

Winning the ‘Answer Engine’ War

In perhaps the most significant shift for digital marketers, HubSpot introduced its Answer Engine Optimization (AEO) solution. With organic traffic for HubSpot customers down 27% year-over-year, the company is pivoting toward the “referral economy” of LLMs like ChatGPT, Gemini, and Perplexity.

Unlike traditional SEO tools, HubSpot AEO uses a company’s own CRM data to predict the prompts real customers are likely to use. The tool provides:

• Competitor benchmarking within AI responses.
• Citation analysis to track brand authority.
• Direct integration for Marketing Hub Enterprise users, starting at a $50/month standalone entry point.

Complementing this is the Breeze Assistant, now trained on HubSpot’s “Loop Marketing” playbook. The assistant can now build brand guides and campaign briefs grounded in actual customer records rather than generic marketing templates.

Sales Agents that Think Like Reps

To combat the administrative “deal killers” that plague sales teams, HubSpot unveiled Smart Deal Progression and an overhauled Prospecting Agent.

The Prospecting Agent now monitors external signals—such as funding rounds and job postings—to surface high-priority accounts. Early data suggests the agent’s personalized outreach is achieving response rates double the industry benchmark. Meanwhile, Smart Deal Progression acts as a “second brain” for reps, analyzing call transcripts against the full CRM history to suggest pipeline updates and draft follow-up emails that reflect the nuances of long-term relationships.

Also Read: Your Rebrand Is Failing. Have You Tried Listening?

Efficiency at Scale

On the post-sale side, the new Customer Agent has expanded to email, the highest-traffic support channel for most firms. By drawing on the full customer relationship rather than isolated tickets, the agent is reportedly resolving 70% of inquiries autonomously.

For human-led teams, the agent offers “reply recommendations” for review, ensuring that AI speed never comes at the cost of brand voice.

The post HubSpot Debuts AI Tools to Reclaim Shrinking Search Reach appeared first on MartechView.

Salesforce already owns more CRM customers than anyone else. On March 10, it argued that the contact center should be next.

The company launched Agentforce Contact Center, a platform that natively combines voice, digital channels, CRM data, and AI agents in a single architecture. The pitch is straightforward: contact centers built on disconnected systems cannot operationalize agentic AI at scale, and Salesforce — with its unified platform — can solve that problem in a way that point solutions and legacy CCaaS vendors cannot.

The Problem It’s Solving

Most enterprise contact centers are, beneath the surface, an archaeology project. Years of layered additions — telephony platforms, digital messaging tools, CRM integrations, AI add-ons — have created service operations that can technically support omnichannel engagement but routinely lose context when customers switch channels or when AI interactions escalate to a human agent.

The customer, of course, experiences none of those system boundaries. They experience one conversation with a company. The context loss is invisible to them until something goes wrong — and then it’s very visible.

“Customers don’t experience a voice system, a digital system and a CRM separately,” said Kishan Chetan, EVP and GM of Agentforce Service at Salesforce. “They experience one interaction with a company. Salesforce’s goal is to treat those systems as a single service nervous system so both AI and human agents operate with the same context.”

That framing — voice, AI, and CRM as a single nervous system rather than three integrated products — is the core of what Salesforce is selling.

Also Read: Your Rebrand Is Failing. Have You Tried Listening?

What Early Customers Are Finding

The platform is already in production with a small group of early adopters, including Savant Systems, Compass Working Capital, Ferguson, and PAM Hotels. Their experience offers a ground-level view of where the value actually shows up.

At Compass Working Capital, a nonprofit that previously ran separate applications for email, text, and phone — each with its own data model and workflow — the shift to a unified platform is expected to eliminate significant manual overhead. Currently, coaches on the team spend up to 30 minutes entering notes after each appointment. Compass estimates that automating call summaries and structured data entry could recover roughly 6,000 staff hours per year.

Savant Systems, which supports smart home installations where every environment is different — different devices, different subscriptions, different integrations — is using the platform to automatically surface case context before agents engage with a customer. The company is also exploring AI-driven escalation detection to identify service issues that require faster intervention before they become complaints.

Also Read: Marketing That Predicts, Not Reacts

Why Salesforce, Why Now

The launch reflects what Chetan described during a media briefing ahead of the announcement as a broader convergence between the CRM market and the contact center-as-a-service market. Customer demand for proactive, personalized, consistent service across every channel is pushing the two categories toward each other — and Salesforce is positioning itself as the natural consolidation point.

The competitive logic is blunt. If an enterprise is already running Salesforce as its system of record for customer relationships, adding a contact center layer that lives natively inside that system eliminates an entire category of integration risk. The alternative — connecting a third-party CCaaS platform to Salesforce — is precisely the fragmentation problem the platform is designed to solve.

Whether Agentforce Contact Center can displace established CCaaS vendors with deep telephony expertise and long enterprise contracts is the open question. But Salesforce is not entering this market without leverage. It has the customer relationships, the CRM data layer, and now the platform architecture. The CCaaS incumbents have been warned.

The post Salesforce’s Agentforce Just Entered the CCaaS War appeared first on MartechView.

In the crowded world of B2B startups, the struggle is rarely product quality. It is alignment — between positioning and pipeline, between early strategy and late-stage deals.

SalientMG, a strategic marketing advisory firm, announced a partnership on Tuesday with Hivekind AI to address what both companies describe as the “pre-pipeline” problem: the decisions made long before a deal enters a CRM.

Hivekind is the company behind HiveLoop, an agentic decision engine designed to improve deal outcomes by focusing on upstream inputs, including prioritizing when to engage and how to coordinate outreach across multiple stakeholders.

Together, the firms say they are targeting a persistent challenge for early- and growth-stage B2B companies: balancing near-term revenue targets with long-term brand and category positioning.

“Startups often have strong products but struggle because their go-to-market isn’t aligned or focused on the right opportunities,” said Mack McKelvey, founder and chief executive of SalientMG. “By partnering with Hivekind, we’re giving teams a way to connect strong GTM fundamentals with real-time execution.”

Also Read: Agentic GTM Isn’t ABM 2.0; It’s a New Model Entirely

From Positioning to Pipeline

Across B2B software companies, go-to-market decisions — including ideal customer profile definition, messaging and buyer persona mapping — often remain static even as market dynamics shift. The result, executives say, is stalled late-stage deals caused by missing stakeholders or weak early qualification.

Hivekind’s system aims to intervene earlier in the cycle. Rather than optimizing the pipeline once it forms, HiveLoop focuses on shaping pipeline quality at the outset by aligning account prioritization, engagement timing and buyer-group coordination.

SalientMG, known for its hands-on advisory on positioning and demand strategy, adds the strategic layer. Hivekind adds automation and continuous decision-making.

The combined offering is designed to give founders a more unified system — one that connects strategy, execution and revenue generation without requiring early hiring sprees or a patchwork of disconnected tools.

For startups navigating crowded markets and tightening capital environments, the promise is straightforward: stronger upstream decisions, fewer downstream surprises.

As B2B companies rethink how the pipeline is built, not just managed, partnerships like this suggest the next competitive advantage may lie not in closing deals faster — but in qualifying them better from the start.

The post SalientMG and Hivekind Target Pre-Pipeline Gap appeared first on MartechView.

Salesforce has completed its acquisition of Informatica, the enterprise cloud data management firm, in a strategic move designed to secure the data infrastructure required for its next-generation artificial intelligence.

The closing of the deal marks a significant expansion of Salesforce’s technological footprint, integrating Informatica’s vast data catalog and governance capabilities directly into the Salesforce platform. The acquisition is the linchpin of Chief Executive Marc Benioff’s pivot toward “agentic AI”—autonomous systems capable of executing complex workflows rather than merely generating text.

‘The True Fuel of Agentforce’

For Salesforce, the logic behind the acquisition is rooted in the industry-wide struggle to make generative AI reliable for business use. Without pristine, well-governed data, AI models are prone to “hallucinations,” or confident errors.

“You have to get your data right to get your AI right,” Benioff said in a statement Tuesday. “Data and context are the true fuel of Agentforce, and without clean, connected, trusted data, there is no intelligence—only hallucination.”

By absorbing Informatica, Salesforce aims to provide the rigorous data context needed for its Agentforce 360 platform to operate safely at an enterprise scale.

Also Read: GenAI Search Is Rewriting the Shopper’s Playbook

Integration and Metadata

The deal will see Informatica’s technology stack merged with MuleSoft, Salesforce’s existing integration platform. This combination is designed to establish a comprehensive data foundation that enables autonomous agents to interpret information across disparate systems.

Crucially, the acquisition bolsters Salesforce’s metadata capabilities. By pulling in lineage and context from outside the Salesforce ecosystem, the company hopes to make its AI responses more explainable and accurate. This “unified metadata foundation” will also feed into Tableau, Salesforce’s analytics platform, to provide deeper context for business intelligence.

Amit Walia, the chief executive of Informatica, described the merger as an acceleration of his company’s mission to act as the “Switzerland” of data management—a neutral, universal connector for enterprise information.

“By integrating Informatica’s data management capabilities… businesses around the world can drive innovation, efficiency and growth by leveraging a single vendor,” Walia said.

Also Read: Edition 3: Sharp Minds Decoding Tech’s Next Wave

Financial Outlook

Salesforce has moved aggressively to reassure investors regarding the financial impact of the deal. The company stated that it expects the acquisition to be accretive to non-GAAP operating margins and earnings per share within 12 months—a timeline accelerated by a full year compared to original projections.

Management is expected to discuss the transaction’s impact on fiscal 2026 guidance during the company’s third-quarter earnings call, scheduled for Dec. 3.

The post Salesforce Seals Informatica Deal to Power Agentic AI appeared first on MartechView.

Customers have become used to being hyperconnected, “always on,” in the digital world. They receive marketing messages on every platform, at every interaction, from pop-up ads to social media sponsored posts to reviews from their favorite influencers.

There’s a lot of competition for their attention, making it more challenging for brands to develop genuine relationships – no matter how much data is available. Personalization without authenticity falls flat, but understanding the behavioral data, what makes the customer tick, can be the key to building the relationship you want.

What Is Behavioral Data?

Behavioral data is the information that reflects how customers interact with a brand, product, or service. This can include website visits and clicks, purchase history, cart abandonment, email open and click-through rates, time spent on pages, and app usage patterns. You can also glean valuable insights from social media interactions like comments and shares or customer service communications.

Unlike demographic or psychographic data, which merely tells you who a customer is or what they value, behavioral data tells you what they do. These insights are more dynamic and can provide an authentic, real-time picture of customer intent and preference, which you can then use to deliver more personalized, timely, and relevant experiences.

How Does Behavioral Data Affect Authenticity?

Customers are increasingly skeptical of traditional marketing tactics. A report from Edelman Trust Barometer found that 71% of consumers say that if they perceive a brand as putting profit over people, they lose trust in the brand.

It’s clear—customers want authenticity. They prefer communications that feel personal, relevant, and rooted in a genuine understanding of their needs. Behavioral data can help you respond to actual customer behavior instead of your own assumptions for more accurate ways to highlight their preferences, anticipate their needs, and engage with them on a human level.

Strategies to Use Behavioral Data to Build Authentic Relationships

Contextual Personalization

Personalization isn’t just about including a first name in an email greeting. Behavioral data is a valuable tool for tailoring content recommendations and messaging based on the customer’s interactions and journey.

For example, a customer may visit a restaurant’s website and check out the brunch menu, but doesn’t book a reservation. This is a restaurant marketing opportunity to use behavioral data to trigger a geo-targeted ad offering a limited-time weekend brunch special or send a personalized SMS reminding them to finish booking. It’s timely, relevant, and based on real behavior, not guesswork.

Timing Is Everything

Behavioral signals can inform not only what you say but also when you say it. For example, triggering a discount offer after a cart abandonment or delivering onboarding content after a customer signs up for a subscription are timely, behavior-driven communications demonstrating attentiveness and respect for the customer’s journey. They reduce friction, support the customer’s goals, and make them feel understood.

Enabling Predictive Engagement

Tools like AI can forecast what customers are likely to do next based on their past behaviors. For example, data demonstrates that customers who engage with a brand’s blog for two months convert into paid subscribers after reading a case study. This information can be used to proactively suggest case studies to engage these users further and speed up the conversion.

Keep in mind that there’s no manipulation or pressure here. Instead, this approach offers value that is aligned with the customer’s current behavior and their likely needs. It gives your brand credibility while gently guiding the customer through the buying journey.

Driving Two-Way Conversations

Behavioral data doesn’t just help brands speak to customers. It helps them listen, too. For example, if customers frequently search for a feature that doesn’t exist or leave feedback in chat interactions, this may indicate they have needs that aren’t met.

You have an opportunity to acknowledge and respond to these insights. You could add a requested feature, improve support workflows, or reach out for more details to better serve the customer. This shows that you’re actively listening and care, which is the foundation of an authentic and valuable business relationship.

Some brands leverage behavioral data to adapt tone and channel preference. Some customers won’t check your marketing emails, but they’re happy to listen when you use SMS or social media messages. That signals that they need you to meet them where they are.

Segmenting with Purpose, Not Stereotypes

Traditional marketing segmentation often groups customers into static categories like “High-Income Professional” or “Gen X Mom.” Leaving people in broad categories can miss the important nuances of each customer, and your messaging could fall flat.

Behavioral data offers more fluid, accurate segmentation. You can group customers by shared behaviors, such as “customers who use social media purchase buttons” or “customers who download content often.” That’s inspiration to design experiences around those actions and deliver more meaningful interactions to these segments.

Improving the Experience Instead of Selling

A key aspect of an authentic relationship is to provide value without always asking for something in return. Behavioral data can help identify friction points in the customer journey, or places where the customer may get stuck, confused, overwhelmed, or frustrated.

If it’s bad enough, the customer may drop off completely. For example, if you see a lot of customers abandoning ships before the final step of a form, it may indicate that there’s a design flaw or that the pages are lagging. You can proactively fix the issue without discussing it with the customer – or waiting for a complaint – and show that you are attentive to the customer’s needs.

Ethical Use of Behavioral Data

Authenticity also relies on transparency and respect. Customers should know how their data is being used and can opt out of data collection or targeting. Personalization can quickly become ” creepy, ” but committing to ethical data practices and privacy can help you avoid these scenarios and maintain trust.

Let Customer Behavior Guide the Experience

Behavioral data helps you cut through the noise with meaningful, personalized experiences. You can respond to real customer actions, not your own assumptions, to build trust, loyalty, and authentic, long-term relationships. 

The post Using Behavioral Data to Drive Authentic Customer Relationships in a Digital World appeared first on MartechView.

Zinrelo, the leading loyalty platform, and TINT, the leader in community-powered marketing, today announced they have merged to create TrueLoyal, the only loyalty platform for multi-channel consumer brands, featuring groundbreaking predictive, generative, and assistive AI at its core to drive hyper-personalized engagement.

The combination of Zinrelo’s enterprise loyalty engine with TINT’s powerful community, user-generated content, and reviews platform creates a solution purpose-built for consumer brands. Combined, these two market-leading companies address a critical need in the market with a platform that reduces the complexity of multi-channel commerce. TrueLoyal provides a comprehensive toolkit to understand customers, deliver hyper-personalized engagement, and retain them for life—capabilities previously fragmented across multiple vendors—bridging the gap between offline and online transactions and different buyer types.

Also Read: The 4Ps of Martech Unlocking Marketing’s Tech Revolution

“This merger marks a pivotal moment for what’s possible for consumer brands,” said Sameer Kamat, CEO of TrueLoyal. “The future of loyalty is here, and it’s built on authentic, data-rich, human connection. Our solution delivers outsized results for flexible, personalized loyalty programs from gamified streaks to predictive churn models and the tools and strategy that brands need to convert one-time buyers into lifelong advocates.”

TrueLoyal is engineered to solve the most pressing challenges facing multi-channel consumer brands. It integrates the best of both Zinrelo and TINT, enhanced with a powerful AI engine, and program strategy to deliver comprehensive retention. Its suite of capabilities empowers customers to:

• Achieve De-Risked Program Design and ROI: Launch with confidence through data-driven program design, expert strategic guidance, and a commercial model based on shared success. This approach ensures financial viability and delivers continuous growth.
• Enable Omnichannel Cohesion: Seamlessly connect with customers across the entire brand ecosystem—including eCommerce, physical retail, and third-party distributors. This powerful flexibility ensures that brands can connect with the platforms they use and deliver a consistent and rewarding experience wherever their customers shop.
• Gain a Complete 360-Degree Customer View: Eliminate critical offline data blind spots with receipt scanning that captures in-store transaction data without requiring POS integration, finally providing a complete understanding of the customer journey.
• Deploy AI-Powered Personalization at Scale: Connect multiple data points on each customer and build smart audience segments that deliver hyper-personalized experiences at every touchpoint.

Also Read: Why Enrollment Systems Fail Without an Operational Blueprint

“We listened intently to the market. Brands are tired of disjointed tools and data blind spots that prevent them from creating truly unified customer experiences,” added Sameer Kamat, CEO. “TrueLoyal directly addresses these pains. Our platform is built for the complexities of modern commerce, allowing our clients to finally capture a 360-degree view of their customers and engage them scalably and meaningfully, whether they shop online, in-store, or through retail partners. TrueLoyal is all about delivering tangible, predictable ROI and retention.”

The post Zinrelo and TINT Merge to Form TrueLoyal appeared first on MartechView.

In today’s digital-first world, where marketing battles for attention across an ever-expanding array of channels and devices, technology is no longer an afterthought—it’s a cornerstone. Marketing technology—“martech”—represents the evolving realm where marketing art meets technological science to create smarter, faster, and more tailored campaigns. But what exactly is martech, why does it matter so profoundly, who are the players driving it, and how do organizations harness its true power? Enter the “4Ps of Marketing Technology,” a clarifying framework to untangle this complex but vital intersection.

What is Martech?

At its essence, martech is the toolkit, the engine, and the ecosystem that powers modern marketing efforts through technology. It includes everything from customer relationship management (CRM) and data analytics platforms to marketing automation, content management systems (CMS), social media management tools, and artificial intelligence (AI)-driven personalization engines. Martech is not just one solution; it is a constellation of integrated tools and platforms designed to reach customers more effectively and efficiently.

By 2025, global spending on marketing technology is predicted to surpass $150 billion, a staggering figure reflecting its critical role in the business agenda. This investment signals a transition point where marketing organizations must deploy technology thoughtfully to compete, innovate, and deliver personalized experiences at scale.

Why Martech Matters

The digital transformation of consumer behavior has redefined marketing success metrics. No longer is it enough to broadcast messages to broad audiences and hope for conversion. Customers expect interactions that are relevant, immediate, and seamless, regardless of device or channel. Martech enables marketers to meet these exacting expectations through precise data capture, real-time insights, and programmatic delivery.

Moreover, martech breaks down traditional silos. It aligns sales, customer service, product development, and digital teams around unified data and shared analytics, resulting in cohesive brand experiences and optimized return on marketing investment (ROMI). Cutting-edge technologies like AI and machine learning infuse these platforms with predictive capabilities—anticipating customer needs and automating decisions—thus boosting efficiency, reducing waste, and elevating customer lifetime value.

Without a strong martech ecosystem, brands risk falling behind competitors who leverage data, automation, and omnichannel outreach to win hearts, minds, and wallets. Martech is not just beneficial; it is foundational to marketing’s survival and growth in the digital age.

Who’s Driving Martech?

The who of martech spans three major groups:

• Vendors and Innovators: The technology companies that build and evolve the martech stack. Giants like Salesforce, Adobe, HubSpot, and Microsoft dominate with comprehensive CRM, content, and analytics suites. Meanwhile, smaller players and startups specialize in niche capabilities—AI personalization, influencer marketing platforms, identity resolution, and customer data platforms (CDPs)—pushing innovation boundaries daily.
  
• Marketers and CMOs: The practitioners who define strategy and orchestrate campaigns using martech. Today’s CMOs must be hybrid leaders—part creative visionary, part data scientist, and increasingly, part technologist. They demand platforms that provide both flexibility and automation, insisting on seamless user experiences for customers and their teams alike.
  
• Customers and Regulators: The final but often overlooked force shaping martech. Consumer privacy expectations, data regulations like GDPR and CCPA, and ethical considerations around AI use shape how martech operates. Technology must serve transparency, consent, and security to uphold trust. The voice of the consumer is not silent; it influences product development and deployment decisions continuously.
  

How to Harness Martech: The Four Pillars

1. Platform

At its core, martech hinges on the platforms chosen to support marketing activities—whether a CRM system that tracks leads and customer journeys, an automation platform that triggers personalized emails, or an analytics suite that visualizes campaign performance. Selecting the right platforms requires an understanding of business needs, scalability, integration capabilities, and ease of use for end-users.

For example, a multinational retail brand might leverage Salesforce Marketing Cloud for its end-to-end capabilities, while a startup could favor HubSpot for its integrated CRM and marketing automation working seamlessly in one application. Whatever the choice, platforms must communicate with each other, turning data into a single source of truth.

2. Process

Technology alone doesn’t produce results; processes ensure that technology supports strategic goals efficiently. The process pillar includes campaign planning, content creation workflows, lead nurturing cycles, performance monitoring routines, and continual optimization protocols. Martech adoption demands cross-disciplinary collaboration—marketing teams coordinating with IT, data analysts, and legal/compliance officers to align technology with governance and brand standards.

Effective martech workflows cut down bottlenecks and empower marketers to innovate rapidly while maintaining quality control—allowing brands to pivot quickly to market shifts or new customer behaviors.

3. People

No martech stack succeeds without skilled people who understand both marketing fundamentals and technology fluency. This means digital-savvy marketers, data analysts who can interpret big data insights, and technologists who can architect, integrate, and secure systems. The talent gap remains a central challenge as enterprises compete for AI and analytics professionals.

Investing in training is critical. Organizations that cultivate martech literacy across teams empower better decision-making and foster creative use of tools rather than mere compliance. Martech leaders also champion a culture of experimentation and learning—recognizing that iterative improvement powered by data beats one-time perfect execution.

4. Performance

The final “P” is performance—that continuous measurement, analysis, and refinement of marketing efforts powered by technology. Martech tools deliver near-real-time data on campaign reach, engagement, conversion path effectiveness, customer sentiment, and ROI. Marketers can slice and dice data by channel, segment, geography, device, and more, identifying what works and what needs tweaking.

Performance feeds back into platform choices, process improvements, and skill development—in an ongoing virtuous cycle. Enterprises with mature martech capabilities embed performance metrics into daily routines at every organizational level, aligning marketing actions tightly with business outcomes and customer experience goals.

The Road Ahead

Martech’s future lies at the confluence of AI, cloud computing, and data privacy evolution. Emerging technologies like generative AI and agentic AI will supercharge personalization, automating content generation, ad targeting, and customer journey orchestration with unprecedented precision. However, they will also heighten the need for ethical guardrails and transparent AI governance.

Sustainability, too, is becoming an integral metric—not just in environmental terms but digital responsibility, including reducing tech waste and optimizing cloud resource consumption. As platforms evolve, marketers who embrace the 4Ps will not only execute campaigns—they will architect brand experiences that resonate authentically in an increasingly complex digital world.

In short, the 4Ps of Marketing Technology©—Platform, Process, People, and Performance—offer a smart, comprehensive lens for marketers seeking to navigate the ever-shifting martech landscape with confidence and creativity. It is no longer a question of whether to invest in martech but how, strategically, responsibly, and boldly.

In the digital arena, mastering the 4Ps is mastering modern marketing itself—an imperative for 2025 and beyond.

The post The 4Ps of Martech Unlocking Marketing’s Tech Revolution appeared first on MartechView.

London-based hospitality CRM app Embargo is targeting Europe-wide growth with its new raise of $3.5 million in funding.

The injection of capital was provided from a group of prominent angel investors as it looks to scale its AI-driven CRM and loyalty platform across Europe.

The round attracted backing from investors including Paul Statham (founder of Condeco), Christo Georgiev (founder of myPOS), Hampton Finance (the Chantler family fund behind Meadow Foods), Mike Branney (founder of Oh Polly), Stephen Zinser, and Carl Christian Reiner.

Founded in 2018 by Frederick Szydlowski and Tsewang Wangkang, Embargo offers a plug-and-play platform tailored for small and medium-sized hospitality businesses (SMEs), including coffee shops, bakeries, and restaurants. The startup helps operators drive customer retention, repeat sales, and digital engagement across in-store, collection, and delivery channels through loyalty programs and CRM tools that are traditionally only accessible to large restaurant chains.

“Our mission is to level the playing field for hospitality SMEs keen to grow their revenues and scale – we do that by giving them access to the kind of tools typically reserved for global enterprises,” said co-founder Frederick Szydlowski. “This investment is not just a vote of confidence in our product and growth to date, but also in the scale of the opportunity ahead. With strong foundations, a growing international footprint, and a clear product roadmap, we’re perfectly positioned to become the go-to platform for hospitality businesses worldwide.”

In a fragmented European market where SMEs represent around three quarters of hospitality businesses, the accessibility of such tools has lagged behind the US.

Embargo is aiming to bridge that gap, offering what investor Oliver Chantler of Hampton Finance called a “sophisticated but easy to use” platform.

“Embargo is closing a critical information gap in the food and hospitality sector, and we are excited to be part of its journey,” said Chantler.

Embargo plans to use the fresh capital to further develop its AI and machine learning engine, which supports personalised marketing and retention strategies for merchants. It also intends to ramp up B2B sales and marketing, especially in existing markets, before launching in new geographies from 2026. Recent integrations with major US-based payment and POS providers such as Square and Lightspeed hint at a broader global strategy.

“For the first time, we have the budget to fully leverage our product-market fit and significantly accelerate sales and marketing,” said co-founder Tsewang Wangkang. “We aim to more than double our growth year-over-year while maintaining a healthy business model and avoiding short-term artificial spikes that don’t deliver long-term value.”

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Wunderkind, the AI decisioning platform that delivers identity resolution and cross-channel personalization to scale performance and reach, today announced the launch of Wunderkind AI Experiences: a breakthrough portfolio of agentic, personalized messaging strategies.

As marketers face growing pressure to drive revenue, AI Experiences offers a powerful and efficient solution. Unlike traditional tools built on static rules and manual logic, AI Experiences uses advanced identity resolution, real-time behavioral data, and agentic decisioning to deliver the highest performing messages. It determines the best timing and channel for each individual across email and SMS, as well as uses affinity modeling for personalized product recommendations. This drives higher conversions, expands reach and scales personalized experiences beyond what human teams can achieve today.“

“Marketers are tired of building decision trees only to watch them underperform,” said Richard Jones, CRO at Wunderkind. “AI Experiences flips the script. It learns and adapts in real time, continuously optimizing message timing, sequencing, and product recommendations to drive performance without requiring hands-on orchestration. This is lifecycle marketing without the heavy lifting.”

From re-engaging abandoners to recommending the next-best purchase, AI Experiences uses behavioral signals and identity resolution to unlock hyper-relevant touchpoints that drive conversions. By dynamically sequencing campaigns based on individual intent—not pre-set logic—Wunderkind enables marketers to maximize engagement, revenue, and brand loyalty at scale.

Key Benefits of Wunderkind AI Experiences:

• Smarter Targeting: Identify and engage high-intent shoppers with precision, using first-party data and behavioral signals.
• Dynamic Sequencing: Automatically determine the next-best message and moment to send, improving engagement and efficiency.
• Cross-Channel Optimization: Coordinate outreach across email and text in a unified, adaptive flow.
• Effortless Execution: Eliminate complex build-outs and ongoing campaign maintenance with plug-and-play strategies that perform from the start.

“We’re excited to be beta testing Wunderkind’s AI Abandonment capabilities at SMCP,” said Erin Pepe, VP of Digital and Customer Experience at SMCP. “It will take the guesswork out of when and how to reach shoppers—optimizing both the timing and the channel automatically—driving more clicks and conversions than classic journeys.”

AI Experiences arrives at a pivotal time. According to Wunderkind’s 2025 Consumer Insights Report, 87% of shoppers are more likely to purchase from brands that send offers based on their browse and click history. With 95% of website traffic still anonymous, and traditional CRM tools under strain, AI-driven, identity-based outreach and decisioning has never been more critical.

For CRM, lifecycle, and digital marketers seeking higher-impact triggered campaigns with fewer constraints, Wunderkind AI Experiences offers a performance marketing advantage rooted in automation, adaptability, and scale.

The post Wunderkind Launches AI for Smarter Customer Messaging appeared first on MartechView.