Agentforce adoption is reshaping how ad sales teams operate, but success starts with the right foundation.

Here’s what needs to be in place before you begin.

A Real-World Perspective on AI Adoption in Ad Sales

There’s a very real shift happening in ad sales right now, and it’s being driven by two forces moving faster than most organizations can keep up with: the pressure to adopt AI, and the pace of innovation within the Salesforce ecosystem.

At the center of both sits Agentforce, Salesforce’s bold promise to reshape enterprise productivity with intelligent, automated agents built directly into the platform. If you’ve seen the demos, you know the pitch: dashboards that think ahead, copilots that anticipate your next move, agents that take work off your team’s plate, not just organize it. It’s impressive. In some cases, it’s exhilarating.

And yet, for most ad sales organizations, the distance between the demo and the reality of deployment feels wider than anyone wants to admit.

In boardrooms and leadership offsites, there’s an assumption building, an expectation, really, that AI will deliver both efficiency and transformation. Faster forecasting. Smarter campaign planning. More responsive sellers. Cost savings. Competitive edge. The stakes are high, and the timelines are tight. The CMO, CRO, and CTO are all under pressure to figure it out fast.

But here’s the problem: most ad sales organizations aren’t ready. And it’s not because they’re behind. It’s because AI adoption, especially at the level Salesforce is envisioning, requires a level of operational and data maturity that many teams simply haven’t been asked to build. Until now.

The illusion of readiness is everywhere. It comes from slick product pages and keynote walk-throughs. It comes from internal enthusiasm and executive mandates. It comes from the understandable desire to move quickly and prove you’re doing something, anything, with AI. But in ad sales, where the operating model is complex and the data lives in a tangle of CRM systems, OMS platforms, billing tools, spreadsheets, and Slack messages, speed without structure leads to failure.

And failure isn’t just about an underwhelming proof of concept. It’s about losing momentum, credibility, and, most critically, internal trust.

The reality is that most organizations don’t need to be convinced of why Agentforce matters. They need help figuring out how to make it work. That’s a much harder conversation, and it’s the one most teams are avoiding.

The truth is, AI isn’t plug-and-play. It’s process-first. It’s people-first. It starts with hard questions about your data: where it is, what shape it’s in, who owns it, who trusts it. It starts with being honest about whether your current systems are ready to support intelligent agents acting on real-time signals. It means assessing whether your workflows are documented, whether your teams are aligned, whether your use cases are clearly defined and tied to business value.

Most companies haven’t done that work—not because they’re negligent, but because no one asked them to. Until now, automation has largely lived in the realm of point solutions and internal ops teams. But AI—true AI at scale—is different. It touches everything. And it requires executive sponsorship, cross-functional collaboration, and a willingness to rethink the way work gets done.

In ad sales, that’s especially true. The organizational design of a media company or a retail media network doesn’t look like a clean enterprise blueprint. It’s messy, human, and full of nuance. Campaign delivery still hinges on manual approvals. IO changes flow through email. Rate cards get revised in Excel. Every exception has its own exception.

This isn’t a critique—it’s a reflection of reality. But it’s also why the Agentforce model of automation, orchestration, and augmentation needs to be implemented with deep industry understanding. Otherwise, you risk building elegant systems that no one uses.

That’s where most pilot programs go wrong. The technology is capable. But the organization isn’t ready. The data isn’t structured. The workflows aren’t defined. The teams aren’t aligned. The implementation lacks clear governance, and the outcomes are measured with metrics that don’t connect to executive priorities. The result is a failed pilot—and a lingering sense that “AI didn’t work here,” even if the real issue was far more solvable.

At V2, we’ve seen this pattern enough times to spot it early. We’ve spent the last 20 years helping ad sales organizations modernize their operations, adopt Salesforce platforms, unify fragmented data, and optimize for growth. We’ve been there for the transition from linear to digital, from print to programmatic, from CRM silos to integrated sales planning. We’ve worked with organizations that were ready to move fast, and others that needed to take a beat and build the foundation first.

What we’ve learned is that successful AI adoption isn’t about finding the flashiest agent or launching the quickest POC. It’s about sequencing the work. It’s about asking: Where are we today? What do we want to achieve? And what will it actually take to get there—technically, operationally, and culturally?

Agentforce, when done right, can absolutely reshape ad sales. It can accelerate opportunity management, streamline campaign delivery, automate forecasting inputs, and surface insights that once took hours to compile. But to get there, you need more than access. You need clarity.

That’s where strategic partners matter. Not vendors. Not resellers. Partners who understand the ecosystem, the industry, and the underlying dynamics of organizational change. Partners who don’t just “turn things on,” but help you figure out why you’re doing it, how it will work, and what success looks like on the other side.

There’s a phrase we use often with our clients: measure twice, cut once. In the rush to adopt Agentforce and AI more broadly, it’s easy to forget that principle. But we’ve seen firsthand what happens when organizations slow down just enough to get the plan right. The outcomes are better. The adoption is stronger. The value is real.

Agentforce isn’t a fad. It’s a new paradigm for how work gets done. But like any paradigm shift, it requires preparation, structure, and serious thought. The companies that treat this moment like a strategic inflection point—not just a tech initiative—will be the ones that win.

Building Trust Starts With A Conversation.

If you’re leading an ad sales organization and you’re evaluating how to bring Agentforce into your environment, our advice is simple: don’t go it alone. Talk to people who have done it before. Ask the hard questions. And work with a team that knows your world well enough to guide you through the messiness and the momentum.

Because you only get one shot at getting this right. And getting it right starts long before the first agent is deployed. Reach out to our team today if you have any questions on the best way to think about, and or approach your Agentforce implementation. We’d love to be able to share our experience and help guide you along the path to AI adoption and Agentforce success. 

Why the Smallest Shifts Often Require the Most Expertise

and How V2 Helps Move Giants

Tugboats are easy to overlook. In a world of massive cargo ships, sprawling ports, and towering cranes, these compact vessels blend into the industrial backdrop. But anyone who understands how global shipping works knows: without tugboats, nothing moves. These small, unassuming machines guide the giants. They know the waters, the currents, the constraints — and they provide the essential force, timing, and insight needed to steer colossal vessels through tight turns and into the right channels.

At V2 Strategic Advisors, we play a similar role for organizations evolving their ad sales operations.

In media, retail media, and digital advertising, companies often reach a pivotal point: their vision outpaces their infrastructure. Processes built on spreadsheets and siloed tools begin to break under the weight of scale. Teams feel the friction. Leaders sense the opportunity — but also the complexity. The question becomes: how do we change course without capsizing?

This moment, that uneasy space between recognizing the need for change and knowing how to begin, is where V2 thrives.

Transformation Isn’t a Big Swing, It’s a Series of Strategic Nudges

The mythology of transformation is that it’s dramatic: a full replatforming, a sweeping restructure, a clean slate. But in reality, meaningful transformation is subtle. It’s a patient, practiced discipline. It’s understanding that real change — sustainable change — happens in thoughtful increments. Like tugboats easing a massive vessel out of port, we guide companies through turns that look small but are everything.

At V2, we believe that change should be strategic, not reactive. Our D3P consulting framework — rooted in Data, People, Process, and Platform — enables us to assess where friction exists, uncover root causes, and prioritize interventions that make a difference. We help our clients orchestrate these shifts thoughtfully, ensuring every move is grounded in business logic and aligned with long-term goals.

These nudges add up. A revised lead intake form that aligns with campaign setup. A redefined opportunity stage that brings clarity to sales forecasting. A shared language between sales, ops, and finance. One by one, these changes start to reorient the organization — and unlock the momentum needed to move.

The Real Obstacles Are Rarely Technical

Despite the buzz around AI, automation, and enterprise platforms, the most stubborn barriers to transformation are almost never technological. They’re human.

We’ve led transformations where sales teams didn’t trust their own data. Where finance refused to validate revenue until every spreadsheet was manually reconciled. Where ad ops, drowning in workarounds, hadn’t met with sales in months. And yet these were organizations with best-in-class tech stacks.

That’s because the toughest work is internal. It’s about aligning teams with different goals. Surfacing the power dynamics no one wants to name. Navigating the inertia of “how it’s always been done.”

Most system integrators shy away from this kind of work. It’s messy, nonlinear, hard to scope. But this is where V2 stands apart. Our team is made up of former media executives, operators, and strategists who understand both the political landscape and the practical levers of change. We know how to facilitate the difficult conversations. We know how to design for compromise. And we know how to build solutions that don’t just meet technical specs — they meet people where they are.

True Consulting Brings Teams Together

Some of the most transformative work we do doesn’t start with a system at all. It starts with a conversation. We get people from intake, ad ops, billing, marketing, finance — even legal — in the same room, sometimes for the first time in months. We ask them to map what’s happening today. Then we ask them to imagine what could be different.

It’s not uncommon to hear a comment like: “I’ve worked with this person for three years, but I’ve never actually heard them describe what they do.”

That’s where change begins.

V2’s D3P approach isn’t just a framework. It’s an invitation. It brings cross-functional teams into the fold early, not just to weigh in, but to co-create. We surface pain points, flag dependencies, and define success together. This isn’t theoretical alignment — it’s organizational clarity, forged in real-time. And it’s this clarity that enables systems to actually work the way they’re supposed to once the tech goes live.

Designing for Scale, Even If You’re Just Starting

Whether you’re building a brand new ad product or modernizing an aging infrastructure, scalability isn’t just about system load, it’s about process resiliency. It’s about designing your business in a way that lets it grow without constantly reinventing the wheel.

For some clients, that means connecting Salesforce to downstream billing systems. For others, it’s about finally abandoning spreadsheets for a purpose-built campaign planning solution. In every case, it’s about giving teams tools that support their ambition without adding unnecessary complexity.

Think of it this way: you don’t build a new ship and then decide where to go. You chart the course, define the vessel, crew it properly, and then you launch. At V2, we help you do just that.

We Don’t Just Manage Change, We Design for It

The firms that promise speed over strategy often skip one crucial truth: change only sticks if people believe in it.

That’s why change management isn’t an afterthought in our projects — it’s embedded from the start. We plan for adoption as aggressively as we plan for delivery. That includes aligning leadership, creating internal advocates, and building feedback loops that extend well beyond go-live.

Our goal is to make the system your own. Not something that needs to be constantly explained, but something that feels like second nature. That’s how you future-proof your operation. That’s how you build resilience into your business model.

Your Business Might Be the Cargo Ship. But You Don’t Have to Move Alone.

Large organizations often carry the weight of their own momentum. Even when the desire to change is strong, the act of changing can feel paralyzing. The risk of disruption looms large. The politics of platform decisions can stall progress. And still — the business must evolve.

This is where the tugboat metaphor becomes real. You don’t need to turn the whole ship at once. You need the right partner, applying pressure in the right places, at the right time.

Building Trust Starts With A Conversation.

V2 Strategic Advisors is that partner. We help you orchestrate the shifts — large and small — that position your ad business to scale with confidence. From strategic planning to technical execution, from cross-team alignment to go-to-market readiness, we are your guide through uncertain waters.

Whether you’re launching something new or finally bringing structure to a patchwork of tools and spreadsheets, we help turn ad sales chaos into clarity.

Accurate data. Scalable design. A real system of record. That’s what we build.

If your ad business is ready to evolve, let’s talk.

We’re the team ad sales experts turn to when they want to level up.

Why Salesforce Data Cloud, Supported by Agentforce

Is the Next Frontier in Ad Sales

When we sit down with CROs or ad‑sales VPs these days, a familiar pattern emerges. Their CRM is bursting with advertiser history, their data lake has petabytes of streaming behavior, and their marketing team has stitched together three different CDPs—yet none of it feels actionable in the moment that matters. A sales rep preparing a proposal still has to Slack an analyst for reach counts; the analyst submits a ticket to data engineering; the numbers arrive days later—too stale to headline a pitch deck, too late to secure incremental budget.

Salesforce’s Data Cloud is marketed as a “real‑time CDP,” but that label undersells its strategic resonance for ad‑sales organizations. It’s more accurate to call Data Cloud an operating layer that sits above every warehouse, lake, and CRM table you already own and turns those assets into a living, queryable service. Combined with Agentforce—Salesforce’s generative‑AI automation framework—the platform removes the latency between data, decision, and revenue. It’s not hype; it is the connective tissue modern media and retail‑media companies have been missing.

Understanding the DNA of Data Cloud

Data Cloud’s design begins with a straightforward premise: data gravity lives where it lives. Instead of requiring wholesale migration, the platform uses zero‑copy federation to map existing Snowflake tables, Databricks notebooks, or S3 objects into a canonical Customer 360 model. Identity resolution runs in‑platform, stitching first‑party IDs with hashed device signals and consent flags. What emerges is a real‑time profile graph continuously refreshed as events stream in.

That architectural choice matters because ad‑sales velocity is measured in hours—not quarters. When a premium video campaign under‑delivers on connected TV impressions at noon, the ops lead must re‑allocate budget before primetime. Lake‑house analytics are indispensable for trend analysis, but Data Cloud excels at sub‑second queries that feed segment counts to planners, eligibility flags to ad servers, and real‑time intent to opportunity owners.

Agentforce enters once that unified profile graph exists. Generative agents grounded in Data Cloud’s truth layer can compose proposals, recommend flight optimizations, or draft insertion orders—all without hallucinating fictitious reach numbers or misclassifying PII. Think of Data Cloud as the authoritative memory, and Agentforce as the muscle memory that automates routine motions.

Where Data Cloud Meets the Ad‑Sales Lifecycle

Opportunity & Pipeline Management
Every revenue cycle begins with a question: who is most primed to buy? In traditional stacks the answer hides in disparate systems—CRM activities, web analytics, and ad‑server logs rarely intersect. With Data Cloud’s profile graph feeding directly into Salesforce Opportunity objects, sellers see live intent signals side‑by‑side with historical spend. Reach projections update the moment an audience grows, enabling reps to quote inventory with confidence instead of conservatism. Agentforce adds a second layer, automatically drafting personalized outreach that references the advertiser’s most recent brand‑site engagement, not last quarter’s CTR.

Order & Campaign Activation
The hand‑off from sales to ad‑ops is a notorious friction point. Orders arrive with segment definitions that don’t match the DSP’s taxonomy; segments make it to the DSP but stale overnight; make‑goods pile up. Data Cloud’s hashed audience sync to Google DV360, Amazon DSP, or LinkedIn bypasses manual onboarding and preserves privacy compliance. Within minutes, operations can traffic a new line item or re‑balance frequency caps. Meanwhile, Agentforce monitors pacing, flags under‑delivery, and proposes intra‑campaign reallocations—freeing human traffickers to focus on high‑touch clients, not spreadsheet gymnastics.

Marketing & Prospecting
Retail‑media networks live and die by first‑party reach. Data Cloud offers deterministic identity that can be enriched in‑line with ecommerce, loyalty, and offline transaction feeds—no third‑party lookups required. Marketers build real‑time look‑alikes that update as soon as a shopper abandons a cart or streams a new series episode. The result is an always‑on supply of high‑intent audiences ready for cross‑sell or upsell. And because those segments live inside Salesforce Marketing Cloud as well, continuity between paid media and lifecycle email is finally achievable.

Measurement, Attribution & Finance
The post‑campaign scramble to reconcile delivery, invoice, and make‑good terms is another drain on margin. By feeding impression logs, cost data, and CRM revenue back into Data Cloud, finance teams can match realized spend to booked revenue in near real time. Incrementality studies that once required weeks of offline analysis now refresh nightly dashboards. Agentforce can even draft billing summaries, flag anomalies, and suggest make‑good allocations backed by deterministic logs.

Governance & Cost Control
CIOs often push back: “We already have Databricks—why add Data Cloud?” The answer lies in governance and cost alignment. Snowflake or Databricks remain ideal for heavy ML training and historical analysis; Data Cloud owns real‑time activation, consent enforcement, and integration with Salesforce surfaces. Used together, they create a layered architecture where high‑cost compute is reserved for modeling, while low‑latency activation stays within a governed perimeter. In practice that hybrid pattern reduces total cost of ownership versus forcing every workload into a single monolith.

Agentforce: Automation That Knows the Numbers

Generative AI in a vacuum is novelty; generative AI grounded in trusted data is leverage. Agentforce draws its context from Data Cloud’s real‑time profile graph, which means an agent crafting a proposal has the same audience math your planner signed off on ten minutes ago. Early pilots show a 30‑40 percent reduction in proposal turnaround time and measurable upticks in pipeline velocity—because AEs spend less effort consolidating numbers and more time narrating value.

For ad‑ops, Agentforce acts as a watchtower: observing pacing logs, querying Data Cloud for eligible make‑good inventory, and proposing adjustments before humans notice a miss. In a market where under‑delivery erodes trust, that form of pre‑emptive remediation is more than efficiency—it is a brand advantage.

Navigating the Hype Cycle

It is tempting to treat Data Cloud as a silver bullet or to dismiss it as marketing gloss. Experience suggests a middle path: start with a narrow, revenue‑adjacent use case and iterate outward. We advise clients to begin with CRM and ad‑server unification—often the easiest integration with the highest commercial impact—then layer on marketing IDs, retail transaction feeds, and real‑time streaming. Each loop ships tangible value while sharpening governance, consent, and cost controls.

Within ninety days, most teams graduate from static audience exports to dynamic look‑alikes. By the six‑month mark, Agentforce automates proposal drafts and pacing adjustments. Twelve months in, finance monitors revenue‑per‑segment in real time—closing the data‑to‑dollars loop executives have sought for a decade.

The Executive Checklist

• Do we know, in real time, which audiences are shrinking, growing, or qualifying for premium packages?

• Can our ops team push a corrected segment to a DSP without filing an IT ticket?

• Are finance and ad‑ops working from the same impression ledger?
  If the honest answer is “not yet,” Data Cloud, and Agentforce, belong on your roadmap.

Building Trust Starts With A Conversation.

Ready for a Deeper Conversation?

V2 Strategic Advisors has helped media, streaming, and retail‑media companies navigate twenty years of technology shifts. Our Data Cloud Strategy Sprint translates possibilities into a phased, ROI‑anchored blueprint: clear use cases, consumption guardrails, and an Agentforce automation plan.

Book a 60‑minute session to see how your first‑party data can become a revenue engine, without rewriting your stack from scratch. 

Beyond Buzzwords: What Salesforce’s Latest Acquisitions

Mean for Enterprise AI and Ad Sales Transformation

The enterprise technology landscape has been abuzz with Salesforce’s recent strategic moves. First, the acquisition of Convergence.ai, an AI agent company specializing in human-like adaptability in digital workflows. Then, just weeks later, the monumental announcement of the $8 billion acquisition of Informatica, a long-standing leader in enterprise cloud data management. As consultants deeply immersed in the Salesforce ecosystem and the broader tech trends, we understand that for many, these announcements might seem like complex, disparate events. But when viewed together, they reveal a profound, meticulously planned vision for the future of enterprise AI.

This isn’t just about adding new tools to a portfolio; it’s about fundamentally reshaping what Salesforce’s AI capabilities, particularly Agentforce and Data Cloud, can achieve. It’s about moving beyond AI as a helpful assistant to AI as an autonomous, trustworthy, and highly effective business driver. And for sectors like ad sales and retail media, the implications are nothing short of transformative.

The AI Capability Salesforce Didn’t Have (Until Now)

Before these strategic acquisitions, Salesforce, while a CRM powerhouse with growing AI ambitions, faced inherent challenges in delivering truly autonomous, enterprise-grade AI. The limitations stemmed from two critical areas:

1. The Data Trust Deficit: Salesforce’s growth, fueled by numerous acquisitions over the years, naturally led to a fragmented data landscape. While Data Cloud was making strides in unifying customer data, the sheer volume, variety, and often inconsistent nature of enterprise data across disparate systems posed a significant hurdle. For AI to be reliable and responsible, it needs a “trusted data foundation”. Without robust data quality, governance, and comprehensive metadata management, AI outputs can be unreliable, leading to poor decisions and a loss of trust. This was a gap that even Salesforce’s existing capabilities couldn’t fully bridge at the scale required for truly autonomous AI.

2. The Adaptability Gap for AI Agents: Salesforce’s Agentforce platform was designed for AI agents to plan, reason, and take action. However, the real world is messy. Digital interfaces change, unexpected errors occur, and workflows are rarely perfectly linear. The ability for AI agents to navigate these dynamic, unpredictable environments with human-like adaptability – to perceive, reason, and adapt on the fly – was a complex challenge. Traditional automation often falters when faced with such variability.

This is where the strategic pairing of Informatica and Convergence.ai steps in, offering a powerful, synergistic solution that unlocks unprecedented AI capabilities for Salesforce.

Informatica: The Unshakeable Foundation of Trusted Data

Informatica is the answer to the “data trust deficit.” For decades, Informatica has been the gold standard in data integration, data quality, data governance, metadata management, and Master Data Management (MDM). Its core strength lies in centralizing metadata to classify, secure, and ensure the reliability of information across an entire enterprise.

As Salesforce CEO Marc Benioff has emphasized, “AI agents are only as good as your data”. Informatica ensures that the data feeding AI models is accurate, consistent, auditable, and contextually rich. It cleanses, unifies, and governs data from disparate sources, including those from Salesforce’s numerous past acquisitions, effectively making the entire data estate “AI ready”. This is the bedrock of trustworthy AI, providing the fuel and the map for intelligent agents.

Convergence.ai: Adaptive Intelligence for Real-World Action

Complementing Informatica, Convergence.ai addresses the “adaptability gap.” This company specializes in advanced AI agents that can perform complex, human-like tasks in dynamic digital environments. Their technology allows AI agents to navigate unpredictable interfaces, adapt to real-time challenges like pop-ups or UI changes, and execute multi-step processes with human-like problem-solving capabilities.

While Informatica ensures the data is pristine, Convergence.ai ensures the AI agents can effectively use that data in the messy, unpredictable real world. It moves Salesforce beyond simple “copilot” tools to truly autonomous agents that can perceive, reason, and adapt to the complexities of modern digital workflows.

The Synergistic Power: Agentforce and Data Cloud Unleashed

The combination of Informatica and Convergence.ai creates a comprehensive, end-to-end AI solution that was previously beyond Salesforce’s reach. This isn’t just an incremental improvement; it’s a fundamental shift in what’s possible for Agentforce and Data Cloud:

Supercharging Agentforce: Agentforce is Salesforce’s platform for autonomous AI agents. Agents need three things to get work done: data, reasoning, and actions.

• • • Data: Informatica ensures Agentforce agents have access to the cleanest, most comprehensive, and most trusted data from across the entire enterprise, not just within Salesforce’s native clouds. This includes rich metadata that allows agents to understand the context of business data and available actions.
    • Reasoning & Actions: Convergence.ai enhances Agentforce’s ability to reason and take action in dynamic environments. It enables agents to adapt to changing conditions, plan complex multi-step tasks, and execute them autonomously with a new level of resilience. This means Agentforce can now automate more complex processes like modifying orders, scheduling appointments, or processing returns without constant human intervention.

Strengthening Data Cloud: Informatica significantly bolsters Data Cloud’s leadership as a Customer Data Platform (CDP). It ensures that data unified within Data Cloud is not just aggregated, but also clear, trusted, and actionable. This robust, high-quality data foundation is indispensable for feeding Agentforce and other AI models, ensuring they produce accurate and personalized insights for a true Customer 360 view.

This strategic pairing means Informatica provides the reliable, governed data (the “what”), and Convergence.ai provides the adaptive intelligence and execution capabilities (the “how”). This allows Salesforce to build a “system of intelligence on a trusted system of understanding,” enabling AI agents to operate safely, responsibly, and at scale.

Not a Shift Away from MuleSoft, But Profound Augmentation

A common question arising from these acquisitions is whether they signal a strategic shift away from MuleSoft. The answer is a resounding no. Instead, this is a profound augmentation of MuleSoft’s capabilities.

• MuleSoft’s Role: MuleSoft is the enterprise’s digital highway for API-led connectivity, real-time application integration, and process automation. It excels at building reusable APIs and facilitating seamless, real-time communication between diverse applications and devices. It’s about moving data and orchestrating workflows between systems.
• Informatica’s Role: Informatica is fundamentally data-centric, focusing on comprehensive data integration (especially ETL), robust data quality, rigorous data governance, and Master Data Management (MDM). It’s about preparing, cleaning, and governing the data itself.  

In essence, MuleSoft builds the roads and manages the traffic (data flow). Informatica ensures the “goods” (data) being transported on those roads are clean, properly packaged, and trustworthy. It also provides the “maps” (metadata) so the drivers know where everything is. Convergence.ai provides the “intelligent drivers” (AI agents) who can navigate those roads, understand the maps, and handle unexpected detours to deliver the goods effectively. Informatica’s advanced data quality, integration, cataloging, and governance will ensure that data flowing through MuleSoft APIs is not just connected, but also enriched, standardized, and trustworthy. This creates a “reliable stream ready to fuel AI-powered decisions and actions across the enterprise”.

Not a Shift Away from MuleSoft, But Profound Augmentation

A common question arising from these acquisitions is whether they signal a strategic shift away from MuleSoft. The answer is a resounding no. Instead, this is a profound augmentation of MuleSoft’s capabilities.

• MuleSoft’s Role: MuleSoft is the enterprise’s digital highway for API-led connectivity, real-time application integration, and process automation. It excels at building reusable APIs and facilitating seamless, real-time communication between diverse applications and devices. It’s about moving data and orchestrating workflows between systems.
• Informatica’s Role: Informatica is fundamentally data-centric, focusing on comprehensive data integration (especially ETL), robust data quality, rigorous data governance, and Master Data Management (MDM). It’s about preparing, cleaning, and governing the data itself.  

In essence, MuleSoft builds the roads and manages the traffic (data flow). Informatica ensures the “goods” (data) being transported on those roads are clean, properly packaged, and trustworthy. It also provides the “maps” (metadata) so the drivers know where everything is. Convergence.ai provides the “intelligent drivers” (AI agents) who can navigate those roads, understand the maps, and handle unexpected detours to deliver the goods effectively. Informatica’s advanced data quality, integration, cataloging, and governance will ensure that data flowing through MuleSoft APIs is not just connected, but also enriched, standardized, and trustworthy. This creates a “reliable stream ready to fuel AI-powered decisions and actions across the enterprise”.

Transforming Ad Sales: A Concrete Example

For media companies and those in the burgeoning retail media space, this combined power is a game-changer for ad sales. Imagine the following scenario:

An ad sales team at a major retail media network needs to launch a highly personalized campaign for a new product line, targeting specific customer segments across multiple digital channels.

1. Data Unification & Trust (Informatica + Data Cloud): Customer data from various sources – CRM, e-commerce transactions, loyalty programs, in-store purchases, website browsing behavior, ad impressions, and campaign performance metrics – is ingested and unified by Informatica. It cleanses duplicates, resolves identities, and applies robust data governance rules, ensuring a single, trusted 360-degree view of each customer. This high-fidelity data then populates Salesforce Data Cloud, creating real-time, actionable customer segments.

2. Intelligent Campaign Optimization (Agentforce powered by Convergence.ai): An Agentforce AI agent, leveraging the trusted data in Data Cloud, is tasked with optimizing the campaign.

Perceive: The agent continuously monitors real-time campaign performance across all channels (e.g., ad clicks, conversions, impressions, cost-per-acquisition) and cross-references it with the unified customer data. It identifies that a particular ad creative is underperforming for a specific demographic segment, or that a new, high-value customer segment is emerging based on recent purchase patterns.

Reason: The agent analyzes the data, identifies the root cause (e.g., creative fatigue, mis-targeting, competitor activity), and formulates a plan. It might determine that a new ad copy is needed, or that budget should be reallocated to a different channel or audience.

Act (Adaptively): Here’s where Convergence.ai’s magic comes in. The agent doesn’t just suggest; it acts. It navigates the complex UIs of various ad platforms (e.g., Google Ads, Meta Ads Manager, retail media DSPs), automatically adjusting bidding strategies, reallocating budget, or even generating new, personalized ad copy variations (leveraging generative AI) and deploying them. If it encounters a pop-up, a broken link, or a UI change on an ad platform, Convergence.ai’s adaptive intelligence allows it to overcome these obstacles and complete the task without human intervention. It can also proactively alert the human ad sales team to significant shifts or new opportunities, providing context-aware recommendations.

3. Seamless Connectivity (MuleSoft): Throughout this entire process, MuleSoft ensures the seamless, real-time flow of data between all these disparate ad tech systems (DSPs, SSPs, ad servers, CRM, CDP) and Salesforce’s platform. It’s the connective tissue that allows Informatica to ingest data, Data Cloud to unify it, and Agentforce to act on it across the entire ad sales ecosystem.

This integrated approach means ad sales teams can move from reactive adjustments to proactive, intelligent, and autonomous campaign optimization, driving unprecedented efficiency, scalability, and ROI.

The Path Forward: A Call to Action for Your AI Strategy

Salesforce’s acquisitions of Informatica and Convergence.ai are not just headlines; they are a clear declaration of intent to lead the next wave of enterprise AI. They signal a future where AI agents are not just intelligent but also trustworthy, adaptable, and capable of driving complex business processes with minimal human oversight. This is the strategic advantage Salesforce is pursuing, and it promises to unlock unprecedented efficiency and intelligence for its customers.

For organizations navigating this rapidly evolving landscape, understanding how to optimally leverage these powerful new capabilities, integrate them seamlessly with existing Salesforce and MuleSoft deployments, and define the most impactful use cases for autonomous AI agents requires specialized expert guidance.

At V2 Strategic Advisors, our team of strategists specializes in helping companies navigate these intricate tech stacks, optimize their data and AI strategies, and drive efficiency and scalability, particularly in dynamic areas like ad sales and retail media. We are actively working across the ad sales landscape, helping teams take this leap into strategic action.

Building Trust Starts With A Conversation.

Whether your organization is questioning how to integrate these new capabilities, seeking to understand their impact on your specific business processes, or analyzing what this means for your overall AI roadmap, our team is equipped to provide clarity and actionable recommendations.

To explore what these transformative acquisitions mean for your organization and to gain guidance on how to best leverage these powerful new capabilities, please reach out to our team of strategists at V2 Strategic Advisors. 

For a deeper dive into each individual acquisition, please refer to our dedicated blog posts:

• Salesforce’s $8 Billion Informatica Acquisition: Powering the Future of Enterprise AI with Trusted Data
• Salesforce Acquires Convergence.ai: The Strategic Brains Behind Autonomous AI Agents

A Strategic Bet on Data Quality and Governance

for the Age of Autonomous AI

Today marks a pivotal moment in the enterprise technology landscape, as Salesforce announced its definitive agreement to acquire Informatica for approximately $8 billion in equity value. As strategic advisors, we view this not merely as another large-scale acquisition but as a foundational investment in the quality, governance, and accessibility of data—the very lifeblood of responsible and effective enterprise AI. This strategic maneuver – which they kept a complete secret during their big Agentforce World Tour NYC last week – aims to establish the “most complete, agent-ready data platform in the industry”.  

The core rationale behind this significant investment is to enhance Salesforce’s “trusted data foundation”. This foundation is critical for deploying powerful and responsible agentic AI, which empowers autonomous AI agents to operate safely, responsibly, and at scale, transforming how businesses leverage their data for smarter outcomes. Beyond its immediate impact on Salesforce’s product portfolio, this acquisition is poised to reshape the competitive landscape, particularly against rivals like Microsoft and Amazon. Furthermore, it carries profound implications for industries heavily reliant on precise customer data, such as media and retail media, by enhancing their ability to drive personalized advertising experiences and operational efficiency.  

A Partnership Forged, A Future Acquired: Salesforce and Informatica’s Journey

Informatica, established in 1993, has long been a stalwart in enterprise cloud data management. Over decades, it has solidified its position as a leader specializing in crucial areas such as data integration, data quality, data governance, metadata management, and Master Data Management (MDM). A key aspect of Informatica’s enduring strength lies in its ability to centralize metadata, which is fundamental to classifying, securing, and ensuring the reliability of information across an enterprise.  

Salesforce and Informatica have not been strangers; their relationship spans several years, marked by a history of collaboration. Informatica has offered dedicated solutions like “Informatica Cloud Integration for Salesforce” and developed connectors for various Salesforce clouds, including Marketing Cloud, Financial Services Cloud, and Einstein Analytics. These integrations were designed to enhance data integration, MDM, and provide a comprehensive 360-degree view of customers within the Salesforce ecosystem. This prior collaboration underscores a proven technical compatibility and a shared understanding of the intricate data needs of their mutual customer base.  

The transition from a long-standing partnership to a full acquisition signifies a deeper strategic imperative for Salesforce’s AI ambitions. While existing integrations were valuable for data movement and basic synchronization, the stringent data requirements of autonomous AI agents demand a level of native embedding of Informatica’s capabilities directly within the Salesforce platform. The stated goal of a “unified architecture for agentic AI” and the emphasis on “deep, native integration” indicate that the previous partnership, while beneficial, was insufficient to meet the advanced demands of AI. Artificial intelligence, particularly autonomous agents, requires not just data flow, but data trust, governance, and profound contextual understanding at a systemic level. A full acquisition enables Salesforce to intrinsically weave data quality and governance into its core platform, ensuring that AI can truly deliver on its promise of reliable and impactful outcomes.  

The acquisition was announced today, with Salesforce entering a definitive agreement to acquire Informatica for approximately $8 billion in equity value. Under the terms of the agreement, Informatica shareholders will receive $25 in cash per share. The transaction has received approval from both companies’ boards of directors and is anticipated to close early in Salesforce’s fiscal year 2027, pending necessary regulatory clearances. This acquisition represents Salesforce’s most substantial investment since its $28 billion acquisition of Slack in 2021. The timing of this acquisition is clearly linked to the accelerated push for agentic AI across the enterprise landscape. Salesforce recognizes that data quality and governance are not merely important, but rather the critical bottleneck preventing the widespread, reliable deployment of autonomous AI. This recognition compelled Salesforce to act decisively to secure this foundational piece for its ambitious AI roadmap. 

Unlocking New Dimensions: What Informatica Brings to Salesforce’s Ecosystem

The acquisition of Informatica is fundamentally driven by Salesforce’s strategic imperative to enhance its “trusted data foundation critical for deploying powerful and responsible agentic AI”. Marc Benioff, Salesforce’s Chair and CEO, has consistently articulated that “AI agents are only as good as your data”. Informatica’s capabilities are designed to empower autonomous AI agents to interpret and act on complex enterprise data, thereby constructing a true “system of intelligence on a trusted system of understanding”.  

The prevailing narrative around artificial intelligence often simplifies the challenge to “more data is better.” However, Salesforce’s repeated emphasis on a “trusted data foundation,” “responsible agentic AI,” and robust “data governance” reveals a more nuanced understanding of enterprise AI. It is not merely about having access to massive datasets; it is about ensuring that this data is accurate, consistent, auditable, and contextually rich. Unreliable data inevitably leads to unreliable AI outputs, which is an unacceptable risk for enterprise-grade applications where decisions have tangible, real-world business impacts. Informatica’s core strengths in metadata management, comprehensive data quality controls, and data lineage tools directly address this critical need for data trust. This strategic move elevates Salesforce’s AI strategy from simply being “AI-powered” to becoming “AI-trustworthy.”  

Informatica’s comprehensive suite of services fills critical gaps in Salesforce’s existing data capabilities, particularly for the demands of modern AI:

• • • Data Catalog & Metadata Management: Crucial for AI agents to interpret, connect, and act on diverse enterprise data with meaningful context. 
    • Data Integration & Lineage: Meticulously tracks data origin, transformations, and usage, vital for auditability and compliance. 
    • Data Quality & MDM: Ensures all data feeding AI models is standardized, accurate, consistent, and secure, eradicating duplicates and inconsistencies. 
    • Data Governance & Privacy: Establishes principles and practices for safe, secure, and responsible data use, including automating processes with AI/ML.  

Salesforce’s growth strategy has historically involved numerous acquisitions, which, while expanding its capabilities, have also introduced diverse technology stacks and fragmented data models. Informatica offers a “possible solution for outdated Salesforce solutions” and can effectively “bridge the gap to those outdated applications, or to enable some kind of migration”. This capability is particularly important for customers seeking to leverage advanced AI functionalities, as many older applications may not be inherently suitable for Agentforce, Salesforce’s AI initiative. Informatica’s expertise in data integration, data quality, and MDM provides the critical plumbing necessary to unify these disparate data sources, thereby making the entire Salesforce ecosystem—including data from previously acquired applications—”AI ready”.  

By integrating Informatica’s capabilities, Salesforce CRM applications will be significantly enhanced, empowering teams to deliver more personalized and effective customer experiences, all backed by trusted data. Informatica already facilitates smarter customer relationships by enriching Salesforce data with information from various cloud applications and on-premises systems, resulting in a “trusted, holistic view of your customer”.  

MuleSoft and Informatica: A Symphony of Integration and Data Management

To understand the strategic necessity of Informatica given Salesforce’s existing MuleSoft asset, it is crucial to delineate their distinct yet complementary strengths.

MuleSoft’s Core Strengths: Acquired by Salesforce in 2018, MuleSoft is renowned for its API-led connectivity, real-time application integration, and process automation capabilities. Its Anypoint Platform excels at building modular, reusable APIs, managing the full API lifecycle, and facilitating seamless, real-time communication between diverse applications and devices. MuleSoft is particularly strong in scenarios requiring instant data updates and automating complex workflows across an enterprise.  

Informatica’s Core Strengths: In contrast, Informatica is fundamentally data-centric. Its strengths lie in comprehensive data integration (particularly ETL – Extract, Transform, Load), robust data quality management, rigorous data governance, extensive metadata management, and Master Data Management (MDM). Informatica is optimized for managing and processing large volumes of data, excelling in batch processing and supporting a broad range of data sources, including complex legacy systems. Its proprietary CLAIRE AI copilot functionality automates many data management tasks, enhancing efficiency and reliability.  

The acquisition is not about replacing MuleSoft but rather about profoundly augmenting its capabilities. Informatica’s advanced data quality, integration, cataloging, and governance will ensure that data flowing through MuleSoft APIs is not just connected, but also enriched, standardized, and trustworthy. This creates a “reliable stream ready to fuel AI-powered decisions and actions across the enterprise”.  

MuleSoft is exceptionally adept at connecting disparate systems and enabling data flow. It serves as the enterprise’s digital highway for data exchange. However, a highway alone does not guarantee the quality or integrity of the goods transported. Informatica provides the “intelligence layer” that prepares and governs the data before, during, and after it traverses MuleSoft’s network. This means that while MuleSoft efficiently moves data, Informatica ensures that the data being moved is clean, compliant, and contextually rich—qualities that are absolutely essential for AI models to produce accurate, reliable, and responsible outputs. Without Informatica, MuleSoft might connect systems and facilitate data movement, but the data itself could be fragmented, duplicated, or inconsistent, thereby undermining the efficacy and trustworthiness of AI initiatives. Together, they form a holistic data supply chain: MuleSoft for connectivity and orchestration, and Informatica for data quality, governance, and AI readiness. 

The AI Catalyst: Supercharging Agentforce, Data Cloud, and Einstein

This acquisition marks a profound strategic shift for Salesforce towards autonomous AI agents. The company is moving beyond basic “copilot” tools to deploy more sophisticated, “autonomous agentic AI tools”. This transition necessitates a fundamental enhancement of data capabilities, and Informatica’s acquisition is central to providing the “critical foundation for autonomous AI agents to interpret and act on complex enterprise data”.  

Informatica will significantly strengthen Salesforce Data Cloud’s leadership as a Customer Data Platform (CDP). This enhancement will ensure that data from across an organization is not only unified but also clear, trusted, and actionable. This is paramount for building a truly comprehensive “Customer 360” view, which serves as the indispensable foundation for delivering highly personalized and effective customer experiences across all touchpoints.  

The acquisition strategically unites Salesforce’s existing Einstein AI capabilities with Informatica’s powerful CLAIRE AI engine. This combination is designed to forge the “ultimate AI-data platform — trusted, explainable, and built to scale”. Informatica’s CLAIRE AI, a core component of its Intelligent Data Management Cloud (IDMC), specializes in automating data management tasks through “unified metadata intelligence”. By combining Einstein, which provides AI capabilities within the CRM context, with CLAIRE AI, which focuses on automating data management itself, Salesforce is creating a powerful virtuous cycle. This means that AI will be leveraged to manage and refine data, which in turn fuels better and more reliable AI within the CRM applications.  

The integration will profoundly elevate Agentforce, Salesforce’s initiative for autonomous AI agents. Informatica’s capabilities will provide the “most comprehensive understanding of their data” for these truly autonomous and trustworthy AI agents. Specifically, Informatica’s advanced catalog and metadata capabilities, when combined with the Agentforce platform, will enable AI agents to understand not just data points, but their full context, including origin, transformation, quality, and governance. This newfound clarity from the unified solution will empower businesses to automate more complex processes and make significantly more reliable AI-driven decisions.  

Upon the close of the acquisition, Salesforce plans a rapid integration of Informatica’s technology stack—including its data integration, quality, governance, metadata, and MDM capabilities—into Data Cloud and Agentforce. The goal is to create a “single data pipeline” and seamlessly embed Informatica’s “system of understanding” directly into the Salesforce ecosystem. 

The Strategic Pairing: Informatica and Convergence.ai

Salesforce’s commitment to enterprise-grade AI is further illuminated by another recent acquisition: Convergence.ai. Acquired just weeks before Informatica (on May 15th, 2025), Convergence.ai specializes in advanced AI agents capable of navigating complex digital workflows with human-like adaptability. Their technology enables AI agents to handle dynamic interfaces, adapt to real-time challenges like pop-ups, errors, and UI changes, and perform multi-step processes.

This pairing reveals a comprehensive, two-pronged strategy for Salesforce’s AI future:

1. 1. Informatica provides the “trusted data foundation”: It ensures that the data feeding the AI agents is clean, governed, and contextually rich—the bedrock of reliable AI outputs.
   2. Convergence.ai provides the “adaptive intelligence”: It equips the AI agents with the capability to perceive, reason, and act on that trusted data within the unpredictable and dynamic real-world digital environment. 

In essence, Informatica ensures the AI agents have good, reliable information, while Convergence.ai ensures they have the intelligence and adaptability to effectively use that information in complex, real-world scenarios. This strategic combination is designed to move Salesforce beyond basic “copilot” tools to truly autonomous, enterprise-grade AI agents that can drive complex business processes with unprecedented accuracy and efficiency. It’s a clear signal that Salesforce is building a complete, end-to-end AI solution that addresses both the data quality and the operational intelligence required for widespread AI adoption. For a deeper dive into the Convergence.ai acquisition, please see our dedicated blog post on the topic. 

Upon the close of the acquisition, Salesforce plans a rapid integration of Informatica’s technology stack—including its data integration, quality, governance, metadata, and MDM capabilities—into Data Cloud and Agentforce. The goal is to create a “single data pipeline” and seamlessly embed Informatica’s “system of understanding” directly into the Salesforce ecosystem.  

Shifting the Sands: Salesforce’s Competitive Edge Against Microsoft and Amazon

This $8 billion acquisition represents a “decade-defining bet on Data and AI” for Salesforce. It is a clear declaration of the company’s intent to lead in AI-powered enterprise solutions. By integrating Informatica’s robust data management capabilities, Salesforce significantly strengthens its ability to collect, cleanse, and classify large volumes of data—functions that are absolutely crucial for building accurate and well-structured data sets that underpin effective AI.  

The deal is being “watched closely across the technology industry” as it “potentially alters the competitive landscape for enterprise data management and AI services”. Industry analysts note that this strategic move could “rattle Microsoft and Amazon” , both of whom are similarly integrating data and generative AI technologies into their extensive cloud offerings.  

In a highly competitive AI market where tech giants are investing heavily, Salesforce’s acquisition of Informatica signals a distinct strategic differentiation: a profound focus on governed, trustworthy data as the foundational bedrock for enterprise AI. Many enterprises harbor significant hesitation about adopting AI, primarily due to legitimate concerns regarding data privacy, compliance, and accuracy. By acquiring Informatica, Salesforce is making a clear assertion that its ability to provide “trusted, explainable, and built to scale” AI through superior data management will be a key differentiator against its rivals, particularly for large, regulated enterprises. This move is not merely about having an AI offering, but about delivering an enterprise-grade, reliable, and auditable AI solution.  

Salesforce is strategically shifting its focus from offering basic copilots to developing and deploying autonomous agentic AI tools. Informatica’s data capabilities are expected to power these advanced agents with cleaner, smarter data, thereby significantly increasing their efficiency and utility for enterprise customers. This strategic pivot is designed to position Salesforce ahead in the competitive AI software race by offering more intelligent, action-taking agents that can drive complex business processes. Ultimately, Salesforce’s consolidation of data management, analytics, and AI under a unified architecture is presented as essential to driving the next wave of digital transformation. 

Driving Ad Sales Transformation: Benefits for Media and Retail Media

For media companies and those active in the burgeoning retail media space, effective ad sales and campaign performance are inextricably linked to a deep, accurate, and real-time understanding of the customer. Organizations in these sectors critically need to “gain a trusted view of information about known customers” and simultaneously “broaden their knowledge about unknown customers”. This comprehensive and reliable customer intelligence is then leveraged to “create more engaging and relevant interactions” , which directly translates to more effective advertising and increased revenue.  

Informatica’s capabilities will significantly enhance ad sales tech stacks by providing foundational data management strengths:

• • • Customer 360 for Targeted Advertising: Informatica’s Customer Data Management (CDM) capabilities, including Master Data Management (MDM) and robust data quality functions, enable the creation of a “true 360-degree customer view”. This is achieved by unifying disparate data from various sources, critical for precise audience segmentation and targeted ad delivery. 
    • Data Quality and Enrichment for Campaign Efficiency: Informatica’s ability to “transform, cleanse, enrich and standardize your data” ensures that data utilized for ad campaigns is “fit for use,” leading to more effective marketing campaigns and optimized ad spend. 
    • Automated Data Management for Scalability: The integration of AI and machine learning capabilities within Informatica automates numerous data management tasks. This automation significantly boosts efficiency and productivity, vital for media and retail companies grappling with the unprecedented volume and variety of customer data. 
    • Data Governance for Compliance and Trust: Robust data governance ensures adherence to critical data privacy regulations such as GDPR and CCPA. This is paramount for handling sensitive customer data, reducing regulatory risk, and building consumer trust. 
    • Breaking Down Data Silos: Informatica helps organizations dismantle “departmental silos” and combine customer data with product data and other critical information to uncover hidden relationships and patterns. This unified data foundation is essential for implementing effective omnichannel retail media strategies and optimizing cross-platform ad sales.  

Media companies and retail media operations rely on vast amounts of first-party and third-party data for ad targeting, personalization, and monetization. However, this data frequently resides in disparate systems—CRMs, DMPs, CDPs, ad servers, e-commerce platforms—leading to fragmentation, duplicates, and inconsistent customer views. Informatica’s core strengths in data integration, MDM, and data quality directly address these pervasive challenges. By providing a “single source of truth” and ensuring data is “clean, protected, consistent and actionable” , Informatica empowers media and retail companies to move beyond mere data aggregation to truly actionable ad intelligence. This translates into more precise targeting, significant reductions in ad waste, improved campaign return on investment, and the agility to rapidly adapt to evolving privacy regulations, ultimately driving greater efficiency and scalability in their ad sales operations. 

The Path Forward: What This Acquisition Signals for Salesforce’s Future

This acquisition solidifies Salesforce’s overarching vision of a comprehensive, AI-powered customer platform. By deeply integrating Informatica’s advanced data management capabilities, Salesforce is moving beyond merely providing CRM solutions; it is offering a complete system of intelligence designed to understand, govern, and act on all enterprise data. This strategic positioning enables Salesforce to deliver on the promise of “autonomous agents” that can drive complex business processes with unprecedented accuracy and efficiency.

Looking ahead, we can anticipate a deeper integration of Informatica’s data quality, governance, and metadata management features across all Salesforce clouds. The synergy between Salesforce’s Einstein AI and Informatica’s CLAIRE AI will likely lead to the development of more sophisticated, data-driven AI applications that are inherently more trustworthy, explainable, and performant. The strategic emphasis will be on creating seamless, end-to-end data pipelines that consistently feed AI models with high-fidelity, governed information, ensuring reliable outputs and accelerating business value.

This significant move also signals Salesforce’s conviction that the next wave of enterprise AI adoption will be fundamentally driven by an organization’s ability to effectively handle and derive value from complex, messy, and disparate enterprise data. Companies that can master their data will be the ones truly capable of harnessing the transformative power of AI. Salesforce is strategically positioning itself as the indispensable partner to help enterprises achieve this critical data mastery, thereby accelerating their digital transformation journeys and securing a competitive edge in the AI-first era.

Building Trust Starts With A Conversation.

Partnering for Strategic Advantage: Your Data and AI Journey with V2

The Salesforce-Informatica acquisition, while strategically brilliant for Salesforce, introduces new layers of complexity for organizations striving to optimize their data and AI strategies. Understanding how to optimally leverage Informatica’s capabilities, integrate them seamlessly with existing Salesforce and MuleSoft deployments, and define the most impactful use cases for agentic AI requires specialized expert guidance.

At V2 Strategic Advisors, our team of strategists specializes in helping companies navigate these intricate tech stacks, optimize their data strategies, and drive efficiency and scalability, particularly in dynamic areas like ad sales and retail media. Whether an organization is questioning when to use MuleSoft versus Informatica, seeking to understand how to integrate them for maximum impact, or analyzing what this acquisition means for their specific ad sales tech stack, our team is equipped to provide clarity and actionable recommendations.

For more insights into the evolving AI landscape and its profound impact on your business, we encourage you to review our recent post on the big takeaways from Agentforce NYC.

To explore what this transformative acquisition means for your organization and to gain guidance on how to best leverage these powerful new capabilities, please reach out to our team of strategists at V2 Strategic Advisors.

How AI Agents and Salesforce Media Cloud

Are Reshaping Ad Sales Operations for Media Firms

Psssttt…. The future of ad sales isn’t coming—it’s already here.

This week, our team at V2 Strategic Advisors had the opportunity to attend Agentforce World Tour in New York City. Hosted by Salesforce, this one-day event brought together clients, partners, and product leaders to explore the next frontier of AI-powered business transformation. Held at Pier 60 in Manhattan, the event featured demos, customer stories, and product deep-dives with one major theme front and center: Agentic AI has arrived, and it’s reshaping how media companies sell advertising.

We had several team members on the ground throughout the day, reconnecting with clients, meeting with Salesforce colleagues, and taking in all the action from the sessions dedicated to Media & Entertainment. Being there firsthand—talking to others, seeing what’s live, and what’s coming next—reminded us how rapidly the rules are changing. Actually, the rules aren’t the only things changing, as witnessed last week, the technology is also changing too, as evidenced by Salesforce’s latest acquisition of Convergence.ai, which was just announced last week.

Yes, AI is everywhere now. But what’s still scarce is understanding. And in this moment of flux, that understanding doesn’t come from reading another white paper. It comes from experience. From walking into a room full of other people who’ve tried something, failed, tried again, and are now willing to share how they did it better the second time. That’s what made this event worth it.

As a firm rooted in the media and advertising world, we’re always thinking about what these developments mean for the companies we serve. Many of the biggest breakthroughs discussed at Agentforce World Tour directly apply to the ad sales motion—a space we’ve helped clients optimize for nearly two decades. Below, we’re sharing the most important takeaways for media companies navigating the path ahead.

1. Agentic AI Is About Orchestration, Not Just Automation

The headline shift isn’t from manual to automated. It’s from disconnected to coordinated.

Agentforce isn’t just another AI feature—it’s a platform-wide evolution that enables real-time orchestration across the full ad sales lifecycle. Through use cases shared live on stage, Salesforce showed how Agentforce is being embedded into Slack, Salesforce Sales Cloud, and Media Cloud to surface high-impact signals, automate repetitive workflows, and drive faster, smarter decision-making.

Imagine opening your laptop and instantly seeing two key alerts from your Agent: a new qualified lead already calendared and briefed, and a campaign underperforming with one of your top clients. That’s not theory—it’s happening now. And it means sellers can act faster and focus on strategy, not chasing down data.

2. Ad Sales Use Cases Are the AI Beachhead

One of the clearest messages from the day was this: ad sales is where AI is gaining the most traction first.

In multiple sessions, Salesforce leaders walked through how agents can now handle everything from RFP response generation to campaign reporting. The new Advertising Proposal Skill, for example, automatically digests incoming RFPs, populates Salesforce opportunity records, assembles product recommendations, and creates a proposal-ready deck—reducing a process that often takes days down to minutes.

Agents also help course-correct underperforming campaigns in real time. One demo showed how a sales rep used Agentforce to identify which inventory was dragging down campaign performance, re-segment the audience by age group, and reallocate underutilized placements—all before the reporting cycle closed.

These are not science fiction demos. They’re practical, configurable, and available to media firms today.

3. AI Can Unlock Revenue/Retention, But Only If It’s Trusted

Beyond efficiency, what Agentforce really unlocks is better business outcomes—for both revenue and employee experience.

During the sessions, we heard from leaders at Salesforce and clients like Pearson who reinforced that bots may handle linear tasks, but agents operate with nuance. They understand the context, adjust dynamically, and complete tasks end-to-end. That’s what allows companies to move beyond “ticket deflection” and start enabling upsell, cross-sell, and personalized engagement at scale.

Just as important, these tools elevate the employee experience. By offloading repetitive, time-consuming tasks, AI agents help teams focus on higher-value work—improving job satisfaction and reducing turnover. That’s not a side benefit—it’s a strategic imperative for media firms trying to retain top sales talent and support hybrid work.

4. Media Cloud Is Still the Foundation

While Agentforce took the spotlight, the backbone of the solution stack remains Salesforce Media Cloud—purpose-built to manage the full ad sales journey from lead to cash. With deep data models, workflow automation, and native integrations into Data Cloud and Tableau, Media Cloud helps organize the chaos of fragmented ad tech stacks and gives teams a single system of truth.

For companies that haven’t yet consolidated onto a unified platform, this is a critical first step. And for those ready to layer in AI, Media Cloud ensures the data foundation is solid—so agents act on relevant, trustworthy, and timely information.

5. Start Small, But Start Now

The strongest advice from Salesforce speakers? Don’t try to boil the ocean.

Start with high-volume, repetitive use cases—like proposal generation, campaign reporting, or subscriber support. Out-of-the-box skills are available today, and early adopters are already seeing ROI in areas like reduced turnaround time, increased self-service, and better campaign performance.

But the key to success is trust. Media sellers and ad ops leaders must understand why an agent recommends a specific action. Salesforce emphasized that Agentforce is built with explainability and guardrails—giving humans confidence to act, and teams the ability to measure and iterate.

Building Trust Starts With A Conversation.

This Is the Moment to Lean In

At V2, we’ve spent nearly 20 years guiding media companies through ad sales transformation. And this moment—with Agentforce, Data Cloud, and AI reshaping how work gets done—feels like one of the most important inflection points yet.

If you’re a media company trying to make sense of what to do next, we’d love to connect. We’re not just implementers—we’re former operators who’ve sat in your shoes. We help you evaluate paths A vs. B, and make sure your team not only launches, but lands the changes that matter most.

The future of ad sales is coordinated, intelligent, and powered by agents. Let’s build it together.

Want help getting started with Agentforce or evaluating your ad sales tech stack?
Get in touch with the team at V2 Strategic Advisors. We’re ready to help you make sense of it all—and unlock the next level of performance.

A Deep Dive into Salesforce’s Latest Move

to Redefine Enterprise AI with Human-Like Adaptability

Today, the enterprise technology world is still buzzing with news that broke yesterday: Salesforce has announced a definitive agreement to acquire Convergence.ai. While the financial details remain undisclosed, this move is far more than a typical tech acquisition; it’s a profound strategic statement about the future of enterprise AI, particularly for Salesforce’s ambitious Agentforce platform. As consultants who’ve been tracking Salesforce’s trajectory for years, we see this as a critical piece of a much larger puzzle, signaling a shift towards truly autonomous AI agents that can not only process information but also act on it with remarkable, human-like adaptability.

Unpacking Convergence.ai: The Art of Adaptive AI

So, what exactly does Convergence.ai bring to the table, and why are they considered best-in-class in their domain? At its heart, Convergence.ai is an AI agent company. They specialize in developing sophisticated systems that can perform complex, multi-step tasks within dynamic digital environments. Think beyond rigid automation scripts; think AI that can perceive, reason, and adapt to the unpredictable nature of real-world digital workflows.

Their flagship product, Proxy, is an AI-powered digital assistant designed to automate a wide array of daily tasks through natural language commands – from scheduling meetings and managing emails to conducting online research and handling data entry. What truly elevates Convergence.ai is their technology’s uncanny ability to navigate ever-changing interfaces and adapt in real-time to common digital challenges like pop-ups, unexpected errors, or subtle UI changes. This mimics human-like problem-solving in a way that traditional automation often struggles to achieve. It’s this “human-like ingenuity” and resilience in dynamic digital environments that sets them apart, making their technology uniquely transformative for business automation.

Why Salesforce Made This Strategic Play

Salesforce’s decision to acquire Convergence.ai is a clear, decisive investment in the next generation of its AI offerings. Adam Evans, EVP & GM of Salesforce AI Platform, succinctly captured the essence of this move, stating that “The next wave of customer interaction and employee productivity will be driven by highly capable AI agents that can navigate the complexities of today’s digital work”.

This acquisition empowers Salesforce to achieve capabilities that were previously out of reach for its AI initiatives. While Salesforce has been diligently building Agentforce as a platform for AI agents, Convergence.ai provides the specialized “adaptive intelligence” crucial for these agents to truly operate autonomously and reliably in dynamic, real-world scenarios. This isn’t just about automating single, scripted tasks anymore; it’s about enabling “end-to-end, decision-driven workflows where multiple agents collaborate and hand off seamlessly”.

The integration of Convergence.ai’s team and technology will be central to advancing Agentforce. It will strengthen Salesforce’s AI capabilities by accelerating the development of next-generation agents built for increasingly sophisticated workflows. This includes unlocking NLP-driven insights for hyper-personalized support, enabling more fluid conversational AI, creating workflows for automated resolution to reduce agent workload, and providing context-aware agent guidance based on CRM history, customer tone, and intent detection. Ultimately, this move is about boosting productivity and significantly reducing manual work for Salesforce customers by deploying more adaptive and capable AI agents.

This purchase sends an unmistakable message: Salesforce is making substantial investments in AI-native platforms. When viewed alongside other strategic moves, such as the upcoming acquisition of Informatica (which will provide the critical “trusted data foundation” for AI), the Convergence.ai deal completes a powerful strategic pairing. Informatica ensures that AI agents have access to clean, governed, and contextually rich data – the bedrock of reliable AI outputs. Convergence.ai, in turn, equips these agents with the intelligence and adaptability to effectively use that trusted information within the unpredictable, real-world digital environment. It’s a comprehensive, end-to-end AI solution designed to address both the data quality and the operational intelligence required for widespread enterprise AI adoption.

What This Means for Salesforce Customers

For Salesforce customers, this acquisition translates directly into a new realm of possibilities for AI-driven automation and customer experience. You should expect to see these advanced features and capabilities emerge primarily within the Agentforce platform, which is natively integrated with the entire Salesforce Customer 360.

Customers will gain access to:

• • Truly Adaptive and Capable AI Agents: These agents will be able to perform tasks previously requiring human intervention, leading to improved customer interactions, enhanced productivity, and streamlined workflow efficiency.
  • Automated Complex Workflows: Imagine AI assistants that can intuitively navigate ever-changing interfaces and intelligently manage intricate tasks with a new level of resilience. This means automating common service processes like modifying orders, scheduling appointments, processing returns/refunds, or updating account information without constant human oversight.
  • Hyper-Personalized Support: With enhanced NLP-driven insights and conversational AI, agents will engage with customers in real-time, providing proactive suggestions based on CRM history, customer tone, and intent detection, eliminating the need for constant tab-switching or guesswork.
  • Significant Reductions in Manual Effort: Industries from financial services to healthcare are already seeing the impact. For instance, Agentforce has autonomously resolved a significant percentage of chat engagements for some financial services clients during peak seasons. In healthcare, it can automate patient data retrieval, freeing up nurses’ time for direct patient care. Recruiters can automate resume screening and interview scheduling, ensuring engagement with 100% of applicants.

This acquisition accelerates Salesforce’s ability to deliver AI that genuinely transforms how work gets done, enabling customers to deploy sophisticated AI solutions faster and realize tangible business benefits more quickly.

Key Takeaways for Salesforce Partners

For Salesforce partners, this acquisition is a clear indicator of the strategic direction Salesforce is taking with its core AI capabilities. Salesforce is investing heavily in building out foundational AI agent capabilities internally, rather than solely relying on partners to develop these core adaptive intelligence layers.

The primary takeaway for partners is to:

• • • Focus on Specialization and Extension: Partners should pivot their focus from attempting to build core AI agent technology from the ground up. Instead, the opportunity lies in leveraging Salesforce’s enhanced Agentforce platform. This means concentrating on developing industry-specific solutions, specialized workflows, and unique integrations that extend the capabilities of Salesforce’s robust AI agents.
    • Add Value on Top of the Platform: Convergence.ai offers a level of deep expertise in adaptive systems and human-like task execution in dynamic digital environments that would be incredibly challenging for most partners to replicate independently. Salesforce is providing the “brains” and “adaptability” for the agents; partners can then build the “domain expertise” and “tailored applications” on top of this powerful foundation.
    • Align with Salesforce’s AI R&D: Salesforce plans to establish a world-class AI R&D center in London, with Convergence.ai forming its nucleus. This presents a significant opportunity for partners to engage with Salesforce’s evolving AI roadmap and align their offerings with these cutting-edge advancements.

By providing a robust, adaptable AI agent platform, Salesforce empowers partners to innovate faster and deliver more sophisticated solutions to customers without the immense R&D burden of developing core AI agent intelligence.

Partnering for Strategic Advantage: Your AI Journey with V2 

Salesforce’s acquisition of Convergence.ai, following closely on the heels of other strategic AI investments, is not an isolated event. It’s a calculated move to solidify its position at the forefront of the enterprise AI revolution. These acquisitions introduce powerful new capabilities but also layers of complexity for organizations striving to optimize their AI strategies. Understanding how to optimally leverage these new assets, integrate them seamlessly with existing Salesforce and MuleSoft deployments, and define the most impactful use cases for autonomous AI agents requires specialized expert guidance.

At V2 Strategic Advisors, our team of strategists specializes in helping companies navigate these intricate tech stacks, optimize their data and AI strategies, and drive efficiency and scalability. Whether your organization is questioning how to integrate these new capabilities, seeking to understand their impact on your specific business processes, or analyzing what this means for your overall AI roadmap, our team is equipped to provide clarity and actionable recommendations.

Building Trust Starts With A Conversation.

For more insights into the evolving AI landscape and its profound impact on your business, we encourage you to review our recent blog posts on advertising and AI, such as how AI-Powered Retail Media strategies could help ad sales teams finally conquer that personalization goal, and what this might do for revenues. 

To explore more about what this transformative acquisition means for your organization and to gain guidance on how to best leverage these powerful new capabilities, please reach out to our team of strategists at V2 Strategic Advisors so we can help you get started. 

How a Boutique Salesforce Partner Grew From an Apartment Startup to a Global Force

—and Why Our Best Work Is Still Ahead

When V2 Strategic Advisors opened its doors in 2005, “software-as-a-service” sounded more like a venture-capital pitch deck than the bedrock of enterprise IT. Founder John Tanner, a physics major-turned-sales rep, wagered that two concepts—velocity (speed with direction) and voltage (stored potential energy)—could do for consulting what Salesforce was about to do for software: make progress faster, more iterative, and ultimately more valuable. That gamble, launched from an apartment in New Hampshire with a single credit card, has proved prescient.

Two decades later, V2 has only sharpened its focus around ad sales optimization, management consulting, and helping clients navigate a new breed of technologies: AI, data clean rooms, CDPs, and more. We guide organizations to understand not only where and how to layer in these tools but how to maximize their impact to deliver the most revenue and overall efficiency.

It is tempting to mark an anniversary by tallying medals: more than 500 multi-cloud projects, a client roster that spans global broadcasters, Fortune-100 retailers, and enterprise disruptors, and accolades as one of the most experienced Salesforce Media Cloud partners in the ecosystem. But numbers alone do not explain why a boutique consultancy routinely goes toe-to-toe with global systems integrators ten times its size.

The deeper story is strategic, rooted in how V2 blends management-consulting rigor with hands-on platform expertise, and why that hybrid DNA is suddenly in higher demand than ever. Part of that is due to the rate of technology innovation we’ve seen in recent years. Part of that is due to the complexity of pairing new tech with old, and accounting for the change management that must follow—adjustments that are not always obvious or easy to make. Having an outside resource to guide this process can be critical. Even large organizations that are well-funded and full of brilliant teams need support from tactical partners like ours who can help shepherd new tech and process adoption, along with many other benefits.

From First-Mover to Framework Builder

The early V2 playbook was straightforward: replace spreadsheets with Sales Cloud or Service Cloud, train account executives, move on. It did not stay simple for long. Media clients soon asked V2 to stitch CRM data to ad servers and order-management systems so planners could see inventory in real time. That request forced the firm to cultivate integration talent, data-modeling chops, and an instinct for what actually moves the revenue needle.

By 2012, V2 was connecting half-a-dozen systems per engagement, expanding beyond pure-play CRM work, and developing critical firsthand experience across a wider spread of products, solutions, and advertising strategies. By 2021, because of our deep heritage in ad sales and middle office operations, we were invited to become an official launch partner for Salesforce’s Media Cloud product, a first-of-its-kind industry-focused solution for the Media & Entertainment industry. We impacted not only the final product but also helped create the examination materials used for qualifying other partners and technical resources.

These projects had a curious spill-over effect: they trained V2 consultants to think less about features and more about operating models. An ad-sales workflow is ultimately a chain of promises—from a salesperson’s pitch to an accountant’s invoice. Break any link and revenue leaks out. V2’s answer was a repeatable framework, later branded D3P—Data, People, Processes, Platforms—that begins nearly every engagement with a deep diagnosis of data integrity, team dynamics, and workflow friction before getting hands-on with the tech and thinking about licenses.

This formula still powers much of our firm’s success. Our clients don’t think about solutions through the lens of “which license will solve my problem,” as business is more complex than that. One change here has downstream impacts there, so it requires consultation and deep hands-on technical expertise.

Boutique by Design, Enterprise by Necessity

As Salesforce ballooned into a multi-cloud universe, many consultancies chased breadth: more partnerships, more logos, more bodies. V2 took the opposite tack: stay boutique, stay specialized, and outrun bigger firms on people count and brute force, with deeper expertise around technical know-how, developing strong client relationships, and strategy and decision speed.

Internally, we sometimes refer to this as “a special-forces approach,” deploying smaller, more senior teams who can whiteboard strategy in the morning and deploy code that afternoon. That model resonates with clients who have endured the hand-off whiplash of large integrators—strategy deck from Team A, requirements gathering by Team B, offshore configuration by Team C.

At V2, the same architects who draw the blueprint own the build and shepherd change management all the way through. There is no bait and switch; our teams are all A-players who bring years of industry experience to the table—and that has profound impacts on the results we are able to cultivate and deliver. The result is accountability, velocity, and ultimately trust. Small project teams delivering high-impact results.

The Inflection: Advertising Everywhere

If the first decade of V2 was about mastering media, the second was about exporting that mastery. In the last 4-5 years, retailers, travel brands, and even financial institutions have discovered they are sitting on monetizable first-party data—and they all want ad-operations plumbing that works and is scalable.

V2’s deep background in CRM-based ad sales optimization has given us a particular pedigree that has become highly valuable to clients and our partners alike. The common denominator for us has always been that intersection where CRM meets ad revenue, and the common bottleneck is operational or technological complexity. This is the intersection where we help fix problems and drive value for our clients.

V2’s ability to merge CRM, OMS, Ad Server, ERP, Integrations, and Analytics into a single revenue engine has become our sharpest competitive edge. It is also why the firm’s most recent wins involve Data Cloud architectures and AI experiments that aim to embed Agentforce assistants into seller workflows. The lesson: once you solve the data quality and plumbing, AI is no longer a science project—it is a repeatable and accessible feature.

Why AI Needs D3P

Talk of AI is everywhere, yet most organizations are still quarreling with the basics: siloed metrics, partial customer views, manual hand-offs that turn quarter-close into an endurance sport. V2’s consultants argue that AI without operational hygiene is like a self-driving car on pothole roads: the tech may be brilliant, but the ride will be bumpy. That is why the firm’s next chapter doubles down on data architecture and process discipline as prerequisites for AI value capture.

Picture a planner who simply asks, “Which premium video slots can we package for CPG advertisers next quarter?” and receives an answer grounded in live CRM opportunity data, ad-server availability, and finance’s margin constraints. That scenario—trivial to describe, devilishly hard to engineer—is exactly the type of outcome V2 is building towards.

It explains the firm’s investments in partnerships with MuleSoft integration patterns, Snowflake data modeling, Einstein GPT prompts for ad-sales scenarios, and Tableau Pulse dashboards that surface KPIs at the point of decision making.

Culture as an Operating System

Tools and frameworks matter, but they rest on culture. V2’s internal mantra—”people are our product”—is not marketing fluff; it is a talent filter. The firm hires consultants with at least a decade of prior industry experience and often a second act: creative writers, former COOs, data scientists.

The diversity of backgrounds fuels what clients describe as “lateral insight,” the ability to see how a revenue challenge in streaming might illuminate a sponsorship model in grocery. Our teams carry a quantitative rigor, respect for process artistry, and a passion for global business dynamics. Those virtues sound lofty, but they translate into practical advantages: questions that cut to the root cause, deliverables that survive executive turnover, and solutions that scale.

The Road to 2030

So where does velocity and voltage take V2 next? Three vectors stand out:

1. Enterprise-grade data foundations. Clean, connected data is the ticket to AI. V2 will continue refining ingestion pipelines, data models, and governance rules that let machine learning sit on rock-solid ground.
2. AI in the flow of work. Agent-driven forecasting, yield optimization, and conversational analytics are no longer demos—they are Q3 roadmap items. V2’s role is to translate capability into adoption.
3. Cross-industry ad-sales excellence. Whether a client is a streaming giant or a seed-stage loyalty app, the mechanics of ad revenue rhyme. V2 intends to keep exporting best practices across verticals, proving that boutique size can deliver enterprise impact.

Building Trust Starts With A Conversation.

A Note of Thanks—and an Invitation

Twenty years on, V2 Strategic Partners remains animated by the same two physics ideas that sparked its founding: move fast but choose your vector; harness potential energy, but convert it into measurable work.

To the clients who placed their trust in our boutique consulting firm, against other shops, the partners who pushed us to broaden our horizons, and the teammates past and present who keep velocity and voltage alive—thank you.

If your organization is ready to evolve its ad-sales engine—launch or scale a retail-media network, rationalize a patchwork tech stack, or embed AI where it counts—we would love to talk. Drop us a line here or explore our thinking at our blog. The next twenty years promise more complexity, more opportunity, and, if we have anything to say about it, a lot more voltage!

Why the Shopper Experience Must Stay

at the Center of Every Retail Media Strategy

Retail media has quickly become one of the most lucrative developments in modern commerce. But in the rush to monetize, a critical question is surfacing across boardrooms, brand meetings, and executive roundtables: Are we enhancing the shopping experience—or compromising it?

There’s no doubt that retail media has unlocked new revenue streams and transformed how retailers think about their digital and physical assets. But as media inventory expands into product detail pages, search results, in-store signage, and mobile apps, retailers face a delicate balancing act. The desire to grow ad revenue must never come at the cost of the shopper experience. And if it does, the long-term consequences—brand erosion, shopper fatigue, and reduced loyalty—can be hard to undo.

Monetization and Experience Are Not Mutually Exclusive

The good news? Done thoughtfully, retail media doesn’t have to feel invasive or exploitative. In fact, when executed well, it can enhance the customer experience.

Take personalized offers delivered at just the right time, or helpful product recommendations that streamline the path to purchase. A digital screen in-store that surfaces relevant promotions based on aisle-level data can feel like a service—not an interruption. Or a mobile push notification triggered by loyalty data, alerting the shopper to an in-stock item they’ve been waiting for. These moments are additive. They respect context. They reinforce the retailer’s brand promise.

The key is to design media experiences with intention. And that starts with a mindset shift: Retailers must view themselves not just as media sellers, but as stewards of the customer journey.

The Warning Signs of Over-Monetization

Unfortunately, not all retail media deployments follow this principle. We’ve all encountered sites where ads outnumber organic content, search results are dominated by pay-to-play listings, or store environments feel more like Times Square than trusted spaces for decision-making. These are the cautionary tales—and they’re becoming more common.

The symptoms are clear:

• Slower site performance from excessive ad placements
• Shoppers abandoning search or cart flows due to irrelevant promotions
• Store associates struggling to manage in-aisle displays or QR code interactions
• Brands questioning the ROI of placements buried beneath cluttered pages

These issues aren’t just tactical—they’re strategic. They erode shopper trust. And in a competitive landscape where loyalty is already hard to earn, they can blunt the very monetization strategies they aim to support.

Designing for Value: A Strategic Imperative

So what does a customer-first retail media experience look like?

It starts with a clear understanding of the shopper journey, mapped not just by channel, but by intent. What does the shopper need at each stage—from discovery to consideration to purchase to post-sale? How can media align to that need, delivering relevance without intrusion?

It also requires governance. Someone—usually a cross-functional team—must own the guidelines that define acceptable ad load, creative standards, personalization thresholds, and integration points across owned and paid channels. These aren’t static documents. They evolve as new formats emerge and customer expectations shift.

Finally, it demands measurement. Retailers must track not just media revenue, but its impact on core retail KPIs—conversion rate, basket size, NPS, return frequency. If the media strategy boosts one metric while dragging others, it’s time to recalibrate.

Where Salesforce and Others Fit In

Retailers leveraging Salesforce and other CRM, OMS, or ad tech platforms are in a strong position to enforce this balance. Salesforce’s Data Cloud can help ensure that targeting strategies are grounded in unified identity data. Marketing Cloud can coordinate messaging across owned and paid touchpoints. Tableau can provide the visibility needed to understand when media supports or undermines shopper behavior.

Paired with campaign execution tools like Kevel, CitrusAd, or The Trade Desk, these systems give retailers control over both the what and the how of their media programs. But even with the right stack, success depends on strategy.

V2’s Point of View

At V2, we often work with clients who are excited about the promise of retail media—but wary of its risks. We help them create blueprints for success that consider monetization and experience as dual goals, not trade-offs.

Our approach focuses on:

• Mapping customer journeys and identifying value moments
• Auditing current media placements and shopper pain points
• Designing governance frameworks for sustainable growth
• Integrating technology in a way that supports—not distracts from—the brand

We believe the best retail media programs are invisible in the best way: seamlessly integrated, highly relevant, and anchored in empathy for the end customer.

Building Trust Starts With A Conversation.

Let’s Build With the Customer in Mind

Retail media isn’t just a growth lever—it’s a brand statement. If you’re navigating how to scale media revenue without alienating shoppers, we can help.

At V2 Strategic Advisors, we bring a strategic, operational, and technical lens to retail media—ensuring that every ad experience is one your customers, partners, and teams can stand behind.

Let’s build something that benefits everyone.

Why Zero Copy Is Transforming

Real-Time Data Strategies and AI Readiness

As the pace of business accelerates and AI-driven decision-making becomes the norm, data operations are under more pressure than ever. Traditional data replication strategies and complex Extract-Transform-Load (ETL) pipelines often struggle to keep up with the need for real-time, governed, and unified data. The cost, latency, and complexity introduced by these older methods can be a significant blocker for businesses aiming to stay ahead. Salesforce Data Cloud’s Zero Copy provides a way to remove the need for copying or replicating data, giving users immediate, AI-ready insights across their entire data estate.

The promise of Zero Copy lies in its ability to connect various data sources—like Snowflake, Databricks, Redshift, or BigQuery—with Salesforce apps in real time, sidestepping the costly and cumbersome process of constantly moving data. Instead of performing repeated, time-consuming transformations, it provides a powerful approach to data federation: it allows Salesforce apps such as Sales Cloud, Service Cloud, Marketing Cloud, and Commerce Cloud to access and harmonize data from wherever it already resides, delivering a live, unified view.

This federated model is crucial because it eliminates the headaches that come with redundant copies. Anyone who has tried to maintain multiple data repositories knows how quickly those copies can drift out of sync, leading to stale insights and governance complexities. With Zero Copy, Salesforce does the heavy lifting behind the scenes, so organizations don’t have to replicate and store data in multiple places just to feed different applications. By keeping data “in place,” it not only reduces latency but also ensures data quality, consistency, and governance remain intact. Such a model is a game-changer for AI applications, which thrive on accurate and current data. Rather than feeding your AI models last night’s data, your systems get the most up-to-date information possible.

Although Zero Copy sounds like a straightforward idea—“just don’t copy the data”—the technology is quite sophisticated. Salesforce Data Cloud uses what can be described as an intelligent data virtualization layer. Queries from Salesforce apps or your custom-built applications are routed through this layer, which fetches results on demand from the source system. That means when a customer service agent needs a 360-degree profile, Data Cloud reaches out to each relevant warehouse or platform, pulls the relevant details, and merges them into a single view in real time. If performance is critical for certain high-volume scenarios, Zero Copy includes a caching mechanism to serve up critical datasets as quickly as possible while still enforcing consistent governance rules.

The strategic advantage extends beyond simply saving on storage costs or reducing ETL overhead. Because Zero Copy ensures real-time, accurate data is always on tap, it grants you better agility in delivering new experiences and analytics. For a media conglomerate, for example, streaming subscription metrics might live in Redshift, customer subscription analytics in Snowflake, and clickstream data in Databricks. Without Zero Copy, unifying those insights would involve repeated data replication. By the time the data is consolidated for analytics or personalization, it’s often outdated. With Zero Copy, a dashboard or customer-facing AI recommendation engine can dynamically pull the latest information from all three platforms at once, guaranteeing fresher insights while eliminating the operational expense of maintaining multiple copies.

From a governance perspective, Zero Copy unifies metadata across systems. Rather than having conflicting data definitions in each environment, you have a single place to define policies, ensuring data is always used and interpreted correctly. This is especially important when it comes to compliance and auditing requirements, where any lack of uniform data definitions can open the door to risk.

Because Zero Copy resides in the Salesforce Data Cloud, it directly supports Salesforce’s own apps, as well as any custom or third-party applications you’d like to build on top. As AI continues to reshape how we do business, Zero Copy is poised to become the standard for real-time data connectivity. Instead of being tied to batch pipelines that send snapshots to your machine learning models, you can have a consistent flow of governed data that responds to changes as they happen.

Salesforce itself has highlighted that this approach is already handling enormous volumes—billions to trillions of records—and has the support of a growing partner network. The diversity of options extends to federated file queries, which are on the roadmap, offering a flexible future that can handle virtually any data format. And if you prefer to keep some data in your data warehouse for cost, compliance, or performance reasons, Zero Copy still bridges these systems without forcing you to uproot everything.

All of this isn’t just a nice-to-have feature; in a business landscape where real-time insights and AI-driven actions increasingly determine winners and losers, Zero Copy is a genuine difference-maker. It can reduce operational costs, ensure uncompromised governance, and accelerate innovation by removing data silos that slow down even the most capable teams.

If you’re intrigued by the potential of Zero Copy—how it can eliminate the burden of ETL, enable instantaneous access to governed data, and serve as the backbone for AI-driven insights—there are numerous resources available. Salesforce provides extensive documentation on their official Zero Copy page, and you can also read more about it in their blog post and press releases detailing the partner network that’s growing around this capability. For a deeper technical perspective, you might find the conversations over at SalesforceBen a worthwhile read.

Building Trust Starts With A Conversation.

For any organization still mired in the challenges of siloed data and replication overhead, Zero Copy represents a genuine leap forward. By freeing businesses from the complexities of copying and moving data, it allows them to focus on what really matters: generating real-time insights, delivering excellent customer experiences, and empowering AI applications with the freshest data possible.

If you’d like to explore how Zero Copy could transform your data strategy, we’re here to help. Reach out to us for a customized assessment and let’s see how we can integrate this new approach into your existing environment—so that you can do more, innovate faster, and stay ahead in the rapidly evolving world of data-driven business.