Marketing Operations rarely fails loudly. It doesn’t usually break in a way that triggers emergency meetings or executive panic. Instead, it degrades quietly. Performance flattens. Reporting becomes decorative. Campaigns still go out, but they take longer, cost more, and rely on increasingly heroic effort from a shrinking number of people. And because the machinery still technically works, most organisations assume the issue must be something else. Strategy. Budget. Technology. Talent. Marketing Operations maturity is almost never the first suspect, and that’s precisely why so many teams get stuck. This article is about what immature  versus mature  Marketing Operations actually looks like in the real world. Not in theory. Not in vendor decks. Not in “best practice” diagrams that assume perfect behaviour. But in how teams operate day to day, how decisions are made, and how performance is really enabled (or constrained). The biggest misconception: Immature doesn’t mean bad Let’s clear something up early. Immature Marketing Operations does not  mean: Incompetent teams Lazy processes Poor intent Low ambition In fact, immature MOPs environments are often staffed by some of the hardest-working people in the organisation. The difference between immature and mature Marketing Operations isn’t effort. It’s leverage . Immature teams apply effort to keep things moving. Mature teams apply structure so things move without effort. That distinction changes everything. What immature Marketing Operations looks like in practice Immaturity in Marketing Operations tends to show up as a collection of small, reasonable decisions that compound over time. Individually, none of them feel catastrophic. Together, they create fragility. 1. Operations exists to “support” marketing, not shape it In immature environments, Marketing Operations is positioned as a service function. Their role is to: Build campaigns someone else designed Fix broken automations Pull reports when asked Keep the platforms running They are reactive by default. Decisions about strategy, measurement, and tooling are made around  them, not with  them. Ops is brought in late, usually once timelines are tight and expectations are already set. The result? Operational debt baked into every initiative. Mature organisations understand something immature ones don’t: Operations is not execution support... it’s performance infrastructure. 2. Process lives in people’s heads Ask an immature MOPs team how something works and you’ll get answers like: “It depends” “Normally we just…” “Sarah knows how that flows” “We’ve always done it this way” Processes exist, but they’re implicit rather than explicit. They’re learned socially, not designed intentionally. This creates two immediate problems: Onboarding takes forever The organisation becomes dependent on individuals, not systems When someone leaves, capability leaves with them. When demand spikes, everything slows down. When priorities shift, no one is sure what can safely change. Mature Marketing Operations makes process visible. Not bureaucratic... visible. 3. Tooling decisions are driven by features, not outcomes Immature teams often own impressive tech stacks. The issue isn’t lack of tools. It’s lack of intent behind them. Common symptoms: Platforms added to solve isolated problems Overlapping functionality across tools Features enabled “just in case” Complex setups with no clear owner The stack grows, but capability doesn’t. In these environments, the marketing technology ecosystem becomes something teams work around , not something that actively enables better performance. Mature teams reverse this thinking. They design for outcomes first, then decide what tooling is required to support them. 4. Reporting describes activity, not influence Immature reporting answers questions like: How many emails were sent? How many leads were generated? How many campaigns ran? It is often detailed, visually polished, and strategically irrelevant. Dashboards look impressive but fail to influence decisions. Metrics exist in isolation, disconnected from commercial context or operational constraints. Leadership gets updates. They don’t get insight. Mature Marketing Operations shifts reporting from what happened  to why it happened and what to do next . Fewer metrics. More consequence. 5. Success depends on heroics This is one of the clearest signals of immaturity. If performance relies on: People working late Last-minute fixes Constant Slack firefighting A handful of “go-to” experts Then the system is fragile, no matter how good results look on paper. Heroics feel good in the short term. They create stories. They get praise. But they are a tax on sustainability. Mature Marketing Operations designs environments where success is repeatable without burnout. Effort is applied where it creates leverage, not just momentum. Discover our Podcast What mature Marketing Operations actually looks like Maturity isn’t about complexity. It’s about intentional design . Mature Marketing Operations doesn’t mean everything is perfect. It means the system is conscious of its own limitations, and built to evolve. Here’s how that shows up. 1. Operations is embedded in strategic decision-making In mature organisations, Marketing Operations is involved early. Not because they “own the tools”, but because they understand: Constraints Trade-offs Dependencies Measurement implications Strategy isn’t handed to Ops to implement. It’s shaped with  Ops to ensure it’s executable, measurable, and scalable. This is where MOPs moves from support function to performance partner. 2. Process is designed, documented, and deliberately flexible Mature teams treat process as a product. They: Document it clearly Review it regularly Improve it deliberately Retire it when it no longer serves Importantly, mature process is not rigid. It’s predictable . People know what happens next. They know who owns what. They know where exceptions live and how to handle them, and this creates speed without chaos... a combination immature teams rarely achieve. 3. Tooling is rationalised around capability Mature Marketing Operations teams can answer questions like: What is this tool for ? What outcome does it enable? What breaks if we remove it? They don’t chase features. They design capability. Platforms are configured intentionally. Complexity is justified. Integrations exist for a reason, not because they were possible. The result is a stack that feels boring and works brilliantly. 4. Measurement is tied to decisions Mature reporting does three things well: It aligns to business outcomes It reflects operational reality It influences behaviour Dashboards are not built for reporting’s sake. They’re built to answer specific questions leaders actually need to make decisions. When reporting doesn’t influence action, it’s redesigned or removed. 5. Performance scales without pain This is the real test. In mature environments: New campaigns don’t require reinvention New regions don’t break the system New hires become productive quickly Growth adds complexity, but it doesn’t add chaos. That doesn’t happen accidentally. It’s the result of deliberate operational design over time. The four stages most organisations move through Across hundreds of teams, the same progression appears again and again. Not as a straight line, but as a pattern. Foundation Teams focused on stability. Getting the basics to work. Heavy reliance on individuals. Value Seeker Early optimisation. Tools and processes exist, but value is inconsistent and fragile. Value Influencer Marketing Operations actively shapes outcomes. Reporting influences decisions. Ops has a seat at the table. Value Creator Operations doesn’t just support performance, it creates it. Marketing becomes predictable, scalable, and strategically influential. Most teams believe they’re further along than they are. Not because they’re dishonest, but because immaturity is subtle. The four stages of MOPs maturity Why teams struggle to self-diagnose maturity Here’s the uncomfortable truth: You can’t accurately assess Marketing Operations maturity from inside the system that created it. Normalisation happens quickly. Workarounds become invisible. Limitations are accepted as “just how it is”. That’s why so many teams invest in: New tools New hires New agencies …without seeing meaningful improvement. They’re solving symptoms, not structural issues. This is where a snapshot matters A high-level maturity snapshot isn’t designed to diagnose everything. It’s designed to challenge assumptions . To surface patterns. To reveal friction. To show whether foundations are strong enough to support what the organisation wants next. It’s not the answer. It’s the signal that tells you whether deeper work is worth doing. Final thought Marketing Operations maturity is not a badge. It’s not a score. And it’s definitely not a destination. It’s the difference between a marketing organisation that survives on effort... and one that performs by design. If performance feels harder than it should, the problem probably isn’t ambition. It’s maturity. Discover our MOPs Maturity Indicator

AI was supposed to clean this mess up. That was the promise. Smarter decisions. Fewer spreadsheets. Less guesswork. Calmer, clearer Marketing Operations where machines handled the complexity and humans focused on strategy. Instead, many marketing teams are now running the most advanced stacks they have ever owned and have never felt less certain about what is actually happening. AI budgets are higher. Dashboards are shinier. Recommendations arrive faster. Yet ask a simple question like "why this lead was prioritised", "why that campaign was paused", or "why performance suddenly dipped", and the answer is often a shrug followed by “the AI decided.” That is not clarity. That is abdication. This is not an anti-AI argument. AI is not the villain here. But pretending it has simplified the MarTech landscape is wishful thinking at best and negligent at worst. In many organisations, AI has not reduced confusion. It has professionalised it. The MarTech landscape was already broken Before AI became the default feature on every roadmap slide, MarTech was already a problem child. Bloated stacks. Redundant tools. Integrations held together by duct tape and hope. Reporting that required three meetings and a whiteboard to explain. Marketing teams were drowning in data but starving for understanding. AI did not arrive to fix that. It arrived on top of it. Rather than forcing consolidation, AI justified expansion. New tools appeared promising intelligence rather than functionality. Copilots instead of workflows. Orchestration instead of rules. Prediction instead of logic. The stack grew. The complexity deepened. The understanding did not. AI has become a branding exercise One of the fastest ways to lose clarity is to let language lose meaning, and AI has been stretched to the point of near uselessness as a term. Rules engines are now AI. Simple scoring models are machine learning. If something outputs a number, it is predictive. If it suggests an action, it is intelligent. This is not innovation. It is relabelling. For buyers, this creates a fog where comparison becomes impossible. Everyone claims intelligence. No one explains behaviour. And very few are willing to show what happens when the system is wrong. When everything is AI-powered, nothing is truly understood. Black boxes scale ignorance AI is designed to abstract complexity. That is its strength. It is also its danger. The more decisions are hidden behind models, the easier it becomes for teams to operate without understanding. Not maliciously. Just gradually. A lead score changes. A segment reshuffles. A campaign is suppressed. The explanation is no longer logic, it is likelihood. Not rules, but probability. Over time, teams stop interrogating outcomes. They trust the system because challenging it feels slow, political, or technically intimidating. Ignorance scales quietly. The machine keeps working. Performance might even improve. But the organisation’s understanding of its own marketing deteriorates. That is a terrible trade. Confidence without accountability AI outputs arrive with confidence. Scores to two decimal places. Rankings. Forecasts. Recommendations that sound decisive, but what they rarely arrive with is accountability. Models are trained on historical data that may no longer represent reality. They are shaped by incentives that are rarely visible to end users. They degrade over time, often invisibly. Yet the outputs look authoritative long after the assumptions have expired. This creates a dangerous dynamic. Decisions feel safer when blamed on an algorithm. When things go well, the AI is brilliant. When they go badly, the data must have been wrong. Clarity requires knowing when a model is guessing. AI platforms rarely volunteer that information. Speed has replaced thinking AI has made marketing faster than ever. Content appears instantly. Campaigns launch continuously. Optimisation happens in the background. But faster is not smarter. Many teams are now moving at a pace that leaves no room for interpretation. Tests run without hypotheses. Variations launch without intent. Results are accepted without reflection. The system keeps optimising, but nobody can articulate what is being learned. AI removes friction, and friction is often where thinking used to happen. The skills gap is being politely ignored There is an uncomfortable truth most organisations avoid. They have bought or upgraded systems that are more sophisticated than their teams are equipped to understand. This is not about data science. It is about judgment. Understanding bias. Recognising spurious correlations. Knowing when automation is reinforcing bad assumptions rather than correcting them. Most teams are trained on where to click, not on how the system reasons. As a result, AI becomes either blindly trusted or quietly ignored. Both outcomes are failures. Vendors often optimise for wow, not work AI demos are impressive. They are also highly curated. Clean data. Perfect integrations. Clear objectives. None of the mess that defines real Marketing Operations. In production, data is incomplete. Signals conflict. Business logic changes. The AI still produces outputs because it has to, but the quality of those outputs quietly erodes. Few vendors are transparent about this. Fewer still make it easy to audit decisions or understand model decay. Clarity would be less exciting in a demo. Confusion sells better. Personalisation has become accidental AI-driven personalisation is often celebrated as a major win. And in isolation, it can be. But many brands can no longer explain why a customer received a specific message, at a specific time, through a specific channel. Personalisation now emerges from models, not from strategy. It works, until it does not. And when it fails, diagnosing the cause becomes a forensic exercise. Brands perform better while understanding themselves less. That is not maturity. That is dependence. More insights, fewer answers AI reporting surfaces insights constantly. Anomalies. Predictions. Trends. Most of them are interesting. Few of them are decisive. The problem is not lack of data, it is lack of relevance. AI tends to optimise what is measurable, not what matters. Teams end up tuning micro-metrics while macro questions go unanswered. Clarity would mean fewer metrics and stronger opinions. AI delivers the opposite by default. Governance is lagging badly As AI systems take on more decision-making, ownership becomes blurry. Who approved this logic. Who is accountable for this outcome. Who can override the model. In many organisations, nobody has a clean answer. Marketing, IT, data, and legal all touch AI-powered MarTech, but responsibility is fragmented. Risk accumulates quietly. AI moves faster than governance, and confusion fills the gap. When AI actually helps None of this is to say AI cannot deliver clarity. It can. Detecting broken integrations before revenue is impacted. Flagging churn risk early enough to act. Making data accessible to people who previously could not get answers. The difference is posture. Teams that treat AI as a collaborator rather than an authority get value. They challenge outputs. They validate assumptions. They design feedback loops. They use AI to narrow focus, not expand noise. The fundamentals are being skipped AI hype has made it tempting to bypass unglamorous work. Data quality. Definitions. Process design. Clear success metrics. AI does not fix weak foundations. It amplifies them. Bad inputs now produce confident nonsense at scale. Clarity still starts with fundamentals. AI only makes them louder. Leadership sees progress, Operators see risk At the executive level, AI adoption signals innovation. Modernity. Momentum. On the ground, it often feels like opacity. Another black box. Another system making decisions that are hard to explain to stakeholders. This disconnect breeds frustration. Leaders expect acceleration. Teams experience ambiguity. Without honest feedback loops, AI becomes theatre. So yes, AI has created more confusion In many organisations, it has. Not because the technology is flawed, but because it has been layered onto broken systems without discipline, education, or intent. AI has accelerated execution faster than understanding. It has produced answers faster than it has improved questions. That imbalance creates confusion. Clarity is still possible But it is not automatic. Clarity requires ownership. Transparency. Willingness to question outputs. Investment in understanding, not just capability. AI should make marketing easier to explain, not harder to defend. When it obscures logic, hides accountability, or replaces thinking, it is being misused. AI is not a shortcut to clarity. It is a multiplier. If your foundations are solid, it will sharpen them. If they are not, it will help you get lost faster, with far more confidence than you deserve. Discover our AI Services

We sat down with a few of our Europe based team to find out what they believe Marketing Operations in 2026 will look like - this is what they had to say. Discover our Podcast

It’s that time of year again - when office Slack channels slow down (thanks office holiday parties ), email sends drop like the temperature outside, and Marketing Ops leaders everywhere dare to dream about real  vacations. But before we collectively power down our dashboards, it’s worth pausing for a moment of introspection. Because 2025 wasn’t just another year in the Marketing Operations playbook. It was a year of pitched battles against broken data, sprinting toward automation nirvana, and learning that the tech stack will never, ever be truly under control. So here we are: Lights up, tree blinking in the corner, perhaps a mug of eggnog in hand, and the kind of recap only someone who eats spreadsheets for breakfast could appreciate. The year started like every other: Chaos before calibration January 2025 arrived with the same energy every Ops Pro knows all too well... too many dashboards, too many priorities, and a tech stack that looked like it had been rebuilt by a committee after every holiday party since 2020. At the start of the year, the industry was deep into the “Marketing Ops renaissance”: AI wasn’t just a buzzword anymore, it was the promised land. Guys, remember how every  whitepaper in Q1 said AI would build, execute, analyse, and (apparently) tuck us into bed? Spoiler: We’re still doing the tucking. But we got closer than ever before.  Your own Sojourn Solutions blog shone early light on this reality with pieces like “ AI needs guardrails: Why integrating new tech into your MarTech stack shouldn’t be a leap of faith ”  and “ Building trust in AI: Why MOPs needs human oversight, not just automation. ”  That wasn’t pessimism, it was pragmatism, a message we’ll thank ourselves for later.  Because if 2025 taught us anything, it’s this: AI without structure is just another buzzword with a terrible memory. The tech stack got bigger, the problems got smarter Over the last 12 months, it became painfully clear that a bloated tech stack isn’t a badge of honour. It’s an operational liability. If your MarTech looks like an overstuffed stocking, overflowing with tools that don’t talk to each other, you’re not alone. Your peers spent the year consolidating, trimming, and asking the tough questions like: Does this dashboard actually tell us something actionable, or is it just shiny?  That’s real talk. Sojourn’s content on “ What’s in your stack (that MOPsy could quietly replace)? ”  and “ Scaling without the burnout: Why Marketing Ops needs a new kind of teammate ”  hit a nerve. They weren’t just hypotheticals, they were diagnostic tools. Because mid-year, when everyone started realizing they were paying subscription fees for pain, these themes became central to real  operational planning.  And yes, MOPsy, your AI co-pilot, emerged as the MVP for a lot of teams this year, picking up the grunt work while humans focused on strategy. That wasn’t optional luxury. That was survival. Data governance wasn’t sexy, but it was necessary Raise your hand if your biggest headache this year was data hygiene.  Anyone? ( No judgment... we’re all friends here. ) Data privacy and governance marched up the priority list, not because anyone wanted  to deal with GDPR nuances in December, but because it had  to be done. With privacy regulations tightening globally, Ops leaders were forced to get smarter about how they collected, stored, and activated data. Compliance wasn’t a checkbox exercise anymore - it was foundational to campaign optimisation and personalisation at scale.  Halfway through the year, teams that previously treated governance as an afterthought were scrambling to build frameworks that supported both creativity and compliance. This wasn’t just about avoiding fines; this was about trust.  Trust in your data flows. Trust in your automation logic. Trust in the outcome of your segmentation. And honestly, trust that you weren’t about to send an email to someone who had opted out six months ago. Personalisation at scale feels great - until it doesn’t Ah yes, personalisation at scale... the promise that kept us all up at night in Q2. It sounded good on paper: Hyper-relevant campaigns delivered to each unique buyer persona with the precision of a Swiss watch. But in reality? It looked more like a mad scramble to unify disconnected data sources while marketers shouted over one another about dynamic content blocks  and real-time orchestration. To their credit, Ops teams plowed through. By late summer, organisations were finally stitching together CDPs, CRMs, and automation platforms into a semblance of a unified customer view. And even then, it still felt  like someone had tossed extra variables into the mix for fun. Sure, personalisation levels increased. Campaigns got smarter. But nothing made teams feel more alive than a last-minute pivot because someone “forgot to update the buyer persona logic.” It’s like holiday gift buying, you think you’re done, and then someone remembers Uncle Bob hates socks. Cross-functional alignment: More than a buzzword If there was a theme that actually  matured this year, it was alignment. Not the kind of alignment you scribble on a sticky note, but the operational alignment between Marketing, Sales, and Customer success. In 2025, silos didn’t just collapse, they were actively dismantled. Ops teams stepped up as the connective tissue in enterprise organizations, ushering in workflows that enabled smooth handoffs and shared visibility across teams. This wasn’t just about dashboards that everyone could see, it was about processes  that everyone used. You could smell change in the air by Q3, when campaigns that used to get stuck between departments suddenly had a roadmap, a set of owners, and, dare we say it, accountability. Team communications improved. Predictive analytics started informing pipeline conversations. And suddenly, marketing wasn’t throwing leads over a wall; they were partnering.   The AI reality check: Hype meets humility If early 2025 was the year of AI will solve everything,  then late 2025 was the year of AI will solve some things, but good luck without human context. That was the real takeaway from countless industry discussions this year, from Cannes Lions panels to internal Ops boardrooms. Leaders weren’t asking if  AI would matter anymore, they were asking how  to blend it with human intelligence effectively. We saw numerous discussions around striking that balance: Letting AI automate where it makes sense, and letting humans drive empathy, strategy, and narrative.  Your own commentary on “Building trust in AI”  and the need for collaboration between humans and machines wasn’t just philosophical, it was foundational strategy.  Because let’s face it: AI can suggest subject lines that perform well by the numbers, but only humans can tell when those subject lines read like they were written by - well - an AI. Trends that moved the needle (and the eyeballs) Let’s rewind the tape and talk trends... the ones that didn’t just make noise, but shaped actual operational decisions. One of the clearest industry shifts this year has been toward depth over breadth.  Marketing moved beyond shallow reach and big audiences, focusing instead on building meaningful resonance  with smaller, more engaged segments. This isn’t just nostalgia for better days. It’s a pragmatic response to consumer fatigue with generic, spray-and-pray tactics. Brands realised that resonance matters more than reach.  Another trend was the return of escapism  in marketing narratives, making campaigns emotionally engaging and creatively rich rather than purely performance focused. This tied into the broader push for storytelling that doesn’t feel like it’s from the same template everyone else used.  And let’s not forget the continued evolution of personalisation. This year, personalisation wasn’t just about first-name tokens in emails... it was about anticipating customer needs with predictive analytics and using machine learning to fine-tune journeys in real time. It was messy, it was imperfect, but it worked - when done right. The wins: What Ops actually achieved Okay, time to stop talking about trends and talk about results, the stuff that actually matters in the trenches. By year-end: Most Marketing Ops teams finally tamed parts of their tech stack , pruning tools that didn’t deliver ROI and folding others into more coherent ecosystems. Cross-functional alignment became a workable reality , not just a PowerPoint slide. Data governance went from check-the-box to operational backbone , and compliance didn’t derail campaigns as often as feared. Automation didn’t eliminate jobs, it elevated them.  Campaign builders startted to become strategic architects rather than ticket responders. AI got smart enough to take on repetitive toil, but humans still drove narrative strategy, interpretation, and value alignment. These are not small wins. These are the kinds of outcomes that move teams from firefighting mode to strategic growth mode. What went sideways (and what we learned) But let’s keep it real: It wasn’t all miracles and green lights. There were months when personalisation logic broke mid-campaign. There were tech migrations that felt like they rattled the very fabric of time. There were dashboards no one looked at but everyone felt  like they had to maintain. And yes, there were meetings that could have been emails... and should have been emails. But from each setback came a lesson: Poor data hygiene cripples even the best strategies. Tools without governance become liabilities. AI without context is noise. Alignment without ownership is confusion. And most importantly: A resilient Ops team beats a perfect plan every time. Looking ahead: 2026 is already calling As you close your laptop and side-eye that last holiday email, remember this: 2026 isn’t a blank slate. It’s a loaded one ... with AI that’s smarter, buyer expectations that are higher, and operational complexity that will continue to grow. Some shifts to watch for: Even deeper integration of AI into your campaigns, but with explainability baked in. A continued push for personalisation that feels human . Operational maturity becoming a competitive advantage, not a luxury. And possibly a few surprises from emerging tech that will make us all go, “oh, that’s how we do it now.” Whatever comes next, one thing’s certain: Marketing Operations isn’t going anywhere. It’s not a support function. It’s the engine. And this year, that engine didn’t just run. It powered through.  Despite the chaos, the curveballs, and the relentless innovation cycle, you made things work. That deserves more than a pat on the back - it deserves a moment of pride. So deck the halls, set your OOO, and know this: Uou survived. You learned. You grew. And 2026 doesn’t stand a chance. Merry Christmas, Happy Holidays or whatever politically correct way it is these days of just wishing everyone a wonderful time of year... but most importantly, Congratulations on making it through another wild ride of a year in MOPs!

When a global organisation like The Associated Press (TAP) wants to modernise its Marketing Operations, the goal isn’t just new tools, it’s creating clarity, compliance, and consistency that scale. Before partnering with Sojourn, TAP’s marketing processes were functional but fragmented. Reporting on marketing ROI required manual effort and offered only partial visibility into which campaigns were driving meaningful outcomes. The existing Email Preference Centre was outdated, creating both compliance concerns and a less-than-ideal experience for subscribers. And when it came to lead management, there was no clear structure for routing, field values, or campaign attribution. A challenge made even trickier by the need to align with TAP’s new preference centre design. Sojourn worked with TAP to build a connected, transparent foundation for modern marketing. We started by tackling the visibility gap. Our team built new ROI reporting capabilities that allowed TAP to connect marketing activity directly to business impact. Leadership could finally see which campaigns were performing, and make investment decisions backed by real data, not spreadsheets. Next, we turned our focus to compliance and customer experience. We designed and delivered a new Email Preference Centre , built from the ground up to meet TAP’s internal requirements, whilst providing a cleaner, more intuitive experience for users. The process was collaborative and iterative, with demos, revisions, and full stakeholder sign-off ahead of the September go-live. Finally, we addressed one of the most critical, yet often overlooked, elements of scalable Marketing Operations: Lead Management . We created a detailed design model that defined routing logic, field values, and process documentation, ensuring the marketing and sales systems could work together seamlessly. Everything was captured in actionable, accessible documentation so TAP’s internal teams could confidently own and evolve the framework going forward. The result is a more modern, compliant, and data-driven marketing ecosystem. All three core deliverables, ROI reporting, the Preference Centre, and the Lead Management design, were delivered on time and within scope, giving TAP a clear foundation for its next phase of growth. Today, leadership has full attribution visibility, marketing teams have a centralised way to manage subscriptions and preferences, and both Sojourn and TAP have a shared blueprint for how their Marketing Operations will scale into the future. This wasn’t a flashy technology project, it was about getting the fundamentals right. By bringing structure, transparency, and alignment to TAP’s marketing systems, Sojourn helped transform a complex operational environment into one that’s simple, compliant, and built to last. Discover our Services

If 2025 has taught Marketing Operations anything, it’s that change no longer arrives politely. It lands like a bowling ball on a glass table. AI, data fragmentation, technical debt, buying-committee drama, and the ever-expanding MarTech universe have turned MOPs from a “nice-to-have” efficiency function into the team holding the whole commercial engine together. Now we’re heading into 2026, that pressure isn’t going to ease; it’s going to crystallise. The companies that thrive will be the ones that rewire how marketing works altogether, not the ones who simply try to duct-tape AI onto last decade’s processes. These are the five shifts that we genuinely believe will move the needle in Marketing Operations in 2026... not vague futurism, but the disruptive, systemic changes already brewing under the surface. 1. AI becomes fully agentic and MOPs becomes the governing layer Remember when “AI in marketing” simply meant predicting send times, auto-tagging leads, or generating subject lines that still somehow sounded like a mildly apologetic intern wrote them? That era is done . In 2026, the centre of gravity shifts from AI as an assistant to AI as an autonomous operator. Multi-agent systems will run full campaign cycles end-to-end: research, segmentation, creative generation, QA, deployment, monitoring, and optimisation. Not in theory. In production. Daily. And here’s the twist : This doesn’t kill MOPs jobs. It elevates them. The role of Marketing Operations becomes less about mechanically executing campaigns and more about architecting the environment those autonomous systems operate within. Human oversight becomes about setting strategic intent, defining constraints, building governance frameworks, reviewing outputs, and ensuring that the AI works inside the brand, legal, ethical, and operational guardrails you define. Think less “keyboard warrior in Marketo,” more “air traffic control for intelligent systems.” The maturity curve evolves quickly: First teams use AI to speed up tasks, then to orchestrate workflows, then to manage entire marketing cycles with minimal human touch. What matters now is the ability to design systems that can scale safely. This is where MOPs becomes a strategic powerhouse. The teams who embrace this shift will move faster, make fewer mistakes, and spend their time on revenue strategy, not admin. The ones who don’t will drown in manual processes while their competitors run circles around them with fully autonomous optimisation loops. 2. Marketing becomes a real-time system... not a scheduled one The old cadence of marketing: Plan the quarter, schedule the campaigns, run the operation, pull the dashboard, build the slide deck, repeat... is being quietly replaced by something more dynamic, more reactive, and frankly more intelligent. Data systems are finally catching up with what marketers have always wanted: Live visibility into what’s happening, not a backwards-looking snapshot of what already happened. And when your view becomes real-time, your execution inevitably follows. In 2026, marketing starts behaving more like a living system than a calendar of deliverables. Campaigns will adapt in-flight based on customer signals, behavioural triggers, market context, even competitor movements. Creative will shift in response to fatigue signals. Segments will reorganise themselves. Email nurture flows will morph in response to sequence-level performance. Ad budgets will reallocate mid-hour instead of mid-month. Marketing stops being a linear machine. It becomes an anticipatory system. This also eliminates one of the biggest silent killers of pipeline velocity: lag. The lag between lead engagement and follow-up. The lag between performance issues and optimisation. The lag between insights and action. Most teams lose weeks of opportunity momentum because they can’t react in real-time, they’re trapped in workflows built for a slower era. In 2026, those lags become unacceptable. Real-time MOPs isn’t a “nice feature.” It’s the competitiveness tax. Fall behind the speed benchmark and you become invisible to buyers who expect the right message, at the right moment, in the right format, without friction. And yes, this increased speed doesn’t mean recklessness. It means MOPs becomes the engine that ensures real-time doesn’t devolve into real chaos. Governance, QA layers, controls, and oversight become critical infrastructure. It’s the only way to safely operate a system that never sleeps. 3. The monolithic MarTech suite dies... and modular, composable stacks win Remember when every vendor was trying to sell you an “all-in-one” platform that allegedly did everything? And remember when you actually tried to use it for everything and discovered it did most things… poorly? That model is finally breaking. In 2026, high-performing MOPs teams shift fully to composable architecture. Instead of buying a single suite that promises the world, they’re assembling best-in-class components that plug together cleanly. A CDP for identity, a data cloud for enrichment, a messaging engine for automation, AI systems for orchestration, analytics tools for insights, and so on. APIs become more important than features. Interoperability outranks vendor loyalty. You’re no longer locked into a stack based on what you bought five years ago, you swap in and out modular pieces as technology evolves. The reason is simple: AI innovation cycles move too fast for monoliths. By the time a giant platform ships an AI feature, specialist tools have already iterated five times. Composable stacks give MOPs teams the agility to upgrade continuously. And yes, this puts more pressure on MOPs because you become the backbone of integration design, data flow governance, API management, and system reliability. But the payoff is enormous: faster adoption of new capabilities, cleaner data flows, and freedom from platform stagnation. It also changes how procurement, IT, and marketing collaborate. Instead of huge multi-year contracts, teams begin treating tools like interchangeable strategic components. You evaluate based on how well something connects to your system, not how shiny the demo is. In other words, 2026 is the year MarTech stops looking like a collection of apps and starts looking like a living ecosystem that can evolve without burning down your entire architecture every time. 4. Attribution matures into revenue contribution... finally! Let’s be honest: Attribution models have been a mess for years. They’ve become more of a political tool than a measurement tool. Convenient for internal debates, meaningless for strategic clarity. The world has moved too far beyond linear, serial buying journeys for last-click, first-touch, or weighted multi-touch to tell any kind of truth. Buyers self-educate, self-navigate, arrive from everywhere, and make decisions long before they ever fill out a form. Marketing Operations has been tasked with measuring what can’t be measured using the old models. But in 2026, something shifts. Teams stop trying to force fit marketing’s value into brittle attribution frameworks and instead adopt revenue contribution models - a more holistic, statistical, and multi-layered approach. Contribution modelling looks at how marketing influences pipeline velocity, deal quality, opportunity acceleration, renewal probability, expansion likelihood, and lifetime value. It measures impact across time, across channels, and across buying committees. It answers a more meaningful question: How does marketing improve the business? Not which click “caused” the revenue? This shift matters because contribution metrics elevate MOPs from “owners of dashboards” to “owners of commercial insight.” When you can quantify how marketing drives pipeline health, revenue posture, and customer profitability, you’re speaking the language of the CFO, not the CMO. And in 2026, as organisations tighten spend and scrutinise ROI, this shift becomes the difference between being seen as a cost centre and being recognised as a strategic engine. 5. Ethics, governance, and human-centred systems become non-negotiable As AI scales across marketing - running campaigns, analysing data, handling operations autonomously - a new priority explodes into view: Governance. Not the checkbox compliance version. The operationally serious version. When you have AI systems generating customer-facing outputs at scale, any mistake becomes a multiplied mistake. A mis-categorised segment triggers dozens of incorrect messages. A hallucinated fact becomes a reputational risk. An overly confident optimisation loop can warp performance in ways you don’t notice, until the damage is done. A missing data rule can set off a privacy violation. 2026 is the year MOPs teams recognise that speed without governance is chaos. So the focus shifts toward human-in-the-loop systems, ethical oversight, cross-functional ownership of data and AI, and rigorous QA processes... the same way software engineers use code reviews, version control, and systematic testing before deployment. Marketing becomes accountable the same way product and engineering are. The teams that implement this properly will move faster, not slower. Because governance removes friction, prevents damage, and builds confidence, both internally and externally. Customers will trust brands that use AI responsibly. Regulators will demand it. Executives will insist on it. And MOPs will be the group keeping the system safe, stable, and compliant. This is the part of the job that’s invisible when it works well and painfully obvious when it doesn’t. So what does this all add up to? 2026 is not the year MOPs becomes easier. It’s the year it becomes unavoidable... the critical function determining whether marketing teams can adapt to the speed, complexity, and intelligence of modern buying behaviour. AI doesn’t replace Marketing Operations. It makes MOPs more important than ever, because someone needs to be steering the machine. Marketing no longer survives without: Real-time data Dynamic orchestration Composable stacks Intelligent governance and the ability to quantify real business value MOPs is the team that holds all of that together. This is the moment where Marketing Operations stops being backstage… and becomes the operating system of the entire Go-To-Market engine. Discover our Services

When Progress acquired ShareFile, they faced a classic challenge in Marketing Operations: How to migrate an entire marketing automation system into an existing production platform without disrupting campaigns, losing data, or compromising compliance. The stakes were high. ShareFile’s Acquia Campaign Studio (ACS) contained over a million records, multiple custom fields, and complex compliance requirements. Progress needed a partner to manage not just the technical migration, but also day-to-day campaign execution and alignment with GDPR and email regulations. Sojourn stepped in to make the transition smooth, structured, and reliable. The first priority was campaign continuity . We embedded a Sojourn team member with the Progress team to review email and campaign deployment processes, provide training on ACS, and take over campaign management during the migration. This ensured that ongoing communications were uninterrupted, maintaining trust with both internal stakeholders and external customers. Next came data migration , the backbone of the project. We audited ShareFile’s ACS instance to understand data structures and processes, then created a master migration field mapping document to align every source field with its Eloqua destination. We carefully defined migration requirements, including exclusions, duplicate handling, GDPR alignment, and the order of operations for data transformations. Once the initial migration was complete, we executed a delta migration to capture any updates after go-live, leaving no record behind. Finally, we tackled email compliance . ShareFile’s simple single opt-in structure had to be aligned with Progress’s more complex email compliance framework, including explicit opt-ins across multiple countries. Sojourn designed and implemented program logic to process the newly migrated records efficiently while meeting all regulatory requirements, ensuring compliance from day one. The results speak for themselves. Over 1.2 million records  were successfully migrated into Progress Eloqua, all aligned with strict email compliance standards, and every project milestone was met on time. Campaigns continued without interruption, data integrity was maintained, and leadership had confidence that both systems were consolidated safely. This project wasn’t just about moving data, it was about protecting Marketing Operations, preserving compliance, and enabling Progress to leverage their newly acquired assets immediately. With Sojourn’s structured approach, the migration became a seamless, risk-free transition that set the stage for scalable marketing success. Discover our Services

Because “ just add AI ” is not a strategy... it’s a cry for help. Marketing Operations is already the unsung backbone of most organisations. It’s the invisible architecture holding campaigns, data, and processes together. It’s the dashboards, the workflows, the lead routing rules, the naming conventions, the odd “ don’t add another lifecycle stage ” arguments that never end. Now we’ve added AI into that ecosystem, and everyone expects instant magic. Spoiler : Magic without method looks a lot like chaos dressed in a shiny interface. Why roles matter more than tools AI doesn’t replace people, it amplifies what they already do. That means your operating model needs to start with clarity on roles . Without it, AI becomes a free-for-all, and humans step back, assuming the model “ knows best ”. It doesn’t. MOPs leaders  become conductors, orchestrating which tasks stay human-led, which are automated, and where judgment is essential. Analysts  move from dashboard janitors to translators of insight, interpreting patterns flagged by AI. Copywriters  shift from volume production to clarity specialists, letting AI handle repetitive drafts while they focus on nuance, tone, and brand voice. Campaign managers  supervise outputs and coordinate handoffs across teams, ensuring the AI doesn’t execute something that breaks governance rules. Defining roles explicitly ensures everyone knows what they’re responsible for and what the AI can safely do, and what it absolutely cannot . Responsibilities: No one can shrug and hope The most common AI-related failure in Marketing Operations isn’t the technology itself. It’s the assumption that someone else will “ deal with it. ” Without clear responsibilities, AI becomes the corporate equivalent of a toddler left alone with a can of paint. Questions your operating model must answer include: Who reviews AI outputs before they go live? Who approves workflow changes suggested by the model? Who monitors data quality and model accuracy? Who escalates anomalies or misfires? If these aren’t explicit, AI will multiply confusion faster than any human could. Cross-functional communication: Keeping everyone honest AI doesn’t operate in a vacuum. Sales, Marketing, RevOps, Product, IT and Security all have different needs and priorities. If communication isn’t baked into your model, the AI becomes the excuse for misalignment. Instead, build a simple loop that ensures visibility and accountability: Teams can see what AI is generating in real time. Decisions about execution are clearly documented. Escalation paths exist for edge cases or unexpected outputs. This isn’t just about avoiding disasters. It’s about letting the AI accelerate work instead of creating friction. Guardrails: Boundaries that save sanity AI is clever, confident, and occasionally delusional. Guardrails stop it from making “ helpful ” suggestions that blow up your portal. Some practical examples: Models can flag anomalies, draft copy, and propose segments. Models cannot approve campaigns or push workflow changes directly. AI suggestions must be reviewed, contextualised, and approved by humans. Without these guardrails, AI doesn’t multiply effectiveness, it multiplies chaos. The human handoff: Where judgment matters AI shines when it can do the heavy cognitive lifting, but humans are still essential for context, nuance, and brand alignment. This is the handoff point: AI surfaces insights, highlights anomalies, drafts options, and runs QA checks. Humans interpret results, make strategic decisions, and determine final execution. Define the handoff explicitly: What the AI produces, how humans evaluate it, and who signs off. This keeps AI a tool and not a rogue operator. Oversight and governance: Keeping the AI honest AI doesn’t break loudly; it drifts. Yesterday’s brilliant output can become tomorrow’s hallucination. Oversight is critical: Regular audits of AI outputs and recommendations. Bias reviews to ensure model suggestions align with business goals and ethics. Prompt and performance review logs to trace decision-making. Evaluation of AI impact on KPIs and business outcomes. Oversight isn’t glamorous, but it prevents small mistakes from escalating into catastrophic misfires. Policy and compliance: Not optional A strong operating model requires formal policy. Without it, AI adoption turns into a free-for-all. Policy should address: Approved AI tools and integrations. How customer data can (and cannot) be used. Governance around workflow automation and content approvals. Logging, documentation, and version control requirements. Thresholds for AI decision-making and human review. This prevents teams from inadvertently breaking privacy rules, regulatory requirements, or brand standards. Integrating AI into your operational rhythm AI isn’t a one-off project. It’s a continuous rhythm that needs structure: Weekly:  QA for campaigns, anomaly alerts, workflow checks. Monthly:  Model refinement, backlog cleanup, insights review. Quarterly:  Lifecycle evaluations, automation optimisations, cross-team alignment. Annual:  Deep audits to prune obsolete workflows and validate governance. A consistent cadence ensures AI becomes infrastructure, not a novelty. Culture and adoption: Humans first No model, no matter how well designed, will succeed without adoption. People need training, transparency, and confidence in the system. Encourage a culture of questioning AI outputs, not blind reliance. Celebrate insights and improvements that AI brings, but don’t shy away from pointing out mistakes. Make it clear that AI is an assistant, not a replacement, for human judgment. Measuring success: What good looks like An effective AI operating model isn’t measured by how much AI is used, but by outcomes: Reduction in repetitive tasks. Faster campaign cycles without errors. Improved data quality and fewer manual interventions. Insights that inform better decision-making across teams. Success is measured by human impact amplified by AI, not AI activity alone. Final thoughts AI is a multiplier. It can amplify clarity or chaos, speed or mistakes, insight or nonsense. The difference isn’t the tool, it’s the operating model. When roles are defined, responsibilities are explicit, guardrails are enforced, and humans remain central to decisions, AI becomes a quiet superpower. Without those foundations, it’s a very enthusiastic system doing a lot of damage very quickly. The future of Marketing Operations is not “AI everywhere.” It’s humans and AI working together, each doing what they do best. Nail the operating model, and AI stops being a novelty. It becomes the infrastructure behind campaigns that are smarter, faster, and actually work. Discover our Services

For Norstella’s marketing team, reporting had become a scavenger hunt. Data lived across multiple systems, filters didn’t align, and every “simple” question about performance meant another round of manual pulls, spreadsheets, and late nights reconciling mismatched numbers. It wasn’t that the data didn’t exist, it just wasn’t telling the full story. Attribution stopped at the lead source, leaving no real visibility into how campaigns, channels, and touchpoints actually influenced opportunities and revenue. Leaders wanted answers faster, but the team was trapped in fragmented systems and inconsistent reports. Sojourn partnered with Norstella to change that. Not just by building dashboards, but by redefining how marketing performance was understood across the organisation. We began by bringing order to the chaos. Using data from Snowflake, we built a set of Tableau dashboards that became the single, central source of truth for marketing and funnel performance. Every metric, every definition, every filter - aligned and documented. For the first time, Norstella’s teams were speaking the same data language. Defining the full marketing and sales funnel was a pivotal step. Together, we mapped every stage, agreed on conversion metrics and KPIs, and established the shared framework needed for true performance visibility. With that foundation in place, we introduced something entirely new to Norstella: Multi-Touch Attribution (MTA) . MTA changed everything. Instead of crediting revenue to a single lead source, Norstella could finally see how all channels contributed to the journey. With three attribution models ,first touch, last touch, and full path, leadership gained a balanced, transparent view of ROI across the board. No channel left behind. We also built flexibility into the system. Drill-down functionality made it easy for users to self-serve insights and export targeted data subsets, while a rigorous validation process ensured every dashboard was accurate and trusted before launch. Importantly, this wasn’t a “set it and forget it” project. We used an iterative, feedback-driven approach, engaging senior stakeholders early and often to ensure adoption. As a result, these dashboards aren’t just sitting in a shared drive somewhere, they’re actively used across teams and leadership meetings. The impact has been transformative. Reporting that once took days is now accessible in seconds. Leadership can finally see the full funnel, from campaign to opportunity to ROI, and make investment decisions based on live, trusted data. And with plans to integrate email performance metrics next, Norstella is well on its way to having a truly unified marketing view. This wasn’t just a technology upgrade; it was a mindset shift. Norstella’s marketing team moved from reactive reporting to proactive insight - from manually pulling numbers to trusting what they see . The result? A faster, smarter, more confident marketing organisation, with data it can finally rely on. Discover our Services

Most enterprise Marketing Operations teams have a familiar pattern: Once they’ve picked a consultancy, they stick with them. For years. Sometimes for many  years. There’s a kind of unspoken rule that if nothing is on fire and invoices arrive on time, then continuity must be good. Safe. Sensible. But here’s the uncomfortable bit: Playing it safe can be the very thing stopping teams from evolving. While the world around them accelerates... new tech, new data expectations, new pressures from sales and finance... many teams are still working with agencies that deliver “maintenance,” not momentum. And all the while, there are consultancies out there that operate on a completely different level: More forward-thinking, more experienced, more measurable, and frankly, more enjoyable to work with. So why stay put? And what would actually happen if they didn’t? The emotional comfort of the familiar. Let’s start with the psychology behind long-standing vendor relationships. People don’t cling to their current consultancy because they believe it’s the perfect one, they cling because it’s the known one. They know who to email. They know who will pick up the phone. They know roughly what they’ll get, and roughly what they won’t. That sense of predictability feels secure. There’s also the fear factor: Switching partners can feel like opening Pandora’s box. Procurement steps in. Onboarding takes time. Senior stakeholders ask questions. There’s a risk, imagined or otherwise, that things might dip before they improve. And then there’s internal politics: Someone in the business championed the incumbent years ago. Changing course can feel like announcing they backed the wrong horse. It’s not irrational. But it isn’t strategic either. The quiet cost of staying where you are. What rarely gets acknowledged is what companies give up  by staying with the same consultancy too long. It’s not just the cost of the retainer, it’s the cost of opportunities missed. A consultancy that’s comfortable will rarely be the one pushing you to adopt new technologies, rethink your data model, or redesign your measurement framework. They’ll keep your dashboards ticking along and your automations functioning, but innovation? Transformation? True optimisation? Not likely . Over time, teams end up operating in a slow decline without noticing it. They deliver campaigns, but don’t learn. They manage workflows, but don’t evolve them. They get reports, but not insight. And the team morale quietly flattens, because working with an uninspired partner makes even the most capable internal people feel like they’re treading water. Stability is only useful until it becomes inertia. Why pushing back is a feature, not a flaw. The consultancies that genuinely move organisations forward are the ones that challenge them. They ask “ why ”, sometimes repeatedly, until the real blockers surface. They poke at assumptions that have been sitting around like old furniture nobody wants to move. They force conversations about data quality, attribution gaps, workflow bloat, and KPIs that look impressive but mean nothing. This isn’t being difficult. It’s being valuable. Teams don’t improve because someone nods politely. They improve because someone cares enough to test the logic, the process, the tooling and the expected outcomes. A good consultancy is part technician, part coach, part business economist, and absolutely not a “yes-machine.” What the best modern consultancies actually look like. The top-tier firms today don’t behave like traditional agencies. They don’t treat clients as project tickets, and they definitely don’t believe short-term wins are the whole game. They immerse themselves. They’re the kind of partners with decades upon decades of accumulated experience, not just senior figureheads on slide decks, but full teams who’ve lived through migrations, integrations, restructures, global rollouts and the occasional dumpster fire that only a true ops veteran can clean up. Picture nearly 500 combined years of Marketing Operations experience, stretched across 12 and a half time zones, 11 languages and more cultures than can fit neatly into a PowerPoint slide. That’s not diversity for the sake of it, that’s perspective you can’t buy off the shelf. These firms treat your team like an extension of their own. They get embedded. They train. They transfer knowledge. They build capability instead of hoarding it. And because they’re comfortable having real conversations, they bring energy into the work - which matters more in B2B marketing than most people admit. When the work is complex, dry, or relentless, the right partner can make it feel manageable, creative, even enjoyable. And yes, in B2B, “enjoyable” actually matters. Why enterprises hesitate to switch, and how to break the stalemate. Even when leaders know something isn’t working, switching can feel like a huge leap. But it doesn’t have to be. The simplest route is a controlled test - a pilot that focuses on one specific problem area: Attribution clarity, lead quality, nurture performance, marketing–sales alignment, whatever hurts the most. The incumbent handles the day-to-day while the new partner runs a tightly defined experiment. The risk stays low. The insight goes up. And if the new partner proves they can deliver measurable improvements in a short window, everyone suddenly becomes a lot braver. If an incumbent consultancy can’t clearly articulate your architecture, your processes or your success metrics, that’s already a sign you’re relying on people rather than systems. And if they’re unable, or unwilling, to document handover plans, then they’re serving their own retention strategy, not yours. The ROI conversation most consultancies avoid. The modern consultancies that actually drive value don’t hide behind vague language. They talk in commercially meaningful terms: Revenue influenced, conversion velocity, operational cost savings, CAC reduction, sales productivity, margin impact. They measure. They hypothesise. They improve. And they do it out loud, with transparent dashboards and experiments you can audit. That’s the difference between a partner that delivers activity and one that delivers outcomes. If a consultancy can’t show you precisely how they move one core business metric in the next quarter, the red flag is already waving. So why choose a partner like Sojourn Solutions? Because Sojourn is built in that modern mould, not the “keep things tidy” version of consulting, but the “help us grow, challenge us, integrate with us, and be part of the team” version. We bring almost half a millennium of combined Marketing Ops expertise, which is an absurd amount of lived experience to have on your side. Spread across 12.5 time zones and fluent in 11 languages... we can support global programs without the usual cultural or logistical headaches. We don’t arrive with a cookie-cutter playbook; but instead adapt to each client, and we’re not shy about saying when something doesn’t make sense. Most importantly, we behave less like an external supplier and more like an internal capability accelerator. We push. We guide. And we get into the weeds. We surface opportunities others overlook. And know exactly how to make the work feel lighter without ever losing rigour. If your team wants a consultancy that integrates like a partner, challenges like a strategist and executes like an operator, we are what that looks like. The one question every Marketing Ops leader should be asking... If your incumbent consultancy has been “good enough” for years… is that actually good enough for where you need to be in the next 18 months? The market is evolving too fast for passive partnerships. You don’t need to fire your existing agency tomorrow. You don’t need to leap into a radical transformation. You just need to start with one metric you care about and ask your consultancy, in fact any consultancy, to show you the exact experiment they’d run next week to move it. If the answer is vague, slow, or wrapped in excuses, then you’ve already outgrown them. And if you’re ready for a partner who asks better questions, drives measurable progress, brings real experience, and makes the journey more enjoyable along the way. You already know where to look. Discover our Services

For Dash Solutions, marketing is more than sending campaigns. It's about driving measurable impact in a competitive healthcare disbursements market. Despite a solid Account-Based Selling (ABS) foundation, the company was facing a familiar challenge: Marketing and sales often targeted the same accounts independently, account prioritization was inconsistent, and pipeline attribution was limited. Teams were spread thin, chasing the same prospects, and struggling to understand what was truly working. Sojourn partnered with Dash to take their ABX efforts to the next level, introducing structure, alignment, and visibility while building a repeatable framework for scalable execution. Fast, focused ABX execution The first step was an ABX Readiness Assessment , which laid the groundwork for a "1:Many" ABX pilot for healthcare disbursements. Launched in just 90 days. Accounts were segmented into tiers to focus effort where it mattered most. Tier 1 accounts received dedicated Sales attention, Tier 2 received personalized Marketing nurture, and Tier 3 were targeted with broader "1:Many" campaigns. As Elizabeth Worrell, SVP of Marketing, noted: “The account tiering model has already saved us time and ensured Sales focuses on the right opportunities.” To operationalize alignment, we introduced a soft SLA  with bi-weekly check-ins, giving Sales and Marketing a clear structure for accountability. Meanwhile, a live feedback loop  ensured insights from SDR outreach and prospect conversations flowed directly back into Marketing, enabling real-time optimization of messaging. “Having a live feedback loop with Sales has been a game-changer. We can adjust messaging based on real prospect conversations instead of waiting for quarterly reviews,” said Elizabeth. Finally, the ABX pilot was supported by a complete toolkit : The pilot framework, journey map, Sales partner plan, SLA + cadence, and content recommendations, all designed to support execution and scalability across the business. Early impact The results were immediate and tangible. Dash launched their "1:Many" healthcare disbursements pilot and is preparing to scale across additional business lines. Sales efficiency improved as Tier 1 accounts received focused attention while Marketing nurtured Tiers 2 and 3. The Sales/Marketing feedback loop enabled real-time optimization, and SDR outreach using optimized content delivered net-new prospect meetings. Perhaps most importantly, trust and alignment between Sales and Marketing strengthened, creating a foundation for long-term ABX success. Elizabeth reflected on the partnership: “Working with Sojourn helped us move fast. In just weeks, we went from fragmented efforts to a structured, scalable framework. The process was approachable, the deliverables were clear, and the early results give us confidence to expand this model across the business.” Business benefits delivered Efficiency gains:  Account tiering and aligned workflows eliminated wasted effort. Higher-quality pipeline:  SDR activity powered by optimized content generated early prospect traction. Scalable ABX foundation:  Dash now has a repeatable framework to expand across additional business lines. What’s next Dash is proving ABX today. The next phase is integrating Customer Success  into the model, completing the ABX lifecycle to ensure alignment, measurement, and advocacy across the full customer journey. Discover our Services

Marketing Operations leaders occupy one of the most challenging roles in modern marketing. They are the glue that holds strategy, technology, and execution together, responsible for ensuring campaigns run smoothly, data flows accurately, and the marketing engine generates measurable impact. But today, MOPs leaders face a unique pressure that feels almost relentless: The pace of innovation. The marketing technology landscape is evolving faster than most organisations can realistically adapt. Artificial intelligence, generative content, predictive analytics, and intent-driven tools are no longer optional, they are rapidly becoming essential. For leaders already juggling multiple platforms, complex workflows, and mountains of data, understanding which technologies truly matter, and how to implement them effectively, can feel overwhelming. The innovation dilemma: Speed vs. strategy One of the most fundamental challenges is distinguishing between fleeting trends and technologies that offer lasting value. Every month, new platforms, features, and automation solutions hit the market. AI-driven content generators promise to replace hours of copywriting. Predictive analytics claim to forecast buyer behaviour with startling accuracy. Personalisation engines suggest hyper-targeted messaging for every segment of your audience. While the potential is tantalising, adopting every shiny new tool indiscriminately is a trap. Each new technology comes with hidden costs: Training, integration, maintenance, and the risk of fragmenting your existing workflows. MOPs leaders must make calculated decisions, ensuring that innovation aligns with business objectives, enhances efficiency, and improves customer experience  rather than complicating operations. A common pitfall is focusing on technology for technology’s sake. Many teams invest in advanced platforms but fail to integrate them into their broader strategy. Campaigns might run, but insights are scattered, and results are difficult to measure. In the worst cases, a new tool can disrupt a previously smooth operation, creating more headaches than it solves. The role of data: Both a boon and a burden Keeping pace with innovation is inseparable from managing data effectively. Modern marketing is data-driven, but the explosion of platforms has made data both abundant and unwieldy. Every campaign, email send, and digital interaction produces data points - often hundreds of thousands per quarter, sometimes millions. The challenge for MOPs leaders is twofold: Ensuring data quality  and extracting actionable insights . High-quality, integrated data allows teams to optimise campaigns, measure ROI accurately, and predict buyer behaviour. Poor-quality data, however, can mislead decision-making, resulting in wasted spend, underperforming campaigns, and frustrated stakeholders. Innovative tools can help, but only if they are implemented thoughtfully. For example, AI-powered analytics platforms can automatically detect trends or anomalies in campaign performance, but if your underlying data is inconsistent or siloed, even the most advanced algorithms will produce unreliable outputs. This is why strategic adoption, rather than reactive experimentation, is critical. Managing the human side of innovation Technology alone doesn’t solve the innovation challenge. One of the most underestimated aspects of keeping pace is change management. Even the most promising tool fails if teams don’t adopt it effectively. MOPs leaders must champion cultural and behavioural shifts  alongside technological implementation. Training is essential. Teams need to understand not just how to use a new platform, but why it matters and how it supports larger business goals. Standardised processes must be established to ensure consistency and efficiency. Leadership alignment is critical: Without executive buy-in, adoption can falter, leaving new tools underutilised and ROI unrealised. For instance, consider a company implementing a predictive lead-scoring platform. The technology might be excellent, but if sales teams don’t trust the scoring model, they will bypass it in favour of familiar manual processes. The innovation fails not because of the technology, but because the human elements: trust, training, and alignment, were neglected. Knowing when to partner with experts This is where consultancy firms like Sojourn Solutions provide immense value. Experienced consultants bring both technical expertise and strategic perspective . They can help MOPs leaders identify which innovations are worth adopting, design workflows that integrate seamlessly with existing systems, and ensure teams are set up for success. A consultancy does more than implement technology, they guide organisations through adoption, training, and change management. They can provide an external perspective  that challenges assumptions, highlights gaps, and ensures that innovation drives measurable business outcomes rather than just creating noise. For example, when a client approaches Sojourn with a sprawling tech stack and unclear ROI, we assess the full marketing ecosystem, identified redundant tools, and implemented AI-driven reporting to unify data streams. The result is not just a more efficient stack, but a team that can confidently leverage new technologies without fear of disruption. Balancing experimentation with operational stability Another nuance of keeping pace with innovation is balancing experimentation with operational stability . MOPs teams must run campaigns reliably every day, yet simultaneously explore emerging technologies that could transform marketing outcomes. This balancing act requires careful prioritisation. Leaders should categorise potential innovations into three buckets: Low-risk, high-impact : Technologies that can be implemented quickly and deliver immediate efficiency gains. Moderate-risk, strategic : Tools that require some investment but have the potential to significantly improve targeting, personalization, or measurement. High-risk, exploratory : Emerging technologies that could be game-changers but require experimentation, pilot programs, and careful evaluation. This framework ensures teams are not paralysed by options, and that innovation is purposeful rather than reactive. Leveraging AI without losing control Artificial intelligence is now at the forefront of MOPs innovation. From generative content to predictive analytics, AI promises faster, more intelligent decision-making. Yet leaders face a delicate challenge: Trusting AI outputs while maintaining oversight. Blindly relying on AI can introduce errors, bias, or strategic misalignment. Successful MOPs leaders implement guardrails, validation processes, and ongoing monitoring  to ensure AI enhances decision-making rather than replacing human judgment. AI should be viewed as an augmentation tool , not a replacement for operational expertise. We help accelerate AI adoption responsibly by providing frameworks for evaluating AI tools, integrating them into workflows, and training teams  to use AI outputs effectively. This approach maximises benefits while minimising risk. Innovation as a competitive advantage Organisations that embrace innovation strategically gain a significant edge. AI-driven insights, automated workflows, and predictive capabilities allow teams to respond faster to market shifts, deliver personalised experiences at scale, and ultimately drive revenue growth more effectively than competitors. MOPs leaders who stay ahead of innovation position their teams as strategic partners , rather than operational support. They are able to demonstrate clear ROI, influence business decisions, and lead the organisation toward future-ready marketing practices. Conversely, organisations that fall behind struggle with inefficiency, missed opportunities, and a reactive posture. In a world where buyer expectations evolve rapidly, falling behind on innovation is not merely inconvenient, it can be a strategic liability. Cultivating a culture of continuous improvement Keeping pace with innovation is an ongoing process. It’s not about implementing a single tool or completing a one-time project; it’s about cultivating a culture of continuous improvement . This means embracing curiosity, experimenting responsibly, and iterating based on data-driven insights. Leaders must encourage teams to share learnings, highlight successes and failures, and remain open to new approaches. A culture that rewards experimentation and learning is better equipped to navigate rapid change, adopt meaningful innovations, and maintain operational excellence. Consultancies can play a crucial role in fostering this culture. Beyond technology and process, firms like ours offer mentorship, frameworks, and strategic guidance that help organisations embed innovation into their DNA. This ensures that MOPs teams aren’t just reacting to change, they are actively anticipating it. Final thoughts Keeping pace with innovation is one of the most pressing challenges for Marketing Operations leaders today. It requires balancing speed with strategy, leveraging data effectively, managing human and technological adoption, and making informed decisions about which innovations will deliver real business impact. The good news is that with the right approach, and the right partners, innovation doesn’t have to be overwhelming. Strategic adoption, careful prioritisation, and guidance from experienced consultants like Sojourn Solutions allow MOPs leaders to harness the power of emerging technologies while maintaining operational stability. Ultimately, staying ahead in Marketing Operations isn’t about chasing every trend, it’s about selecting the right innovations, integrating them thoughtfully, and creating a team and culture capable of executing at the highest level . Leaders who master this balance will not only keep pace - they’ll set the pace, driving measurable impact and positioning marketing as a true strategic force within their organisations. Discover our Services