Here is a scene playing out in B2B boardrooms right now. The CRO pulls up the quarterly pipeline review. Marketing’s numbers show 400 MQLs. Sales says they only received 60 worth calling. CS is quietly watching four accounts go quiet before their renewal dates. Finance wants a number they can hold people to. Everyone has data. Nobody agrees on what it means.
This is not a 2021 problem. It is a 2026 problem. And it is getting worse, not better, because the addition of AI tools across all three teams is amplifying the misalignment rather than fixing it.
In 2026, the defining question in B2B revenue is not which AI tool to buy. It is whether your revenue engine is aligned enough for AI to actually help you.
That is what RevOps answers. Revenue Operations is the operating model that aligns marketing, sales, and customer success around shared data, shared processes, and shared accountability so that AI, automation, and every investment you make in growth compounds rather than collide.
This guide covers everything B2B organisations need to know about RevOps in 2026: what it is, what has changed this year, how to build it, which tools to use, and specifically how AI is reshaping every part of the function. Whether you are a CRO rebuilding your GTM model, a CMO trying to prove pipeline contribution, or a RevOps leader navigating the shift to agentic AI, this is the guide you need.
What Is RevOps? The 2026 Definition
Revenue Operations (RevOps) is the alignment of sales, marketing, and customer success under a single operational framework, with shared processes, shared data, shared technology, and shared accountability for revenue outcomes across the full customer lifecycle.
That definition has not changed. What has changed in 2026 is the scope. RevOps now has a fourth responsibility: governing the AI and automation layer that runs across all three GTM teams. When marketing runs an AI scoring model, when sales uses an AI agent to update the CRM, when CS deploys automated churn alerts, someone has to own the logic, the data inputs, the accuracy, and the governance of all of it. In 2026, that someone is RevOps.
Think of it this way. In 2020, RevOps was the team that made the relay race run smoothly, ensuring the baton was handed between teams without being dropped. In 2026, RevOps is also responsible for the timing systems, the AI coaching software, the track conditions, and the rules that govern when AI is allowed to take over the baton entirely.
And yet Forrester’s 2025 State of RevOps survey found that 58% of B2B companies still cite process misalignment as their primary barrier to growth. The aspiration and the execution are still far apart for most organisations. The opportunity is enormous for those who get it right.
Why 2026 Is the Most Important Year for RevOps Yet
B2B markets in 2026 are under more pressure than at any point in the past decade. Customer acquisition costs remain high, buying cycles have lengthened, and budget scrutiny has never been tighter. At the same time, AI experimentation has moved from pilots to production, and the results are mixed at best.
The B2B buying reality in 2026
Gartner’s latest buyer research shows that B2B buyers complete 70 to 80% of their decision journey before speaking to a sales representative. Buying groups now average five or more stakeholders in enterprise deals. And 61% of B2B buyers in a July 2025 Gartner survey said they prefer a rep-free experience for initial stages, yet still expect expert human engagement when complexity rises.
This creates a paradox. Digital and AI-driven marketing needs to do more of the early-stage work. But the handoff to sales still matters enormously. And the gap between digital experience and human conversation is exactly where most B2B organisations are leaking revenue.
The cost of getting it wrong in 2026
Misalignment is not just frustrating in 2026; it is expensive in ways that are now measurable:
- 36% higher CAC: Poor alignment drives customer acquisition costs up by 36% (McKinsey 2023, still the definitive benchmark).
- 30% longer sales cycles: Uncoordinated handoffs between marketing and sales directly extend deal timelines (Forrester Research 2024).
- 58% of B2B companies cite process misalignment as their primary growth barrier in 2026 (Forrester State of RevOps 2025).
- 60% of revenue leaders say data silos are blocking their ability to forecast accurately, the number one RevOps pain point this year.
- AI making things worse: For teams without data and process alignment, AI tools are amplifying the misalignment. Bad data fed to an AI agent produces bad routing decisions and flawed forecasts at scale.
In 2026, the companies adding AI on top of broken processes are not accelerating; they are accelerating in the wrong direction. RevOps fixes the direction first.
The growth case for doing it right
The organisations that have invested in RevOps foundations over the past two years are now compounding those returns. According to ORM Technologies and SiriusDecisions 2024–2025 data:
- 30% reduction in GTM costs for companies with mature RevOps functions.
- 10 to 20% higher sales productivity measured in opportunities created and deals closed per rep.
- 40% increase in sales efficiency for teams that invested in clean, governed data foundations before layering AI.
- 67% more revenue per customer: Existing customers with high health scores spend 67% more than new prospects, and RevOps is what makes expansion plays systematic.
The Four Pillars of RevOps Updated for 2026
The four pillars of RevOps have not changed. What has changed is the urgency and the specific execution requirements within each pillar in 2026.
Pillar 1: Process Optimisation Now Including AI Process Governance
Process has always been the starting point for RevOps. In 2026, process optimisation has a new dimension: defining which processes are human-owned, which are AI-assisted, and which are fully automated.
The organisations getting this right in 2026 are drawing what operators at NVIDIA and Samsara call a clear line between deterministic workflows, where the rules are fixed, and AI can execute autonomously, and probabilistic workflows, where human judgment is still required. The job of RevOps is to map this boundary across the entire revenue process and keep it updated as AI capabilities evolve.
Traditional process work still applies: mapping the lead-to-revenue journey, standardising handoff criteria, defining MQL and SQL, and eliminating bottlenecks. But in 2026, you are also mapping AI touchpoints and deciding how to govern them.
Pillar 2: Data Integration and Governance The Make-or-Break Pillar in 2026
If there is one pillar that separates the RevOps leaders from the laggards in 2026, it is data. This year, the companies that invested in clean, governed, integrated data in 2024 and 2025 are seeing compounding returns on every AI investment they make. The companies that skipped this step are watching their AI budgets produce noise.
The 2026 data reality: 38% of RevOps leaders cite poor data accuracy as their top barrier to growth. 60% say data silos are blocking forecasting. The data governance market is projected to triple from $5.38B to $18.07B by 2032 (CAGR 18.9%) because organisations are finally realising that data quality is not a cleanup project; it is a competitive infrastructure investment.
In 2026, leading RevOps teams are building formal data governance frameworks: establishing canonical definitions for every revenue object in the CRM, implementing enrichment and deduplication at the point of data entry, running regular data audits, and maintaining a live data quality score that they report to leadership alongside pipeline metrics.
Pillar 3: Technology Alignment Consolidation Over Accumulation
The RevOps tech stack conversation in 2026 has shifted completely. The question is no longer which AI tools to add. The question is which tools to cut and which to consolidate around.
LeanData, Gartner, and multiple RevOps practitioners have made the same point clearly this year: when multiple tools surface different next-best-action recommendations to the same rep, trust in AI drops fast, and adoption follows. The most effective RevOps stacks in 2026 are built around fewer, deeper-integrated platforms that share the same data definitions and logic rather than a collection of point solutions producing conflicting signals.
Pillar 4: Performance Measurement AI Fluency as a New KPI
RevOps measurement in 2026 goes beyond CAC, CLV, and NRR, though those remain the board-level metrics that matter most. The new dimension is measuring the effectiveness of the AI layer itself: are AI recommendations being acted on? Are forecasting models improving in accuracy? Is data quality trending up or down?
The most forward-thinking RevOps teams in 2026 are introducing AI Adoption ROI and Data Integrity Score as formal RevOps metrics reported to the CRO and CEO. This creates accountability not just for revenue outcomes but for the operational infrastructure that makes those outcomes sustainable.
What a RevOps Structure Looks Like in 2026
The RevOps org structure debate has matured significantly. In 2026, three models dominate, and the choice depends on company size, stage, and the maturity of your AI ambitions.
The Centralised RevOps Model
A VP or Head of RevOps owns a central team that serves marketing, sales, and CS equally. In 2026, this team also owns the AI governance layer, deciding which agents run, what data they access, and how their outputs are monitored. This works best for companies with 50 or more GTM headcount and is the most common structure among Series B and above organisations.
The Embedded Model
Each team retains its own operations function, Marketing Ops, Sales Ops, CS Ops, but reports into a central RevOps leader. In 2026, the central RevOps leader also coordinates the AI strategy across embedded ops functions, ensuring that AI tools and agents across different teams are not creating contradictory actions or duplicate data writes.
The Fractional and External Model
Smaller B2B organisations are increasingly using fractional RevOps leaders who come in with pattern recognition and proven playbooks, building the foundation quickly without the cost of a full VP hire. In 2026, the best fractional leaders also bring AI implementation experience, not just process design expertise.
Important note for 2026: The RevOps function is no longer just reacting to requests from sales or marketing. The best RevOps teams in 2026 operate like internal product teams owning workflows end-to-end, defining SLAs, monitoring system health, and iterating based on what is actually driving revenue. This shift from support function to product owner is the defining cultural change in RevOps this year.
How AI Is Reshaping RevOps in 2026: What Is Actually Working
AI in RevOps is no longer a future topic. In 2026, 96% of revenue leaders expect their teams to use AI, according to Gong’s State of Revenue AI report. The question now is not whether to use AI; it is which use cases are delivering real returns and which are producing expensive noise.
What Is Actually Working in 2026
AI Use Case 1: Agentic Workflows Across the Bow-Tie
2025 was the year of AI agent experiments. 2026 is when someone has to make those agents work together, and that someone is RevOps. The most advanced B2B organisations are now running coordinated AI agents across the full revenue bow-tie: marketing agents qualifying inbound, sales agents doing account research and personalisation, CS agents monitoring usage signals and flagging renewal risk.
The keyword is coordinated. An AI agent in marketing that scores an account differently from the agent in sales creates confusion and erodes trust. RevOps owns the coordination layer, ensuring consistent definitions, consistent data, and consistent action logic across all agents. McKinsey projects that organisations integrating agentic AI into daily workflows can achieve productivity gains of up to 40%, with measurable improvements beginning as early as this year.
AI Use Case 2: Conversational Analytics Replacing Static Dashboards
In 2026, the most effective RevOps teams have moved from static dashboards to conversational analytics, where any GTM stakeholder can ask a natural language question and get an immediate, usable answer from their revenue data. ‘Which accounts in our pipeline have slowed deal velocity in the last 30 days?’ ‘What is the win rate for deals where we had two or more stakeholders engaged?’ These used to require a data analyst and two days. Now they take seconds.
This democratisation of data access is changing RevOps hiring patterns. AI fluency, the ability to prompt, interpret, and act on AI-generated insights, has become the most important non-negotiable for RevOps roles in 2026.
AI Use Case 3: Adaptive Forecasting Replacing Gut-Feel With Continuous Learning
Traditional forecasting was a quarterly ritual based on rep-submitted numbers that were optimistic by design. AI forecasting in 2026 works differently. Machine learning models are continuously retraining on live deal activity, engagement signals, historical win patterns, and pipeline velocity. They auto-flag risks declining win rates by product line, accounts where stakeholder engagement has dropped, deals that are aging out of typical conversion windows, and adjust projections in real time.
Forrester found that companies using integrated platforms with AI forecasting reduce forecast variance from 30–40% to under 10%. For a company with a $10M annual revenue target, that reduction in forecast variance can mean the difference between confident investment and reactive cost-cutting.
AI Use Case 4: AI-Powered Sales-to-CS Handoffs
One of the most consistently broken processes in B2B has been the handoff from sales to customer success. Sales closes the deal. CS inherits a sparse CRM record. The first onboarding call is a rediscovery session. The customer notices. Trust erodes before the relationship has really started.
In 2026, AI tools automatically synthesise every sales conversation into a structured handoff document covering the pain points discussed, the success criteria agreed, the stakeholders met, the objections raised, and the commitments made. CS teams arrive at the onboarding call already knowing what matters to this customer. This single change, now deployed in production at hundreds of B2B organisations, has measurably improved onboarding satisfaction and early renewal intent.
AI Use Case 5: Intent-Driven Account Orchestration
Platforms like 6sense and Demandbase have matured significantly. In 2026, intent data is no longer just a signal; it is an orchestration trigger. When an account moves into an active buying stage (based on intent signals, website behaviour, and engagement patterns), AI automatically adjusts that account’s priority in the scoring model, triggers a coordinated outreach sequence across email and LinkedIn, alerts the relevant AE, and updates the CRM, all without manual intervention.
For ABM-led B2B organisations, this is transformative. The average ABM programme at The Smarketers now runs with an AI orchestration layer that would have required three people to manage manually two years ago.
What Is Not Working And Why
RevOps Metrics That Matter in 2026
The metrics framework for RevOps is more mature in 2026, and the board-level conversation has shifted significantly toward efficiency and retention over pure growth.
Net Revenue Retention (NRR) The Board's Favourite Number
NRR is the metric that matters most in 2026, particularly for SaaS and subscription-model B2B. An NRR above 100% means you grow even without a single new customer because existing customers expand faster than they churn. RevOps directly drives NRR by connecting CS health data to sales expansion plays and ensuring no renewal falls through the cracks. Investors, boards, and acquirers now use NRR as a primary proxy for go-to-market health.
Customer Acquisition Cost (CAC) Under More Scrutiny Than Ever
With budgets tighter in 2026, CAC efficiency has become a top-three board metric. RevOps reduces CAC by improving lead quality (so fewer resources are wasted on bad-fit prospects), shortening sales cycles through better pipeline management, and eliminating process waste at every stage of the funnel.
Pipeline Coverage Ratio
A healthy pipeline still requires 3 to 4x coverage of your revenue target in qualified opportunities. But in 2026, coverage quality matters as much as coverage quantity. RevOps teams are now tracking coverage by stage, by segment, and by AI confidence score, not just overall volume.
Forecast Accuracy
With AI forecasting now mainstream, the benchmark for acceptable forecast accuracy has risen sharply. The industry average for rep-submitted forecasts is still plus or minus 30%. AI-enabled RevOps teams that have clean data and adaptive models are hitting accuracy within 5 to 10% of actuals. If your forecast variance is still above 20%, you have a data quality or process problem, not just a forecasting problem.
Data Integrity Score: The New RevOps KPI
In 2026, leading RevOps teams report a Data Integrity Score to their CRO alongside pipeline metrics. This measures CRM completeness, accuracy, and consistency because if the data foundation is weak, every other metric on this list is unreliable. Companies that have embedded data governance into their RevOps workflows are seeing 40% higher sales efficiency as a direct result.
AI Adoption ROI
A new metric for 2026: what return is the organisation getting on its AI investments in the revenue function? This is tracked by comparing process cycle times, manual work hours eliminated, forecast accuracy improvements, and conversion rate changes before and after AI deployment and attributing those changes to specific tools and use cases.
How to Build RevOps in 2026: A Practical Roadmap
The RevOps implementation playbook has evolved. In 2026, the sequencing matters more than ever because teams that skip the foundational work and go straight to AI are discovering expensive mistakes.
Phase 1: Diagnose Your Revenue Engine (Weeks 1–4)
Before anything else, map reality. This means:
- Mapping your current lead-to-revenue process end-to-end with all three teams in the room
- Auditing CRM data quality, completeness, accuracy, recency, and consistency
- Cataloguing every AI tool currently in use across marketing, sales, and CS, and understanding what data each one reads and writes
- Identifying where AI agents are already operating without coordination (this is more common than most RevOps leaders expect)
- Establishing baseline metrics: CAC, NRR, cycle length, forecast accuracy, data integrity score
Phase 2: Align the Fundamentals (Weeks 5–8)
This is the cultural and definitional work. Without it, everything else fails. Bring GTM leaders together and agree on:
- A shared definition of MQL, SQL, and Opportunity, one that all three teams sign off on
- Lead handoff SLAs: what happens to an MQL within 24 hours, within 48 hours, and what triggers escalation
- Which metrics are all three teams accountable for, particularly NRR and Pipeline Coverage
- A clear boundary between AI-automated decisions and human-judgment decisions across the revenue process
- A weekly or bi-weekly revenue review cadence that all three GTM leaders attend with shared data
Phase 3: Build the Infrastructure (Weeks 9–20)
- Integrate CRM with MAP, CS platform, and analytics tools bidirectionally
- Build shared dashboards that all three teams use as their single source of truth
- Implement data governance: deduplication, enrichment, field-level validation, and a weekly data quality review
- Deploy intent data and AI scoring as coordinated inputs, not siloed tools
- Establish AI governance: register every automation touching revenue data, define approval processes, and set review intervals.
Phase 4: Layer in AI Intelligently (Months 5–12)
AI comes after the foundation, not before. With clean data and aligned processes, AI in 2026 works. Without them, it amplifies problems. Start with the highest-confidence, lowest-risk AI use cases: automated CRM updates, AI-generated handoff summaries, and forecasting models. Build from there as accuracy and trust improve.
Phase 5: Operate and Compound (Ongoing)
RevOps is not a project; it is an operating model. The best RevOps teams in 2026 operate like internal product teams: owning the revenue engine end-to-end, defining and enforcing SLAs, continuously improving based on what drives revenue rather than what looks good on a dashboard, and adapting the AI layer as capabilities and use cases evolve.
The RevOps Tech Stack in 2026: Fewer Tools, Better Integrated
The tech stack conversation in 2026 has decisively shifted from accumulation to consolidation. The leading RevOps teams are working with fewer, deeply integrated platforms rather than large collections of point solutions because coordination matters more than coverage.
CRM The Non-Negotiable Foundation
HubSpot and Salesforce remain the two dominant CRM platforms for B2B RevOps. In 2026, the CRM is not just a database; it is the operational core of the revenue engine. Every AI agent, every automation, every dashboard reads from and writes to the CRM. The quality of your CRM is the quality of your RevOps function. This is why data governance starts here.
Revenue Orchestration and Forecasting
Salesloft (which completed its merger with Clari in December 2025 and was recognised as a Leader in Gartner’s first Magic Quadrant for Revenue Action Orchestration) is the category-defining platform in 2026. Forecastio is emerging as a strong alternative specifically for HubSpot-centric teams. These platforms provide AI-powered forecasting, pipeline risk detection, and the intelligence layer that RevOps needs to make data-driven decisions at speed.
Conversation Intelligence
Gong leads this category in 2026, analysing every sales call for objections, buying signals, talk-track effectiveness, and coaching opportunities. For RevOps, conversation intelligence connects what happens in calls to what happens in the pipeline, giving a signal-rich view of deal health that CRM data alone cannot provide.
Intent Data and ABM Orchestration
6sense and Demandbase have both matured into full orchestration platforms in 2026, not just intent data providers. They now connect intent signals directly to CRM updates, sales sequences, and ABM advertising in a single coordinated workflow. For The Smarketers’ ABM clients, this integration is where the biggest pipeline acceleration has come from in 2025 and 2026.
Customer Success Platform
Gainsight and Totango remain the leaders for CS health scoring, renewal management, and expansion intelligence. In a RevOps model, the CS platform is bidirectionally integrated with the CRM so that CS health data informs sales expansion plays, and sales activity data informs CS risk assessments. NRR improvement is impossible without this integration.
Data Enrichment and Governance
Clay has become the data layer of choice for fast-moving RevOps teams in 2026, combining enrichment, de-duplication, and workflow automation in a flexible, API-first platform. Openprise is the enterprise choice for large organisations that need formal data governance tooling at scale.
Common RevOps Challenges in 2026 And How to Solve Them
Challenge 1: AI Tools Creating Conflicting Signals
The 2026 problem: Marketing’s AI scores an account as high-priority. Sales’ AI scores the same account as medium. CS’s AI flags a usage risk. The rep has three contradictory data points and ignores all of them.
The fix: RevOps owns a single account intelligence layer. All AI recommendations flow through one governed system with one scoring model. Introduce AI tools sequentially, validating accuracy before expanding to new use cases. Limit the number of places where AI surfaces ‘next best action’ recommendations to avoid competing signals.
Challenge 2: Data Debt Blocking AI ROI
The 2026 problem: The AI tools you bought in 2025 are producing wrong outputs because the CRM data they depend on is incomplete, stale, or inconsistently structured. 38% of RevOps leaders cite this as their top barrier.
The fix: Stop adding AI tools and start a six-week data remediation sprint. Fix field definitions, remove duplicates, implement enrichment at entry points, and build a data quality review into your weekly RevOps rhythm. This is not glamorous, but it is the highest-ROI work a RevOps team can do in 2026.
Challenge 3: RevOps Still Seen as a Support Function
The 2026 problem: RevOps is still being asked to run reports and fix Salesforce rather than being treated as a strategic revenue partner. This limits the function’s impact and makes it impossible to govern the AI layer effectively.
The fix: RevOps leaders need to reframe their value in the language of the CRO: forecast accuracy, pipeline efficiency, NRR improvement, and GTM cost reduction. Present RevOps as the operating system of revenue, not the support desk. The VP of RevOps title has grown 300% because organisations that elevate this function see compounding returns.
Challenge 4: No Executive Mandate
The 2026 problem: RevOps requires the CRO, CMO, and VP CS to operate differently to share data, share accountability, and give up some autonomy. Without CEO or board-level sponsorship, it reverts to another siloed initiative.
The fix: Build the business case in revenue language: the 36% CAC reduction, the 10 to 20% sales productivity gain, the NRR improvement. Quantify the cost of the current misalignment. Get the CEO in the alignment session. Make RevOps a board-level priority, not a middle-management experiment.
RevOps and ABM: The Winning Combination for B2B in 2026
For B2B organisations running Account-Based Marketing, RevOps is not just compatible; it is the foundation on which ABM actually works at scale. ABM in 2026 requires exactly the kind of tight coordination, shared data, and AI orchestration that RevOps provides.
Here is the challenge that most ABM programmes run into without RevOps: marketing identifies a target account list. Sales does not trust the list. CS is not informed about the accounts being targeted. Intent data signals are sitting in a marketing tool that sales has never seen. The ABM programme produces content and ads. Nothing converts because the handoffs do not work.
The ABM programmes producing the best results in 2026 are built on RevOps foundations: a unified account list governed by RevOps, an AI-powered scoring model that marketing and sales both trust, intent data feeding directly into CRM account records that CS can also see, and a shared ABM performance dashboard that all three teams review weekly.
At The Smarketers, India’s first ITSMA-awarded ABM agency and HubSpot Gold Partner, every ABM programme we implement in 2026 starts with a RevOps readiness assessment. If the data foundation and team alignment are not there, the ABM tactics will not produce predictable results, no matter how sophisticated the intent data or how good the creative. We have seen this pattern consistently across 40+ B2B ABM implementations.
The Future of RevOps: What Comes Next
RevOps in 2026 is already dramatically different from RevOps in 2022. Here is where the most forward-thinking B2B organisations are heading over the next two to three years.
AI Agents as Standard GTM Infrastructure
Gartner predicts AI agents will command $15 trillion in B2B purchasing decisions by 2028. For RevOps, this means that by 2028, a significant portion of lead qualification, deal progression, renewal management, and expansion outreach will be executed by AI agents operating within RevOps-governed frameworks. The organisations investing in AI governance and clean data now will have a structural advantage when this shift accelerates.
Unified Revenue Data Platforms
The trend toward fewer, more powerful platforms is accelerating. The Salesloft-Clari merger in December 2025 is one signal. Expect more consolidation as the market recognises that the value of AI comes from intelligence flowing across a connected system, not from individual AI features in isolated tools. By 2027, the concept of a ‘revenue operating system,’ one platform that natively combines CRM intelligence, forecasting, conversation analytics, CS health, and AI orchestration, will move from aspiration to mainstream.
Data Governance as Strategic Advantage
The data governance market is on track to triple by 2032. The organisations that treat data governance as infrastructure investment, not a cleanup project,t will see compounding AI returns while competitors struggle with unreliable outputs. RevOps will increasingly own this function at the board level, with data integrity scores reported alongside financial metrics.
RevOps as the Conscience of the Revenue Engine
Perhaps the most interesting evolution in 2026 is cultural. RevOps is moving from being the team that keeps the CRM clean to being what ORM Technologies calls ‘the strategic conscience’ of the revenue organisation, guiding leadership decisions with data, flagging when AI recommendations should be questioned, and ensuring that efficiency metrics do not come at the expense of customer experience. This is a significant step up, and the RevOps leaders who make this transition will be the CROs of 2030.
Getting Started: Your Three Actions for This Quarter
RevOps does not have to start as a massive transformation. Here are three things you can do this quarter that will have a measurable impact by the end of the year.
- Run a 48-hour Revenue Process Audit. Get marketing, sales, and CS in one room for a half-day session. Map the current lead-to-revenue process on a whiteboard. Identify the top three gaps where leads get lost, where data breaks down, and where handoffs fail. You will learn more in that session than in six months of dashboard reviews.
- Establish One Shared MQL Definition. A single, agreed definition of a marketing-qualified lead co-authored by both marketing and sales, with clear criteria and an SLA for follow-up, is the highest-ROI process change most B2B organisations can make in 2026. It costs nothing but conversation. The impact shows up within 60 days.
- Score Your Data Before Adding More AI. Before deploying another AI tool in 2026, run a CRM data quality audit. Check completeness on your top 50 open opportunities. How many have a clear next step? A last activity date in the past 14 days? A buying group with two or more contacts? Fix what you find. Then evaluate which AI use cases your data is ready to support.
RevOps is not about perfection. It is about building the systematic capability to improve revenue outcomes predictably, quarter after quarter. Every organisation that has made this investment, regardless of size or stage, has found that the returns compound in ways that purely tactical growth investments never do.
At The Smarketers, we work with B2B organisations across India and globally to build RevOps foundations, implement HubSpot as an integrated RevOps platform, and connect ABM programmes to a governed revenue engine. If you want to talk about where your revenue operations stand in 2026 and what it would take to get to the next level, reach out. We have run this conversation dozens of times, and we can usually identify the highest-leverage action in the first conversation.
