What if your B2B marketing could predict and propel every buying group toward closed-won, rather than chasing leads in the dark?
In today's complex B2B landscape, where Forrester reports average buying groups encompass 13 stakeholders across departments, and 81% of buyers crave longer-term connections beyond single deals, traditional account-based marketing falls short. Opportunity-based marketing (OBM) elevates this by laser-focusing marketing strategies on active opportunities and their stakeholders—decision-makers, influencers, champions, detractors, Executive Sponsors, business users, and more—personalizing outreach based on sales funnel stages like discovery, evaluation, or negotiation[1][2][7].
The Business Imperative: Why OBM Redefines Sales Alignment and Pipeline Revenue
Imagine a college textbook publisher targeting chemistry department and history department buying groups within the same account, or a manufacturing deal spanning contractor, manufacturer, and distributor roles. OBM shines here, analyzing CRM data, engagement history, and intent to deliver personalized outreach and lead nurturing that resonates with each buyer persona's role in the customer lifecycle. This isn't just efficiency—it's reallocating budget to high-intent opportunities, boosting marketing ROI amid 60+ touchpoints across 3.7 channels[1][2].
Salesforce powers this shift through Agentforce Sales and Agentforce Marketing, creating unified data unification across CRM systems, ERP systems, data lakes, data warehouses, and marketing automation tools. The result? A true single view of customer engagement, enabling AI-powered marketing to drive AI-driven propensity-to-buy scores and buyer group heatmaps[1].
Step 1: Harness Relationship Maps for Unrivaled Audience Insight
Start with Agentforce's connected platform, where Relationship Maps in Agentforce Sales reveal stakeholder hierarchies, sentiments, and roles like Decision-Maker or Influencer. Shared dashboards expose customer engagement and propensity scores, letting sales reps time outreach perfectly while marketers prioritize pipeline revenue opportunities. This data 360 harmony eliminates silos, turning raw CRM data into actionable intelligence for deeper trust-building[1][7].
For organizations looking to implement these advanced relationship mapping systems, comprehensive customer success frameworks can provide the foundation for building effective stakeholder engagement processes.
Step 2: Orchestrate Omnichannel Experiences Tailored to Intent
Agentforce Marketing deploys AI agents to craft segments, campaigns, and assets for under-engaged stakeholders. Leverage Data 360 for hyper-relevant personalized outreach—dynamic web experiences, ads, and chats that adapt to real-time intent and organizational role. When readiness signals hit, notifications arm sales reps with contextual records, buyer group heatmaps, and conversion likelihood scores, accelerating handoffs and closed-won velocity[1][3].
Businesses seeking to implement these omnichannel systems can leverage Make.com's automation platform to build scalable workflows that integrate AI-driven marketing operations with existing business processes.
Step 3: Prove Impact with Multi-Touch Attribution and Optimization
The Marketing Cloud Spring '26 Release introduces multi-touch attribution models, unifying CRM and marketing data to quantify influence across intricate journeys—no more stitching disparate systems. AI surfaces natural-language insights on marketing ROI, while paid media optimization autonomously pauses underperformers, freeing teams to scale winners. Track pipeline revenue via custom dashboards, scoring categories, and engagement histories to refine marketing strategies iteratively[1][5].
Thought Leadership Insight: OBM Isn't a Tactic—It's the Evolution of B2B Relevance. As B2B marketing matures, success hinges on coordinating experiences across roles, functions, and stages—not volume of content, but precision in building trust. With Salesforce's Agentforce, Marketing Cloud, and tools like Relationship Maps, you're not scaling activity; you're engineering customer lifecycle loyalty that turns buying groups into enduring advocates. What opportunities in your pipeline are waiting for this precision?
For organizations seeking to navigate this evolving landscape, specialized CRM solutions can help manage the complex stakeholder relationships and data flows that emerge from implementing opportunity-based marketing systems.
By Megan Cohn, December 2, 2025 | 5 min read
What is opportunity-based marketing (OBM)?
OBM focuses marketing effort on active opportunities and the specific buying groups tied to them—targeting decision‑makers, influencers, champions, detractors, executive sponsors and business users—rather than broadly targeting accounts or anonymous leads. Outreach is personalized by buyer role and sales‑funnel stage (discovery, evaluation, negotiation) to accelerate closed‑won outcomes.
How does OBM differ from account‑based marketing (ABM)?
ABM targets specific accounts as a whole; OBM narrows the focus to active opportunities inside those accounts and the multi‑stakeholder buying groups driving each deal. OBM allocates budget and personalization based on intent and pipeline value rather than simply account selection.
What is a buying group and why does it matter?
A buying group is the collection of stakeholders involved in a B2B purchase. Forrester research cited in the piece notes buying groups average roughly 13 stakeholders across functions. Understanding each person's role and influence is critical for crafting the right message and nudging the group toward a decision.
What are Relationship Maps and how do they help OBM?
Relationship Maps (as described for Agentforce Sales) visualize stakeholder hierarchies, roles, and sentiment inside opportunities. They surface who is a decision‑maker, influencer, champion or detractor and help both sales and marketing coordinate timing and messaging for each stakeholder in the buying group.
How does data unification enable OBM?
Unifying CRM, ERP, data lakes/warehouses and marketing automation (a "Data 360" approach) creates a single view of customer engagement. That consolidated data lets AI derive propensity‑to‑buy scores, buyer‑group heatmaps and contextual signals so teams can prioritize high‑intent opportunities and personalize outreach effectively.
What role does AI play in OBM?
AI agents and models create segments, predict propensity to buy, surface intent signals, generate dynamic assets, and produce natural‑language insights on marketing ROI. These capabilities power automated orchestration (e.g., personalized web, ads, chat) and help optimize which campaigns to scale or pause.
How do you personalize omnichannel experiences by intent and role?
By combining relationship and propensity data with real‑time signals, marketing systems can serve dynamic web experiences, tailored ads, emails and chat flows that reflect a stakeholder's role and current stage. Notifications and contextual records then arm sales reps for timely, role‑specific handoffs.
Which KPIs prove OBM is working?
Common KPIs include pipeline revenue influenced, closed‑won rate and velocity, conversion rates by buying‑group stage, marketing ROI, engagement depth across stakeholders, changes in propensity scores, and performance reported through multi‑touch attribution models.
How does multi‑touch attribution support OBM?
Multi‑touch attribution (as in Marketing Cloud Spring '26) unifies CRM and marketing interactions to quantify the influence of each touch across complex, multi‑person journeys. That clarity enables marketers to reallocate spend to the channels and creative that move buying groups toward closed‑won.
What are the practical first steps for implementing OBM?
Start by mapping buying‑group relationships in your CRM, unify key data sources, define role‑based segments and intent signals, deploy omnichannel journeys for under‑engaged stakeholders, implement AI scoring and heatmaps, and set multi‑touch attribution to measure impact. Organizations can leverage comprehensive customer success frameworks to align sales and marketing around shared dashboards and ownership of pipeline revenue.
What common challenges should organizations prepare for?
Key challenges include data quality and silos, unclear stakeholder ownership, privacy and compliance constraints, change management across sales and marketing, and the need for repeatable playbooks. Address these with executive sponsorship, clear processes, and incremental pilots that prove value.
Do you need specific platforms to run OBM?
OBM requires tools that support data unification, relationship mapping, AI scoring and omnichannel orchestration. The article highlights Salesforce's Agentforce Sales and Agentforce Marketing plus Marketing Cloud features as an example, but equivalent capabilities can be built with other platforms that integrate CRM, analytics and marketing automation. Teams can leverage Make.com's automation platform to build scalable workflows that integrate AI-driven marketing operations with existing business processes.
How do you scale OBM across multiple opportunities and teams?
Scale by automating repeatable workflows, surfacing shared dashboards and buyer‑group heatmaps, codifying playbooks per industry/role/stage, continuously optimizing using attribution and propensity insights, and embedding cross‑functional routines for handoffs between marketing and sales. For organizations seeking to navigate this evolving landscape, specialized CRM solutions can help manage the complex stakeholder relationships and data flows that emerge from implementing opportunity-based marketing systems.
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