Blog Posts:
How Do I Prove Marketing’s Revenue Impact When All My Data is Imperfect? [Blog]
What happens when your revenue data isn’t perfect, but you still need to demonstrate marketing’s impact? This article provides a practical framework for proving marketing’s contribution to revenue even when data completeness and quality are challenges most RevOps teams face.
The piece highlights:
- Ways to work with imperfect data and still extract meaningful signals
- Techniques for aligning marketing metrics with business outcomes
- Why choosing pragmatic models and setting measurement guardrails matters
Readers will find strategies to make better decisions and tell a stronger data story without waiting for flawless systems. Read the full article here
The 10 Best Amazon Connect Alternatives & Competitors [Blog]
By: Revenue.io
What if your contact center solution could be simpler, more integrated or better aligned with your go-to-market systems? This article reviews Amazon Connect and its alternatives to help teams identify platforms that fit their current needs and future growth plans.
The review covers:
- Key differences between Amazon Connect and competing solutions
- Features that matter for sales, service and RevOps teams
- Considerations for scalability, integrations and operational efficiency
Readers will get a clear comparison to help guide decisions when evaluating contact center tools in a complex technology stack. Explore the alternatives here.
The Guide to Account-Based Marketing for Revenue Operations [Blog]
What’s involved in moving from one major marketing automation platform to another? This guide outlines the full migration process from Marketo to HubSpot, with practical checkpoints to make the transition smoother for RevOps, marketing and ops teams.
The guide walks through:
- Planning and scoping the migration project
- Mapping data, workflows and integrations between systems
- Validating results and maintaining continuity during the cut-over
Readers gain a clear picture of what to expect and how to avoid common migration pitfalls. Read the step-by-step guide here
Podcast Episodes:
VC 2: How Cassie Young Picks Winners Before They Even Leave Their Jobs [Podcast]
What if early signals could predict which startups will succeed? In this conversation, Cassie Young shares how she identifies promising companies and founders before they hit mass recognition, blending pattern recognition with real-world investment experience.
The discussion explores:
- Early indicators that separate strong teams from the rest
- How to evaluate product, market and execution signals simultaneously
- The mindset investors use to anticipate future winners
Listeners gain insights into decision-making approaches that can apply beyond venture capital, including how RevOps and GTM teams might spot trends before they scale.
Listen to the full episode here.
A CMO’s Guide to Working with the Board [Podcast]
How can marketing leaders build trust and credibility with their board of directors? This episode offers practical advice for CMOs on communicating strategy, metrics and risk in a way that resonates with board expectations, especially during periods of growth or transformation.
The conversation touches on:
- Which metrics boards care about most and why
- How to frame marketing impact in revenue-centric terms
- Best practices for transparent, strategic board conversations
Listeners come away with a better sense of how marketing and RevOps can align with executive leadership to drive business outcomes. Explore the full discussion here.
Metrics, Community Insights & AI Strategy [Podcast]
By: RevOps Lab
What can RevOps teams learn from a year of experimentation, metrics and community interaction? This episode recaps key takeaways from 2025, emphasizing what growth signals mattered most, where teams found traction, and how community insights shaped best practices.
The episode highlights:
- Growth metrics that stood out for high-performance teams
- Operational lessons from real RevOps practitioners
- How community feedback influenced evolving approaches to revenue operations
Listeners gain a practical snapshot of trends, benchmarks and tactical lessons to carry into upcoming quarters. Listen to the recap here.
Webinars:
AI + Account Data: the Use Cases Ops Can’t Ignore [Webinar]
By: RevOps Co-op ft. Traction Complete
What does it look like when AI moves from experimentation into real operational value? This webinar explores practical use cases where AI enhances account strategies and data operations, helping revenue teams extract insight and drive performance.
The session examines:
- How AI can uncover patterns in account data that humans might miss
- Real implementations where AI accelerates pipeline analysis and segmentation
- Ways teams operationalize AI insights into playbooks and execution flows
Attendees walk away with concrete examples of how AI is being applied today inside RevOps teams. Register here to save your spot.
Aggressive Revenue Targets. Flat Headcount. How to Operate in The 2026 Reality [Webinar]
By: RevOps Co-op
What will operating models look like as revenue teams move toward 2026? This webinar focuses on how RevOps leaders can adapt to evolving buyer behavior, AI adoption and growing operational complexity while maintaining execution clarity.
The discussion centers on:
- Shifts in GTM operating models and team structures
- Strategic priorities for RevOps as AI and data become core inputs
- How to align teams around outcomes that matter in the next phase of growth
Viewers gain a forward-looking perspective on how to prepare their organizations for what’s coming next. Save your spot and register here.
Execution Lessons for Modern RevOps Teams
This week’s curated content centers on practical execution. From working with imperfect data and attribution to platform decisions and AI-ready operating models, the focus is on building RevOps systems that support clarity, efficiency and scale.
RevOps teams can apply these insights to make better technology choices, strengthen data foundations and operate with confidence as AI becomes part of everyday workflows.
