Blog Posts:
The Future Of AI And The Role Of Data In Marketing In 2026 [Blog]
How will AI reshape marketing and RevOps in 2026 without amplifying bad data or weak strategies? This analysis shows why strong data foundations and human oversight remain essential for scalable GTM efficiency.
Key topics covered:
- AI as a multiplier that reveals (not fixes) marketing fundamentals
- Shift from ad-hoc prompts to standardized AI workflows
- Data quality as the real competitive edge (firmographics, signals, connected sources)
- Human judgment and clear ICP/strategy before AI adoption
- RevOps implications: embedding AI across marketing-sales alignment
For practical ways to prepare your marketing and RevOps stack for 2026, read the full article here.
Executive vs. Practitioner AEO Dashboards: What Each Team Should Actually See [Blog]
Why do generic AEO dashboards fail both executives and practitioners in RevOps teams? This guide explains how role-specific dashboards deliver the right visibility for better revenue decisions.
Key differences highlighted:
- Executive view: high-level brand presence, citations, revenue influence (MoM/QoQ trends)
- Practitioner view: granular prompt performance, page-level diagnostics, AI bot signals
- How practitioner data rolls up to executive outcomes
- Linking AEO metrics to pipeline and GTM priorities
- Avoiding noise while keeping reports actionable
To build dashboards that actually serve both teams, check the complete guide here.
How to Build an AI Layer on Top of HubSpot CRM (Without Breaking Your Workflows) [Blog]
Can you add AI intelligence to HubSpot without breaking existing automations or losing data trust? This practical guide shows an event-driven approach that keeps HubSpot as the single source of truth.
Implementation steps covered:
- Using webhooks and APIs for non-invasive triggers
- Middleware for AI tasks (summarization, enrichment, scoring)
- Writing back only to custom fields with confidence thresholds
- Human approval loops and full audit trails
- Common risks and how to avoid data corruption
For a safe way to layer AI on your HubSpot CRM, explore the full guide here.
Podcast Episodes:
Why It's Time to Bury the MQL – With Jon Miller, the Marketo Co-Founder Who Helped Popularize It [Podcast]
Is the MQL model finally dead in modern B2B GTM? Jon Miller (Marketo co-founder) explains why traditional lead scoring and attribution no longer work.
Main discussion points:
- Why the Marketo playbook failed at Demandbase
- Nonlinear buying journeys vs old funnel models
- New CMO dashboard for 2026 including brand ROI
- AI enabling true 1:1 personalization at scale
- Reframing marketing impact with the CFO
To hear why it’s time to retire the MQL, listen to the full episode here.
GTM: Lessons from Figma, Dropbox, and Building Iconic Brands in the Age of AI with Figma’s CMO, Sheila Vashee [Podcast]
What separates iconic brands in the AI era according to Figma’s CMO? This episode extracts real GTM lessons from Dropbox and Figma scaling journeys.
Key lessons shared:
- Brand as “what people say when you’re not in the room”
- PLG-to-enterprise transition tactics
- Staying obsessively close to customers
- AI enhancing (not replacing) human creativity
- Social and GEO as new growth levers
For actionable GTM strategies from real scale-ups, listen to the full episode here.
Why You Should Stop “Doing AI” and Start Solving Problems [Podcast]
Why do 95% of AI initiatives fail in RevOps and GTM teams? This conversation cuts through the hype and focuses on practical problem-solving.
Core advice given:
- Start small with independent use cases
- Top-down vs bottom-up AI adoption
- Data readiness before any AI project
- Real examples in HubSpot (marketing-to-sales handoffs)
- Building AI solutions without being an expert
To turn AI into actual revenue impact, listen to the full episode here.
Webinars:
RevOps Leadership Live: AI for RevOps [Webinar]
Are RevOps leaders ready to move from AI experimentation to quick, practical automations? This live session (March 12) shares 10 real use cases you can deploy in 10 days.
AI applications discussed:
- Streamlining lead routing
- CRM hygiene and automated data cleanup
- Intelligent follow-up triggers
- Forecasting confidence with insights and anomaly detection
- Fast-deploy automations for core revenue processes
To get implementable AI tactics for RevOps leadership, join the live event or access the recording here.
Signals vs Noise: Building the RevOps Decision Gap w Active AI Intelligence [Webinar]
How can RevOps teams cut through data chaos and turn real signals into faster decisions? This session explores active AI intelligence to close the RevOps decision gap.
Key topics covered:
- Differentiating signals from noise in dashboards
- Cost of inaction in data overload
- Building AI-powered decision frameworks
- Practical ways to reduce noise in forecasting and operations
- Active intelligence for revenue teams
To learn how to build smarter RevOps dashboards, watch the full session here.
