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Senior Web Developer and AI Solutions Architect
Builds the sites, tracking and AI workflows behind client programs, from headless architecture to Claude implementations.
Put AI to work in how your revenue team actually operates
In short
PlanConversion helps enterprise marketing and revenue teams adopt AI where it pays off. We map the processes behind campaigns, content, reporting and lead handling, find the steps AI and automation should own, build governed Claude agents and workflows connected to your systems, train the team, and measure cycle time, hours returned and adoption.
Measured by: Cycle time, hours returned and adoption by team
Last updated
Clients
The problem
What usually goes wrong
AI use is scattered
Individuals experiment with prompts, but nothing is shared, governed or connected to real workflows.
Processes are slow and manual
Briefs, approvals, reporting and lead handling pass through too many hands and spreadsheets.
Leadership cannot see the return
There is no baseline, so nobody can show what AI changed in speed, cost or output.
Our approach
How we run it
Every step is reviewed with your team, and every result is reported from your CRM.
Map the work
Document how campaigns, content, reporting and lead handling run today, with time and handoffs per step.
Prioritize
Score each step on volume, effort, risk and data access to find where AI and automation pay off first.
Build and integrate
Ship Claude agents, skills and automated workflows connected to your CRM, MAP, docs and analytics, with approval steps.
Adopt and measure
Train teams, set usage norms and governance, and report cycle time, hours returned and adoption monthly.
Deliverables
What you get
Process and readiness assessment
Current-state process maps, data and tool audit, risk review and a prioritized AI roadmap.
Agents and automations
Claude agents and workflows for briefs, research, content QA, reporting narratives and lead follow-up.
Governance
Approved data sources, human review points, usage policies and claim controls.
Enablement
Role-based training, playbooks, office hours and an adoption dashboard.
A good fit when you have
- Marketing or revenue teams with repeatable, high-volume work
- Leadership that wants measurable time and cost savings
- A CRM and content stack AI can connect to
- IT and legal willing to agree data and review rules
Your stack
We work in the tools your team already runs
Browse the platforms we operate by job. Logos name the tools we work in. They belong to their owners and do not imply endorsement.
Account selection, intent, advertising and sales alerts, run weekly.
- DemandbaseOfficial partner
- 6sense
- ZoomInfo
- Bombora
- G2
The system of record every program is measured in.
- Salesforce
- HubSpot
- Marketo
- Pardot
- Eloqua
- Dynamics 365
One paid plan across channels, optimized against pipeline.
- Google Ads
- Microsoft Advertising
- Meta Ads
- YouTube
- Reddit Ads
Tracking, attribution and reporting you can defend to management.
- GA4
- Tag Manager
- Looker
- Tableau
- Power BI
- Snowflake
- BigQuery
- Segment
Testing, behavior analytics and web builds for conversion.
- Optimizely
- VWO
- Hotjar
- Clarity
- Webflow
- WordPress
- Contentful
- Figma
Claude, AI search visibility and the tools that measure it.
- Claude
- ChatGPT
- Gemini
- Perplexity
- Copilot
- Search Console
- Semrush
- Ahrefs
PlanConversion went beyond flagging a misfiring tracking tag. They brought the fix and a forward-looking testing plan to keep our tracking reliable.
Pipeline quality and win rates improved within a quarter. We finally had one connected demand engine with shared metrics.
Your team
Who runs your ai adoption and process optimization program
Founder and Director of Revenue Growth Strategy
Leads strategy on every engagement. Former enterprise marketing leader at Coveo, Assent and Nakisa with 20+ years in B2B demand generation.
LinkedInDirector of Marketing Operations and Automation
Owns marketing operations: CRM structure, lifecycle stages, routing, scoring and the attribution that connects spend to pipeline.
Insights
Read before you decide
AI adoption for enterprise marketing teams: a 90-day plan that sticks
A practical 90-day plan for moving an enterprise marketing team from scattered AI experiments to governed, measured AI workflows.
Marketing process optimization: finding where AI and automation actually save time
How to map marketing and revenue processes, score each step for automation, and decide where AI agents, rules-based automation or people should do the work.
FAQ
AI adoption and process optimization: common questions
Related services
What is AI adoption for a marketing team?
Moving from scattered individual AI use to shared, governed workflows where AI handles defined steps (research, drafting, QA, reporting) inside the processes your team already runs, with clear review points.
Which processes should we automate first?
High-volume, rules-based steps with clear inputs: campaign briefs, account research, content QA, weekly reporting summaries and lead follow-up drafts. Start with two or three and measure before expanding.
How do you measure the return on AI adoption?
Against a baseline set before rollout: cycle time per process, hours returned per role, output volume, first-pass approval rate and adoption by team.
How is this different from Claude implementation?
Claude implementation sets up the knowledge, agents and skills. AI adoption and process optimization starts with how work flows across the team, redesigns the process, and then applies AI and automation where it changes speed and cost.