clarity starts at row-j

A week of discovery, then a week on site building with your team in workshops: the account set up and managed, the team trained, and the first workflows and projects live.

2 weeks

• Set up an enterprise AI account and train the whole team on it together.
• Build a team's first workflows and projects in on-site workshops.

A scored report on how you use your systems, a roadmap, and a readout.

3 or 4 weeks

• Score your systems on how you use them, then build the plan to transform.
• Create a marketing plan that drives more sales and finds the right customers.

Requirements, the RFP, scoring, contract review, and a launch window, or a running program system in your own tools.

6 to 8 weeks

• Run a CRM selection: requirements, demos, scoring, contract terms, launch window.
• Set up the roadmap, sprint board, and meeting rhythm for a platform transition.

A program plan, an independent review of the vendor's work, a risk log, launch readiness, and a clean handoff.

3 to 6 months

• Advise a CRM program from build to launch, with an independent review of the vendor's work.
• Land a CRM rollout with a guide the sales team actually uses.

One named project: the strategy and the tool that runs it, handed to an owner on your team.

4 to 8 weeks per tool

• A game-by-game pricing model the ticketing team can update.
• A reporting layer on the club's own data, handed to the team to run.

A standing working session and access between sessions.

Monthly, three-month minimum

• A weekly session with a new head of analytics through the first 90 days.
• A standing session with a strategy and analytics lead through a platform change.

• A CRM usage guide and a five-stage sales pipeline
• Pipeline reporting in Tableau: rep leaderboard, pacing, campaigns, and overdue deals
• Ticketing platform vendor management: releases, bugs, and the issue log
• A ticket sales operations roadmap the team runs
• Strategy and execution support for a marquee record-setting event

• A diagnostic across sales, marketing, analytics, and technology, with a phased roadmap
• The transformation roadmap and tracker across CRM, the data warehouse, ticketing, marketing automation, and partnerships
• An independent review of the implementation vendor's work
• A launch-readiness review: data model, pipeline, account structure, integrations
• Advice on AI tools for the data and CRM teams
• A written risk log raised ahead of each decision
• Knowledge transfer so the team runs it after

• A review of digital spend by channel, campaign, vendor, and attribution across every property
• One playbook with local adaptations: paid media, email, social, planning templates, benchmarks, and tracking conventions
• Advice on vendors, agencies, and tools

• A read of the data: sales against listings, comparable seats, and outliers
• A model in Python that returns a volume price and a revenue price inside a range
• Run and method notes so the vendor's engineers can extend it