Consulting

Better reporting. Faster follow-up. Less manual work.

I help marketing and sales teams improve reporting, lead scoring, routing and everyday workflows. Where AI is useful, I help put it into practice.

Let's talk

When reporting and follow-up take too much work.

Marketing and sales may be working from different numbers. Leads might sit in an inbox before someone responds. Reporting can take hours because the data lives in several places.

I help teams work through those gaps: agree on definitions, connect the relevant tools and improve how information moves between people.

What I do

Reporting and attribution

Review how performance is measured, align definitions and build reporting that helps teams make decisions. Combine tracked sources with customer-reported discovery where useful.

Shared definitions for pipeline and revenue, agreed before the dashboard gets built.
Self-reported attribution: asking customers how they heard about you, and using the answer.
AI referrals: track identifiable AI referrals and supplement them with self-reported discovery. Make the limits of attribution clear.

Lead scoring and routing

Define useful qualification signals, assign leads to the right people and reduce delays in follow-up.

Fit and intent signals that reflect how people actually arrive.
Measure response times and reduce avoidable delays.
Routing that sends each lead to the right person or sequence automatically.

CRM and workflow automation

Connect tools, improve data capture and automate repeatable steps between marketing and sales. (Some people call this GTM engineering, the technical side of go-to-market.)

CRM and marketing automation set up to match how you sell.
Enrichment that fills in what forms don't ask.

AI workflows and internal tools

Identify repetitive work, build a practical workflow or prototype, and define where people review the output.

Review: what a workflow can do on its own, and what a person checks first.
Logging: a record of what ran and what it produced.
Measurement: time saved, output quality, and adoption by the team.

What the work usually includes

It usually starts with a 30-minute conversation. From there, the work tends to include:

Map the current process
Understand the tools, data, people and repeated work involved.
Build and test
Implement the agreed improvements with your team.
Document and hand over
Instructions, training and clear ownership.

Questions people ask

What kinds of workflows can you help with?

Reporting, lead routing and follow-up, CRM data capture and enrichment, and repeated tasks like research, ad analysis or content operations that AI can take on with a person reviewing the output.

Which tools can you work with?

HubSpot, Salesforce, GA4, Looker or Domo, Zapier or n8n, Claude and Gemini. The right stack is the one your team will actually use.

Can you improve our existing setup?

Usually that's where it starts. Improving how your current tools work together tends to beat adding another one.

How do you measure whether an AI workflow is useful?

Against the work it replaces: hours saved, turnaround time, error rates and, where it applies, revenue influenced. If a workflow isn't saving time after a few weeks, we change it or stop using it.

What ongoing support is available?

That depends on what your team needs. Some teams want a few hours a month after the handover; others want a review every quarter. We'll agree on it in the scope.

Have a process your team is tired of working around?

Tell me how it works today and where it slows people down.