01
Your systems disagree
CRM says one thing. Finance says another. Marketing reports something else.
I create one reliable source of truth.
- Ad platforms
- 1,431
- CRM
- 1,284
- Finance
- 1,190
Data Engineering · Analytics · Automation
Taking on new work.
I connect the systemsbehind your business.
From data collection and CRM integration to cloud warehouses, automated workflows and executive dashboards, I design and build end-to-end solutions that turn complex business data into measurable results.
One customer. Seven systems. Nine days.
End-to-end data services, across your existing stack.
Grouped by where each one sits in the chain.
CRM
- Salesforce
- GoHighLevel
- HubSpot
- Pipedrive
Acquisition
- Google Ads
- Meta Ads
- LinkedIn Ads
Analytics
- GA4
- PostHog
Calls
- Aircall
Payments
- Stripe
- Chargebee
Warehouse
- BigQuery
- Supabase
- PostgreSQL
Reporting
- Power BI
- Looker Studio
- Apache Superset
- Custom Dashboards
Automation
- n8n
- Apps Script
- Python
- Webhooks
Business data should create value.
Not more manual work.
Problems I fix
The biggest issues usually happen between systems, teams and reporting processes.
Leads, last month - 02
Reporting is still manual
Teams export files, update spreadsheets, reconcile numbers and rebuild the same reports every week.
I automate the workflow.
One reporting cycle - Mon 09:00
- Export 6 files
- Mon 15:00
- Reconcile by hand
- Wed 11:00
- Report finally out
- 03
Revenue cannot be explained
You know how much revenue came in, but cannot confidently explain which activity generated it.
I connect marketing and sales activity to revenue.
Closed revenue, by source - Attributed
- 38%
- Partial / guessed
- 24%
- Unknown
- 38%
- 04
Opportunities disappear between systems
Leads, calls, follow-ups and customer activity exist, but nobody sees the full journey.
I connect the customer journey.
Inbound leads, one quarter - Received
- 2,140
- Contacted
- 1,655
- Never contacted
- 485
Selected outcomes
Three of 12 · names withheld
Three of the problems I have been brought in to solve. Client names are withheld, so each is identified by sector.
Case 01Replacing Paid Data ConnectorsInternational training and subscription business
~$10ksaved annually
Problem
Recurring third-party connector fees added cost to reporting across Salesforce and multiple advertising platforms.
What changed
Built and maintained direct API integrations using Google Apps Script to retrieve and standardise data from Salesforce, Meta Ads, Google Ads and LinkedIn Ads, reducing dependency on paid extraction tools such as Supermetrics.
Outcome
Replaced recurring connector subscriptions with owned, maintainable data pipelines, saving approximately $10,000 per year while keeping the reporting data available.
- Google Apps Script
- Salesforce
- Meta Ads
- Google Ads
- LinkedIn Ads
| Source | Customer | Campaign | Revenue |
|---|---|---|---|
| Salesforce | feeds Customer | feeds Campaign | does not feed Revenue |
| HubSpot | feeds Customer | feeds Campaign | does not feed Revenue |
| GoHighLevel | feeds Customer | feeds Campaign | does not feed Revenue |
| Google Ads | does not feed Customer | feeds Campaign | does not feed Revenue |
| Meta Ads | does not feed Customer | feeds Campaign | does not feed Revenue |
| GA4 | does not feed Customer | feeds Campaign | does not feed Revenue |
| Stripe | feeds Customer | does not feed Campaign | feeds Revenue |
| Chargebee | feeds Customer | does not feed Campaign | feeds Revenue |
| Xero | does not feed Customer | does not feed Campaign | feeds Revenue |
Brand is a column on every one of them, not a separate report.
- ~$10k
- Annual connector savings
- 4
- Major platforms integrated
- Direct API
- Instead of paid connectors
Case 02Moving High-Volume Automation to n8nInternational training and subscription business
~200kZapier tasks migrated
Problem
Growing task volume on Zapier increased reliance on usage-based automation fees and made workflow costs harder to control.
What changed
Rebuilt existing Zapier flows in self-hosted n8n, retaining integrations and business logic while bringing execution and infrastructure under direct control.
Outcome
Migrated workflows representing approximately 200,000 Zapier task executions, reducing exposure to per-task charges. A specific annual dollar saving has not been independently established.
- n8n
- Zapier
- APIs
- Webhooks
SpendRevenue attributed
Google Ads
Meta Ads
LinkedIn Ads
Organic / direct
Same spend, redistributed. The channel with the largest budget was not the channel producing the revenue.
- ~200k
- Task executions migrated
- Self-hosted
- n8n automation
- Lower
- Usage-based fee exposure
Case 03Reporting AutomationMulti-channel training provider
30 hrs → 2 hrsper week
Problem
A recurring management reporting process relied on manual exports from five platforms, spreadsheet updates, data checks and repeated reconciliation. By the time the numbers were agreed, the week they described was already over.
What changed
The workflow was rebuilt around scheduled data pipelines, a modelled reporting layer with agreed KPI definitions, automated validation rules and alerting when a source stops delivering.
Outcome
Reporting preparation dropped from roughly 30 hours per week to around 2 hours of review and validation. Numbers now arrive before the meeting instead of after it.
- BigQuery
- n8n
- Power BI
- Google Ads
- Meta Ads
- Stripe
- 93%
- Less manual preparation
- 6
- Sources consolidated
- Daily
- Refresh instead of weekly
Case 04360° Lead & Sales IntelligenceSubscription business with an outbound sales team
One customer.One view.
Problem
CRM records, call activity, marketing source data and payment history lived in four systems. Nobody could answer a simple question — what actually happened with this customer — without opening four tabs and guessing.
What changed
Lead, call, opportunity and payment signals were resolved to a single customer identity, cleaned of duplicates, and combined into one unified view with follow-up quality and pipeline movement made visible.
Outcome
Sales teams and management gained one clear picture of customer activity, follow-up and opportunity status — including the leads that had never been contacted at all.
- Salesforce
- Aircall
- GoHighLevel
- Chargebee
- PostgreSQL
Sources joined
4
To first call
11 min
Record status
Complete
- META ADSClicked campaign · Q3 Webinar
- GOHIGHLEVELForm submitted · 14:02
- SALESFORCELead assigned · owner set
- AIRCALLOutbound call · 4m 12s · connected
- SALESFORCEOpportunity created · £14,400
- CHARGEBEESubscription active · annual
- 4 → 1
- Systems to check
- 100%
- Calls matched to CRM records
- Visible
- Follow-up quality per rep
Case 05Revenue AttributionPaid-acquisition-led business, multiple markets
Marketing → Revenueend to end
Problem
Marketing spend, lead activity and closed revenue were held in separate systems with inconsistent campaign naming. Channel performance was argued about monthly and never settled.
What changed
Campaign, lead, opportunity and payment data were connected through one attribution model, with enforced naming standards, validated tracking and revenue joined back to the original acquisition source.
Outcome
Management could finally see which channels and campaigns were contributing revenue rather than volume — and move budget on evidence instead of opinion.
- Google Ads
- Meta Ads
- LinkedIn Ads
- GA4
- BigQuery
- Stripe
SpendRevenue attributed
Google Ads
Meta Ads
LinkedIn Ads
Organic / direct
Same spend, redistributed. The channel with the largest budget was not the channel producing the revenue.
- Spend → £
- Joined at customer level
- 3
- Ad platforms reconciled
- CAC / ROAS
- Reported on real revenue
Positioning
From raw data to business decisions.
I own the full journey.
My work spans data engineering, business intelligence, revenue operations and automation, from the first API connection to the decisions made from the final dashboard.
I bring these disciplines together into one accountable, end-to-end delivery.
A paid media agency
Ad platforms, campaigns, budget, creative
SeamCampaign data lands in the CRM with the source stripped out.
A CRM consultant
Objects, fields, pipelines, automation rules
SeamA pipeline stage means one thing to sales and another to the model.
A RevOps hire
Process, stages, forecasting, sales discipline
SeamThe dashboard reports revenue nobody can trace back to a campaign.
A BI contractor
Dashboards, models, definitions, reporting
What I can own
Most engagements start in one row and end up touching all three.
Connect
Build reliable data foundations across CRM, advertising, payments and operations.
- APIs and webhooksCRM integrationsETL / ELT pipelinesBigQuery and cloud data warehousesCRM data qualityHistorical CRM data and archivingPayment integrationsMarketing platform integrations
Understand
Model the data, define meaningful KPIs and make performance visible to every team.
- Power BI, Looker Studio and SupersetRevenue attributionLead-to-revenue reportingMarketing analyticsCustomer journey analysisSales reportingExecutive and custom web dashboardsFunnel analytics
Automate
Replace expensive manual processes and disconnected tools with scalable automation.
- Self-hosted n8n and Zapier migrationCRM automationAI workflowsData validationAlerts and monitoringReporting automationLead routing
From source data
to actionable business outcomes.
Sources
- Google Ads
- Meta Ads
- Salesforce
- GoHighLevel
- Aircall
- Stripe
- GA4
Data layer
Ingestion, ETL/ELT, BigQuery, historical storage, validation and modelled data.
Business logic
Consistent KPI definitions, customer identity, revenue attribution and sales logic.
Dashboard
- Executive view
- Marketing performance
- Sales performance
- Revenue attribution
Automation
- Lead routing
- Follow-up triggers
- Data validation alerts
- Anomaly detection
I cover the full lifecycle: collect, validate, store, transform, model, visualise and automate. The result is dependable data that supports faster decisions and better operations.
How I work
From discovery and data architecture to implementation, reporting and ongoing optimisation.
- 01
Diagnose
Understand what is broken, unclear, duplicated or unnecessarily manual.
Ends withA written map of your systems, data gaps and the cost of each one.
- 02
Design
Define the simplest architecture that solves the actual business problem.
Ends withAn architecture and KPI definition your team agrees with before build.
- 03
Build
Connect, automate, validate and document the solution.
Ends withA working system, monitored, documented and handed over.
- 04
Improve
Use the resulting data to identify the next opportunity.
Ends withA prioritised shortlist of what is now worth fixing next.
You do not need to manage the technical details. That is part of the job.
End-to-end data expertise. Hands-on delivery.
I am a hands-on data, BI and revenue operations consultant with four years of cross-functional delivery for an international training and subscription business, alongside broader experience building data-driven solutions.
I have worked across Salesforce, GoHighLevel, BigQuery, Power BI, Google and Meta Ads, Stripe, Chargebee, Aircall and n8n, owning the journey from integrations and data quality to executive reporting and operational workflows.
My work has included replacing paid data connectors with Apps Script pipelines, migrating high-volume Zapier automations to self-hosted n8n, building custom dashboards, and improving subscription and marketing performance through clearer customer and revenue data.
- Practice
- Data Engineering & BIMarketing AnalyticsRevenue OperationsCRMAutomationAI WorkflowsEnd-to-End Data Services
- Engagement
- Fixed scope, retainer or implementation + support
- Works with
- Founders, CEOs, COOs, CMOs, Heads of Sales & RevOps
- Availability
- Selected projects, working internationally
Working internationally
What clients say
Attributed by role and sector
01
Commercial Director
B2B training group
We stopped arguing about whose number was right. That sounds small. It changed how the whole leadership meeting runs.
02
Head of Sales
Subscription fintech
The first two weeks were uncomfortable — he showed us leads we had paid for and never contacted. Then he built the thing that makes sure it cannot happen again.
03
Marketing Operations Manager
Multi-brand e-commerce
Monday used to cost me a full day of exports and formatting. Now I spend twenty minutes checking a report that built itself overnight.
04
Chief Operating Officer
Professional services firm
He is the only external person we have worked with who understood the Salesforce side and the finance side well enough to make them agree with each other.
Where I am most useful
I support companies that need a practical partner across the entire data lifecycle, from system integration and data modelling to dashboards, automation and measurable business improvements.
Best fit if you
- You use several SaaS platforms that do not talk to each other
- You have meaningful lead or customer volume
- Your reporting still depends heavily on spreadsheets
- You need better visibility across departments
- You have recurring processes worth automating
- You need reliable marketing-to-revenue reporting
- You need end-to-end data delivery without hiring a full internal team
- Your problem crosses more than one system
Probably not a fit
- A single one-off chart or spreadsheet formula
- Hourly technical support without a defined outcome
- Work that stays inside one tool and one team
From data infrastructure to better commercial decisions.
Need your data to work harder?
I can build the full solution.
Whether you need dependable data pipelines, CRM optimisation, better reporting or automation, I can help design, build and improve the solution from end to end.
hello@mehrdadfashami.comStart with whichever is true
- 01“Our numbers do not match between systems”
- 02“Reporting takes too long every week”
- 03“We cannot explain where revenue comes from”
- 04“Leads are falling through the process”
Taking on new work.