📍Non-Profit Sector | Jan 2025 – Mar 2025
Designed best-practice solution architecture to enhance donor retention and optimize engagement journeys.

Mapped the customer/donor journey across GTM teams, aligning operations and design frameworks to improve campaign performance.

📍Property Tech | Aug 2024 – Nov 2024
Led end-to-end HubSpot CRM implementation, ensuring accurate data migration and optimized system architecture.

Developed cross-functional RevOps frameworks aligning Sales and Marketing, boosting lead conversion efficiency.

Implemented and streamlined HubSpot CMS, improving content delivery and campaign scalability.

Delivered data-informed process improvements, increasing operational efficiency and executive-level insights.

Flywheel AI | Fractional Consultant and Freelancer(RevOps)

Auckland Business Chamber

•Automated resume-building services that supported Employment Programmes across New Zealand. The solution reduced resume building time from 20 minutes to 2 minutes.
•Led comprehensive project lifecycles from initial research and design to rigorous testing, seamless implementation, and meticulous documentation, ensuring precision and attention to detail.
•Customized and optimized the HubSpot platform to meet specific business needs, enhancing capabilities through custom integrations, automations, and sequences that streamlined workflows and significantly boosted operational efficiency.
•Improved Go-To-Market strategy by cleaning and organizing data adhering to privacy laws and boosting email deliverability using Hubspot. 
•Implemented robust analytics practices, continuously monitoring and improving performance metrics to drive growth and success.
•Collaborated effectively across teams and organizational levels, fostering cohesive efforts to achieve common goals and deliver impactful project outcomes.
•Lead the digital transformation project for Bay of Plenty and Hawke's Bay transforming their CRM system to a digital solution.

Data and Automation Specialist

Woop

- Implemented Woop's operations through automation by curating automated recipe cards, saving 50% of organizational time.
- Engineered an ingenious workflow that automates the recipe card curation process, enhancing productivity and accuracy.
- Implemented automated dashboarding for the Operations department, providing stakeholders with real-time insights into labor costs, cost per meal, and more.

Sales Operations & Automation Strategist | Fractional Consultant

RevPartners - Elite RevOps HubSpot Partner

RevOps Strategist 

Proposition

Solution Architect.

Systems Design and Implementation

Few of my responsibilites is as follows
1. Build RevOps strategy for scale-ups and SMB's
2. Hubspot Enterprise, Professional Implementation for sales and marketing
3. Hubspot onboarding/training
4. CRM data migration to Hubspot
5. Low code/No-code integration
6. CMS / Landing page builds
7. Complex Hubspot Workflows.
8. Data cleansing and migrations
9 Integrations between Hubspot and third-party apps like Shopify, Webflow, WordPress, Airtable, Zendesk, 9. Xero, Eventbrite, Webinar software, Salesforce, Slack, Stripe and more.
10. Business Intelligence and Analytics

RevOps Lead 

Building data architecture and analytics framework along with dashboarding solutions contracting for 2Degrees (telecom), AKQA (part of WPP) and Proposition (Agency).

The wide range of problem solving tools comprised of -
Martech and Web Analytics: Unica, Hubspot, Google Analytics
Analytics: SQL
Dashboarding: Google Data Studio, Databox

Media and Marketing Analyst

Stats NZ

The housing demand in New Zealand is constantly growing and there has been a lot of concern about the adequate supply of houses for a number of people. The aim of the research was to examine which statistical model correctly estimates time to completion of a dwelling.
Time to Event Analysis was adopted using Kaplan Meier curve, the trajectory to define time to completion of a dwelling. 
Probability of completion to any point was estimated from cumulative probability of completion of the preceding time intervals.
Kaplan-Meier analysis facilitated the understanding of time to completion across different time lengths considering both completed as well as cancelled dwellings.
A transition probability matrix was then created based on the consented and the completion dwellings on quarterly basis. This aggregated matrix helped in forecasting the approximate time to completion for the dwellings consented recently.

Data Research Analyst Intern - Accomodation, Building and Consent

Engineyaars (Educational startup)

• Founder and Curator at Engineyaars.
• Web development using front end frameworks like html, CSS.
• Develop ideas, research and generate topic wise content.

An Educational Startup catering to Engineering students (Peer to Peer Learning Platform)

Revenue and data automation at an intersection of AdTech and Martech. I have been working for brands across E-commerce, Automotive, Finance and FMCG sectors providing business intelligence and analytics solutions helping them attain maximum ROI on their marketing budgets.

BI solutions: Datorama, Domo, Data Studio, Tableau, Power BI and honorable MS excel

Adtech (Analytics and tracking): Google Analytics, Google Tag Manager, DV360, Google Ads, Facebook, Mediamath, TTD, Zedo (Publisher side).

Martech: Hubspot (Certified), Mailchimp 

Open Source Analytics/Data Wrangling: R, SQL, Google BigQuery

Skilled in Data Analysis, Visualisation and Predictive Analytics. Passionate about Data and problem-solving. 

Hiking, reading or gigs over the weekend.

I learned data science from strangers on the internet. Stack Overflow was my classroom. 

No bootcamp. No formal training. Just curiosity, broken code, and people who took the time to help. Someone always had the answer. Real peers. Real problems. Real respect.

I faced challenges like:
- pip install pandas AttributeError: 'DataFrame' object has no attribute 'append' 
- merge vs join on Stack Overflow, which has 47 answers where one stranger saved my weekend.

This was my routine for years, from 2016 to 2020. That circled section in the graph? That's me.

Then, things began to change. Not because I stopped building, but because the questions evolved. I found myself in situations like:
- cd into-the-unknown 
- npm run figure-it-out 

The age of peer evaluation is quietly ending. Agentic systems are now solving agentic problems. 

It's a different era, but my love for building remains the same. I am grateful for every stranger who answered at 2 am. 
You know who you are. 🫡

#RevOps #DataScience

Pratik Mehta

From Revenue Guesswork to Growth Certainty | Revenue Operations | GTM Engineering | Data-Driven B2B SaaS Consultant

Over the last year, I’ve been inside multiple builds where companies were experimenting with AI.

The tools weren’t the problem.

The system was.
-Disconnected lifecycle stages.
-Undocumented automation logic.
-Legacy workflows no one fully understands.
-“Temporary” processes that became permanent.

Then we expect AI agents to sit on top and make autonomous decisions.

That’s not an AI capability issue.
That’s a decision infrastructure issue.

In one project, before automating anything, we did something uncomfortable:

We audited every workflow.
Deleted what didn’t make sense.
Forced teams to write down actual decision logic.

We killed more than we automated.

That changed everything.

AI doesn’t create clarity.
It amplifies whatever already exists.

If your system is clean, it compounds leverage.
If your system is messy, it compounds chaos.

The companies seeing real value from AI aren’t the ones with the most pilots.

They’re the ones willing to confront their decision debt first.

taplio

Pratik Mehta's Linkedin Analytics

Pratik Mehta

Performance ScorePratik Mehta's LinkedIn Performance

Pratik Mehta's Best Posts (last 30 days)

Ready to grow your LinkedIn presence?

taplio

.css-6ytdur{background-image:linear-gradient(284deg, rgba(39, 43, 72, 1) 0%, rgba(33, 47, 183, 1) 100%);color:transparent;-webkit-background-clip:text;background-clip:text;}Pratik Mehta's Linkedin Analytics

Pratik Mehta

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Pratik Mehta's LinkedIn Performance

Pratik Mehta's Best Posts .css-1emoo84{font-size:var(--chakra-fontSizes-md);font-weight:400;color:var(--chakra-colors-gray-600);}(last 30 days)

Ready to grow your LinkedIn presence?

Pratik Mehta's Linkedin Analytics

Performance ScorePratik Mehta's LinkedIn Performance

Pratik Mehta's Best Posts (last 30 days)