I build the systems that make ad spend provably profitable.

Building the systems behind measurable growth

I don’t optimize campaigns in isolation. I work through six pillars in a fixed order, because most wasted spend comes from skipping the first one.

1. 1

   Measurement & Revenue Integrity

   Can I trust the numbers, and do they match real revenue?

   UTM schemas down to keyword and placement, GCLID capture, Enhanced Conversions, and reconciliation of platform conversions against Stripe or the CRM.

   Cut the Google vs Stripe conversion gap from 36% to 17% on Alidrop. Re-anchored a Rs. 50L/month account to CRM outcomes when Google over-reported leads.

2. 2

   Campaign Intelligence

   What is each campaign, keyword and country really delivering?

   Revenue tied to campaign ID, keyword and country, with branded and non-branded performance read separately so strong brand demand can’t hide weak acquisition.

   Spocket non-branded ROAS moved from about 0.20x to a sustained 2.3x to 2.5x.

3. 3

   Conversion Optimisation

   Where does the funnel leak between click, trial and paid?

   Cohort-level checks on trial-to-paid conversion, so volume is judged by the customers it produces, not the sign-ups it generates.

   Ran a deliberate scale test on Dropshiptool, saw the cohort convert poorly, and cut the spend instead of chasing volume.

4. 4

   Acquisition Economics & BI

   Is every customer profitable at true CAC?

   CAC, ROAS and LTV:CAC computed from actual revenue, then used to right-size budgets with leadership.

   Across four accounts, spend was cut while ROAS rose, once true unit economics were visible.

5. 5

   Business Automation

   How do I get this answer every day without manual work?

   Scripts and API pipelines that join ad cost to real revenue and publish dashboards the team actually uses.

   Built a daily KPI tracker and a campaign-level revenue-vs-cost system, both used for daily budget and bid decisions.

6. 6

   Prioritized Action Plan

   What do we fix first, and in what order?

   Findings ranked by profit impact, rolled out in phases with checkpoints, so a bad call is caught early and reversed cleanly.

   Led a phase-wise turnaround on Alidrop, taking it from losing money to profitable while spending far less.

Most accounts are optimized from pillar 2. Most profit is lost in pillars 1 and 4.

Case studies

Each one shows which pillars did the work.

Alidrop: from losing money to profitable, at lower spend

• 1 Measurement
• 2 Campaign
• 4 Economics
• 6 Action plan

Problem

Joined at 0.56x revenue-to-spend, with no campaign-level view of revenue.

What I did

Worked with engineering on a UTM schema down to keyword, placement and device. Tied Stripe revenue to campaign, keyword and country, then made budget calls from that.

Result

Revenue-to-spend rose to a 2.48x peak while monthly spend came down by roughly two-thirds, a joint decision with the CEO based on true profitability.

Spocket Google Ads: halving spend while ROAS improved

• 2 Campaign
• 4 Economics
• 5 Automation

Problem

About 60% of revenue was branded, which flattered overall ROAS and hid weak non-branded performance.

What I did

Split branded from non-branded and cut non-branded spend by about 70%, guided by the daily revenue-vs-cost dashboards.

Result

Non-branded ROAS went from about 0.20x to a sustained 2.3x to 2.5x.

Dropshiptool: scale on purpose, cut on evidence

• 2 Campaign
• 3 Conversion
• 4 Economics

Problem

Needed to know whether higher spend would turn into paying customers.

What I did

Ran a planned scale test, checked the trial cohort’s conversion to paid, and cut the inefficient spend when it fell short.

Result

Google ROAS climbed from 0.37x to a 3.91x peak. Bing reached 2.4x cumulative on a lean budget.

Geny Medium: when Google and the CRM disagreed

• 1 Measurement
• 2 Campaign
• 6 Action plan

Problem

On a Rs. 50L/month account, Google reported more leads than the CRM confirmed.

What I did

Made the CRM the source of truth, implemented Enhanced Conversions, and built a creative evaluation framework linking CTR and CPC to MQL, SQL and sales.

Result

15 to 20% better cost per lead across a 20 to 25 brand portfolio, with a team of 15+.

Spocket: owning a bad call and recovering from it

• 3 Conversion
• 6 Action plan

Problem

A large location-exclusion change cut trials and revenue across three accounts.

What I did

Ran a pre/post analysis by country, persuaded leadership to reverse it, then proposed phased rollouts and a recoup plan with checkpoints.

Result

Revenue recovered gradually, and future changes now ship in phases.

Systems I’ve built

Tools that keep the numbers honest every day.

Experience

• Jun 2025 to Sep 2026
  Spocket Inc

  Senior Manager, Performance Marketing. Google and Bing across Spocket, Alidrop and Dropshiptool, plus affiliate. CAC, ROAS and profitability owner.

• Feb 2023 to Feb 2025
  Geny Medium

  Performance Marketing Director. Led 15+ people across Google, Meta, GA4, GTM and DV360 for 20 to 25 brands in real estate, education and healthcare, directing about Rs. 4 crore a month.

• Oct 2020 to Jan 2023
  Ethinos Digital Marketing

  Senior Manager. Large-budget accounts for Decathlon, Country Delight and ICICI Direct. Managed a team of 5 and ran Google and Meta training.

• Apr 2019 to Oct 2020
  Seagull Advertising

  Digital Marketing Manager. Real estate and education across Google, Meta, LinkedIn, YouTube and display.

• Jul 2018 to Apr 2019
  Ting Digital

  Digital Marketing Manager. Australian e-commerce campaigns, with ROAS taken from 2x to 4x through Merchant Center feed optimization and segmentation.

• May 2013 to May 2018
  Genpact and Teleperformance

  Agency Development Manager at Genpact, managing 40+ ad agencies and running QBRs with senior stakeholders. Team Lead at Teleperformance.

Let’s talk

If your paid spend is growing faster than your confidence in the numbers, I can help.

• devrajpichchuka@gmail.com
• Download resume (PDF)
• +91 76759 15227
• LinkedIn profile