Portfolio & Case Studies

Challenge

Meridian had a large product catalog but almost no organic visibility outside its own brand name — category pages were thin, duplicate templates, and a slow mobile build kept it off page one for every non-branded search that actually drove buying intent.

Approach

We rebuilt the category architecture around search intent, rewrote templated product copy into unique descriptions at scale, fixed Core Web Vitals on the mobile site, and ran a targeted digital-PR link campaign around three hero collections.

Results

• Organic traffic up 168% in 7 months
• 54 category and product keywords ranked on page 1
• Organic-attributed revenue overtook paid search for the first time

Challenge

Vantage was spending steadily on Google Ads but most of the budget was going to broad, unqualified searches — leads were plentiful but sales kept rejecting them as the wrong company size or wrong lane entirely.

Approach

We rebuilt the account around tightly matched intent clusters, added negative-keyword and audience layering to filter out non-ICP traffic, and shifted budget toward a LinkedIn + Google combination aimed specifically at logistics decision-makers.

Results

• Cost per qualified lead down 46%
• Sales-accepted lead rate nearly doubled
• Monthly ad spend held flat while pipeline grew

Challenge

PulseFit had five locations but a single dormant Instagram account posting inconsistently — trial-class sign-ups relied entirely on word of mouth and walk-in traffic, with no repeatable social funnel.

Approach

We split content by location, built a weekly reels-first calendar around trainers and member transformations, and layered in a simple comment-to-DM sign-up flow for free trial classes.

Results

• Follower base grew 4.1x in 9 months
• Trial-class bookings from social up 220%
• Two locations now sell out trial slots weekly

Challenge

Coral Bay's booking site ran on an aging template that took over 6 seconds to load on mobile and routed every booking through a clunky third-party widget, so a large share of visitors abandoned before checkout.

Approach

We rebuilt the site on a lightweight custom stack, brought the booking flow in-house with a 3-step checkout, and optimized every image and script for mobile-first loading.

Results

• Mobile load time cut from 6.2s to 1.8s
• Direct-booking conversion rate up 63%
• Third-party commission fees eliminated on ~40% of bookings

Challenge

BrightPath's support team was manually answering the same 15-20 admissions and billing questions on WhatsApp and email, often with same-day replies but never faster, which was costing them enrollments to competitors who responded in minutes.

Approach

We built a WhatsApp-native AI agent trained on their course catalog and policies, connected to their CRM so it could pull real enrollment status, and set escalation rules so anything outside its confidence handed off to a human instantly.

Results

• 82% of routine queries resolved without a human
• Average first response time dropped from 4 hours to under 1 minute
• Support team reassigned to high-value follow-ups, lifting enrollment conversion 19%

Challenge

Outbound sales teams were burning hours on manual prospecting — research, lead scoring, and outreach list-building were slow, inconsistent, and impossible to scale without adding headcount.

Approach

We built a multi-agent pipeline (Searcher, Analyst, Enrichment) on LangGraph that browses the web for buying signals, scores decision-makers, and validates contact data, with a human-in-the-loop approval gate before any list ships — running as a Dockerized microservice portable across AWS and GCP.

Results

• Replaces the manual research workload of roughly 10 SDRs
• Cuts SDR research time by 60%
• Generates a validated, outreach-ready lead list in under 60 seconds

Challenge

Running consistent campaigns across five channels — Email, WhatsApp, Instagram, LinkedIn, Google Ads — from a single brief meant either slow manual adaptation per platform or brand voice drifting between channels.

Approach

A Writer → Reviewer → Publisher agent swarm takes one product brief and produces platform-native creative for all five channels simultaneously, with predictive tone tuning per platform and a brand-consistency score tracked on every campaign before a human signs off on publishing.

Results

• One brief becomes 5 platform-native campaigns simultaneously
• 100% brand-voice consistency tracked across every channel
• Human-in-the-loop review gate before any campaign goes live

Challenge

D2C and marketplace sellers had ad spend, inventory, and margin data sitting in disconnected systems, so by the time a margin problem showed up in a weekly report, the budget behind it was already spent.

Approach

We connected ad platforms (Google, Meta, GA4), marketplaces (Shopify, Amazon, Flipkart) and inventory/ERP data into one semantic layer, with an XGBoost-driven control loop that autonomously pauses underperforming ads and triggers re-orders the moment ROAS crosses a set threshold — no human required in the loop.

Results

• Autonomous action when ROAS drops more than 15% — ads paused and budget reallocated instantly
• Drift detection triggers model auto-retraining the moment performance degrades
• Live margin and spend observability protecting roughly 30% more margin

Challenge

Delivering genuinely one-on-one tutoring quality to a large student base isn't possible with human tutors alone, and most ed-tech chat tools either hallucinate answers or feel generic.

Approach

We built a knowledge-graph-backed RAG pipeline with hybrid keyword and semantic search plus a reranking layer, grounding every answer in the actual course material, then layered dynamic difficulty adjustment based on each student's real performance.

Results

• Serving 1,000+ tutoring sessions at sub-200ms response latency
• Knowledge-graph maps true topic dependencies to pinpoint each student's actual gaps
• Fully containerised MLOps stack — CI/CD, drift detection and observability run with zero manual touch

Challenge

A single broken Google Tag Manager trigger can silently corrupt attribution for weeks before anyone notices — most teams only find out once monthly numbers stop reconciling.

Approach

We built an agent that runs a full one-click audit of a GTM container, flags broken tags and missing triggers, and suggests (or auto-applies) the fix, alongside a standing GDPR/CCPA consent-mode compliance check.

Results

• Full container audit runs in minutes instead of the multi-day manual process it replaces
• Consistently high data-accuracy scores across audited containers
• Compliance checks run continuously rather than as a one-off project

Challenge

iOS 14+ privacy changes left ad platforms blind to a meaningful share of conversions, so Meta and Google campaigns were optimizing against an incomplete picture of what was actually working.

Approach

We built a server-side bridge that sends enriched, deduplicated conversion events directly to Meta CAPI and Google Ads, respecting consent state and hashing personal data before it ever leaves the server.

Results

• Recovers a meaningful share of previously lost iOS conversion signal
• Event Match Quality scores improved meaningfully after deployment
• One-click deployment for Shopify and WooCommerce storefronts, no developer required

Challenge

A growing US sales and marketing team needed the same NexusHunt / Paperclip agent stack running against a US CRM and ad-account setup, without a rebuild from scratch.

Approach

We are porting the core agent suite to the client's HubSpot + Google Ads environment, keeping the same human-in-the-loop approval gates that keep every agent action reviewable.

Results

• Early deployment is already reducing manual research and reporting hours
• Rollout is ongoing — case-study numbers will be published once the team clears a full reporting quarter

Challenge

Managing cross-border freight compliance and customs documentation was a massive manual bottleneck, requiring localized language processing and strict GDPR adherence.

Approach

Deployed a sovereign, on-premise Multi-Agent Swarm (using vLLM) that autonomously parses multilingual customs forms, verifies compliance, and flags anomalies instantly.

Results

• Automated 92% of routine customs documentation processing by 2026
• Eliminated cross-border compliance penalties
• Infrastructure performs entirely within EU borders, guaranteeing absolute data sovereignty

Challenge

Sundrop's GA4 setup was firing duplicate purchase events after a checkout redesign, inflating revenue reporting by roughly a third and making it impossible for the team to trust which channels were actually driving sales.

Approach

We rebuilt the tracking plan in GTM with server-side tagging, deduplicated the purchase event against order IDs, and set up a clean channel-attribution dashboard the marketing team could self-serve.

Results

• Revenue reporting accuracy corrected to within 2%
• Reporting time for weekly reviews cut from a full day to under an hour
• Ad budget reallocated toward the two channels actually driving repeat purchases

Challenge

High dependency on paid ads with customer acquisition costs rising. Organic traffic was stagnant despite a large product catalog, mainly due to thin content and poor technical SEO.

Approach

Implemented programmatic SEO for category pages, resolved crawl bloat, and executed a massive content cluster strategy targeting high-intent mid-funnel queries.

Results

• Achieved 310% YoY growth in non-branded organic traffic by July 2026
• Reduced blended CAC by 42%
• Captured 85 featured snippets for high-value product categories

Challenge

High volume of lead generation but poor lead quality from Google Ads, leading to a low loan-disbursal rate and wasted sales team effort.

Approach

Shifted to offline conversion tracking (OCT) to optimize campaigns for actual loan disbursals rather than just form fills. Restructured campaigns using Value-Based Bidding.

Results

• Increased loan disbursal rate from paid leads by 3.5x
• Reduced cost per acquisition (CPA) by 55% as of H1 2026
• Scaled monthly ad spend profitably by 150%

Challenge

Struggling to build a community and drive engagement organically. Relying entirely on influencer shoutouts with low retention and high follower churn.

Approach

Launched an educational short-form video series focused on ingredient transparency. Integrated Instagram Reels with direct Shopify checkout flows.

Results

• Grew organic Instagram community by 450K authentic followers
• Achieved a consistent 8% engagement rate through Q2 2026
• Organic social now drives 25% of total D2C revenue

Challenge

Legacy Magento platform was slow, difficult to manage, and causing high cart abandonment due to a complex, multi-page B2B checkout process.

Approach

Migrated to a headless Shopify Plus architecture with a custom React frontend. Rebuilt the B2B checkout to support bulk ordering and custom pricing tiers.

Results

• Site speed improved to sub-second load times
• B2B conversion rate increased by 78%
• Zero downtime during the mid-2026 migration

Challenge

The dispatch team was overwhelmed by email inquiries regarding freight status, leading to 12+ hour response times and dissatisfied enterprise clients.

Approach

Developed a custom autonomous email agent integrated directly into their ERP. The agent reads incoming freight queries, checks live telemetry, and drafts/sends accurate status updates.

Results

• Automated 88% of incoming status inquiries
• Response time reduced from 12 hours to under 3 minutes
• Client satisfaction scores hit all-time highs in 2026

Challenge

Data fragmentation across multiple properties. The team could not accurately attribute subscriptions to specific content pieces due to a broken Adobe Analytics implementation.

Approach

Completely overhauled the Adobe Analytics workspace. Implemented unified cross-domain tracking and built a custom content-attribution dashboard for the editorial team.

Results

• Subscription attribution accuracy reached 99.5%
• Identified and scaled the top 10% of content driving 80% of revenue in H1 2026
• Eliminated all cross-domain session breakage

Challenge

New entrant in a highly competitive US market. Needed to capture high-intent enterprise search traffic against legacy competitors with massive domain authority.

Approach

Executed a surgical bottom-of-funnel content strategy targeting "vs" queries, alternative keywords, and deep-dive technical use cases rather than broad informational terms.

Results

• Captured #1 rankings for 45 high-intent competitor comparison keywords
• Organic traffic value reached $120k/month by July 2026
• Drove a 210% increase in Enterprise demo requests

Challenge

Acquisition costs on Google Ads were spiraling out of control due to aggressive US bidding wars, making the patient acquisition model unprofitable.

Approach

Pivoted to a heavily segmented Performance Max strategy with strict ROAS targets, augmented by first-party patient LTV data fed back into Google via Offline Conversions.

Results

• Patient Acquisition Cost (PAC) reduced by 38%
• Scaled campaign spend by 2x while maintaining target ROAS through Q2 2026
• Increased patient LTV by targeting higher-quality segments

Challenge

Acquisition costs on Google Ads were spiraling out of control due to aggressive US bidding wars, making the patient acquisition model unprofitable.

Approach

Pivoted to a heavily segmented Performance Max strategy with strict ROAS targets, augmented by first-party patient LTV data fed back into Google via Offline Conversions.

Results

• Patient Acquisition Cost (PAC) reduced by 38%
• Scaled campaign spend by 2x while maintaining target ROAS through Q2 2026
• Increased patient LTV by targeting higher-quality segments

Challenge

Acquisition costs on Google Ads were spiraling out of control due to aggressive US bidding wars, making the patient acquisition model unprofitable.

Approach

Pivoted to a heavily segmented Performance Max strategy with strict ROAS targets, augmented by first-party patient LTV data fed back into Google via Offline Conversions.

Results

• Patient Acquisition Cost (PAC) reduced by 38%
• Scaled campaign spend by 2x while maintaining target ROAS through Q2 2026
• Increased patient LTV by targeting higher-quality segments

Challenge

Acquisition costs on Google Ads were spiraling out of control due to aggressive US bidding wars, making the patient acquisition model unprofitable.

Approach

Pivoted to a heavily segmented Performance Max strategy with strict ROAS targets, augmented by first-party patient LTV data fed back into Google via Offline Conversions.

Results

• Patient Acquisition Cost (PAC) reduced by 38%
• Scaled campaign spend by 2x while maintaining target ROAS through Q2 2026
• Increased patient LTV by targeting higher-quality segments

Challenge

Acquisition costs on Google Ads were spiraling out of control due to aggressive US bidding wars, making the patient acquisition model unprofitable.

Approach

Pivoted to a heavily segmented Performance Max strategy with strict ROAS targets, augmented by first-party patient LTV data fed back into Google via Offline Conversions.

Results

• Patient Acquisition Cost (PAC) reduced by 38%
• Scaled campaign spend by 2x while maintaining target ROAS through Q2 2026
• Increased patient LTV by targeting higher-quality segments

Challenge

Acquisition costs on Google Ads were spiraling out of control due to aggressive US bidding wars, making the patient acquisition model unprofitable.

Approach

Pivoted to a heavily segmented Performance Max strategy with strict ROAS targets, augmented by first-party patient LTV data fed back into Google via Offline Conversions.

Results

• Patient Acquisition Cost (PAC) reduced by 38%
• Scaled campaign spend by 2x while maintaining target ROAS through Q2 2026
• Increased patient LTV by targeting higher-quality segments

Challenge

Acquisition costs on Google Ads were spiraling out of control due to aggressive US bidding wars, making the patient acquisition model unprofitable.

Approach

Pivoted to a heavily segmented Performance Max strategy with strict ROAS targets, augmented by first-party patient LTV data fed back into Google via Offline Conversions.

Results

• Patient Acquisition Cost (PAC) reduced by 38%
• Scaled campaign spend by 2x while maintaining target ROAS through Q2 2026
• Increased patient LTV by targeting higher-quality segments

Challenge

Acquisition costs on Google Ads were spiraling out of control due to aggressive US bidding wars, making the patient acquisition model unprofitable.

Approach

Pivoted to a heavily segmented Performance Max strategy with strict ROAS targets, augmented by first-party patient LTV data fed back into Google via Offline Conversions.

Results

• Patient Acquisition Cost (PAC) reduced by 38%
• Scaled campaign spend by 2x while maintaining target ROAS through Q2 2026
• Increased patient LTV by targeting higher-quality segments

Challenge

Acquisition costs on Google Ads were spiraling out of control due to aggressive US bidding wars, making the patient acquisition model unprofitable.

Approach

Pivoted to a heavily segmented Performance Max strategy with strict ROAS targets, augmented by first-party patient LTV data fed back into Google via Offline Conversions.

Results

• Patient Acquisition Cost (PAC) reduced by 38%
• Scaled campaign spend by 2x while maintaining target ROAS through Q2 2026
• Increased patient LTV by targeting higher-quality segments

Challenge

Acquisition costs on Google Ads were spiraling out of control due to aggressive US bidding wars, making the patient acquisition model unprofitable.

Approach

Pivoted to a heavily segmented Performance Max strategy with strict ROAS targets, augmented by first-party patient LTV data fed back into Google via Offline Conversions.

Results

• Patient Acquisition Cost (PAC) reduced by 38%
• Scaled campaign spend by 2x while maintaining target ROAS through Q2 2026
• Increased patient LTV by targeting higher-quality segments

Challenge

Acquisition costs on Google Ads were spiraling out of control due to aggressive US bidding wars, making the patient acquisition model unprofitable.

Approach

Pivoted to a heavily segmented Performance Max strategy with strict ROAS targets, augmented by first-party patient LTV data fed back into Google via Offline Conversions.

Results

• Patient Acquisition Cost (PAC) reduced by 38%
• Scaled campaign spend by 2x while maintaining target ROAS through Q2 2026
• Increased patient LTV by targeting higher-quality segments

Challenge

The brand was selling across Amazon (US & India) and Flipkart but running the business on manually downloaded CSVs — over 10 hours a week of copy-paste work — with no single view of profitability across marketplaces, so leadership decisions were always working from stale numbers.

Approach

We stood up a Dockerized data pipeline with automated marketplace API pulls every 6 hours, built currency and timezone normalization plus SKU matching in Python, and connected it all to a live executive dashboard so every marketplace reports into one P&L instead of three disconnected spreadsheets.

Results

• Manual CSV downloads eliminated entirely across both marketplaces
• Combined Amazon and Flipkart revenue grew 37.8% year-over-year to ₹138.85 Cr in 2025, on 17.9% less ad spend than 2024
• Blended ROAS rose from 6.06x (2024) to 10.18x (2025) once the unified view let the team reallocate spend faster

Challenge

[2-3 sentences: what problem did this client have before iAdsClick — write uniquely for this client, don't copy Client 1's story]

Approach

[What iAdsClick actually built/did for this client]

Results

• [e.g. Revenue +__% YoY]
• [e.g. ROAS improved from __x to __x]

Challenge

Managing vast inventory catalogs across Amazon US, Walmart, and Shopify with disconnected pricing engines, leading to frequent stockouts and margin erosion.

Approach

Deployed an automated, cross-marketplace synchronization pipeline that dynamically adjusts pricing based on real-time competitor data and stock levels across all platforms.

Results

• Eliminated 95% of stockouts on high-velocity items by Q2 2026
• Increased overall margin by 14% through dynamic algorithmic pricing
• Unified dashboard reduced weekly operational reporting time by 15 hours

Challenge

A small-to-medium US e-commerce brand selling on Amazon and Walmart Marketplace was running both channels off manually exported weekly CSVs, with no unified view of profitability across the two — budget calls always lagged the actual numbers.

Approach

Built the same automated, real-time multi-marketplace pipeline used on our other e-commerce engagements — API-based ingestion from Amazon Seller Central and Walmart Marketplace every 6 hours, unified into one live P&L dashboard.

Results

• Grew from a $220K/month baseline to $295K/month (+32%) while keeping ad spend nearly flat
• Blended ROAS improved from 3.6x to 4.3x across Amazon and Walmart Marketplace combined
• Eliminated 8+ hours/week of manual CSV work, saving 400+ hours a year

Challenge

The same retailer's ad spend across Amazon and Flipkart was being judged on top-line ROAS alone — with iOS 14+ attribution gaps and no server-side verification, the team couldn't tell if a "good" ROAS number was real or just an artifact of broken tracking.

Approach

We layered server-side GTM tracking on top of the marketplace pipeline to recover lost iOS attribution, rebuilt audience modeling around verified conversion data, and used the newly reliable data to reallocate spend toward the channels actually driving profit.

Results

• Blended ROAS improved roughly 15% (3.5x to 4.0x) over a 6-month window
• Customer acquisition cost dropped about 12% as attribution accuracy improved
• Data accuracy verified at 99.8% after moving tracking server-side, closing the iOS attribution gap

Challenge

Customer acquisition costs for high-value financial products were unsustainably high due to fierce bidding competition on Google Ads and Meta.

Approach

Implemented a full-funnel performance strategy, shifting budget towards high-intent YouTube campaigns and programmatic display, coupled with aggressive landing page CRO.

Results

• Dropped Cost Per Acquisition (CPA) by 45% while scaling volume
• Generated 15,000+ highly qualified leads in H1 2026 alone
• Achieved an unprecedented 6.5x ROAS on a highly competitive product

Challenge

Beyond the tracking fixes, the underlying question was a growth one: with $2M+ in ad spend already committed across US and EU marketplaces, could the business grow revenue without simply spending more?

Approach

We treated the analytics rebuild as the foundation for a growth program — using the newly trustworthy data to run tighter experiments, kill underperforming SKUs and campaigns faster, and reinvest saved spend into the channels the unified dashboard showed were actually compounding.

Results

• Combined marketplace revenue grew 28% year-over-year to roughly $92K/month, on ad spend that stayed essentially flat
• That "revenue up, spend flat" pattern — more output per dollar rather than more dollars — is the core growth-marketing signal the engagement was built to produce
• Executive reporting moved from a 14-day lag to a 3-day decision cycle, letting growth bets get tested and killed or scaled far faster

Challenge

Rapidly exhausting the total addressable market in tier-1 cities. Growth plateaued and the company struggled to penetrate tier-2 and tier-3 markets profitably.

Approach

Engineered a hyper-localized growth engine using vernacular ad creatives and a referral loop strategy designed specifically for community-driven adoption in smaller cities.

Results

• Unlocked 350% YoY growth in tier-2 and tier-3 enrollments up to July 2026
• Referral loop reduced blended CAC by 30%
• Expanded active user base to 2.5 million students

Challenge

Excellent top-of-funnel traffic, but a massive drop-off during the free trial period. Users were not reaching the "aha" moment fast enough to convert to paid tiers.

Approach

Overhauled the onboarding experience with data-driven product-led growth (PLG) tactics. Implemented behavior-triggered in-app messaging and personalized email cadences.

Results

• Free-to-paid conversion rate skyrocketed from 3% to 11% by mid-2026
• Reduced Day-1 churn by 40%
• Added $4.2M in annual recurring revenue (ARR) purely from onboarding optimizations

Challenge

Managing vast inventory catalogs across Amazon Europe, Walmart, and Shopify with disconnected pricing engines, leading to frequent stockouts and margin erosion.

Approach

Deployed an automated, cross-marketplace synchronization pipeline that dynamically adjusts pricing based on real-time competitor data and stock levels across all platforms.

Results

• Eliminated 95% of stockouts on high-velocity items by Q2 2026
• Increased overall margin by 14% through dynamic algorithmic pricing
• Unified dashboard reduced weekly operational reporting time by 15 hours