Marketing Services
Growth & GTM Strategy: Strategic planning for product launches and market entry. I build go-to-market engines that scale. Proof: Scaled Dil Mil to acquisition
Lifecycle Marketing: Retention programs that drive LTV. Onboarding flows, engagement campaigns, and win-back strategies. Proof: 39% retention lift at Dil Mil
Performance Marketing: Paid acquisition that actually works. Creative testing, channel optimization, and efficient spend. Proof: $1.30 CPI (50% below benchmark)
Brand Strategy: Positioning that differentiates. I help brands find the gap nobody else owns and claim it. Proof: Repositioned Dil Mil from utility to identity
E-Commerce & DTC: Launch strategies that work without burning cash on ads. Scarcity, email, and community-driven growth. Proof: $122K revenue, zero ad spend (Jaloos)
Influencer & Creative: Creator partnerships that convert. I build influencer engines, not one-off campaigns. Proof: 200+ creator network at Dil Mil
AI Systems & Rapid Builds: Ship marketing assets in days, not months. AI-powered workflows, landing pages, custom agents, and marketing automation — without waiting on engineering. Proof: 5+ client sites and AI tools shipped in weeks
SEO & Local Search: Get found where it matters. Technical SEO, local search optimization, Google Business Profile management, and content strategy that drives organic traffic and real leads. Proof: #1 local ranking, 173% revenue growth (A1 Limo)
Client Outcomes
Community-Led Growth: New DTC e-commerce brand entering a crowded market with zero marketing budget. Result: $122K in revenue in year two with zero ad spend.
Paid Social Strategy: Culturally-focused kids' toy brand with a loyal Instagram following but no paid acquisition strategy. Result: 3x ROAS and 150% revenue growth over 7 months.
App Growth: Post-launch app struggling with user acquisition and retention. Result: $1.30 CPI for app installs and 37% retention increase.
Localized Growth: Luxury transportation company with inconsistent lead generation. Result: 173% revenue growth with predictable inbound leads.
The GTM Playbook Nobody Teaches You
If you're a startup founder about to launch or a VP of Marketing building your first go-to-market strategy, you've probably Googled 'GTM strategy template' and found a bunch of generic frameworks that look great on a slide deck but don't actually help you decide what to do on Monday morning. This is different. This is the GTM playbook I wish I had when I was figuring it out. I didn't build these companies from scratch. I came into <a href="/case-studies/dil-mil-story" class="text-primary hover:underline">Dil Mil</a> four years after it was founded and rebuilt the GTM engine as Head of Marketing. At Cray, I was in demand generation learning ABM tactics in enterprise HPC. At Intuit, I worked inside one of the most data-driven marketing organizations in the world. Each company taught me something different about GTM, and this framework synthesizes those lessons. A Go-To-Market strategy is your plan for getting a product into customers' hands and turning that into revenue. But here's what most frameworks miss: GTM isn't a launch plan. It's an operating system. At Dil Mil, our GTM strategy evolved weekly based on channel performance data. At Cray, the GTM motion was a 12-month ABM play targeting specific enterprise accounts. The framework is different for each company and business type, but the principles remain consistent. The common thread? GTM is not a phase you complete. It's how you operate.
Define Your ICP with Surgical Precision: Generic ICP definitions kill startups. 'South Asian singles aged 25-35' sounds specific, but it's not. At <a href="/case-studies/dil-mil-user-growth" class="text-primary hover:underline">Dil Mil</a>, we mapped specific diaspora corridors: Toronto, Bay Area, Sacramento, London, and Birmingham UK. We used Amplitude and Firebase to analyze which cities had the highest Day-7 retention and subscription conversion rates. Toronto users converted at 2x the rate of LA users. That geographic precision made our campaigns significantly more efficient. At Cray, as part of the demand generation team, I learned how enterprise ICP works differently: HPC buyers at research institutions, financial services firms, and government agencies. We used Demandbase to identify target accounts and built ABM programs around the accounts most likely to buy. That focus contributed to $32M in qualified pipeline. Your ICP should be specific enough that you can name 10 companies or customer profiles that fit it perfectly. If you can't, you haven't done the work. Tools I recommend: Amplitude for behavioral cohort analysis, Firebase for mobile analytics, Demandbase or 6sense for B2B account identification, and Adjust or AppsFlyer for mobile attribution.
Map the Competitive Landscape (But Not How You Think): Most competitive analysis is useless. Teams build feature comparison matrices and miss the actual competitive dynamics. At Dil Mil, we weren't just competing with Tinder or Bumble. We were competing with the 'Seema Aunties' of the world (a reference to the traditional Indian matchmaking culture, popularized by Netflix's Indian Matchmaking), Shaadi.com, and the cultural expectation that South Asian dating should be parent-driven. Our competitive analysis wasn't about features; it was about understanding the cultural positioning gap. We found that no one owned the 'modern diaspora dating' positioning. That insight shaped everything from our brand voice to our influencer partnerships. At Cray, the competitive landscape was IBM, HPE, and a handful of specialized HPC vendors. But the real competition was 'do nothing': companies sticking with existing infrastructure rather than upgrading. Cray's differentiator was having segment-specific leads with deep insights because the team was deeply immersed in those industries and spaces. <a href="https://review.firstround.com/leslies-compass-a-framework-for-go-to-market-strategy/" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">First Round Capital's 'Leslie's Compass' framework</a> is useful here: understand whether you're in a marketing-intensive or sales-intensive market, because that determines your entire GTM motion. Don't just analyze competitor features. Analyze what mental space they own, what positioning gaps exist, and what inertia you're competing against.
Craft a Value Proposition That Actually Differentiates: Your value proposition isn't a tagline. It's the core strategic choice that everything else ladders up to. At <a href="/case-studies/dil-mil-story" class="text-primary hover:underline">Dil Mil</a>, our internal value prop evolved from 'dating app for South Asians' (utility) to 'where the diaspora finds love' (identity), with 'Find Something Real' as one of our external taglines. That shift from utility to identity is what unlocked brand marketing as a growth lever. We could partner with cultural festivals, musicians, and influencers because we weren't just an app; we were a movement. At Trilux Tech, we built positioning around 'trust architecture': the idea that enterprise buyers need to trust you before they'll even fill out a contact form. Every design decision, every content piece, every testimonial was engineered to build that trust. For Bay Area Print Pro, the positioning was hyper-local and urgent: 'The Bay Area's Emergency B2B Print Hub.' That specificity is what made the local SEO strategy work and drove a 3x increase in leads. Your value proposition should pass the 'so what' test. If a customer can respond 'so what?' to your positioning, it's not differentiated enough. And critically, it should be defensible. 'Better customer service' is not a differentiator. 'AI-powered onboarding that reduces time-to-value by 50%' is.
Select Channels Based on Data, Not Assumptions: At <a href="/case-studies/dil-mil-revenue" class="text-primary hover:underline">Dil Mil</a>, we ran Meta, Google UAC, ASO (App Store Optimization), Snapchat, TikTok, Spotify audio ads, and programmatic display. But we didn't launch all channels at once. We started with Meta because it had the highest volume and best targeting for our audience. We proved unit economics there first: getting to a sustainable CPI and positive Day-30 LTV:CAC ratio. Only then did we expand. We tested programmatic display and killed it in three weeks. The audience quality was terrible, and retention metrics were 40% below our Meta cohorts. Knowing when to kill a channel is as important as knowing when to scale one. At Cray, the channel mix was completely different: ABM through Demandbase, Marketo nurture funnels, TechTarget content syndication, and HPC events across the world (from New Orleans to Leipzig, Germany). No Facebook ads. No TikTok. At Barracuda, I worked with partner marketing through Softchoice, Zones, and CDW, building partner training programs and relationships. <a href="https://www.lennysnewsletter.com/p/gtm-motions" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Lenny Rachitsky's research on GTM motions</a> shows that successful companies typically master one channel before expanding. His analysis of 30 B2B SaaS companies found that most scaled to $10M+ ARR on just 1-2 primary channels. Resist the urge to be everywhere. Tools for B2C: Meta Ads Manager, Google UAC, ASO platforms, Snapchat Ads, TikTok Ads, Spotify Ad Studio. Tools for B2B: Demandbase, 6sense, Marketo, HubSpot, LinkedIn Campaign Manager.
Build a Growth Engine, Not Just a Sales Motion: A GTM strategy isn't just about how you sell. It's about building a self-reinforcing engine. At <a href="/case-studies/dil-mil-revenue" class="text-primary hover:underline">Dil Mil</a>, the growth engine was a flywheel: paid acquisition fed organic content (success stories, user-generated content), which fed brand awareness, which lowered CAC. We called it the 'Brand-Performance Flywheel.' Every dollar spent on performance marketing generated content that improved brand perception, which made future performance marketing more efficient. That flywheel is what drove the growth trajectory that led to acquisition by The Dating Group. At Intuit, I owned the lifecycle portion of a major QuickBooks Mobile launch, working closely with a cross-functional team to redesign the first-time user journey around a new monetization model. The shift required rethinking every touchpoint in the onboarding flow to align user activation with revenue capture from day one. That work unlocked $200K+ in incremental revenue in year one. At Aryaka, I reduced churn by 24% in a single quarter by redesigning the customer onboarding experience, driving significant retained revenue. The growth engine for enterprise wasn't acquisition; it was retention. Your growth engine depends on your business model. For PLG (product-led growth), it's activation and virality. For sales-led, it's pipeline generation and conversion. For marketplace businesses, it's liquidity on both sides. Define what 'engine' means for your specific model. Tools: Braze or Leanplum for lifecycle messaging, Segment for data orchestration, GA4 for web analytics, Amplitude for product analytics.
Measure, Learn, Kill: The Operating Rhythm: Metrics aren't dashboards. They're decision triggers. At Dil Mil, we reviewed channel performance weekly. Every channel had a 3-week window to prove positive unit economics. If it couldn't hit our target CPI and show acceptable Day-7 retention, we killed it. No emotional attachment. No 'let's give it another month.' We killed programmatic. We killed certain Snapchat campaigns. We scaled what worked. At Intuit, I co-built an automated lifecycle reporting system with a colleague who handled the UiPath automation. The system pulled data from internal sources and aggregated it into a shared Google Sheet, giving each lifecycle marketer a real-time view of their product's performance. It saved 2.5+ hours per week for 20+ marketers and created the visibility needed for fast decisions. The most dangerous GTM mistake is continuing to invest in channels or tactics that aren't working because you don't have clear data. Build your measurement infrastructure before you scale spend. Your north star metric should be tied to revenue or a strong leading indicator of revenue (like Day-7 retention for consumer apps or SQL-to-opportunity conversion for B2B). Track 3-5 supporting KPIs that explain movement in the north star. Review weekly. Tools: Amplitude or Mixpanel for product analytics, Tableau or Looker for dashboards, GA4 for web, Bizible or HubSpot for B2B attribution, Firebase for mobile.
GTM is not a launch plan. It's an operating system that evolves at a cadence based on your data and business type. The framework I used at <a href="/case-studies/dil-mil-story" class="text-primary hover:underline">Dil Mil</a> changed every quarter as we learned what actually worked.
Channel focus beats channel sprawl. We scaled Dil Mil to acquisition primarily through Meta, ASO, and Google UAC. We tested many other channels and killed most of them within weeks.
Your ICP should be specific enough to name 10 accounts or customer profiles. At Dil Mil, we could name the exact cities. At Cray, we had a list of 100 target accounts tiered by 1:1, 1:few, and 1:many with strategic inputs from our segment leads.
The best GTM strategies create flywheels, not funnels. Every acquisition dollar should also build brand equity that makes future acquisition cheaper.
Knowing when to kill a channel or tactic is as valuable as knowing when to scale one. We killed programmatic at Dil Mil in three weeks. That decision saved us hundreds of thousands in wasted spend.
Stop the Leak: A Lifecycle Marketing Playbook
If you're a growth marketer watching your retention curves flatten or a product manager trying to figure out why users churn after onboarding, the answer is almost always the same: you don't have a lifecycle marketing system. You have a collection of disconnected emails and push notifications that nobody has connected to actual user behavior. According to <a href="https://www.businessofapps.com/guide/mobile-app-retention/" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Business of Apps</a>, the average mobile app loses about 75% of users by Day 1, and only 6% remain by Day 30. I've lived those numbers. At <a href="/case-studies/dil-mil-user-growth" class="text-primary hover:underline">Dil Mil</a>, we realized our acquisition strategy was a leaky bucket. We were scaling ad spend aggressively, but DAU wasn't keeping pace. For every cohort of new users we acquired, the majority would disappear within a week. The math was brutal: we were paying to fill a bucket with a hole in the bottom. The fix wasn't more ads. It was lifecycle. When we invested in retention, specifically the first 7 days after install, everything changed. Our <a href="/case-studies/dil-mil-user-growth" class="text-primary hover:underline">retention improved by 39%</a>, and suddenly every acquisition dollar was worth dramatically more. As <a href="https://www.lennysnewsletter.com/p/what-is-good-retention-issue-29" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Lenny Rachitsky puts it</a>, 'Great retention is the scalable way to grow a product. It's the best indicator of product-market fit, the most important factor in lifetime value, and high retention drives all of the best acquisition strategies.' I've seen this play out across consumer apps, e-commerce, and enterprise SaaS. This playbook is what I learned.
Map the Full User Journey, Not Just the Funnel: Most teams map acquisition funnels. Few teams map the full lifecycle from first touch to loyal advocate. That's where the money is. At <a href="/case-studies/dil-mil-user-growth" class="text-primary hover:underline">Dil Mil</a>, we mapped every touchpoint from App Store impression to Day-30 subscription. We identified 6 stages: Discovery, Install, Onboarding, First Match, Engagement, and Subscription. Each stage had specific drop-off rates we could measure in Amplitude. The visualization alone was eye-opening: we were losing a significant chunk of users between Install and completing their profile. That single insight shaped our entire lifecycle strategy for the next year. At Intuit, the journey was different: Download, First Login, First Invoice, First Payment Received. The 'aha moment' for QuickBooks wasn't signing up; it was getting paid through the app. Once we understood that, we could engineer every touchpoint to drive toward that outcome. Your journey map should include every stage, the actions that define each stage, the drop-off rate between stages, and the signals that predict whether someone will advance or stall.
Find Your 'Aha Moment' and Engineer the Path to It: Every product has a moment where the user 'gets it.' Facebook famously discovered that users who added 7 friends in their first 10 days had dramatically higher retention. The insight wasn't about friends; it was about finding the behavior that correlates with long-term engagement and then engineering the product and messaging to drive that behavior. At Dil Mil, we found that users who received a match within 24 hours of signing up had dramatically higher Day-7 retention than those who didn't. The gap was staggering. That single insight reshaped our entire onboarding flow. We redesigned profile prompts to get better photos and bios, tuned the recommendation algorithm to prioritize early matches for new users, and built a push notification strategy that re-engaged users who hadn't opened the app within 6 hours. The goal was simple: get every new user to their first match as fast as possible. At QuickBooks Mobile, the aha moment was sending your first invoice. Our first-time user campaign used email, push, and in-app messaging to guide users toward that action within the first 3 days. The redesigned FTU journey drove meaningful incremental revenue by getting users to the aha moment faster.
Build Onboarding That Actually Activates: Generic welcome emails don't work. 'Welcome to [App Name]! Here's what you can do...' is lazy and ineffective. At Dil Mil, our onboarding flow was behavior-triggered, not time-triggered. If a user completed their profile but hadn't swiped, they got a different message than someone who had swiped but hadn't matched. We used Braze for push and in-app messaging, with Segment piping behavioral data in real-time. The segmentation wasn't 'Day 1 users' vs 'Day 3 users'; it was 'completed profile but no swipe' vs 'swiped 10+ but no match' vs 'matched but no conversation.' Each segment got tailored messaging designed to move them to the next step. This is what <a href="https://www.braze.com/resources/articles/customer-lifecycle-marketing" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Braze calls behavior-based lifecycle marketing</a>: triggering messages based on what users do (or don't do), not just when they signed up. At Aryaka (enterprise SaaS), onboarding meant something completely different: implementation support, training webinars, and proactive check-ins from customer success. But the principle was the same: reduce time-to-value. We redesigned the entire onboarding experience, cut time-to-value dramatically, and reduced churn by 24% in one quarter. That translated to significant retained revenue from fixing one part of the lifecycle.
Create Engagement Loops That Compound: Retention isn't about sending more emails. It's about building loops where each action reinforces the next. At Dil Mil, the engagement loop was: match notification leads to conversation leads to date leads to success story leads to UGC leads to brand content leads to more users leads to more matches. Each step reinforced the next. Our lifecycle messaging wasn't just about re-engaging inactive users; it was about accelerating users through the loop. Match notifications were timed for maximum response. Conversation prompts were sent when users hadn't replied in 24 hours. Success stories were showcased to users who had gone on dates. For <a href="/case-studies/jaloos" class="text-primary hover:underline">Jaloos</a> (streetwear e-commerce), the engagement loop was scarcity-driven: email teaser building anticipation leads to drop announcement leads to purchase leads to unboxing UGC leads to social sharing leads to more email subscribers. Some drops sold out in under 24 hours because the loop was self-reinforcing. The Klaviyo flows we built achieved 6.5x email ROAS across the full lifecycle. At Intuit, engagement meant usage depth. We built campaigns around feature adoption: 'You've sent a few invoices. Here's how to set up recurring invoices.' Each feature adopted increased switching costs and LTV.
Build Win-Back Before You Need It: Most teams build win-back campaigns after they notice churn. That's too late. By the time someone has been inactive for 30 days, they've mentally moved on. At Dil Mil, we identified churn signals early: no app open in 3 days, no swipe in 5 days, no conversation reply in 60 hours. Each signal triggered a specific re-engagement sequence before the user mentally churned. We called it the 'Safety Net' strategy. The automated push notification sequence for users who stalled during onboarding recovered a meaningful percentage of 'lost' installs. That's not a small number when you're spending significantly on acquisition. Every recovered user was pure margin. At <a href="/case-studies/jaloos" class="text-primary hover:underline">Jaloos</a>, win-back was email-driven: 'You missed the last drop. Here's what sold out.' FOMO as a retention tool. At <a href="/case-studies/plated-by-py" class="text-primary hover:underline">Plated by Py</a>, we built re-engagement campaigns for customers who hadn't ordered in 90 days, with personalized offers based on their past purchases. At Aryaka, win-back meant executive outreach and custom retention offers. Different tactic, same principle: intervene before the customer decides to leave.
Measure LTV, Not Just Open Rates: Email open rates are vanity metrics. What matters is whether your lifecycle program is actually driving revenue and retention. At Dil Mil, we tracked the incremental impact of each lifecycle touchpoint on Day-7 retention, Day-30 retention, and subscription conversion. We could attribute specific revenue to specific acquisition channels, email touchpoints, and push sequences. This wasn't guesswork; we ran holdout tests to measure true incrementality. At Intuit, I co-built an automated lifecycle reporting system with a colleague who handled the UiPath automation. The system pulled data from internal data lakes and dashboards into a shared Google Sheet, giving each lifecycle marketer a real-time view of their product's performance. It saved hours per week for the lifecycle team and, more importantly, gave us the visibility to make fast decisions about what was working. At Jaloos, the metric was simple: email ROAS. We tracked revenue per email sent and optimized ruthlessly. 6.5x ROAS doesn't happen by accident; it happens by measuring every flow and killing the underperformers. Tools I recommend: Amplitude or Mixpanel for product analytics, GA4 for web, Klaviyo for e-commerce email analytics, and Tableau or Looker for cross-channel dashboards.
Build behavior-based flows, not time-based flows. 'Day 3 email' is lazy. 'User completed profile but hasn't swiped in 48 hours' is smart.
Lifecycle is cross-channel, not just email. The best programs orchestrate email, push, in-app, and SMS based on where the user is and what channel they respond to.
Start win-back before users churn. If your first re-engagement message goes out after 30 days of inactivity, you've already lost them. At Dil Mil, we triggered re-engagement within 72 hours of inactivity.
Measure incrementality, not just engagement. Are your lifecycle campaigns actually driving behavior change, or are they just reaching users who would have converted anyway? Run holdout tests.
Fixing the leaky bucket is the highest-leverage investment most companies aren't making. At <a href="/case-studies/dil-mil-user-growth" class="text-primary hover:underline">Dil Mil</a>, a 39% improvement in retention meant every acquisition dollar was worth significantly more. That's the difference between a company that scales and one that stalls.
Creative Is the New Targeting: A Paid Media Testing Framework
If you're a performance marketer watching your CPAs climb and your ROAS decline, the problem probably isn't your targeting. It's your creative. Most paid media teams are still optimizing audiences and bid strategies while ignoring the single biggest lever they have: the ad itself. Creative is the new targeting, and this framework shows you how to treat it that way. The shift from targeting-driven to creative-driven performance marketing is the biggest change in paid media in the last five years. Most teams still spend 80% of their time on audience targeting and 20% on creative. It should be the reverse. Meta's Advantage+ and Google's Performance Max have automated most targeting decisions. According to <a href="https://www.marpipe.com/blog/meta-advantage-plus-pros-cons" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">recent research</a>, 70-80% of Meta ad performance now stems from creative quality, not budget or targeting. At <a href="/case-studies/dil-mil-story" class="text-primary hover:underline">Dil Mil</a>, we learned this the hard way. Early on, we obsessed over audience segments and lookalike percentages. The breakthrough came when we shifted focus to creative velocity: testing more variations, killing losers faster, and scaling winners aggressively. That mindset shift is what enabled us to scale paid acquisition profitably.
Start With Hypotheses, Not Random Ideas: Before we launched a single ad at <a href="/case-studies/dil-mil-story" class="text-primary hover:underline">Dil Mil</a>, we listed our assumptions. What emotional triggers would resonate with the South Asian diaspora? Was it belonging? Cultural identity? Fear of missing out on 'the one'? We mapped these hypotheses to creative concepts before spending a dollar. For the <a href="/case-studies/dil-mil-valentines-day-love-is" class="text-primary hover:underline">Love Is Valentine's campaign</a>, the hypothesis was specific: our audience loves music, art, and dance. Instead of creating an ad that interrupted their experience, we decided to become part of their experience by partnering with creators like Humble the Poet, Samica, and Raaginder. That hypothesis shaped the entire campaign and drove millions of views. Random creative testing is expensive. Hypothesis-driven testing is how you learn.
Build a Testing Matrix: We structured every test around four variables: Hook (first 3 seconds), Format (UGC vs produced vs motion graphics vs static), Message (benefit-focused vs identity-focused vs social proof), and CTA (soft vs hard). At any given time, we had a live matrix tracking which combinations were active, what stage of testing they were in, and performance against benchmarks. This wasn't a spreadsheet someone updated weekly; it was a living system reviewed daily. The matrix forced discipline. When someone pitched a new creative concept, the first question was: 'Which variable are we testing?' If the answer was 'everything,' we sent them back to isolate the hypothesis.
The Quick Kill Discipline: Most teams let underperforming ads run for weeks hoping they'll 'optimize.' We gave every creative 5-6 days. That's enough time for the algorithm to exit the learning phase and gather meaningful signal, but not so long that you're wasting budget on losers. If a creative couldn't hit minimum CTR and hook rate thresholds in that window, it was dead. No emotional attachment. No 'let's give it another week.' This discipline is what enabled our velocity. By making kill decisions quickly, we freed up budget and attention for new tests. Over a month, we'd cycle through dozens of variations while a typical team might test a handful. The key insight: you learn more from testing many creatives and killing underperformers decisively than from slowly optimizing a few mediocre ones. As <a href="https://www.facebook.com/business/help/1738164643098669" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Meta's guide to A/B testing ad creatives</a> emphasizes, the goal is to validate insights quickly while accounting for the constantly changing digital landscape.
The Content Waterfall (Maximize Every Asset): One piece of content should never be one ad. For the <a href="/case-studies/dil-mil-valentines-day-love-is" class="text-primary hover:underline">Love Is campaign</a>, we started with a single long-form video featuring five creators. From that one shoot, we produced: 15-second teasers for IG Stories, vertical cuts optimized for TikTok, behind-the-scenes footage for organic posts, the full-length video for YouTube, and still frames for static ads. This 'Content Waterfall' approach meant every production investment generated many distinct ad units across platforms. It's not about creating more content; it's about extracting more value from the content you create. We applied the same thinking to the <a href="/case-studies/music-videos" class="text-primary hover:underline">Fateh DOE music video</a>. As associate producer, we had access to raw footage, BTS content, and multiple cuts. Each became a distinct creative asset for the paid campaign.
Platform-Native Creative (Not One-Size-Fits-All): A Facebook carousel does not work on TikTok. A polished 30-second brand video does not work on Snapchat. Every platform has its own creative language. At Dil Mil, our Meta creative leaned polished: carousel ads, video testimonials, dynamic retargeting with profile photos. Our Snapchat creative was raw and fast: full-screen vertical video that felt native to the platform. TikTok was even more casual: creator-led content that looked like organic posts, not ads. <a href="https://ads.tiktok.com/help/article/creative-best-practices?lang=en" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">TikTok's own research</a> shows that 90% of ad recall impact is captured within the first six seconds, and ads featuring talent showing 4+ emotions see significantly higher conversion rates. For the Love Is campaign, we didn't just resize the same video. We re-edited for each platform's consumption pattern: hook-first for TikTok (you have one second), story-arc for YouTube (they'll watch longer), swipe-friendly for IG Stories. The <a href="/case-studies/music-videos" class="text-primary hover:underline">Fateh DOE campaign</a> reinforced this: the winning thumbnail on YouTube was an emotionally charged close-up showing the artist's face alongside the female lead from the music video. <a href="https://www.searchenginejournal.com/do-faces-help-youtube-thumbnails-heres-what-the-data-says/563944/" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Research on thumbnail best practices</a> confirms why this works: thumbnails featuring expressive human faces can significantly increase click-through rates. That creative wouldn't have worked on Meta. Platform-native means rethinking the creative, not just the crop.
The Double-Funnel (Creative as Retargeting Fuel): Most teams think of creative testing as top-of-funnel only. We used creative performance data to build our retargeting strategy. For the <a href="/case-studies/dil-mil-valentines-day-love-is" class="text-primary hover:underline">Love Is campaign</a>, anyone who watched a significant portion of the video got retargeted with 'Install Now' performance ads. The long-form content warmed them up emotionally; the retargeting ad closed the deal. This 'Double-Funnel' approach drove meaningful uplift in installs during the campaign window. The principle: your best awareness creative creates warm audiences. Your best conversion creative harvests them. Test both, and connect them. This is where creative testing intersects with lifecycle. The creative that acquires a user and the messaging that retains them should tell a consistent story.
Scale Winners, Fight Fatigue: Even your best ad has a shelf life. We called high-performing variations that were starting to decay 'fatigue fighters.' When a winning concept's CTR started declining (usually after a few weeks at scale), we'd launch several variations on the same concept: different hooks, different music, different thumbnails, same core message. At Dil Mil, our best-performing concepts often ran for months in different iterations. The core insight or emotional hook stayed the same; the execution refreshed constantly. Keep a 'Creative Hall of Fame' document that logs every winning concept, why it worked, and what variations were tested. This institutional knowledge is invaluable as the team scales. When the person who discovered a winning insight leaves, that knowledge shouldn't leave with them.
Test one variable at a time. If you change the hook, format, message, AND CTA simultaneously, you learn nothing. Isolate variables.
Judge creative on conversion metrics, not vanity metrics. High CTR with terrible conversion rate means your ad is clickbait, not effective creative.
Invest in production that generates multiple assets. One video shoot should produce 10-15 distinct ad units across platforms. One asset = one test is a losing formula.
Refresh retargeting creative constantly. Your retargeting ads fatigue even faster than prospecting ads because the audience is smaller.
Document everything. If the person who ran the test leaves and nobody knows why Concept A worked, you're starting from zero. Build institutional creative knowledge.
Positioning Is a Strategy, Not a Tagline
If you're a founder trying to figure out how to differentiate in a crowded market, or a CMO tasked with repositioning a brand that's lost its edge, you've probably been handed a 'positioning statement template' that looks like a Mad Libs exercise. Fill in the blanks: 'For [target] who [need], [brand] is the [category] that [benefit].' That template is fine for a slide deck. It's useless for actually making decisions. Most companies confuse positioning with taglines or mission statements. They're not the same thing. As <a href="https://www.aprildunford.com/post/a-quickstart-guide-to-positioning" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">April Dunford</a>, the leading authority on positioning, puts it: positioning defines how your product is different and better than alternatives for a particular set of customers. Strong positioning makes every marketing decision easier: creative direction, channel selection, partnerships, and pricing all ladder up to it. Weak positioning forces you to compete on features and price, which is a race to the bottom. <a href="https://www.alries.com/positioning" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Ries and Trout's foundational work</a> established that positioning happens in the customer's mind, not on your website. You don't create positioning; you claim a space that already exists in how customers think about your category. At <a href="/case-studies/dil-mil-story" class="text-primary hover:underline">Dil Mil</a>, the positioning shift from utility ('dating app for South Asians') to identity ('Find Something Real') changed everything downstream. This framework is how I approach positioning across consumer apps, e-commerce brands, and B2B services.
Understand What You're Actually Competing Against: Most competitive analysis is useless because it looks at the wrong competitors. At <a href="/case-studies/dil-mil-story" class="text-primary hover:underline">Dil Mil</a>, our real competition wasn't Tinder or Bumble. It was cultural inertia: the 'Seema Aunties' of the world (if you've seen Indian Matchmaking on Netflix, you know exactly what I mean), Shaadi.com, and the deeply held expectation that South Asian dating should be family-driven. At <a href="/case-studies/trilux-tech" class="text-primary hover:underline">Trilux Tech</a>, the competition wasn't other consulting firms. It was 'do nothing': enterprise buyers sticking with their current vendor because switching felt risky. At <a href="/case-studies/bay-area-print-pro" class="text-primary hover:underline">Bay Area Print Pro</a>, the competition was FedEx Office and Staples: the 'good enough' default. Before you can position yourself, you need to honestly name what you're positioning against. And it's rarely who you think. Your competition might be another product, inertia, an old way of doing things, or a deeply held belief. Name it specifically.
Find the Gap Nobody Else Owns: At Dil Mil, we mapped the landscape and found a clear gap: nobody owned 'modern diaspora dating.' There were matrimonial sites (Shaadi.com, BharatMatrimony) on one end and mainstream dating apps (Tinder, Hinge) on the other. The space between, where young South Asians wanted cultural connection without the parental pressure, was wide open. At Bay Area Print Pro, the gap was urgency. Big-box print shops offer convenience but not speed. BAPP could promise same-day and emergency turnaround. That gap became the entire positioning: 'The Bay Area's Emergency B2B Print Hub.' Finding the gap requires talking to customers, not just analyzing competitors. At Trilux Tech, conversations with the founders revealed that their clients chose them because of deep domain expertise in specific verticals (ServiceNow, data analytics). That trust and specialization was the gap. The gap must be: real (customers actually care about it), defensible (you can actually deliver on it), and ownable (no one else is claiming it the way you are).
Choose Identity Over Utility: This is the single biggest positioning lesson I've learned. Utility positioning ('we do X for Y') is clear but forgettable. Identity positioning ('we are the brand for people who Z') creates emotional connection and loyalty. At <a href="/case-studies/dil-mil-brand-reach" class="text-primary hover:underline">Dil Mil</a>, 'dating app for South Asians' is utility. 'Find Something Real' is identity. The first describes a feature. The second describes a feeling. The identity positioning unlocked brand partnerships with cultural festivals, musicians, and creators because we weren't selling an app; we were championing a cultural movement. At <a href="/case-studies/plated-by-py" class="text-primary hover:underline">Plated by Py</a>, we made the same shift. Payal's old Squarespace blog positioned her as 'a food blogger.' The rebrand positioned her as a Creative Chef blending heritage with modern craft. That identity carries through the visual design, the product packaging direction, and the brand voice. Not every brand needs to be a 'movement.' Trilux Tech's positioning is straightforward B2B trust. BAPP's positioning is speed and reliability. But even in B2B, the positioning should connect to something the buyer cares about emotionally: trust, risk reduction, confidence.
Carry Positioning Through Every Touchpoint: Positioning that lives in a strategy doc but doesn't show up on your website, in your ads, in your onboarding emails, and in your customer support tone is useless. At <a href="/case-studies/plated-by-py" class="text-primary hover:underline">Plated by Py</a>, we designed the complete brand identity from scratch: logo, color palette, typography, visual language. Then we carried it through every touchpoint: product pages, recipe content, packaging photography direction, email templates, and the overall site experience. Every element communicates 'heritage meets modern craft.' At <a href="/case-studies/trilux-tech" class="text-primary hover:underline">Trilux Tech</a>, 'trust architecture' wasn't just a positioning statement. It was a design principle. Clean layouts, professional photography, structured service pages, client testimonials prominently featured. Every pixel was designed to make an enterprise buyer think: 'these people are serious.' At Dil Mil, the positioning shift showed up in creative (identity-driven campaigns outperformed feature-driven ads), in partnerships (cultural festivals and creators, not just performance media), and in product (the app experience reflected cultural understanding). Test: pick any touchpoint in your customer journey. Does it reinforce your positioning? If not, you have a gap.
Validate With Real Customers, Then Commit: Positioning is a hypothesis until customers confirm it. At Dil Mil, we tested identity-driven creative against feature-driven creative. Identity won consistently: higher engagement, better brand recall, stronger downstream metrics. At BAPP, the 'emergency print hub' positioning was validated by search data: the highest-converting keywords were urgency-driven ('same day printing near me,' 'emergency print shop Bay Area'). The market told us the positioning was right. At Plated by Py, we validated through organic search performance. Within months of launching the repositioned brand, the site gained meaningful search visibility. The SEO strategy worked because the positioning was clear and specific enough to target. Once validated, commit. The biggest positioning mistake is hedging: trying to be everything to everyone. Strong positioning means saying no to opportunities that don't fit. At Dil Mil, we turned down partnership opportunities that didn't align with the 'modern diaspora' identity, even when they offered reach. As <a href="https://www.shopify.com/blog/brand-positioning" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Shopify's brand positioning guide</a> emphasizes, differentiation requires making clear choices about what you are and what you're not.
Know When to Evolve: Positioning isn't permanent. Markets shift, audiences evolve, and what worked at one stage might not work at the next. Dil Mil's positioning evolved as the company grew. Early on, it was about establishing credibility ('we're a real dating app, not a joke'). Mid-stage, it shifted to cultural identity ('Find Something Real'). Later, as the user base scaled, it evolved again to reflect the breadth of the community. The key is knowing when to evolve versus when to stay the course. Evolve when: customer feedback consistently doesn't match your positioning, you've outgrown your original market segment, or competitive dynamics have shifted. Stay the course when: you're tempted to chase a trend, a loud minority wants something different from your core audience, or you haven't given the current positioning enough time to work. Repositioning is expensive and confusing. Don't do it because of one bad quarter. Do it because of a fundamental market shift.
Confusing positioning with taglines is the most common mistake. A tagline is an expression of your positioning, not the positioning itself. 'Find Something Real' only works because the underlying positioning ('modern diaspora dating for people who want cultural connection without traditional pressure') is solid.
Positioning by committee produces bland results. If everyone in the room has input, you'll end up with something that offends nobody and inspires nobody. Positioning requires a strong point of view.
Copying competitor positioning isn't positioning at all. If your positioning sounds like your competitor's with one word changed, you don't have positioning. You have a slightly different tagline.
Not stress-testing with customers is a fatal error. The positioning that sounds brilliant in a boardroom might mean nothing to your actual buyer. Test early, test often.
Every marketing decision gets easier when your positioning is clear. Channel strategy, creative approach, influencer selection, and pricing all ladder up to positioning. Get it right, and marketing gets easier. Get it wrong, and no amount of ad spend will save you.
The Influencer Playbook: Building an Engine That Actually Converts
If you're a brand marketer trying to figure out influencer marketing, or a DTC founder who's been burned by paying creators for posts that generated likes but no sales, the problem isn't influencer marketing itself. It's that you're running campaigns when you should be building a system. One-off sponsored posts are the equivalent of running one ad and calling it a strategy. Influencer marketing is now a $32+ billion industry according to the <a href="https://influencermarketinghub.com/influencer-marketing-benchmark-report/" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Influencer Marketing Hub's 2025 Benchmark Report</a>, but most brands waste money on it. The gap between 'paying someone to post' and 'building a creator engine' is massive. Most guides focus on finding influencers. The hard part is structuring partnerships, measuring ROI, and scaling without losing authenticity. At <a href="/case-studies/dil-mil-brand-reach" class="text-primary hover:underline">Dil Mil</a>, we built a decentralized influencer network of 200+ creators generating tens of millions of impressions. That network wasn't a vendor list; it was a community. Some of our best-performing creators started as actual users of the app. This guide is what I learned building that engine from scratch.
Start With Community, Not Follower Count: At <a href="/case-studies/dil-mil-brand-reach" class="text-primary hover:underline">Dil Mil</a>, we didn't search for influencers with the biggest followings. We searched for creators who were already part of the South Asian diaspora community. The difference matters: a creator with 500K followers who happens to be South Asian is not the same as a creator with 50K followers who is deeply embedded in the culture. For our #StraightfromtheDil campaign, every creator was selected because their audience already cared about the same things our users cared about: identity, culture, dating, and belonging. That alignment meant their Dil Mil content didn't feel like an ad; it felt like a natural extension of what they already posted. For <a href="/case-studies/jaloos" class="text-primary hover:underline">Jaloos</a>, we didn't partner with traditional influencers at all. We went to Desi and Brown meme accounts on Instagram. These pages had massive, highly engaged audiences of exactly our target demographic. They posted our drop announcements as native content, and it drove traffic directly to the Shopify store with zero traditional ad spend.
Build a Creator Pyramid (But Weight It Toward Micro): We structured Dil Mil's creator program in tiers. At the top: celebrity partnerships for massive reach and credibility. In the middle: established creators (50K-500K) like Humble the Poet and Samica who brought both audience and creative quality. At the base: a wide network of micro-creators (5K-50K) who drove volume and authenticity. The counterintuitive learning: our micro-creators often outperformed the bigger names on engagement rate and cost-per-acquisition. Their audiences were tighter, more trusting, and more likely to take action. <a href="https://grin.co/blog/macro-influencers-or-micro-influencers/" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Research from GRIN</a> confirms this pattern: micro-influencers consistently deliver higher engagement rates and conversion rates than macro-influencers. Over time, we scaled to 200+ creators in the network. But it started with 10 creators we knew personally. Start small, prove the model, then scale.
Let Creators Be Creators (The Anti-Script Approach): The biggest mistake brands make is handing creators a script. We learned this early at Dil Mil. The best-performing content came from creators who integrated the brand into their natural style. For #StraightfromtheDil, we gave each creator a brief with key messages and brand guidelines, but we let them interpret it through their own lens. A musician wove Dil Mil into their creative process. A lifestyle creator worked it into their daily routine. A comedian turned it into storytelling. The result was 9+ pieces of content that all felt different but all felt real. The <a href="/case-studies/dil-mil-valentines-day-love-is" class="text-primary hover:underline">Love Is campaign</a> took this further. We partnered with Humble the Poet, Samica, Ritual by Design, bfunk, and Raaginder and asked each of them to showcase what love meant to them. Not 'download Dil Mil.' Not 'swipe right.' Just: what does love mean to you? The brand was the platform for the conversation, not the subject of it. This approach requires trust. You have to be comfortable with creators interpreting your brand in ways you didn't expect. But the authenticity dividend is enormous.
The Content Waterfall (One Shoot, Ten Assets): Production is expensive. The Content Waterfall strategy maximizes every partnership. For the <a href="/case-studies/dil-mil-valentines-day-love-is" class="text-primary hover:underline">Love Is campaign</a>, one shoot with five creators produced: a long-form YouTube video, 15-second teaser cuts for IG Stories, vertical edits optimized for TikTok, behind-the-scenes footage for organic feed posts, still frames for static ad units, and quote cards for Twitter/X. That's 10-15 distinct creative assets from a single production day. Each asset was platform-native, not just resized. When I was associate producer on the <a href="/case-studies/music-videos" class="text-primary hover:underline">Fateh DOE music video</a>, we applied the same thinking. BTS footage, raw cuts, social teasers, the full video, thumbnail variations. Every piece of content from the production became a marketing asset. Always negotiate usage rights upfront. The content creators produce should fuel your paid media for months, not just live on their feed for 24 hours.
Measure Like a Performance Marketer, Not a Brand Marketer: Most influencer programs track vanity metrics: impressions, likes, comments. That's necessary but insufficient. At Dil Mil, we tracked every creator back to installs and downstream engagement. The Love Is campaign Double-Funnel: anyone who watched a significant portion of a creator's video got retargeted with performance ads. This bridged the gap between brand awareness and measurable conversion, driving meaningful uplift in installs during the campaign window. The key metrics we tracked at Dil Mil: CPM (cost per thousand impressions), CPE (cost per engagement), CPI (cost per install via attributed creator content), and downstream retention of influencer-acquired users vs paid-acquired users. For Jaloos, measurement was simpler: unique discount codes per creator/meme account, tracked through Shopify. We knew exactly which partnerships drove revenue. Each business has different measurement needs; the point is to pick metrics that tie back to outcomes, not just engagement. <a href="https://www.creatoriq.com/blog/calculate-influencer-marketing-roi-smv" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">CreatorIQ's ROI measurement framework</a> offers a solid starting point for building your own attribution model. If you can't measure it back to a business outcome, you're doing brand awareness, not influencer marketing. Both have value, but know which one you're doing.
Scale the Engine Without Losing the Soul: Going from 10 creators to 200+ requires systems. At Dil Mil, we built: a creator CRM tracking every partnership (deliverables, compensation, performance, relationship notes), templatized briefs that maintained brand consistency while allowing creative freedom, a content calendar coordinating creator posts with product launches and cultural moments, and a performance dashboard tracking ROI per creator per campaign. We also invested in field marketing partnerships: 5X Fest, Product of Culture, Popshift, and Browngirl Mag. These weren't traditional influencer deals; they were community partnerships that gave us cultural credibility and access to events where our audience gathered IRL. The principle: influencer marketing at scale is community building, not media buying. If you treat it like buying ad placements, you'll get ad-quality results. If you treat it like building a community of brand advocates, you'll get something much more powerful.
Optimize for audience alignment, not follower count. A creator with 10K followers in your exact demographic is worth more than one with 500K general followers.
Don't over-script creators. The whole point of influencer marketing is authenticity. If you wanted to control every word, you should have made an ad.
Build ongoing relationships, not one-off campaigns. Your best creators should be long-term partners. The first post is always the worst; the fifth post, when they actually understand and love the product, is gold.
Always negotiate usage rights. If you can't use creator content in your paid media, you're leaving the best asset on the table.
Integrate influencer content everywhere. At Dil Mil, creator content fed our paid media (whitelisting), our organic social, our lifecycle marketing (email/push creative), and even our app store screenshots.
Zero Ads, Six Figures: An E-Commerce Launch Framework
If you're a first-time e-commerce founder staring at a Shopify dashboard wondering how to get your first sales without burning through savings on Meta ads, this playbook is for you. The default DTC playbook — build store, run ads, pray for ROAS — works if you have budget. But if you're bootstrapping or want to build a brand that doesn't depend on paid acquisition, there's another way. According to <a href="https://www.shopify.com/blog/percentage-of-businesses-that-fail" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Shopify's own research</a>, about 20% of businesses fail in their first year, with e-commerce facing even tougher odds due to low barriers to entry and intense competition. Most e-commerce businesses lose money in their early years because they default to paid acquisition before building organic demand. The tools have never been more accessible: Shopify, Klaviyo, AI development tools. But most stores still launch without a real distribution strategy. The difference between a store that does $5K and one that does $122K in year two isn't the platform or the product. It's the launch engine. At <a href="/case-studies/jaloos" class="text-primary hover:underline">Jaloos</a>, we built that engine around scarcity, cultural timing, and community distribution. At <a href="/case-studies/plated-by-py" class="text-primary hover:underline">Plated by Py</a>, we built it around content-led commerce and SEO. Different strategies, same principle: launch is a strategy problem, not a technical one.
Nail Your Launch Strategy Before You Touch a Single Pixel: Most founders start with the store. Pick a theme, upload products, launch. That's backwards. At <a href="/case-studies/jaloos" class="text-primary hover:underline">Jaloos</a>, we spent weeks defining the launch strategy before writing a line of code. The strategy had three pillars: scarcity (limited-edition drops, not an always-available catalog), cultural timing (drops aligned with Diwali, Eid, and cultural holidays when our audience was most engaged), and community distribution (partnering with popular Desi and Brown meme accounts on Instagram, not running ads). For <a href="/case-studies/plated-by-py" class="text-primary hover:underline">Plated by Py</a>, the strategy was different: content-led commerce. Payal already had an audience through her food blog. The strategy was to migrate that audience from Squarespace to Shopify while adding a hot sauce line alongside the recipe content. The recipes drive organic traffic; the products monetize it. Your launch strategy answers three questions: Who is your first customer? How will they find you? Why will they buy NOW instead of later? If you can't answer those questions clearly, you're not ready to launch.
Build the Store for Conversion, Not Beauty: A gorgeous store that doesn't convert is an expensive portfolio piece. Every design decision should reduce friction between 'I want this' and 'I bought this.' At Jaloos, the store was simple by design. Limited products (scarcity), prominent countdown timers (urgency), clear sizing and shipping info (reducing purchase anxiety), and a streamlined checkout. Nothing fancy. Just fast. For Plated by Py, we used AI-powered development tools (Claude Code, Bolt.new, Replit, Cursor, v0 by Vercel) to build a custom Shopify theme that merged content and commerce. Recipe pages flowed naturally into product pages. The hot sauce wasn't a separate store; it was integrated into the cooking experience. <a href="https://baymard.com/blog/ecommerce-checkout-usability-report-and-benchmark" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Baymard Institute research</a> shows that 70% of e-commerce users abandon their carts, but optimizing checkout design alone can increase conversion rates by up to 35%. Mobile-first is non-negotiable. Over 70% of Jaloos traffic came from Instagram, which means over 70% was mobile. Test your checkout on your actual phone before you test anything else. I guarantee something is broken or annoying. Tools: Shopify (our go-to), Big Cartel (for simpler stores), Printful (for print-on-demand fulfillment).
Build Your Email List Before Launch Day: Your email list is the single most valuable asset in e-commerce. At Jaloos, we built a 1.7K+ subscriber list before our first major drop. That list became our primary distribution channel. The strategy: teaser content on social media ('something's coming'), a landing page with email capture ('get early access'), and a countdown sequence building anticipation. By the time the drop went live, we had hundreds to thousands of people waiting to buy. For Plated by Py, we set up the full email infrastructure before launch: a welcome sequence introducing Payal's story and the brand, abandoned cart recovery flows, post-purchase sequences featuring recipes with the hot sauces customers just bought, and re-engagement campaigns for customers who hadn't ordered in 90 days. According to <a href="https://www.klaviyo.com/blog/abandoned-cart-benchmarks" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Klaviyo's benchmark data</a>, abandoned cart flows achieve a 3.33% conversion rate on average, with top performers hitting 7.69%. Three-email abandoned cart sequences generated $24.9 million across Klaviyo's customer base compared to just $3.8 million from single emails. The Jaloos email engine delivered 6.5x ROAS. For every dollar spent on Klaviyo, we generated $6.50 in revenue. No paid ad channel came close to that efficiency. Tools: Klaviyo (our go-to for e-commerce email), Shopify Email (budget option).
The Drop Model vs Always-On: Choose Your Launch Rhythm: There are two e-commerce models: always-available and scarcity-driven drops. Most guides assume you're doing always-available. Jaloos proved that the drop model can be dramatically more effective for the right brand. The Drop Model works when: your product has cultural relevance, your audience has FOMO tendencies, you can create genuine scarcity (limited runs, not fake countdowns), and you have a distribution channel that can spike traffic on demand. At Jaloos, each drop was a coordinated event. Two weeks before: teaser content on social. One week before: Klaviyo email sequence building anticipation. Drop day: simultaneous email blast + meme account posts + IG stories. The result: concentrated demand that created its own social proof. When people see 'sold out in 24 hours,' they don't want to miss the next one. Some drops sold out in under a day. <a href="/case-studies/plated-by-py" class="text-primary hover:underline">Plated by Py</a> uses the always-on model because hot sauce isn't a scarcity product. The recipe content drives steady organic traffic, and the products are always available. Different product, different model. Know which model fits your brand. Don't force scarcity on a commodity product, and don't do always-on for something that thrives on exclusivity.
SEO and AI Findability: The Long Game: Paid ads give you customers today. SEO gives you customers forever. At <a href="/case-studies/plated-by-py" class="text-primary hover:underline">Plated by Py</a>, we invested heavily in technical SEO and content optimization from day one. The results: 0 to 5.7K search impressions in the first three months, with organic traffic coming from 5 countries. Recipe pages ranking for terms that drive consistent traffic. Each ranking page is a permanent customer acquisition channel that costs nothing per click. Beyond traditional SEO, we optimized for AI findability: structured data, clean semantic HTML, and optimized meta content so the brand surfaces in AI-powered search tools (ChatGPT, Perplexity, Google AI Overviews), not just traditional Google results. The site is crawlable by all major AI tools. For Jaloos, SEO was less critical because the drop model relies on event-driven traffic spikes. But even there, we ensured product pages were indexable and the brand had basic search presence for branded queries. The lesson: invest in SEO infrastructure on day one, even if you won't see results for months. It compounds. Tools: Google Search Console, GA4 for analytics, Ahrefs or SEMrush for keyword research.
Post-Launch Is Where the Real Work Starts: Launch day is exciting but meaningless if you don't have a post-launch operating rhythm. At Jaloos, post-launch meant: daily monitoring of sales velocity and inventory, analyzing which meme accounts drove the most traffic (tracked via UTMs), reviewing email performance (open rates, click rates, revenue per email), and planning the next drop based on what sold and what didn't. At Plated by Py, post-launch meant: monitoring Google Search Console for new keyword opportunities, analyzing which recipes drove the most traffic and adding product CTAs to those pages, optimizing email flows based on performance data, and iterating on the site based on user behavior. For <a href="/case-studies/surinder-seerat" class="text-primary hover:underline">Surinder Seerat</a>, the post-launch focus was different: tracking book sales, monitoring which content drove conversions, and building the roadmap for audiobooks and courses. The first 30 days after launch are about learning, not celebrating. What's converting? What's not? Where are people dropping off? Which email flows are driving revenue? Answer these questions in the first month and you'll have the playbook for the next twelve.
Spending money on ads before you have organic demand is the most common mistake. If nobody wants your product without ads, ads won't fix that. They'll just make your losses faster. Jaloos proved you can do six figures with zero ad spend. Start organic, then amplify with paid.
Skipping email infrastructure leaves money on the table from hour one. <a href="https://www.klaviyo.com/blog/abandoned-cart-benchmarks" target="_blank" rel="noopener noreferrer" class="text-primary hover:underline">Klaviyo data</a> shows abandoned cart flows convert at 3.33% on average, with top performers more than doubling that. Not having them on launch day is leaving revenue behind.
Over-investing in design and under-investing in distribution is a trap. A beautiful store with no traffic plan is a tree falling in the forest. Split your pre-launch time 50/50 between building the store and building the audience.
Launching with too many products creates confusion. Jaloos launched with limited SKUs per drop. Plated by Py launched with a focused hot sauce line. Constraint creates clarity for both you and the customer.
The tools for launching have never been more accessible. But accessibility doesn't mean success. The stores that win treat launch as a strategy problem, not a technical one.
Frequently Asked Questions
Q: Who do you typically work with? A: Everyone from a local pizza shop owner trying to get more foot traffic to a Fortune 500 marketing team launching a new product line. I've worked with mom-and-pop businesses, e-commerce brands, B2B SaaS companies, D2C startups, B2C consumer apps, authors, content creators, luxury service providers, government agencies (DVBE-certified engagements), enterprise tech companies, and nonprofits. The common thread isn't the industry — it's founders and leaders who know they need growth but aren't sure how to build the system.
Q: What does a typical engagement look like? A: It depends on the need. I offer three models:
Fractional CMO / Growth Leadership — I embed with your team as your part-time head of marketing. Strategic direction plus hands-on execution. Typically 3-6 month minimum.
Project-Based — Scoped to a specific deliverable: a product launch, a GTM audit, a paid media overhaul, a website redesign, a brand positioning sprint.
Advisory / Coaching — Ongoing strategic guidance for founders and marketing leaders. Lighter touch, higher leverage. Monthly retainer with async access.
Q: How quickly can you start? A: Most engagements begin within 1-2 weeks. I keep limited capacity intentionally — I'd rather go deep with fewer clients than spread thin across many.
Q: Do you work with companies outside San Francisco? A: Yes. Most of my work is remote. I've worked with companies across the Bay Area, Los Angeles, New York, Toronto, London, and internationally. Location doesn't limit the work.
Q: What's the minimum budget to work together? A: It varies by engagement type. Project-based work starts in the low four figures. Fractional leadership is a monthly retainer. I'm upfront about pricing on the first call — no surprises.
Q: What services do you offer? A: The full spectrum of growth marketing: GTM strategy, lifecycle marketing (onboarding, retention, win-back), performance marketing (Meta, Google, TikTok, programmatic), brand strategy and positioning, e-commerce and DTC launch strategy, influencer and creator marketing, content strategy, email marketing, SEO, local SEO, website design and development, video production, photo production, social media management, AI-enabled marketing systems, and marketing automation. I also build websites, landing pages, and Shopify/Squarespace stores.
Q: Do you do creative work too, or just strategy? A: Both. I've directed music videos, produced brand campaigns, managed photo shoots, and built websites from scratch — alongside the strategic work. That's the difference: I don't just write the playbook, I can execute every page of it. Strategy without execution is a PowerPoint. I build the whole thing.
Q: Can you help with AI and marketing automation? A: Yes. I build AI-native marketing systems — from custom AI agents and chatbots to automated content pipelines, rapid website builds, and prompt engineering systems. The goal is always the same: ship faster, spend smarter, scale without adding headcount.
Q: Do you work with e-commerce and Shopify stores? A: Yes. I've launched e-commerce brands from zero (Jaloos — $122K revenue, zero ad spend), optimized existing stores (Kulture Khazana — 3x ROAS), and built Shopify and Squarespace sites for multiple clients. I handle everything from store setup to email flows to paid acquisition.
Q: Do you do local SEO and Google Business optimization? A: Yes. I've taken local businesses from invisible to #1 in local search results. A1 Limo went from inconsistent leads to 173% revenue growth through Google Business Profile optimization, local SEO, Yelp, and a full site redesign. This applies to any local business — restaurants, service providers, medical practices, law firms, you name it.
Q: Can you help with government or DVBE contracts? A: Yes. I have experience with DVBE (Disabled Veteran Business Enterprise) certified engagements and understand the requirements for government marketing and communications work.
Q: What kind of results can I expect? A: It depends on where you're starting, but here are benchmarks from past work: Scaled Dil Mil from startup to acquisition by The Dating Group, $122K revenue with zero ad spend for a new e-commerce brand (Jaloos), 3x ROAS on paid social (Kulture Khazana), 173% revenue growth for a local service business (A1 Limo), $1.30 CPI at 50% below industry benchmarks (TheSnapback), 40M+ organic impressions through influencer strategy. I don't promise specific numbers, I promise a system that compounds.
Q: How do you measure success? A: Revenue first, always. Then the leading indicators that drive it — CAC, LTV, retention rates, conversion rates, pipeline velocity, organic traffic. I set up measurement infrastructure before scaling spend. If we can't measure it, we don't scale it.
Q: What makes you different from other marketing consultants? A: Three things. First, I've actually done it — scaled a startup to acquisition, managed eight-figure budgets at Intuit, built brands from zero. Not theoretical. Second, I do both strategy and execution — I'll build your GTM roadmap and then run the campaigns myself. Third, I come from both sides: Fortune 500 process and data discipline combined with startup speed and scrappiness. Most consultants have one or the other.