Growth and Lifecycle/CRM leader who scaled monthly revenue $50K → $320K+ by turning customer behavior into repeat revenue, with a paid-acquisition foundation (Meta, Google Ads, Amazon, $480K+/yr, 5.5×–12.19× ROAS) most CRM leaders don't have. GCC, US & South Asian markets.
Growth and lifecycle marketing leader with 10+ years across performance and retention marketing. The last several years I've focused on turning CRM into something that drives revenue, not just a campaign function.
I've led cross-functional teams of up to 7, owning P&L and reporting growth performance directly to founders. Performance marketing discipline, incrementality, attribution, budget efficiency, is what I bring into CRM and lifecycle: behavioral segmentation, automation and treating retention as a revenue channel rather than a support function.
Right now I own end-to-end CRM and lifecycle strategy for a consumer marketplace on Customer.io, covering every email, WhatsApp message and automated flow a customer gets from their first booking onward. I built the segmentation and n8n automation layer myself, connecting real-time customer behavior into Customer.io so messaging responds to what a customer does instead of which list they sit on. I built a Gen-AI voice agent into the live booking funnel that lifted bookings 30% in a month. Monthly revenue on that business grew from $50K to over $320K in 8 months largely off the back of that work.
My foundation is in performance marketing, which is why I lead with numbers. I've owned paid media budgets of $480K+ a year across Meta, Google Ads and Amazon, holding a blended ROAS between 5.5× and 12.19× and scaling paid spend 20× at 1 DTC brand. That's why I build lifecycle systems that account for what a customer actually cost to acquire, not just what they do after they sign up.
Scaled monthly revenue from $50K to $320K+ by owning the entire growth function. Developed bilingual Arabic/English Meta, Google and TikTok campaigns for GCC audiences. Built n8n-powered behavioral booking workflows across WhatsApp, SMS and email and deployed a GenAI voice calling agent driving a 30% booking increase within one month. Onboarded 15+ charter companies and 80+ yachts.
Scaled monthly paid media spend from $2K to $40K+ (a $480K+ annualised run rate, 20× growth) across Meta, Google Ads and Amazon using attribution and incrementality modeling. Owned monthly budget allocation across channels based on incremental ROAS data, holding a blended 5.5×–12.19× ROAS while doubling DTC revenue year on year.
Built end-to-end retention funnels via WhatsApp Business API, email and SMS, segmented by cart value and time-since-abandon rather than a blanket weekly send. Also managed Amazon Sponsored Products, Brands and Display, lifting ROAS to 4.2× through precision keyword targeting and bid adjustments.
Built a systematic creative testing framework developed winning ad concepts, tested copy and visual variations and identified high-performing creatives before data confirmation. Improved CTR by 16% and increased team ROAS by 15% through structured experimentation.
Managed 15+ DTC eCommerce brands across Meta, Google Ads, TikTok and LinkedIn simultaneously spanning luxury, fashion, retail and F&B. Scaled a US Fashion/Retail brand from $20K to $25K/month budget, generating $120K+ in revenue within 3 months at 3.5× ROI.
Ran targeted B2B campaigns across LinkedIn, Meta and Google Ads managing ~$10K/month. Achieved 3.8× ROAS through audience testing. Improved conversion rates by 30% via landing page testing and improved lead quality by 40% through better audience segmentation and targeting.
Content was driving a flood of enquiries (some videos hit a million views), but a lot were going cold before booking. The obvious fix was hiring more people to reply faster. On paper that solves the response-time problem. It also doesn't scale and it's expensive relative to the size of the team.
I dug into where exactly people were dropping off before building anything. The data showed it wasn't creative fatigue or pricing. It was response speed and follow-up consistency. I proposed a GenAI voice agent that responds first, qualifies the enquiry and hands only the serious ones to a human. The risk: a bad automated experience could hurt trust with a premium audience. I tested it on a subset first so I could kill it fast if it hurt conversion.
Bookings went up 30% month over month on enquiries that went through the agent, measured against the pre-agent baseline (same traffic sources, same enquiry type). The lift came almost entirely from response speed and consistent follow-up. The lesson: the instinct to throw people at a speed problem is usually wrong. The right fix is a system and you prove it on a slice before betting the whole funnel on it.
Early lifecycle emails on Klaviyo treated every visitor the same: one welcome sequence, one generic cart-abandonment reminder sent on a weekly calendar, regardless of whether someone was a first-time browser or a repeat buyer who'd purchased three times already. Open and click rates were mediocre and nobody could say why a specific send underperformed, because there was no real segmentation logic underneath, just a fixed schedule.
Building proper behavioral segmentation, tracking what state each customer was actually in (new visitor, cart abandoner, repeat buyer, lapsed) and triggering different messages for each, took real time to design and build in Klaviyo. The easier path was to keep improving subject lines on the existing static list. I chose the harder rebuild because the ceiling on list-based email was low no matter how well optimized, while state-based triggers could compound over time as the customer base grew.
Repeat-buyer revenue became a distinct tracked segment with its own dedicated flow. Recovered $12K a month in abandoned cart revenue through behavior-triggered WhatsApp, email and SMS flows, at 3.2x return on that channel, once triggered by actual cart behavior rather than a blanket weekly send. The lesson: optimising a weak structure has a ceiling. Rebuilding around real customer behavior doesn't.
At Bepro, Amazon was consuming roughly 40% of our total media budget. On paper the numbers looked acceptable ROAS was holding at 4.2x and the channel was generating steady volume. Leadership was comfortable with it. I was not. The attribution data told a different story: Meta was delivering significantly lower CAC on the same SKUs, with faster feedback loops and more control over creative and audience.
The risk was real: Amazon had brand visibility and purchase intent we could not fully replicate on Meta. Pulling budget meant accepting a short-term dip in Amazon sales rank. I built the case with 8 weeks of side-by-side attribution data, modelled the projected CAC and ROAS impact and proposed a phased 30% reallocation over 6 weeks rather than a hard cut. I presented the trade-off clearly to leadership including the downside scenario and got alignment to run the test.
Meta ROAS climbed to 12.19x on reallocated budget. Overall CAC dropped 23.15%. DTC revenue doubled year-over-year. Amazon maintained sufficient spend to protect organic rank while no longer crowding out the higher-performing channel. The lesson: the right call is rarely the comfortable one it is the one you can back with data, model the risk on and execute with a plan for the downside.
Every result in my portfolio came from a repeatable process not luck. Here is exactly how I approach growth and performance marketing.
Before touching any budget I audit the full account: campaign structure, audience overlap, creative fatigue, attribution gaps and funnel drop-off points. I identify exactly what is wasting spend and what has potential. No assumption, only data.
I build separate campaign structures for each funnel stage. TOF for cold audiences (broad + interest), MOF for warm traffic (video views, page engagement), BOF for high-intent retargeting (cart abandoners, past purchasers). Each stage has its own creative brief, bid strategy and success metric.
Every week I introduce 3-5 new creative concepts testing different hooks, formats and copy angles. I track thumb-stop rate, hook rate, CTR and ROAS per creative in a shared tracker. I identify patterns before the algorithm does. This is how CTR improved 16% at Bepro and CPA dropped 21.85% at Getthatboat.
I scale budget only when ROAS holds for 7+ consecutive days and creative fatigue is managed. Budget increases are 20-30% increments not 100% jumps. This is how $2K/month became $40K+/month (a $480K+ annualised run rate, 20× growth) while maintaining 5.5x-12.19x ROAS instead of watching it collapse on scale.
Post-purchase is where margin lives. I build WhatsApp API, email and SMS flows segmented by purchase behavior, cart value and product category. Timed touchpoints, personalized messaging, not a static send calendar. It's the approach behind the abandoned cart recovery at Bepro.
GA4, GTM, Meta Pixel, Amazon Attribution, Microsoft Clarity and Looker Studio dashboards. I set up proper event tracking across every channel, run weekly attribution checks and make budget decisions based on data not gut feel. At Binfosol, attribution data revealed LinkedIn outperformed Meta on lead quality I shifted 30% of budget and ROAS improved immediately.
I treat every unfamiliar platform, market or business model as a structured problem to solve, not a blocker. When I joined Getthatboat, the charter yacht marketplace model was entirely new to me. Within weeks I had onboarded 15+ companies, built the GTM strategy and deployed a GenAI calling agent. Speed of learning is a competitive advantage I bring to every role.
When I encounter something new a channel, a tool or a market I do not wait to feel ready. I research the fundamentals, study what the best practitioners do, run a small test, measure it and iterate fast. This is exactly how I built hands-on expertise in TikTok Ads, WhatsApp Business API, Amazon Seller Central, GenAI automation and GCC market localization all learned and applied in live business environments with real budgets.
You will not need to wait months for me to get up to speed. I ramp quickly, contribute early and consistently close knowledge gaps in myself and my team. I am completing an MBA in Marketing and Business Analytics on weekends alongside full-time work. My output at work does not suffer: the MBA runs on weekends and the job runs Monday to Friday at full capacity. I am also open to relocating anywhere in the world immediately. Geography is not a constraint. The right role and team is what matters.
I do not just manage headcount. I build teams that execute without hand-holding through structured coaching, clear ownership and systems that outlast any individual.
At Bepro I built the performance marketing team from scratch starting at 5 people defined the roles, wrote the briefs, ran the interviews and structured onboarding around channel ownership from day one. In year three I added a dedicated performance marketing strategist, growing the team to 6. Each hire was mapped to a specific gap in execution capacity, not just a seat to fill. At Getthatboat I built a 7-member cross-functional team across marketing and operations, onboarding people into clearly defined SOPs and outcome metrics from week one.
Ran structured weekly 1:1s with every direct report not status updates, but coaching conversations focused on how they were analysing data and making decisions. Asked: what did you see in the data this week, what did you do about it and what would you do differently? This cadence is how I identified individual skill gaps early, co-created development plans and kept the team improving independently. At Bepro this coaching approach drove a 15% increase in team-managed ROAS over 12 months.
Set individual ROAS targets per channel for each team member, not a shared team number. Built a shared performance dashboard visible to the full team everyone could see their own numbers and how they compared. Performance-managed underperformers with documented expectations, timelines and check-ins. Not every hire works out; I treated underperformance as a system failure first and a people problem second fixed the brief, the process and the support before escalating.
I actively created stretch opportunities gave team members ownership of a full channel or campaign segment before they felt ready, then coached them through it. Ran structured knowledge-share sessions where team members presented their channel learnings to the group. The goal was always the same: build a team that does not need me in the room to make good decisions. That is what leadership looks like at the Director level.
Growth does not happen in a marketing silo. Every major result I have delivered required tight alignment across Sales, Product, Engineering, CS and Operations and knowing when to push, when to align and when to escalate.
At Getthatboat I partnered directly with the development team to ensure campaign routing infrastructure, tracking and attribution were built correctly before spend went live not patched after. Worked with engineering on marketplace feature prioritisation to align product releases with acquisition campaigns. At Bepro I collaborated with the tech team on pixel setup, checkout tracking and data layer implementation to eliminate attribution gaps that were distorting ROAS reporting.
Worked closely with operations before scaling spend on any SKU or charter listing confirmed inventory availability, fulfillment capacity and customer support readiness before demand went live. Learned early that driving acquisition into a broken post-purchase experience destroys CAC efficiency. At Getthatboat this alignment between marketing and ops is what made the 30% booking lift stick the experience matched the promise in the ad.
At Binfosol I partnered with the sales team and university partners to align campaign messaging with ICP segmentation rebuilt audience targeting based on sales feedback about lead quality, not just marketing metrics. At Getthatboat I worked directly with founders on positioning and pricing strategy for the B2B charter acquisition segment, ensuring paid media messaging matched the sales conversation charter companies were having with the marketplace team.
Did not just approve assets co-wrote creative briefs with hooks defined by audience data, visual direction set by top-performing formats and success metrics agreed upfront. Gave creative teams context: who the ad is for, what objection it is overcoming and what one action it needs to drive. This collaboration process is what produced the bilingual Arabic/English frameworks at Getthatboat that delivered 18% CTR improvement and 21.85% CPA reduction.
Comfortable presenting to founders and senior leadership with the full picture including risk, downside scenarios and what I do not know yet. At Bepro I built the business case for the Amazon-to-Meta budget reallocation with 8 weeks of attribution data, modelled both upside and downside scenarios and proposed a phased test rather than a hard cut. Leadership aligned because the proposal showed I had thought through failure, not just success.
At Getthatboat built the full GTM strategy for a new charter marketplace segment from scratch ICP definition, channel selection, creative framework, automation stack and performance reporting and had it live within weeks of joining. At Bepro designed and executed segment-specific GTM plans for each product vertical, aligning paid media with product launch calendars, inventory cycles and customer lifecycle stages across Meta, Google and Amazon simultaneously.
Tools I use to unify customer data, build behavioral segments, orchestrate lifecycle journeys and drive retention across email, SMS and omnichannel touchpoints.
Hands-on experience using AI across marketing, automation, content creation, video production and workflow building not just prompting, but integrating into real business systems.
10+ years driving measurable growth across DTC eCommerce, GCC marketplaces and multi-client agency environments. Scaled budgets from $2K to $40K+/month ($480K+/year, 20×). Delivering 5.5×–12.19× ROAS. Available immediately for remote & onsite roles globally.
