Tarek Temamy, Growth & Acquisition

A bit about me

I started in performance marketing at Souq.com in 2014, when the regional e-commerce market was still being built, and I have spent every year since on the acquisition side of it. Marketplace, luxury retail, robo-advisory, B2B fintech, regulated trading. Most of those roles reported to the CEO, which shaped how I work: I would rather walk into a board meeting with one number everybody trusts than five that need explaining.

The thread running through all of it is measurement. Not because it is interesting, but because almost every account I inherit is optimising against numbers that are quietly wrong, and no amount of clever bidding fixes that. I fix the measurement, then I scale the spend. That order matters.

I also run a Shopify store of my own here in the UAE, which keeps me honest. It is one thing to talk about contribution margin, another to watch it on your own bank balance every month.

Where I have worked

Organisation	Roleand period	What it was	What came out of it
UEXO	Regional Head of Growth & Acquisition2026 \| Dubai	GCC online trading platform, CFD, restricted ad category	Spend scaled 4x, $25K to $100K a month, efficiency improving as it scaled. Built the daily attribution pipeline. Team of five.
Qashio	Head of Growth & GTM2024-25 \| Dubai	B2B spend management fintech	Ten times the leads at a third of the cost per lead. One stage model across Marketing, Sales and CSM. Team of four.
Tamra Capital	Digital Marketing Growth Lead2023 \| KSA	Saudi robo-advisory, retail investing	Acquisition behind $53M in assets under management on $133K a month, 10% month-on-month customer growth.
Chalhoub Group	Growth Marketing Manager2020-22 \| Dubai	Luxury fashion and beauty e-commerce	Tripled app revenue across the brand portfolio including Molton Brown, Faces and Level Shoes.
Souq.com / Amazon	App Marketing Manager2014-19 \| UAE	The region's largest marketplace, acquired by Amazon	Up to $500K a month on app acquisition including White Friday, and Project Sunrise, the post-acquisition rebuild. Promoted twice.

E-commerce.

The instrument I build, the machine it runs, the fixes most accounts need, and where it has worked.

Layer	E-commerce	SaaS & fintech
Source of truth	Commerce back end as master, reconciled to every platform	CRM as master, source carried to signed contract
Web tracking	GA4, GTM, server-side tagging, Meta CAPI, deduplicated purchases	GA4, GTM, server-side tagging, form and demo events
App tracking	AppsFlyer, Adjust or Singular on S2S postbacks, iOS and Android	Adjust or AppsFlyer for consumer fintech, funded events as conversions
Qualification	Merchant Center feed with brand and cost of goods per product	HubSpot stage model, lead scoring on channel, company size, title, seniority
Lifecycle	Klaviyo on browse, cart, post-purchase, winback	WebEngage or HubSpot sequences, one per angle, triggered on arrival
Closed loop	Purchase value sent back as profit, not revenue	Offline conversion import on the GCLID carrying the sales outcome
Reporting	Daily refresh across platforms, analytics and back end	CRM entry to contract, cohorted by acquisition month

The dashboard

live, try the controls

Demonstration build | illustrative figures, not a client account

The growth machine

every shopper who drops out is brought back

Each audience stage lands on the page that matches what it wanted, the store computes profit on every order, and anyone who leaves enters a flow built for the exact point they left.

Quick wins

mistakes I find in most accounts

None of these need more budget. They need someone to look.

The product feed is half empty

The mistake

Products sent to Google without brand and the attributes it scores against. The account blames the bids.

The fix

Rebuild the Merchant Center feed with brand, full attributes and cost of goods per product.

What it does

Paid Shopping CPC fell from $2.00 to $0.70, and free listings came back on the organic surface.

Revenue counted twice

The mistake

The native store integration and a manual tag both fire the purchase event. Reported revenue runs close to double.

The fix

Audit the tags, keep one purchase event, deduplicate server and browser signals.

What it does

The bidding stops learning from phantom sales and Finance gets a number it can use.

Buying revenue, not profit

The mistake

Target ROAS on gross revenue. The fastest-growing categories are often the ones with the worst return rates.

The fix

Send profit as the conversion value, haircut by each category's return rate.

What it does

Budget moves toward margin within a week of the first clean report.

Spend behind products that lose money

The mistake

Items selling below cost once returns and shipping are counted still get full catalogue spend.

The fix

Map the catalogue by contribution and exclude or cap the loss-makers in the feed.

What it does

The account stops growing itself into a loss.

And where the checkout leaks

Where the money leaks

Actual step conversion against benchmark | where the money is leaking

Channel

ActualBenchmarkWorst gap

Case studies

pick one

Merchant Center feed rebuild

Hit

Google Shopping CPC sitting at $2.00 with weak impression share on the products that mattered. Bids were not the problem.

Fixed

The product feed was reaching Google without brand and several attributes Google scores against. Rebuilt the feed to carry them properly.

Outcome

CPC fell to $0.70, a 65% cut, and the catalogue picked up free listings on the organic Shopping surface at the same time.

Duplicate purchase events

Hit

GA4 reporting roughly 1.5x the sessions the commerce back end recorded, and almost exactly 2.0x the revenue on single-order days.

Fixed

Sessions running high can be a definition difference. Revenue at exactly double on a one-order day cannot. The purchase event was firing twice, the native platform integration running alongside a manual tag. Removed the duplicate.

Outcome

Clean conversion signal back to Google, which is what the bidding algorithms actually learn from, and a revenue number Finance could use.

The attribution gap

Hit

GA4 was capturing 81% of orders but only 31% of revenue against the commerce back end, measured over seven months.

Fixed

Order capture at 81% is normal. Revenue at 31% is not. The high-ticket items were not completing through the tracked checkout, so the gap was concentrated entirely in the orders that mattered most.

Outcome

Anyone reading ROAS off GA4 had been seeing a third of the money. Reporting moved to the back end as source of truth and the bidding targets were reset against real revenue.

SaaS & Fintech.

The money arrives months after the click, so the dashboard runs past Closed Won and the reporting is cohorted.

The dashboard

MQL through to a live account

Demonstration build | illustrative figures, not a client account

The funnel over twelve months

Volume, cost per stage and step conversion | Qashio, 2025

Granularity

On these numbers. Client figures are confidential. Budget, cost per lead and CAC are real. Funnel volumes are representative: the rates and the trajectory are what the account did, the counts are adjusted.

Deal cohorts

Deals won and share of the cohort | rows are the month the lead arrived

Read a row: every deal won from that month's leads, and the month it actually closed. January has run the longest, so its row is the longest; each month after has had one month less to close. About half close the month the lead arrives, a quarter the month after. Every row adds to 100%, and each month's column adds up to Deal won in the funnel table above.

The growth machine

nobody who drops out leaves the system

A message break between the ad and the page is the most expensive thing in the funnel. Each angle runs its own page and sequence, so lead quality traces back to the angle, not just the channel.

Quick wins

mistakes I find in most accounts

None of these need more budget. They need someone to look.

Optimising on raw leads

The mistake

Meta and Google are told a form fill is the win. The algorithms go and find the cheapest form fillers they can.

The fix

Server-to-server pass-back of MQL and SQL, and offline import of won deals on the GCLID.

What it does

The platforms optimise toward leads that qualify, not leads that are cheap.

Judging ads on a blended month

The mistake

This month's deals are read against this month's spend, but most of them came from leads bought one to three months ago.

The fix

Report by lead cohort: each month's spend against the deals its own leads eventually produce.

What it does

You see what the current ads are actually doing, instead of a number diluted by last quarter.

Three teams, three definitions

The mistake

Marketing, Sales and CSM each use their own meaning of MQL and SQL, so every conversion rate is fiction.

The fix

One written stage model in the CRM, agreed and enforced by all three.

What it does

Arguments about lead quality turn into a report everyone reads the same way.

Stopping at the signature

The mistake

The funnel ends at Closed Won. Deals stall in compliance or onboarding and never go live.

The fix

Track every deal through onboarding to a live account, by acquisition source.

What it does

You stop buying more of the lead that signs and never launches.

Case studies

pick one

Qashio

Head of Growth and GTM | B2B spend management | Dubai, 2024 to 2025 | qashio.com

The objective, and who it was aimed at

Feed a sales team hiring ahead of its pipeline. The buyer: a CFO or finance manager at a UAE company big enough to have a real expense problem. Long cycle, sold to a committee.

My role and what I personally owned

Head of Growth and GTM, reporting to the CEO, four people across media, lifecycle and content. I owned the budget and where it went, and the funnel definition itself, which mattered more than the media did.

Channels, tools and budget

Budget: $30K to $100K a month
Paid: LinkedIn, Google, Meta, X, Reddit
Stack: HubSpot for stages and lead scoring, Looker Studio for reporting from CRM entry through to signed contract
Fast creative testing rather than a fixed evergreen set

The results

Cost per lead $300 to $100
Leads up roughly 10x, on 3.3x the budget
Twice as many leads moving through the funnel, steadily, instead of spike and drought
Marketing, Sales and CSM onto one set of stage definitions

$30K to $100KMonthly budget, start to end of year

$300 to $100Cost per lead over the same period

10xLead volume, on 3.3x the budget

2xMore leads through the funnel, matched to sales headcount

How the cost per lead came down

Hit

Budget sat on LinkedIn and Google, because that is where B2B is supposed to live. Cost per lead was $300, it was not moving, and the plan was to scale into it.

Fixed

Tested Meta properly instead of writing it off as a consumer channel, and let the cost curve decide the split. LinkedIn stayed for what it is genuinely best at: company size, seniority, title.

Outcome

Cost per lead fell from $300 to $100 while monthly budget went from $30K to $100K. Tripling spend usually costs you efficiency. Here it improved, because the money moved to where the leads actually were.

I scale acquisition and cut what it costs at the same time.

A bit about me

Media I buy

Analytics and attribution

Engagement and lifecycle

Where I have worked

Channel coverage, by role

How I grow a business.

The eight stages

The infrastructure

The campaign plan

E-commerce.

The dashboard

The growth machine

Quick wins

The product feed is half empty

Revenue counted twice

Buying revenue, not profit

Spend behind products that lose money

And where the checkout leaks

Where the money leaks

Case studies

Merchant Center feed rebuild

Duplicate purchase events

The attribution gap

Chalhoub Group

The objective, and who it was aimed at

My role and what I personally owned

Channels, tools and budget

The results

Souq.com / Amazon

The objective, and who it was aimed at

My role and what I personally owned

Channels, tools and budget

The results

Project Sunrise

SaaS & Fintech.

The dashboard

The funnel over twelve months

Deal cohorts

The growth machine

Quick wins

Optimising on raw leads

Judging ads on a blended month

Three teams, three definitions

Stopping at the signature

Case studies

Qashio

The objective, and who it was aimed at

My role and what I personally owned

Channels, tools and budget

The results

How the cost per lead came down

UEXO

The objective, and who it was aimed at

My role and what I personally owned

Channels, tools and budget

The results

UEXO | finding the angle that trades

Tamra Capital

The objective, and who it was aimed at

My role and what I personally owned

Channels, tools and budget

The results

Tamra Capital | buying trust, not clicks

What I build with AI.

MCP connectors into Claude

Automated reporting pipelines

Positionly, an AI writing agent

AI-assisted funnel and page analysis