Manuel Gonzalez | Proof of Work

The ads, the retention, and the reporting that proves both.

You have the resume. This is the part it cannot show: dashboards that pull straight from Shopify, the CRM, and the ad platforms, and the mechanics behind the growth numbers.

$40k to $200kmonthly revenue in six months

3xad ROAS across Meta, Google, TikTok

$52ka month in repeat orders

Email me 805-668-5076 Riverside, CA. Remote. The screen-share runs against real accounts.

Reporting that pulls from the source

Ad platforms grade their own homework. I custom code my dashboards to pull programmatically from Shopify, Meta, Google, TikTok, OpenAI Ads, and the CRM, and show me exactly what I want to see, in seconds. No hours spent comparing platforms and calculating numbers by hand. Revenue per ad and cost per good lead are real figures, and a full report generates in about 30 seconds.

Shopify dashboard section showing total spend, orders, revenue, profit, ROAS, cost per order, average order value, abandoned carts, and a per-ad-set campaign table

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Revenue, profit, and ROAS per ad set, in real time

Meta and Google ads matched against Shopify orders and abandoned carts as they happen. Optimization runs on store data, so iPhone tracking limits and blocked pixels do not distort the picture.

Profit, not just revenue. Cost per order and average order value sit next to spend for every ad set.
Timing built in. Sales by hour, day, and weekday show when the money actually lands.
Feeds included. I built the Meta and Google Shopping catalogs behind it; the same feeds plug into any platform.

ShopifyMeta CAPIGoogle ShoppingAbandoned carts

Dashboard combining Meta, Google, OpenAI and TikTok Ads campaign results with Salesforce lead matching: total spend, good leads, cost per good lead, MQLs, cost per MQL, and per-campaign rows

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Every campaign graded on lead quality, not clicks

Meta, Google, OpenAI Ads, and TikTok campaigns matched against CRM leads. The platform reports a lead count; the CRM says how many were good, how many became MQLs, and what each one actually cost.

No hand entry. Spend, leads, and lead status arrive by API from the ad platforms and Salesforce.
Attribution gaps are visible. Leads whose UTMs match no campaign are flagged and excluded, never silently averaged in.
Shareable. Saved views, sharing, and export; a new ad platform plugs into the same pipeline.

SalesforceMetaGoogle AdsTikTokOpenAI Ads

Four plays, with the mechanism behind each

Results are easy to list. These are the moves that produced them.

25%

Repeat marketplace buyers moved to direct orders

Problem: TikTok Shop orders arrive with no email address, so repeat buyers were invisible and every reorder paid marketplace fees and affiliate commissions.
Mechanism: Matched orders by phone number to measure true repeat rate, then ran an SMS win-back with Shopify-only coupons through the Klaviyo email and SMS stack I built for the brand.
Result: About 25% of repeat TikTok Shop buyers switched to ordering direct. Repeat orders reached $52,000 a month of $200,000.

55%

Of store volume from TikTok Shop and creator videos

Problem: TikTok gives no readable report tying revenue and affiliate commissions to an individual video, so creator budget ran on view counts.
Mechanism: Built the affiliate program from zero, coded the recruitment automation, and wrote per-video revenue reporting. AI agents reply to every commenter on creator posts from the brand account.
Result: TikTok Shop and TikTok ads drove about 55% of the brand's volume, and spend followed the videos that sold.

$40,000 to $200,000 a month in six months

Problem: A snack brand with a small store and no growth system.
Mechanism: Built the Shopify store, made every budget and creative decision, ran about $25,000 a month across TikTok and Meta, and built the tracking so scaling decisions used real revenue. Added a post-purchase one-time offer on a premium kit that recovered significant cost.
Result: 3x ad ROAS across Meta, Google, and TikTok while customer-acquisition cost fell 30 to 50%.

$350k

In sales, first four months of a beauty brand I founded

Problem: Launching a foundation brand, Mannico Cosmetics, with no existing audience.
Mechanism: Shopify store, Meta ads as the acquisition channel, and checkout upsells with one-time offers on brushes that lifted order value. Sourced manufacturing in China in person.
Result: About $350,000 in sales in the first four months. Wound down when the manufacturer could not hold shade consistency at volume.

Systems in daily use

Built on top of LLM APIs as agents that take actions, with review layers so humans keep the creative concepts and the money decisions.

Creative

AdMark Studio

AI ad and banner generator: brand analysis from a URL, style variations in seconds, animation, and feedback learning that turns each rejection into a standing rule.

Creative

Hourly video pipeline

Produces and uploads a reviewed ad every hour. AI reviewer agents send substandard work back with feedback.

Conversion

Dynamic-text landing pages

Captures the keyword clicked in Google Search and generates matched hero and intro copy on the spot.

Community

Creator comment agents

Reply from the brand account to every commenter on affiliate videos, with review checks. Commenters are potential followers.

Intake

AI calling centers

Agents place inbound and outbound calls, qualify and score leads, and set appointments end to end.

Integration

An API where none existed

Reverse-engineered a system with no public API and coded the layer that lets agents act inside it without a human.