Portfolio Daniel Liu · 10 yrs · San Francisco

Full-Stack B2B Marketer.
I Also Run Marketing on AI.

Paid and inbound, lifecycle and CRM, and the operations layer under them, run with AI on the team. I turn the messy, repeated work of a marketing org into systems that keep running, and I build the tools it cannot buy.

Resume → Contact me →
What I do
  • Full funnel, paid to retention
  • GTM systems, CRM, attribution
  • Lifecycle and email systems
  • SEO, GEO and content engines
  • AI agents that run the above
growth-api · zsh · illustrative
Recommended by leaders at
. Read their LinkedIn recommendations.
U.S. BankGustoTikTokCloverJeevesPingPongBlackwallU.S. BankGustoTikTokCloverJeevesPingPongBlackwall
TRUSTED AT SCALE

Owned the demand side of one cross-border payments line at PingPong.

Paid acquisition and lifecycle, end to end, from 2021 to 2025: first as Marketing Manager, Ads & Lifecycle, then as Senior Digital Marketing Manager, Growth & Ops. A regulated cross-border product, so speed could never cost us the audit trail.

  • $2M → $76M in year one, past $250M+ by year two. Annual revenue through the line: inbound in year one, then an account-based motion built with sales in year two.
  • LinkedIn cost per lead $300+ → ~$160. Google registrations $90+ → ~$35, with volume held through both.
See the case studies →
$250M+annual revenue on the line I ran paid and lifecycle for, year two
200+automated workflows running in production
~10 releasesUS site shipped solo in ~3 weeks, no front-end team
9 systemsAI GTM tools designed, built and shipped solo
Role fit

Which role are you hiring for?

Hiring for

Enterprise ABM, international launches, lifecycle growth, and the sales partnership around them. I ran all four as one funnel, with numbers that reconcile to finance. Often posted as Senior Growth Marketing Manager, B2B or Demand Gen Manager.

Scope: the demand side of the B2B cross-border payments line at PingPong (2021–2025), paid and lifecycle end to end, as annual revenue grew from $2M to $250M+, with AI now writing the reports. Earlier, VP of Marketing at ToLocal (2016–2021), a team of 7 in the US, with 5 more in China on a $10M annual media budget at 80%+ ROI.

Evidence
$2M → $76M → $250M+ on one cross-border payments line CPL $300+ → ~$160 with volume held Growth framework from diagnose to automate
Growth resume →See the full lane →

Agent-native go-to-market: multi-model agent pipelines research, enrich, build the campaign and report, while a person sets direction. Often posted as GTM Engineer, AI GTM Lead or MarTech Lead.

Scope: nine AI GTM tools designed and shipped solo, every one on a live public URL. Currently Senior Marketing Manager at ThinkingAI, leading GTM systems and marketing ops.

Evidence
Reusable multi-agent systems with a real guardrail catch TechSpy public stack teardowns, one from my interview prep ABM list, 2% → 31% six filter rounds, every one hand-checked stratefuse.com in 24 hours a client site, every layer built solo with AI
AI GTM resume →See the full lane →

I architect workflows, write routing logic, keep attribution clean and govern the site. I build the systems every other team reads its numbers from, so sales, marketing and finance open the same figure on the same morning. Often posted as Senior or Lead Marketing Operations Manager, or Marketing Technology Manager.

Scope: Senior Digital Marketing Manager, Growth & Ops at PingPong (2023–2025), sole owner of a governed 8-tool GTM stack and all of Marketing for 6+ months.

Evidence
8-tool GTM stack on Salesforce · HubSpot · 6sense · GA4 200+ workflows with handoff ~12h → 1–2 min Multi-region tracking with attribution that holds
Marketing ops resume →See the full lane →
About

I run the programs and
build the AI that runs them

I'm Daniel Liu, a marketer who wandered too close to operations and campaigns, discovered AI automation along the way, and decided to stay.

A decade later that detour is the whole job: I sit where GTM judgment meets hands-on technical execution, connecting campaigns, CRM, tracking, lifecycle, reporting and AI automation into one revenue engine a CFO can audit.

  • ToLocal, 2015–2021. Founding marketer, then VP of Marketing from 2016, leading a team of 7 in the US with 5 more in China on a $10M annual media budget at 80%+ ROI.
  • PingPong, 2021–2025. Marketing Manager, Ads & Lifecycle, then Senior Digital Marketing Manager, Growth & Ops, on the cross-border payments line that went $2M to $250M+.
  • ThinkingAI, 2026 to now. Senior Marketing Manager.

See the full timeline →Read the full story →

10 YRS MARKETING $10M BUDGET · TOLOCAL FIRST MARKETING HIRE · TOLOCAL DESIGNS GTM SYSTEMS MULTI-AGENT ARCHITECT 9 AI SYSTEMS SHIPPED AGENT-NATIVE OPS NA · EU · SEA · PINGPONG VP MARKETING · LED 7 · TOLOCAL
Expertise

Six workstreams,
one AI-native growth system

I owned all six end to end, in the stack and the regions they ran in, and rebuilt each one around the part a model can now carry.

01 Growth Marketing

I ran paid acquisition and lifecycle on the cross-border payments line that went from $2M to $250M+ in annual revenue over two years, across NA, EU and SEA.

Learn more → 02 User Acquisition

I ran paid across Google, Meta, LinkedIn and programmatic at PingPong, and cut LinkedIn cost per lead from $300+ to ~$160.

Learn more → 03 Email & Lifecycle

I build behavior-triggered journeys from signup to retention. Identity verification (KYC) submissions climbed from roughly 10% to 35–40%.

Learn more → 04 SEO / GEO & Content

At PingPong I built the workflow that lifts a draft from 0 to the 70s–80s on a 0–100 content-coverage score. I run technical SEO for search and AI answers.

Learn more → 05 Marketing Ops & Analytics

I cut lead handoff from ~12 hours to 1–2 minutes across 200+ governed workflows on Salesforce, HubSpot, 6sense and GA4.

Learn more → 06 Partner & Affiliate

I carried six years of B2C affiliate into a B2B fintech program, setting commission tiers, vetting partners and screening for fraud before payout.

Learn more →
AI Lab

Working prototypes and one production tool

Every one of these started as a problem slowing down work I was running. I built the fix myself, in code, with AI carrying the part that used to eat the week. All of them are live on a public URL.

See the AI architecture →

Ad copy that clears policy before you export it

ReactTypeScriptViteTailwindGemini logoGemini 2.5 FlashDeepSeek logoDeepSeekVercel

Reads your site for the voice, writes for Google, Meta, LinkedIn and Bing, and checks every line against policy while it writes.

Open the live tool → Build write-up →
Three review queues → one pass · draft to policy-checked copy
CreativeOS screen
Ad variant · LinkedInpolicy-firstv3
✓Google Ads policy: clear
✓Meta standards: clear
✓LinkedIn policy: clear
✓Brand & legal: clear

Catch the non-compliant phrase before legal does

ReactTypeScriptViteTailwindGemini logoGemini FlashVercel

Paste a fintech draft, pick the jurisdiction, get every risky phrase quoted against the clause it trips.

Open the live tool → Build write-up →
9 jurisdictions · one paste, full audit
FinGuard screen
Draft audit · USFINRA 2210 rulebook3 hits
✓Risky phrases quoted: 3
✓Matched to FINRA 2210
✓Severity ranked
✓Rewrite suggested

Find the policy violation before the platform does

ReactTypeScriptViteTailwindVercel Functions

It checks headline, body, URL and creative against ~84 platform clauses and your own rules. You get a safety score with every risk explained, before upload.

Open the live tool → Build write-up →
~84 policy clauses · checked before any model call
AdGuard screen
Creative auditMeta + Google rulebooks92
✓Destination policy: clear
✓Prohibited claims: none
✓Trademark: clear
✓Image safety: clear

Pull a creator's whole catalog, get the transcripts out

ReactTypeScriptViteExpressNeon PostgresGemini logoGemini 2.5 FlashFFmpegPlaywrightResendStripeVercel

Point it at a Douyin or TikTok profile; it comes back with the whole catalog transcribed, translated and in a spreadsheet. It runs on your own session, which is what keeps the account safe.

Open the live tool → Build write-up →
profile → Excel · transcripts, translated
Hyper Creator screen
Collection runone profile, whole cataloglive
Profile pasted0:00
Catalog collected0:12
Transcribed + polished0:33
Exported to Excel0:38

Applications, resumes and interviews in one workspace

React 19TypeScriptViteExpress 5SupabasePrismaGemini logoGemini 2.5DeepSeek logoDeepSeekGPT-4o · WhisperStripeVercel

One pasted job description becomes a tracked application, a resume run through a four-pass tailoring engine with its ATS read-out, and interview prep built from the same context.

Open the live tool → Build write-up →
4-pass tailoring · with ATS read-out
Career Capybara screen
Application · one JDfour-pass enginev4
✓JD parsed: role + keywords
✓Resume tailored: 4 passes
✓ATS read-out: pass
✓Interview prep: ready

Run client Meta accounts through the API, with a person on every change

React 19TypeScriptNext.js 16Meta Graph APIOpenAIGemini logoGeminiVercel

An agent drafts the campaign, the ad sets, the creative and the copy, then reads results back. Anything that touches a live account passes a guardrail, a named approver and a typed confirmation.

Open the live tool → Build write-up →
agent drafts · a person approves the account change
AdFlow screen
Budget change$50.00 → $65.00 dailyplan
Diff written0:00
Guardrails passed0:02
Approver typed plan ID0:26
Live value re-read, executed0:31

See the real tech stack behind any competitor's URL

Next.js 16React 19TypeScriptSupabaseDeepSeek logoDeepSeekPlaywrightBrowserlessStripeVercel

Fingerprints the bundles, reads DNS and email posture, maps subdomains, then opens the site in a real browser.

Open the live tool → Build write-up →
6 scan modes · static → deep → interact
TechSpy screen
Stack scansix passes, one reportdeep
✓HTML + JS fingerprinted
✓DNS + email posture
✓Subdomains mapped
✓Real-browser deep scan

Read the strategy your competitors put into market

PythonDeepSeek logoDeepSeekPlaywrightMeta Graph APIAds TransparencySQLiteSupabaseStripeVercel

Pulls a rival's whole ad library and returns the campaign anatomy: market, message, funnel posture. Spend stays out, unestimated.

Open the live tool → Build write-up →
Every ad in the set · decoded in one run
AdRadar screen
Campaign anatomypublic ad librarybeta
✓248 creatives collected
✓Landing pages enriched
✓Angles AI-labeled
✓Anatomy returned
Field notes

Notes from the engine room

Working numbers and postmortems from the systems on this page.

01 All writing

Playbooks, postmortems and working numbers from ten years of B2B growth, filed under growth, lifecycle, SEO and ops.

Read → 02 An ABM list from technology signals

I built a North America target universe out of the technology a company runs. Six hand-checked filter rounds took precision from 2% to 31%.

Read → 03 Search Ads research as an agent pipeline

Four models, each on the part it is good at, cut 3,156 competitor keywords down to a 47-keyword buy list the Google Ads API ships.

Read →
Endorsements

In their words
Selected work · 01 · AI-NATIVE GROWTH

Cross-border payments revenue engine

At PingPong, B2B cross-border payments, I owned paid acquisition and lifecycle end to end as Marketing Manager, Ads & Lifecycle (2021–2023), then Senior Digital Marketing Manager, Growth & Ops (2023–2025): I restructured the campaigns, tightened the audiences and rebuilt the landing pages, instrumented by channel.

Stack

Read the full case study →

We worked closely together rolling out a new part of the business, and I was constantly amazed not only by his technical project management skills, but also by his ability to keep the team motivated through the inevitable challenges.
Selected work · 02 · AI-NATIVE GROWTH

Acquisition efficiency at scale

I rebuilt campaign structure, audiences, keywords and landing paths, and instrumented every channel so finance could audit every dollar of CAC. LinkedIn CPL fell from $300+ to ~$160 and Google registration cost from $90+ to ~$35.

Stack

Read the full case study →

Working with Daniel has been a highlight in my career in fin-tech. He is an extremely diligent worker whose attention to detail is matched by his understanding of how the details affect the bigger picture.
Selected work · 03 · MARKETING OPS & SYSTEMS

Marketing ops & automation layer

Built the automation layer across Salesforce, HubSpot, Zapier and GA4: lead handoff compressed to 1–2 minutes across 200+ workflows; the monthly report went from 1–2 hours to under 5 minutes, feeding 8 reports from one cleaned dataset.

Stack

Read the full case study →

… He took over all of Marketing for PingPong for over 6 months and has ensured there was no interruption to the business with minimal support. … His work is thorough and impactful.
Selected work · 04 · MARKETING OPS & SYSTEMS

Global web, tracking & lead flow

I ran website, CMS, CRO, SEO/GEO and landing pages on Webflow across three regions, and rebuilt tracking so every region reconciled to the same numbers.

Stack

Read the full case study →

As our Digital Marketing Manager, Daniel was instrumental in helping us build and optimize our global website, improving lead flow, and implementing effective tracking systems across multiple regions.
Selected work · 05 · AI GTM

Reusable multi-agent systems

The agent teams behind the rest of this work, plus the review loop that improves them. Multi-model pipelines where a person approves the release, including the guardrail that caught a real failure before it reached a customer.

Stack

Read the full case study →

Daniel is a fantastic member of the team with his ability to blend very deep technical knowledge with great interpersonal skills. He is able to quickly understand business requirements and then present a solution in a motivational way in terms appropriate for any level of the audience.
Selected work · 06 · AI GTM

AI sales intelligence

An inherited account list nobody worked, turned into a ranked and reachable book. A pipeline enriches, scores and finds the contacts, and the rep sees why each account ranks where it does.

Stack

Read the full case study →

Daniel has a great track record in the fast-paced environment and has proven himself as an individual who focuses on multi-tasking while balancing the needs and goals of the company. He does what he says he will do, because his word is guaranteed.
Selected work · 07 · MARKETING OPS & SYSTEMS

CMS rebuild on a funnel-aware platform

ThinkingAI's marketing site, rebuilt solo on Sanity in 2026 with the content model built around the demo funnel. I moved publishing in-house so the people who write the content are the people who ship it, with no code in the way.

Stack

Read the full case study →

He is a professional who brings his capability to learn things quickly to get work done successfully. His professional ethic and ease to adapt to any team make him a good element to any organization.
Selected work · 08 · MARKETING OPS & SYSTEMS

Agent-native reporting

The weekly status compiles itself from nine connected channels. I clear the exceptions and sign it off once the agents have pulled and reconciled the numbers, so the number in the deck traces back to the system that produced it.

Stack

Read the full case study →

Always open to new workflows or how to improve existing ones, he brings a collaborative and enthusiastic approach to operational initiatives. For every project, he's also a strong partner to help shepherd and support the development of net new deliverables.
At ThinkingAI · 2026

What I'm building now, at ThinkingAI

I run marketing here on my own, and I have been rebuilding the operation on AI: content and social pipelines, the website, the reporting layer, and the ops beneath them. Above are the case studies; here is what is running now. The newsletter ships weekly and opens at about 22%, on a list past a thousand, almost all of it from the signup popup on the site.

01 AI Video Pipeline

Enterprise video from an agent pipeline, no crew. Generative models for cinematic mood, a frame-by-frame renderer for product truth. One booth film shipped.

Learn more → 02 Content Engines

Social calendar and newsletter rebuilt as agent pipelines when social and the newsletter had no owner. Agents produce, review and package; I approve.

Learn more → 03 Reports & Insights Portal

We own the marketing BI. I pulled five platforms in through their own APIs, and each team opens the report it needs on an encrypted portal that refreshes itself every day.

Learn more → 04 Web-Coded US Site

I moved release authority to the US side: a local web-coded pipeline, an agent-run release round, about ten versioned releases in three weeks, solo.

Learn more →
How I work

One loop, run on
every system I own

Diagnose

Find the real constraint before spending on top of it.

PingPong, 2021: spent nothing new until the tracking could be trusted

Instrument

One cleaned dataset everyone reads. Definitions before dashboards.

8 standing reports, one dataset, every team on the same number

Automate

The judgment stays human. The busywork doesn't.

200+ workflows: lead handoff ~12h → 1–2 minutes ThinkingAI, 2026: the same loop now runs as reusable multi-agent systems →

Scale

Add budget only on instrumented ground.

Cross-border payments line: $2M → $76M → $250M+
100Accessibility
100SEO
100Best practices

The site itself is a work sample

Google's hardware ran the audit on a dated build, next to the sites this one was modeled on. Each score comes with the engineering decision behind it.

See the numbers →
For hiring managers

Let's talk about the role

Hiring for AI-native growth, AI GTM, or marketing ops and systems? Tell me about the role and I'll tell you honestly whether I'm the right operator for it.

Open to full-time roles. Currently Senior Marketing Manager at ThinkingAI.

✉danielsfsu@gmail.com ☎+1 (650) 504-1208 (callback welcome) inlinkedin.com/in/ziqinliu ↓Download resume (PDF)

Goes straight to my inbox, reply within 48 hours.