I'm a business systems leader with repeated success leading technical operations, building internal technology and infrastructure, and surfacing actionable business insights in high-growth SaaS startups. I work with startups and growth-stage companies on the systems behind their go-to-market — scaling techno-functional teams, launching new technology programs, driving user enablement, and operationalizing new products and services. Most engagements start with an audit and branch into the areas below. The through-line: keep the stack lean, the data clean, and the team able to move.
Where I tend to add the most value: managing scaled, global, interconnected, end-to-end business programs that actually deliver business value — not just a Jira board's worth of tickets closed.
Core competencies
Strategic planning & prioritization · integration architecture · C-level engagement · business analytics · budget & vendor management · business process automation · change management · team building & leadership development · ROE design · user policies · CDP design · policy & regulatory governance · SOX / ITGC compliance · metadata management · quality assurance · product development & application lifecycle · Agile · DevOps · data integration, management, and governance · risk management · vendor negotiations.
GTM Systems Audit
An end-to-end review of your marketing and revenue tech stack. I map how data actually flows from first touch to closed revenue, flag the breakage points, and produce a phased current-state vs. future-state plan with a funnel view.
Typical questions answered: where is data coming from and going, where are the manual bottlenecks and single points of failure, what % of your records are duplicates or junk, what's most immature about the stack, and what to fix now vs. later.
Deliverables: architecture diagrams, a system/owner inventory across ToFu / MoFu / BoFu, a prioritized remediation roadmap, and tooling recommendations grounded in the FRIC framework.
Enrichment & Vendor Waterfall Audit
Most enrichment stacks are bought by the seat and audited by nobody. Teams pay per record for several data vendors plus separate phone and email waterfalls, and nobody can say which of them actually changed a field in the CRM last month. I answer that per vendor, against your real records.
I trace the build, not the documentation. I rebuild the dependency graph from the live configuration (every formula, run condition, and field mapping) and compare it to what the design doc claims. On a recent engagement, none of the documented pipeline steps survived that comparison. The doc said a provenance check protected every phone lookup. In fact most phone sources were checked, but the first few, the ones most likely to fire, read straight from the vendor payload unchecked.
I measure contribution, not coverage. Vendor dashboards report match rates, which is not the same as impact. I ran a sample of records through a multi-vendor email waterfall and compared the final verdict to the single validation check that ran first. They matched one to one: the downstream vendors never changed the outcome. Along the way they had correctly found real typo corrections, which the formula threw away because it only credited a vendor whose answer exactly matched the submitted address.
I find the writes that never land. Enrichment that reaches the CRM and gets silently overwritten is worse than enrichment that fails, because it looks like it worked. Examples I've found: a company-size field overwritten by a before-save trigger, a country value that never cascades once the ISO field is set, and tens of thousands of accounts showing zero web traffic because a formula took MAX() across blank inputs.
Deliverables: a column-level map of the enrichment pipeline with each vendor's real contribution rate measured against your records, a ranked list of dead spend (vendor output that never reaches a field, or reaches one that gets overwritten), the gaps between your documentation and your build written up as corrections, and a remediation list ordered by effort that separates "rebuild this" from "move three references."
Stack patterns I work with: Salesforce, Clay, ZoomInfo, Cognism, LeanData, BigQuery, Hightouch, ZeroBounce, Trestle. A typical engagement runs two to three weeks, and most of it is reading. Most findings aren't a system failing loudly. They're a documented guarantee and the deployed behavior drifting apart, producing plausible data nobody had reason to question.
Demand Gen & Lead Management
Standing up (or cleaning up) the pipes that turn inbound and outbound activity into pipeline. Covers signup flows, attribution (start simple — first/last touch), UTM capture, enrichment waterfalls, ICP scoring, and signals-based routing into Slack for real-time "pouncing."
Tool families I commonly recommend: Clay, Zapier, Kondo, Common Room / Koala / Unify, Lemlist / Inflection / Customer.io, Default, Cal.com. Choice depends on volume and motion.
Recent engagement: replaced a client's entire inbound and scheduled-enrichment pipeline, end to end, with Clay. Inbound leads and recurring account refreshes now run through Clay workflows: waterfall enrichment across multiple API providers, LLM-prompted industry classification, and write-back into their existing CRM data, so every record lands enriched, classified, and ready to route without hand-built scripts or manual cleanup.
Opportunity Lifecycle & CRM
Designing the opp lifecycle, territory and account structures, activity capture, and day-to-day rep workflow. I keep Enterprise motions deliberately manual — they're messy and non-linear — and reserve automation for the repeatable, higher-volume segments.
CRM choice is part of the conversation: lightweight tools like Day.ai can carry a company under ~1M records; Salesforce is the right call when complexity and scale demand it. Nektar and Synch for activity capture where useful.
CPQ, Billing & Revenue Recognition
Quote-to-cash design across CPQ, e-signature, CLM, billing, and ERP integration. I help teams decide buy-vs-build for CPQ, get the calculation / UX / approvals layer right first, and defer ERP and billing integration until the shape of the business is stable.
Stack patterns I work with: DealOps, RevOps.io, SequenceHQ, Nue, or a home-grown lightweight calculator; DocuSign for signature; Ironclad for CLM; Stripe / Orb / Metronome / M3ter / Lago for billing (choice driven by subscription vs. usage vs. hybrid pricing).
Customer Success Systems
Post-sales process design: onboarding, account team structure, renewal / upsell / downgrade / churn motions, and the case / ticketing workflow that pulls pre-sales, post-sales, deal desk, ops, and finance into one thread.
Usually includes a reverse-ETL layer to activate product usage data into the CRM so CSMs get pinged on the right accounts at the right time. Enablement tooling (Highspot, Spekit) where content discipline is the bottleneck.
Partnerships & Channel Systems
Partner data is the messiest schema in B2B: one account can be sourced by a referral partner, influenced by an SI, transacted through a reseller or cloud marketplace, and integrated with three tech partners, all at the same time. I design end-to-end partner systems that hold up to that, from the first application to the last payout, and that grow with the program instead of ahead of it.
Every partner type. Referral, reseller / VAR and distribution, technology and integration, SI / agency, and cloud marketplace partners each need different data, incentives, and workflows. I model them on one foundation so a partner can hold several roles without duplicate records or double-counted credit.
Data model, hierarchy & hygiene. A partner account model with parent / child hierarchies across regions, subsidiaries, and distributor-to-reseller tiers; contacts tied to the right level; and partner-on-opportunity relationships that capture role and credit. Then the hygiene work most programs skip: deduping applications against existing accounts, filtering out unqualified or duplicate sign-ups, and running new partners through an enrichment waterfall so firmographics, segment, and fit are scored before anyone approves them.
Portals, onboarding & content. A partner portal for self-serve onboarding, deal registration, lead distribution, and enablement, with role-based access, sharing rules, and user lifecycle governance so access stays clean as partners churn. Content management and certification tracks keep collateral current and tie enablement to tier status.
Deal registration & co-sell. Registration flows with clear approval, conflict, and expiry rules, channel-conflict resolution against direct deals, and account-mapping and co-sell signals routed to reps like any other buying signal, so overlap with partners becomes pipeline instead of friction.
Attribution. Sourced vs. influenced vs. transacted credit, defined once and applied consistently across the CRM, the warehouse, and partner reporting, with the rules finance, sales, and the partner team agree to before anyone gets paid on them.
Money flows. Commission and referral-fee calculation, rebates, partner payouts and payment processing, MDF and co-op fund requests, approvals, and claims, plus cloud marketplace listings and private offers wired into billing and revenue recognition.
Legal & compliance. Partner agreements and terms tracked against the record (tier, territory, discount and margin limits, renewal dates), tax and payee onboarding, data-sharing and privacy terms for account mapping and lead exchange, and the audit trail finance needs for partner spend.
Staged to maturity. Early on, keep it out of the CRM: track partners in a lightweight workspace and sync only the minimum fields. Add the CRM layer once partners source real pipeline, and the portal, payouts, and marketplace once volume justifies them. The goal is a program where every partner touch is credited correctly, paid correctly, and visible to the rep who needs it.
Data, Analytics & Activation
Warehouse-first design so every downstream system is replaceable. ETL (Fivetran), reverse ETL (Hightouch), BI (Omni, Looker), and internal apps (Retool, Superblocks) to stitch views together without burning engineering cycles. API-first and export-capable is a hard requirement for anything I recommend adopting.
RevOps Advisory & Org Design
For early-stage teams: how to hire a founding RevOps generalist who can flex into marketing and sales tech, and when to centralize Ops (marketing, sales, CS, deal desk, strategy, GTM data) under one roof for faster decisions and less risk. For later-stage teams: how to stop over-building.
The goals I optimize for: operational efficiency, growth without tech debt, data-driven decisions, better customer experience, and risk management.
Get in touch
If any of the above sounds like what you need, email me at justin@tungjustin.com with a few sentences on where you are and what's breaking.