Audience
Account, segment, persona and buying-group intelligence focused investment on opportunities with the strongest fit and intent.
OpenAI hiring project · 2026
Paid + signal-based growthCase study
I build demand systems
from signal to revenue.
I combine growth strategy and GTM engineering to connect account intelligence, paid and emerging channels, qualification, nurture, seller activation and revenue measurement into one operating system.
Signals
ICP Fit, Predicted ACV, Engagement Level and ABX Stage turned ambiguous intent into signals that teams could prioritize and act on.
Activation
Paid media, nurture, outbound, events and content activated the same account and person-level signals across the journey.
Handoff
Qualification, routing, research and seller plays moved the right people toward the right follow-up path, with explicit cross-functional handoffs.
Evidence
CRM and attribution data separated execution diagnostics from channel contribution, pipeline progression and business value.
Assignment map
Every required question,
answered in sequence.
Select any section to jump directly to the evidence. Each chapter also names the assignment questions it covers.
01
Paid media strategy & execution
- Business goal and challenge
- LinkedIn and display approach
- Audience, messaging, creative and budget
- Personal ownership and team execution
Building new demand channels
- Channels built beyond paid
- Identification and prioritization
- Launch, testing and scale
- Highest-impact optimizations
Measurement & attribution
- Success criteria and core metrics
- Measurement and attribution framework
- Pipeline and revenue connection
- Investment decisions from data
Results & learnings
- Measurable business results
- Strategic lessons
- What I would do differently today
- Company-level impact
01
Paid media strategy & execution
Prompt coverageBusiness goal · LinkedIn + display · audience · messaging · creative · budget · ownership
The business problem sat downstream of the click.
A Series B B2B infrastructure company needed to increase qualified enterprise pipeline in a technical, still-forming category while improving the economics of a $1.2 million annual paid-media investment. Over six months, I tested demand channels and event formats, reduced weak programs quickly, and found one repeatable growth lever: top-of-funnel LinkedIn ads powered by useful, original content.
LinkedIn: create demand
I centered investment where our technical and commercial buying group learned in public. We targeted product and monetization leaders, CTOs, founders and enterprise AI teams. Thought leadership, especially original research on pricing AI products, consistently beat promotional offers.
Display: reinforce demand
I built retargeting audiences from high-intent site behavior, content engagement and target-account activity, then sequenced category education, product proof and conversion offers. We excluded customers and low-fit traffic, controlled frequency, and judged display through account progression and assisted pipeline. View-through conversions remained a diagnostic signal.
Budget: follow evidence
I owned channel and allocation strategy for a $1.2 million annual program spanning paid media, agency and emerging-channel investments. One operating readout put Google at roughly $580 brand CPL and $960 non-brand CPL. I reduced it and returned budget to LinkedIn. The Q2 attribution readout showed a 12× won-revenue-to-spend ratio and stronger opportunity conversion.
Creative: insight before ask
Document ads, founder/operator perspectives, research and creator-native formats made complex ideas useful. The message explained how the economics of AI and usage-based products were changing and gave operators a framework for designing around them.
Ownership: strategy set in-house, execution scaled through partners
I personally set the audience strategy, messaging, creative direction, budget allocation and agency briefs—including what we tested, how we prioritized spend and when we shifted investment. Agency partners handled platform operations, trafficking and creative production against those briefs, while I retained decision rights over strategy and optimization.
02
Building new demand channels
Prompt coverageChannels built · prioritization · launch · testing · scale · highest-impact optimization
I turned expert distribution into a repeatable channel.
240
top-of-funnel leads from a creator campaign after paid amplification
28
placements across nine creator and newsletter properties
~$39K
tracked placement and program fees
“Borrow trust first.
Scale attention second.
Measure business value always.”
Scale attention second.
Measure business value always.”
I mapped where AI-product builders already learned and prioritized partners using audience fit, credibility, format and economics as the decision criteria.
A sponsored post promoting original AI-pricing research earned 100+ organic reposts. Paid amplification took it to nearly 1,000 likes and 240 leads. Those leads entered the same CRM qualification, routing and revenue-measurement system as paid-media responses.
I built a roughly $50K annual plan spanning creator placements and LinkedIn amplification, with partner scorecards, explicit hypotheses and scale/stop thresholds.
Offer–audience fit mattered most. A finance-focused product story fell flat with one creator’s audience. I replaced it with research on how AI companies price their products, which matched what that audience already cared about.
Portfolio built beyond paid: influencers · newsletters · partnerships · search optimization · AI search optimization · lifecycle · web conversion
03
Measurement & attribution
Prompt coverageSuccess metrics · attribution framework · pipeline + revenue connection · investment decisions
Platform data optimized media. CRM data decided investment.
Click rate · Cost per lead · Conversion rate
Fast diagnostic signals for audience, offer, creative and landing-page performance.
Qualified lead · Sales acceptance · Opportunity
Did the signal survive qualification, routing, seller action and stage progression?
Pipeline · Win rate · Deal size · Revenue
The scorecard that governed budget and determined whether a channel scaled.
Q2 LinkedIn readout
Attribution lookback90 days
SourceThe LinkedIn Revenue Attribution Report (RAR) and CRM lead and opportunity records
Exposure ruleAt least eight ad impressions counted as an opportunity touch
Measurement ≠ attribution ≠ causality.
I connected campaign membership, account engagement, funnel stages and revenue outcomes in the CRM and a multi-touch attribution platform; used cohort and journey evidence to understand contribution; and used holdouts where feasible to test incrementality. The Q2 figures show revenue and pipeline associated with strong LinkedIn exposure under the stated model. Causal impact requires controlled tests.
04
Results & learnings
Prompt coverageMeasurable results · strategic learnings · what I would do differently
The evidence changed the plan.
Q2 LinkedIn outcomes · 90-day attribution lookback · figures use the attribution rule stated above
12×LinkedIn won-revenue-to-spend ratio
$459KQ2 closed-won revenue associated with strong LinkedIn exposure
$433Kadditional open pipeline with LinkedIn contribution
33%win rate for LinkedIn-associated opportunities
45 daysaverage sales cycle
Optimize the system
A channel cannot outperform broken qualification, routing, follow-up or measurement. I owned the connective tissue as seriously as the media plan.
Creative fit beats volume
Specific, useful expertise outperformed broad promotional messaging. The best channel was the intersection of audience, trusted voice and relevant offer.
Reallocation is strategy
I treated budgets as hypotheses. Weak economics lost funding quickly; repeatable qualified-pipeline evidence earned it.
What I would do differently today
Today, I would make qualified account progression the unit of optimization. Matched-account holdouts would estimate incrementality, and each audience, offer and channel combination would carry a downstream target tied to the job it performs. I would scale document and thought-leader ads where they repeatedly create Tier 2 demand inside qualified accounts, use smaller creator pilots to prove audience-offer fit, and introduce customer proof or interactive tools as buying signals deepen. Geographic expansion would begin with matched-market tests in Canada, the UK and selected EMEA markets. Budget would move only after the same account progression and pipeline economics repeated. This would let marketing create more of the conditions that sellers already convert well.
What I personally owned
Business diagnosis · audience and segment strategy · channel roles · offers and messaging · creative briefs · budget allocation · experiment design · agency direction · CRM architecture · attribution and executive recommendations
How the team executed
I directed five specialists across two agencies. Partners handled platform operations, production and trafficking within my briefs and decision rules; internal creative, product marketing, sales and revenue operations supplied expertise and activated the downstream motion.
05
Company-level impact
The learnings changed the company and its financial model.
Previous modelLead → Marketing-qualified lead → Opportunity
Pipeline planning started with lead volume and stage conversion.
New modelQualified account → Person-level intent → Coordinated action
Pipeline planning now starts with qualified account capacity and observable buying signals.
I designed and operationalized a machine-learning qualification system on a unified enrichment, orchestration, attribution and intent stack. It scores accounts into Ideal, Strong and Emerging customer profiles, then combines account fit with person-level web intent from identified leads and contacts.
Capture the person
LinkedIn document-ad lead forms collected work email addresses and professional profiles. Those records gave us durable, person-level identity for subsequent web activity.
Recarve the territory
Seller books were rebuilt around the number of Ideal, Strong and Emerging accounts they contained. Territory capacity became a function of account quality.
Activate by signal
Account fit and recent person-level behavior determined the lead tier, the seller action and the surrounding marketing program.
Tiered lead operating system
Each tier receives a defined level of marketing and sales investment.
Direct handraiser
Contact Us responses with a booked meeting, plus incomplete booking actions from people qualified for ICP fit and routed directly to a seller.
Active signal
Coordinated marketing and seller nurture activated around the same account and its engaged buying-group members.
Developing demand
Marketing newsletter, dynamic advertising surround and invitations to pricing workshops.
Cold account
Zero person-level signals during the previous six months. Investment remains minimal until behavior changes.
The new growth mandate
We rebuilt the demand engine to recognize the right accounts, interpret real buying signals, and coordinate the next best action across marketing and sales.
Strategy, analysis, and direction by Anna K. Puig.Built with GPT-5.6 Sol in Codex.