Houston Teamer

Houston TeamerSenior Demand Generation Strategist

Strategic thinking. Disciplined execution.

I connect revenue strategy, paid media, and ABM—then build the campaigns and systems that put the strategy to work.

  • U.S. Marine Corps veteran · Graduate studies in Management, Harvard Extension School
  • Las Vegas, NV
Explore selected work Get in touch
Download resume (PDF)

Positioning

  • 8+ yearsin B2B enterprise software marketing
  • 5+ yearsin agency-side paid media
  • Globalprograms across North America, EMEA, APAC, and ANZ

My work starts with the commercial question: which markets, accounts, and buying groups matter most, and what it takes to move them.

From there I carry the strategy through campaign architecture, investment decisions, measurement, and the operating standards a team needs to execute it. I came up through hands-on performance marketing, so I stay close to the details that decide whether a strategy actually performs.

Work · Three flagship engagements

Selected work.

Clients are described by industry rather than named. Dollar values are withheld to protect client confidentiality, so results appear as changes, rates, and indexes.

  • Work deliveredStrategies, builds, and frameworks I delivered
  • Verified resultsChecked against CRM, finance, and platform records

Project 01 · Fintech · Global ABM and ABX

One global strategy. Multiple paths to growth.

Three regions, merchant verticals with different adoption barriers, and enterprise, mid-market, and franchise audiences at different buying stages. I built a global account-based strategy spanning regional priorities, merchant segments, buying groups, messaging, and activation across the US, UK, and ANZ.

Creative, destinations, targeting, and measurement work as one system, so investment, attention, and sales follow-up point at the same accounts.

Program structure: one global foundation, three regional programs with tiered account treatment and local categories, and shared measurement. A diagram of the structure, not data.

What I built

  1. A global strategy with regional and vertical adaptations across the US, UK, and ANZ.
  2. Account tiers, buying-group needs, and a clear role for each campaign.
  3. Creative direction, destination readiness, activation, and measurement.
Verified results
90%of target merchant accounts reached
25%of qualified opportunities signed as merchants
83%of signed merchants activated

12-month program, with six more months for opportunities to mature.

Explore the caseStrategy and execution · Commercial results · Measurement notes

AStrategy and execution

What made it complex
  • Different markets needed regional relevance, not translated copies of one campaign.
  • Merchant verticals faced different business problems and adoption barriers.
  • Enterprise, mid-market, and franchise audiences required different treatment.
  • Broad awareness, opportunity development, and active-deal support each needed a distinct approach.
Account and vertical strategy

T1, T2, and T3 programs matched scaled education, opportunity development, and focused deal support to account priority and buying stage. Verticals covered fashion, beauty, retail, QSR, and travel, plus region-specific categories such as US home, UK health and wellness, and ANZ recurring spend.

Buying groups and adoption logic

Messages tied to growth and commercial priorities, considering marketing, commerce, product, technology, finance, procurement, and compliance stakeholders where relevant. The messaging answered what merchants weigh before adopting something new: is it clearly better, does it fit how we operate, how hard is it to implement, can we try it without a big commitment, and will we see that it’s working?

Activation

LinkedIn and Demandbase, supported by stage-appropriate creative, landing-page inventory and readiness review, personalization work, event-related activation, campaign trafficking, and QA. Regional reporting kept local currencies and launch timing separate.

BCommercial results

Verified results

From target account to activated merchant

StageResult
Reached90% of target accounts
Engaged40% of target · 44.4% of reached
Qualified opportunity10% of engaged accounts
Signed merchant25% of qualified opportunities
Activated83% of signed merchants
Marketing contribution1 in 3 wins marketing-sourced; the rest marketing-influenced

Net revenue from activated merchants and an annualized run rate were also verified against finance reporting; dollar values are withheld. The stages show progression, not one linear path every account follows.

CMeasurement notes

  • Reached means at least one valid paid-media impression tied to a target account, deduplicated across channels.
  • Engaged means two meaningful interactions on separate dates within 90 days, at least one of them a website, content, event, or direct-response interaction. Impressions alone don’t qualify.
  • Merchant payment volume is not revenue, and annualized net revenue is not contractual ARR. Sourced and influenced wins don’t overlap. Marketing contributes to this path; sales and the wider business close the deals.
Checked against
  • Targets and reachApproved target-account master matched to CRM account IDs; account-level delivery reports reconciled to it
  • EngagementAccount-engagement platform, supported by website, marketing automation, and CRM activity
  • Opportunities and winsCRM opportunity reports with qualification date, stage, and sales acceptance; closed-won records and executed agreements
  • Activation and revenueOnboarding records and finance-approved merchant revenue reporting
  • AttributionCRM attribution reporting under documented sourcing and influence rules

Project 02 · HR technology · Revenue strategy

From revenue ambition to campaign architecture.

Revenue priorities across regions needed to become a demand program with clear account priorities, campaign roles, investment logic, and measurement, not a collection of channel tactics. I built the revenue framework and the campaign architecture that puts it to work.

It makes the relationship between revenue ambition, account progression, campaign roles, and investment explicit, so progress can be read against the annual target.

  1. Revenue prioritiesmodeled by region
  2. Account tierswhere attention goes first
  3. Buying groupsrole-specific messaging
  4. Campaign rolesbudget follows each role
  5. MeasurementCRM stages, tests, reporting

↺ Measurement informs revenue priorities and the next investment

The architecture in sequence: each layer depends on the one before it, and measurement feeds the next round of priorities.

What I built

  1. Regional revenue priorities and account tiers.
  2. Buying-group strategy, role-specific messaging, and an explicit role for every campaign.
  3. Percentage-based investment allocation, a testing framework, a reporting MVP, and a 90-day roadmap.
Verified results
30%of the annual new-ARR target booked by one quarterly cohort
+20%new ARR booked vs. the prior cohort
33.3%win rate on resolved opportunities

One quarterly cohort, matured six months, against the prior equivalent cohort. The gains followed activation; they don’t prove the architecture alone caused them.

Supporting evidence of analytical judgment: an AI-assisted reconciliation of executive reporting that I directed caught a regional formula omission and an unsupported conversion-rate claim.

Stabilize

Complete

Audits, discovery, targeting foundations, measurement review.

Architect

Complete

Tiers, priorities, messaging, roles, allocation, testing, reporting.

Activate and refine

Underway

Restructuring, launch support, audience experiments.

Explore the caseStrategy and execution · Commercial results · Measurement notes

AStrategy and execution

Strategic decisions
  • Prioritizing accounts and regions by commercial opportunity.
  • Connecting buying-group needs to messaging.
  • Giving each campaign an explicit role, and allocating investment according to those roles.
  • Connecting campaign performance to CRM stages and opportunity context.
  • Using reporting to guide investment rather than simply summarize delivery.
Test design

The testing framework defined experiments for audience sizing, account tiers, industry, and audience sources, including Tier 2 sizing, Tier 3 LinkedIn testing, industry tests, and Primer versus AdRoll audience testing. These are framework components; individual test results aren’t claimed.

Making the revenue story defensible

I directed an AI-assisted review comparing executive reporting with spend, platform, and CRM sources. It separated legitimate scope differences from errors:

  • A quarterly global cost-per-opportunity formula left out one region that the monthly calculations included.
  • An inbound opportunity denominator was broader than the paid-attributed opportunities it was compared with.
  • A conversion rate divided separately counted demo requests and opportunities without a linked cohort behind it.

That review set the standard for the results on this page, including the linked demo-to-opportunity cohort. AI handled much of the source comparison. Deciding what to correct, footnote, or raise with colleagues, and preparing the talk track for the slides I owned, was my part.

BCommercial results

Verified results

This cohort against the prior equivalent cohort

Prior cohort indexed to 100
MeasurePriorThisChange
Demo requests100113+13%
Qualified opportunities100125+25%
Qualified pipeline100125+25%
New ARR booked100120+20%
Demo-to-opportunity rate36.0%39.8%+3.8 pts
Where this cohort’s qualified opportunities stood at the cutoff
Won27%
Lost53%
Still open20%

The cohort booked 30% of the annual new-ARR target. Dollar values are withheld.

CMeasurement notes

  • Both cohorts use identical qualification rules, attribution definitions, and maturation windows.
  • Win rate is 33.3% on resolved opportunities (won ÷ won and lost) and 26.7% across all opportunities, including those still open.
  • Pipeline created includes opportunities later won or lost, on a consistent annual-contract basis. New ARR booked is not revenue recognized in the period.
Checked against
  • Annual targetFinance-approved annual plan and revenue model
  • Demand and opportunitiesDeduplicated CRM demo-request report reconciled with form submissions; opportunities linked to the originating demo cohort
  • Contract values and bookingsCRM values reconciled to signed agreements or billing; finance-approved new-ARR bookings
  • Prior cohortHistorical CRM cohort snapshots and finance bookings under the same rules

The strategy matters. So does everything it takes to execute it.

Work · Supporting systems

The systems behind stronger performance.

Strategy depends on signals that can be trusted, structure that supports investment decisions, launches that go out right, and programs built to perform from the first day.

  1. Healthcare technology · Measurement

    Measurement diagnosis

    After we traced three different tracking failures across three web properties and the fixes went live, identification of engaged accounts rose from 62% to 84%, giving prioritization and retargeting far more to work with.

    before after
    Diagnosis, status, and results
    Work delivered

    Working with colleagues, I helped show that three symptoms looked alike but had three different causes, so one fix would not have solved them:

    • Campaign microsite: empty consent-category signals.
    • Main site: delayed tag-manager loading.
    • Resource hub: a missing account-identification tag.

    A temporary preview-mode diagnostic isolated the consent dependency and was then reverted; the fix keeps consent behavior intact. The handoff separated audited observations from call notes and untested hypotheses, flagged duplicate and legacy tags, and gave each fix its own owner and verification step.

    Status: Fixes deployed and confirmed through deployment tickets, published configuration versions, and completed retests.

    Verified results

    Engaged-account identification, matched 30-day windows

    Before remediation62%
    After remediation84%
    Change+22 pts
    More engaged accounts visible+35%

    Better observation reveals activity that already exists. It doesn’t create demand or pipeline on its own.

    Checked against
    • CoverageBefore-and-after identification exports, deduplicated, against an independent consent-eligible reference set with consistent account matching

  2. Marketing operations · Campaign architecture

    Campaign architecture and taxonomy

    Separating Core, Category, Brand, and Competitor intent made each search role’s economics comparable, and reallocating on that evidence lifted qualified pipeline 8.2% at unchanged spend.

    COREcapture solution demand
    CATEGORYreach market explorers
    BRANDcapture brand demand
    COMPETITORreach active evaluators
    Specification, status, and results
    Work delivered

    An eight-tab specification connecting paid-media naming to UTMs and reporting dimensions for named-account, tiered, and product-level programs, with approved values, existing-to-proposed mappings, motion lookups, GTM parsing guidance, QA rules, and worked examples. In search, it separates Core, Category, Brand, and Competitor intent.

    • Five dimensions: platform, funnel, motion, solution, and period.
    • Platform and funnel read from the start, solution and period from the end, so the middle can hold multi-token motions.
    • Creative format and version live at the creative level, not in the campaign name.
    • Duplicate or ambiguous mappings are flagged for review, never silently accepted.
    • linkedinplatform
    • considerationfunnel
    • segmentmotion
    • productsolution
    • quarterperiod

    Status: Search layer deployed across active campaigns, UTMs, and CRM reporting.

    Verified results

    Two comparable quarters at the same total spend

    GroupShare of spendPipeline ÷ spend
    Core40% → 52.5%5.0× → 4.8×
    Category30% → 22.5%2.5× → 2.8×
    Brand10% → 10%10.0× → 10.0×
    Competitor20% → 15%2.5× → 3.0×
    Total100%4.25× → 4.60×

    The decision moved 12.5 points of search budget into Core, funded by 7.5 points from Category and 5 from Competitor. Core’s ratio dipped slightly as it absorbed more budget, while Category and Competitor rose at lower spend. Brand’s high attributed ratio doesn’t establish incremental impact, and no revenue result is claimed.

    Checked against
    • ReallocationApproved media-plan revisions and platform budget change history
    • Spend and pipeline by groupPlatform exports mapped to the taxonomy; CRM opportunities linked through campaign identifiers, each counted once under one attribution method

  3. Execution governance · Paid media QA

    Launch governance

    In its first 90 days, independent review caught issues in nearly a third of launches before they went live, including a daily budget set at three times plan.

    build review approve correct
    Framework, status, and results
    Work delivered

    A Builder/Reviewer launch framework for paid media across Google, LinkedIn, Meta, Demandbase, Reddit, and 6sense. Review intensity scales with complexity and risk, material changes trigger re-review, and post-launch checks happen at about one hour and 24 hours after go-live.

    1. Builder completes setup and self-checks against campaign requirements.
    2. Handoff identifies objective, targeting, budget, creative, destination, and measurement.
    3. Reviewer independently checks the configuration and records findings.
    4. Builder corrects flagged issues; reviewer verifies the changes.
    5. Approval is documented before launch.

    Status: Framework in use; refining how it’s applied is ongoing.

    Verified results

    First 90 days of framework use

    Launch packages with issues caught30.6%
    Issues critical enough to block approval29%
    Targeting and exclusions share of issues35%
    Budget and flight24%
    URLs and UTMs24%
    Conversion configuration18%

    Shares are rounded. Issues caught show what review found, not money saved. The budget set at three times plan was corrected before activation with no misdelivery; it was excess configured capacity, not a measured loss prevented.

    Checked against
    • Reviews and findingsLaunch register, sign-off records, and reviewer findings linked to unique launch IDs
    • SeverityQA issue log with severity definitions and approval-blocking records
    • CorrectionsBefore-and-after configuration evidence, activation timestamps, and delivery records

  4. Account-based marketing · Personalization

    Account-level personalization

    In an eight-week controlled pilot, accounts that saw their own company name from ad to landing page produced 2.5 times the qualified opportunities of a matched control group.

    ad landing page
    Pilot design, validation, and results
    Work delivered

    Company-name personalization coordinated across the ad and the landing page, with an approved account-name mapping and generic fallback messaging for unknown accounts. I validated the LinkedIn pilot’s tracking and audience requirements, then retested the pages after a content-security-policy change.

    Design: Eight weeks, after technical validation. 200 target accounts split evenly into personalized and control groups, with the same offer, flight dates, and bidding approach, similar spend, and equal impressions.

    Verified results

    Technical validation

    Company-name insertion, ads and page variants50 of 50 passed
    Unknown-account fallback10 of 10 passed
    Insight Tag firing after the policy change20 of 20 sessions
    Tracking requests blocked by the policy0
    Test submissions reaching CRM without duplicates5 of 5
    Verified results

    Personalized against control

    MeasurePersonalizedControlDifference
    Accounts reached92%91%Even
    Click-through rate0.75%0.50%+50%
    Landing-page conversion4.0%2.6%+54%
    Accounts requesting a demo26%12%2.2×
    Qualified opportunities control = 1002501002.5×
    Qualified pipeline control = 1002501002.5×

    The pipeline gap is the difference between the two groups in this pilot, not a causal estimate of incremental pipeline, and opportunity counts are small. Closed-won revenue isn’t included. Dollar values are withheld.

    Checked against
    • Design and deliveryApproved account list and experiment assignment, campaign settings, and LinkedIn account-level delivery reports and exports
    • Demos and opportunitiesDeduplicated form submissions reconciled with CRM; opportunity records linked to the pilot cohort
    • Technical validationQA matrix and screenshots, browser network and console logs, the published policy configuration, and CRM test records

  5. Data infrastructure and healthcare software · Paid search

    Search programs built from scratch

    Two accounts built from a blank slate generated qualified pipeline of 23 and 13 times their search spend within six months of launch.

    blank brand core cat. comp.
    Both builds and their results
    Work delivered
    Build A · Database company · US, India, and Israel

    Regional campaign architecture with 12 campaigns, four per market, organized by Brand, Core, Category, and Competitor intent. The build covered keyword research, market-specific keywords and exclusions, ad copy, landing-page mapping, conversion setup, budget allocation, and launch QA. All 12 campaigns completed documented prelaunch QA.

    Build B · Healthcare software company

    A complete 14-campaign account with 56 ad groups and 112 responsive search ads, organized by intent and supported by tracking, exclusions, and budget controls. It launched four weeks after approved inputs arrived, and 10 of 10 conversion test journeys passed, with test records excluded from results.

    Status: Both launched. Results cover the first 90 days after launch, plus 90 more days of opportunity follow-up.

    Verified results

    Build A by market

    MarketShare of spendDemo → opp.Pipeline ÷ spend
    US60%25%20.8×
    India20%15%15.0×
    Israel20%30%37.5×
    Total100%23.1%23.0×

    India had the cheapest clicks and demos but the weakest pipeline return, which is why cost per demo alone shouldn’t decide budget. Of the opportunities, 20% were won by the cutoff, 40% were still open, and 40% were lost. New ARR booked reached 4.7 times search spend (derived).

    Verified results

    Build B by intent group

    GroupShare of spendLead → opp.Pipeline ÷ spend
    Brand11%20%30.0×
    Core44%20%15.0×
    Category28%14%8.4×
    Competitor17%12%6.0×
    Total100%17.8%13.3×

    Of the opportunities, 20% were won by the cutoff, 30% were still open, and 50% were lost. New ARR booked reached 2.7 times search spend (derived). Brand captures existing demand, so it isn’t treated as entirely new demand created by the build.

    • These are first results from new accounts, not growth against an earlier baseline. Pipeline-to-spend is not ROAS, and new ARR booked is not revenue recognized in the period. Dollar values are withheld.
    Checked against
    • BuildsArchitecture workbooks, platform exports, keyword maps and negative lists, QA checklists and sign-offs, and launch milestones
    • Spend and conversionsPlatform spend reconciled with deduplicated CRM demos and leads
    • Opportunities, pipeline, and bookingsLinked CRM cohort reports, closed-won records, signed contracts, and finance-approved new-ARR reporting

Approach

How strategy becomes execution.

Each stage ends in a decision, not just an activity.

  1. Start with the revenue question

    Define the commercial goal and the evidence needed to judge progress toward it.

    What does success mean beyond a platform conversion?

  2. Architect the program

    Set account priorities, buying-group messaging, and a clear role for every campaign.

    Which accounts deserve priority, and what is each campaign for?

  3. Invest and experiment

    Allocate budget by role, launch carefully, and test what the plan is unsure about.

    What would change our next investment decision?

  4. Measure and decide

    Read platform results alongside account progression and opportunity quality.

    Where should investment move, and what evidence supports it?

Leading the work.

  • Direction and accountability

    I direct and review the contractor teams that run paid media and ABM on my accounts: setting expectations for each build, reviewing what comes back, and keeping the work tied to the strategy.

  • Clear quality standards

    Launch checks and handoffs let execution be reviewed consistently across people and platforms. See launch governance.

  • Repeatable workflows

    Templates, structured workflows, and AI-assisted tools make recurring planning, reporting, QA, and research easier to repeat. I use AI to investigate, reconcile, organize, and draft, and I review what it produces before anything is treated as fact.

  • Currently developing

    An AI-assisted operating approach for paid media and ABM, connecting measurement, audience coverage, media efficiency, QA, and reporting with recurring checks. It’s a design direction, not a finished system.

About

Where my approach comes from.

Houston Teamer

  1. MARINE CORPS

    My background in Marine Corps communications shaped how I approach technical problems, accountability, and execution.

  2. MARKETING PRACTICE

    Hands-on work across search, paid media, and ABM taught me how strategy holds up in real campaigns.

  3. GRADUATE STUDY

    My graduate studies in Management at Harvard Extension School add another perspective to how I think about business decisions and organizational performance.

Career

  1. 2024–Present
    Alcamo MarketingSenior Demand Generation Strategist

    Demand generation and ABM strategy for B2B organizations across North America, EMEA, APAC, and ANZ.

  2. 2021–2024
    HawkSEMSearch Engine Marketing Manager

    Search strategy and optimization across a portfolio of client accounts.

  3. 2021
    Loma MediaDigital Marketing Lead

    Paid search, paid social, and analytics for public-sector, B2B, education, and nonprofit clients.

  4. 2018–2021
    Independent consulting and Eqqo DigitalDigital Marketing Consultant · Marketing Associate

    Strategy, execution, research, and acquisition.

  5. 2010–2015
    U.S. Marine CorpsGround Communications Technician

    Technical troubleshooting, team leadership, and operational accountability.

Credentials

  • U.S. Marine Corps veteran2010–2015
  • ALM in ManagementHarvard Extension School · expected December 2026
  • B.S. in MarketingCalifornia State University, Northridge

Tools in context

Media activation
Google Ads, Microsoft Advertising, LinkedIn, Meta, Reddit, Basis
ABM, intent, and CRM
Demandbase, 6sense, Userled, Bombora, Salesforce, HubSpot, Marketo
Measurement and reporting
GA4, Google Tag Manager, Looker Studio, Sheets, Excel

Let’s build what’s next.

For conversations about demand generation, ABM, and marketing leadership.