Oxford / Applied AI
AI voice agent & officer routing
Led the team building an AI voice workflow, working alongside them to connect lead conversations, loan-officer routing, and handoff reporting.
SELECTED WORK
The systems behind the strategy.
Team-led delivery and hands-on work across growth operations, data infrastructure, and digital acquisition. Each project explains the problem, my contribution, and the evidence.
14 PROJECTS
01
Growth operations
Turn customer interest into a connected, measurable operating process.
Oxford / Lead operations
Credit monitoring & lead suppression
Automated credit-event processing, suppression checks, and campaign-ready data delivery.
Oxford / Contact controls
Automated do-not-call screening
Connected batch contact screening to CRM status updates and processing summaries.
Oxford / Customer experience
Customer feedback & review app
Built an officer-personalized application for collecting feedback after the customer experience.
Oxford / Digital acquisition
Organic lead capture & attribution
Connected digital discovery and website forms to recorded leads and channel attribution.
02
Data & applied AI
Connect the underlying records, tools, and decisions that support growth.
Oxford / Data infrastructure
Snowflake & dbt data foundation
Unified CRM, loan, and campaign data into reusable models for reporting and operations.
Oxford / CRM transformation
HubSpot CRM migration roadmap
Defined the data mappings, dependencies, and delivery roadmap for a CRM migration.
Oxford / Sales visibility
Sales performance & conversion dashboard
Built a live reporting baseline with date filters, period comparisons, and branch-to-officer visibility into volume, conversion, goals, and cost.
Oxford / AI integration
AI access to business data
Connected AI assistants to business systems through purpose-built tools and data access.
Company-neutral / Modeled scenario
Google & Meta milestone optimization
Designed a modeled feedback system that makes setup completion the campaign’s optimization win.
03
Digital experiences
Lead teams translating brand and acquisition strategy into customer journeys.
Brick House Blue / Website
Brick House Blue workspace website
Led the team creating a workspace website that connects brand, locations, and service discovery to clear inquiry paths.
Oxford Home Lending / Website
Oxford mortgage website & lead capture
Led the website team and worked alongside design and development to connect mortgage content, customer tools, and attributed lead capture.
Rouge Aesthetics / Webflow
Rouge Aesthetics consultation website
Led the team building a Webflow experience that makes treatment options clear and guides visitors toward consultation.
Water Lily / Website
Water Lily service-brand website
Led the team translating a service brand into a distinctive website with clear offerings and customer next steps.
DIGITAL GROWTH PLATFORM
Oxford mortgage website & lead capture
Led the website team and worked alongside design and development to connect mortgage content, customer tools, and attributed lead capture.
MY CONTRIBUTION
Team leadership, platform strategy & collaborative delivery
Explore the live experienceTHE PROBLEM
Mortgage choices and next steps can be difficult to navigate online.
HOW I LED & CONTRIBUTED
Led platform strategy and the website team, working with Vladyslav Kuzmenko on design and development and connecting the experience to lead capture.
WHY IT MATTERS
Structured content and customer journeys connect the website to the wider acquisition and measurement system.
01 / EXPLORE THE WORKPROJECT EVIDENCE
02 / HOW THE PARTS CONNECT
Explore the thinking
behind the build.
01
Understand intent
Structure the experience around customer questions and mortgage goals.
03
Keep the context
Carry acquisition information into the CRM and reporting foundation.
02
Illustrative walkthrough of the design. Playback does not run a live workflow.Create a useful next step
Connect content and tools with clear inquiry paths.
BRAND EXPERIENCE / WEBFLOW
Rouge Aesthetics consultation website
Led the team building a Webflow experience that makes treatment options clear and guides visitors toward consultation.
MY CONTRIBUTION
Website team leadership & collaborative execution
Explore the live experienceTHE PROBLEM
A broad treatment offering can be hard to assess before a consultation.
HOW I LED & CONTRIBUTED
Led the website team and collaborated on service structure, visual experience, and the consultation path.
WHY IT MATTERS
Makes the offering easier to explore and discuss with the team.
01 / EXPLORE THE WORKPROJECT EVIDENCE
02 / HOW THE PARTS CONNECT
Explore the thinking
behind the build.
01
Begin with the person
Introduce the practice through a welcoming visual experience.
03
Invite a conversation
Connect uncertainty to a clear consultation path.
02
Illustrative walkthrough of the design. Playback does not run a live workflow.Create understanding
Make treatment categories and common questions easy to explore.
Evidence & scope +
Live Rouge Webflow site inspected September 10, 2026. Website contribution supplied by Logan. Outcome describes the implemented journey, not a measured conversion increase.
BRAND & DIGITAL EXPERIENCE
Brick House Blue workspace website
Led the team creating a workspace website that connects brand, locations, and service discovery to clear inquiry paths.
MY CONTRIBUTION
Website team leadership & collaborative execution
Explore the live experienceTHE PROBLEM
Visitors arrive with different needs for offices, coworking, meetings, and events.
HOW I LED & CONTRIBUTED
Led the website team and worked alongside them on the brand presentation, location structure, and inquiry journey.
WHY IT MATTERS
Helps prospective customers find the right space and next step.
01 / EXPLORE THE WORKPROJECT EVIDENCE
02 / HOW THE PARTS CONNECT
Explore the thinking
behind the build.
01
Find the need
Separate workspace, meeting, office, and event intentions.
03
Start the conversation
Give interested visitors a clear inquiry path.
02
Illustrative walkthrough of the design. Playback does not run a live workflow.Explore the fit
Connect the service to the relevant space and location.
Evidence & scope +
Live website. Portfolio contribution supplied by Logan.
SERVICE BUSINESS & BRAND
Water Lily service-brand website
Led the team translating a service brand into a distinctive website with clear offerings and customer next steps.
MY CONTRIBUTION
Website team leadership & collaborative execution
Explore the live experienceTHE PROBLEM
The website needs to communicate both the service and the person behind it.
HOW I LED & CONTRIBUTED
Led the website team and worked alongside them to connect brand presentation, service discovery, and the customer journey.
WHY IT MATTERS
Gives prospective clients a clear introduction and next step.
01 / EXPLORE THE WORKPROJECT EVIDENCE
02 / HOW THE PARTS CONNECT
Explore the thinking
behind the build.
01
Meet the person
Introduce the story and perspective behind the service.
03
Build a connection
Provide a natural invitation to get in touch.
02
Illustrative walkthrough of the design. Playback does not run a live workflow.Understand the offering
Make service information clear and approachable.
Evidence & scope +
Live website. Portfolio contribution supplied by Logan.
AUTOMATION / OXFORD
Credit monitoring & lead suppression
Automated credit-event processing, suppression checks, and campaign-ready data delivery.
MY CONTRIBUTION
Workflow design and automation
THE PROBLEM
Credit and funded-loan signals arrive through separate operational paths.
WHAT I BUILT
Connected monitoring feeds, record matching, suppression rules, and exports.
WHY IT MATTERS
Gives teams a repeatable way to prepare relevant lead activity.
01 / EXPLORE THE WORKPROJECT EVIDENCE
02 / HOW THE PARTS CONNECT
Explore the thinking
behind the build.
01
Collect & segment
Refresh source access and compile distinct credit and funding audiences.
03
Route with control
Send matched records into the CRM and retain a defined unmatched path.
02
Illustrative walkthrough of the design. Playback does not run a live workflow.Match & enrich
Resolve incoming records against the warehouse and validate officer context.
Evidence & scope +
Two original workflow diagrams supplied by Logan.
OPERATIONAL CONTROLS / OXFORD
Automated do-not-call screening
Connected batch contact screening to CRM status updates and processing summaries.
MY CONTRIBUTION
Operational workflow automation
THE PROBLEM
Screening results must reach the records that teams use for outreach.
WHAT I BUILT
Built batch scrubbing, result mapping, CRM updates, and run summaries.
WHY IT MATTERS
Makes contact-status screening a repeatable part of lead operations.
01 / EXPLORE THE WORKPROJECT EVIDENCE
02 / HOW THE PARTS CONNECT
Explore the thinking
behind the build.
01
Prepare the batch
Check service availability and retrieve the CRM report.
03
Update & repeat
Record timestamps and relevant markers, then pace the next batch.
02
Illustrative walkthrough of the design. Playback does not run a live workflow.Scrub & interpret
Submit a batch and map returned statuses into a consistent structure.
Evidence & scope +
Original workflow diagram supplied by Logan. The workflow is not a claim of complete legal compliance.
CUSTOM APPLICATION / OXFORD
Customer feedback & review app
Built an officer-personalized application for collecting feedback after the customer experience.
MY CONTRIBUTION
Product design and application development
Explore the live experienceTHE PROBLEM
Customers need a straightforward way to share feedback with the team.
WHAT I BUILT
Created personalized feedback pages and response paths.
WHY IT MATTERS
Connects the customer, the loan officer, and the feedback process.
01 / EXPLORE THE WORKPROJECT EVIDENCE
REPUTATION / REPORTED PLATFORM RESULTS
Customer feedback, made visible.
Google4.8/5
87 reviews
Experience.com4.8/5
286 reviews
Facebook5/5
1 vote
Review-platform snapshots supplied by Logan. These describe Oxford’s visible ratings; they do not establish how many reviews the app generated or its incremental impact. See the original screenshots below.
02 / HOW THE PARTS CONNECT
Explore the thinking
behind the build.
01
Personalize the moment
Show the loan officer associated with the experience.
03
Make the loop visible
Connect the application story with independently scoped reputation snapshots.
02
Illustrative walkthrough of the design. Playback does not run a live workflow.Make feedback easy
Use a direct experience question and an understandable response choice.
Evidence & scope +
Application screenshot, live app link, and review-platform screenshots supplied by Logan. Results were supplied September 9, 2026; the screenshot capture dates are not independently verified. These are platform snapshots, not app-attributed review counts or a before-and-after measurement. Platform populations may overlap and are not added together. The application screenshot’s 35,000+ review text has a different stated scope and is not used as a portfolio result.
VAPI CALL AGENT / OXFORD
AI voice agent & officer routing
Led the team building an AI voice workflow, working alongside them to connect lead conversations, loan-officer routing, and handoff reporting.
MY CONTRIBUTION
Team leadership, strategy & hands-on integration
THE PROBLEM
An AI conversation creates business value when the lead reaches the right person and the handoff can be measured.
HOW I LED & CONTRIBUTED
Led the build team and contributed alongside them to the voice-agent workflow, CRM routing, and officer-answer reporting.
WHY IT MATTERS
Routing records can be compared with matched officer answers, making follow-through visible beyond call volume.
01 / EXPLORE THE WORKINTERACTIVE EVIDENCE
Routing and real follow-through.
Routed leadsMatched officer answers
Unique leads · July starts July 9. Select a month to explore its outcome mix. The periods have different lengths.
What happened after routing?
91.1%758 of 832 routed leads
Matched officer answer758
No qualifying matched answer74
An answer requires positive officer talk time without a voicemail tag, matched within ±2 days of distribution. This measures matched follow-through, not direct transfer success.
02 / HOW THE PARTS CONNECT
Explore the thinking
behind the build.
01
AI-assisted intake
Use the voice agent as part of the customer intake experience.
03
Measure follow-through
Compare distribution records with matched officer-answer evidence.
02
Illustrative walkthrough of the design. Playback does not run a live workflow.Assign the next step
Connect the lead to the CRM’s officer-routing workflow.
Evidence & scope +
Verified Snowflake routing and CTM call aggregates, September 9, 2026. A matched officer answer means positive non-voicemail talk time within ±2 days of distribution. This is not a Vapi platform call count or proof of a direct live transfer. Graphs show the verified monthly routing and matched-answer counts.
ORGANIC ACQUISITION / OXFORD
Organic lead capture & attribution
Connected digital discovery and website forms to recorded leads and channel attribution.
MY CONTRIBUTION
Digital growth strategy and acquisition systems
THE PROBLEM
Digital activity needs a traceable path into the CRM.
WHAT I BUILT
Connected lead capture with source context and CRM records.
WHY IT MATTERS
Makes organic acquisition visible beyond website traffic.
01 / EXPLORE THE WORKPROJECT EVIDENCE
02 / HOW THE PARTS CONNECT
Explore the thinking
behind the build.
01
Attract intent
Create an experience that supports search-driven discovery.
03
Preserve the channel
Use explicit source and medium fields to distinguish organic inquiries.
02
Illustrative walkthrough of the design. Playback does not run a live workflow.Capture the inquiry
Connect digital forms with CRM lead creation.
Evidence & scope +
Aggregate Velocify records mirrored in OXFORD_MARKETING.CORE.LEAD_HISTORY, queried September 9, 2026. Counts reflect unique CRM lead IDs and current attribution fields, not incremental lift or qualified borrowers. Architecture graphic illustrates the journey.
AUTOMATED CONVERSION REPORTING
Sales performance & conversion dashboard
Built a live reporting baseline with date filters, period comparisons, and branch-to-officer visibility into volume, conversion, goals, and cost.
MY CONTRIBUTION
Dashboard strategy, reporting automation & performance analysis
THE PROBLEM
A headline total cannot explain whether performance changed because of lead volume, conversion, team execution, or cost. Leaders needed a shared baseline they could investigate.
WHAT I BUILT
Built a live, date-filtered dashboard spanning branches, teams, and loan officers, with period deltas, funnel milestones, setup targets, return rates, and cost per setup.
WHY IT MATTERS
Gives leaders a common view for daily standups and weekly reviews: spot a change, locate it in the funnel, and focus the next coaching or operating decision.
01 / EXPLORE THE WORKINTERACTIVE EVIDENCE
02 / HOW THE PARTS CONNECT
Explore the thinking
behind the build.
01
Set the reporting window
Choose today versus yesterday or comparable weekly periods. A consistent reporting window gives every team the same operating baseline.
03
Turn the baseline into action
Use the shared dashboard to prioritize coaching, review downstream conversion, and monitor whether the next period moves in the intended direction.
02
Illustrative walkthrough of the design. Playback does not run a live workflow.Trace the variance
Compare changes in lead volume, conversion, setup goals, and cost; move from branch to team to loan officer to investigate the variance.
Evidence & scope +
Logan built this as a live baseline dashboard with date filters and period comparisons for the team. This portfolio reconstructs the experience from supplied screenshots. The latest image contains 616 leads, 446 file starts, 72.4% lead-to-start, and 72 disclosures; its date range is not visible. The earlier September 1–10 screenshot is a separate snapshot. The supplied view preserves visible values and percentage deltas. Date-comparison examples use explicitly labeled sample data. Names are anonymized, and only the five visible officer rows are reproduced. No measured performance improvement is attributed to the dashboard.
SNOWFLAKE + DBT / OXFORD
Snowflake & dbt data foundation
Unified CRM, loan, and campaign data into reusable models for reporting and operations.
MY CONTRIBUTION
Data architecture and dbt development
THE PROBLEM
Fragmented systems make identities and outcomes difficult to reconcile.
WHAT I BUILT
Built staging, identity resolution, enriched models, and reporting views.
WHY IT MATTERS
Identity resolution and reusable models connect CRM operations, migration, attribution, and conversion reporting to a shared data foundation.
01 / EXPLORE THE WORKPROJECT EVIDENCE
10 SECONDS / THE DATA FOUNDATION
From disconnected records
to a connected business.
SNOWFLAKE + DBT
01 / 0.0sSource contextExplore02 / 2.1sNormalizeExplore03 / 4.5sConnectExplore04 / 7.0sActivateExplore
Source context
CRM, loan finance, milestone, campaign, and web data begin with different structures. The animation starts with source data already available in the warehouse.
A simplified illustration inspired by my dbt architecture. Labels and examples are company-neutral. The 10-second sequence explains the process; it does not represent production runtime or a measured performance improvement.
02 / HOW THE PARTS CONNECT
Explore the thinking
behind the build.
01
Unify the sources
Bring lead, loan, marketing, and CRM records into a shared environment.
03
Put it to work
Support migration, attribution, and repeatable operational reporting.
02
Illustrative walkthrough of the design. Playback does not run a live workflow.Resolve & model
Establish identities and transform source data into useful business structures.
Evidence & scope +
Original DAG screenshots supplied by Logan, local dbt models, and aggregate Snowflake queries. The 10-second video is a simplified, company-neutral illustration of the architecture; examples are synthetic and the timing is narrative, not measured production runtime.
ARCHITECTURE / MIGRATION LEADERSHIP
HubSpot CRM migration roadmap
Defined the data mappings, dependencies, and delivery roadmap for a CRM migration.
MY CONTRIBUTION
Architecture and migration planning
THE PROBLEM
Moving CRMs requires agreement on data, workflows, and ownership.
WHAT I BUILT
Organized the migration into scoped modules and validation steps.
WHY IT MATTERS
Gives teams a clear sequence for implementation and acceptance.
01 / EXPLORE THE WORKINTERACTIVE EVIDENCE
48MODULES OF ARCHITECTURE · MIGRATION PLANNING02Identity & relationshipsDefine the data modelTranslate fragmented records into a consistent customer and business model.Object relationship modelSee the work & an example 03Routing & lifecycleDesign the operating flowsMake assignment, customer progression, and exception handling understandable.Lead-routing decision mapSee the work & an example 04Integration & controlsConnect the systemsSpecify how systems exchange data and recover when a handoff fails.Integration contractsSee the work & an example 05Reconciliation & qualityPlan validationDefine how the team will know the migrated experience is working as intended.Reconciliation checklistSee the work & an example 06Sequencing & handoffPrepare the transitionTurn the architecture into a staged implementation and operating roadmap.Implementation sequenceSee the work & an example
The through-line
I translated business operations into a connected architecture, documented the decisions and dependencies, and built a detailed plan for implementation. These six phases summarize the scope of a 48-module planning effort.
01
Discovery & scope
Understand the operation
Map how people, data, and decisions move through the business.
The work I did
- Mapped the current systems and the teams that rely on them.
- Documented intake paths, ownership changes, and recurring operational gaps.
- Separated business requirements from platform-specific behavior.
What I produced
- Current-state system map
- Stakeholder and dependency map
- Requirements and decision register
ILLUSTRATIVE MODULE / GENERIC EXAMPLE
System responsibility map
| Layer | Responsibility | Handoff |
|---|---|---|
| Customer touchpoints | Capture requests and context | Validated inquiry |
| Operational workspace | Coordinate ownership and follow-up | Activity and outcome |
| Data platform | Resolve identities and model reporting | Consistent business context |
Why this mattersA shared definition of what the transition needs to preserve.
02
Identity & relationships
Define the data model
Translate fragmented records into a consistent customer and business model.
The work I did
- Defined the purpose and relationships of core business objects.
- Mapped fields by meaning, ownership, and downstream use.
- Documented identity matching, duplicate handling, and conflict rules.
What I produced
- Object relationship model
- Field-mapping examples
- Identity and data-quality rules
ILLUSTRATIVE MODULE / GENERIC EXAMPLE
Identity and relationship module
| Concept | Example rule | Review point |
|---|---|---|
| Customer record | Preserve a stable source reference | Check duplicate candidates |
| Business opportunity | Associate with the correct customer | Review unmatched relationships |
| Conflicting values | Use the designated source of truth | Queue exceptions for review |
Why this mattersAn explicit model for what moves, what connects, and what stays at the source.
03
Routing & lifecycle
Design the operating flows
Make assignment, customer progression, and exception handling understandable.
The work I did
- Mapped intake routes and the conditions that determine the next owner.
- Defined lifecycle transitions, activities, and follow-up responsibilities.
- Designed fallback paths for unavailable owners and incomplete context.
What I produced
- Lead-routing decision map
- Lifecycle and activity definitions
- Exception and fallback playbook
ILLUSTRATIVE MODULE / GENERIC EXAMPLE
Routing decision module
| Decision | Illustrative path | Expected result |
|---|---|---|
| Is the request ready? | Check required context | Proceed or request review |
| Is an eligible owner available? | Evaluate the relevant team | Assign ownership |
| Can no owner accept? | Send to a monitored fallback queue | Keep the request visible |
Why this mattersA documented operating model that teams can follow and implement.
04
Integration & controls
Connect the systems
Specify how systems exchange data and recover when a handoff fails.
The work I did
- Defined the responsibilities of the CRM, data layer, and automation services.
- Documented synchronization direction, field ownership, and event handling.
- Specified replay, exception handling, and access boundaries.
What I produced
- Integration contracts
- Synchronization and recovery rules
- Data access and consent boundaries
ILLUSTRATIVE MODULE / GENERIC EXAMPLE
Integration contract module
| Contract element | Illustrative requirement | Purpose |
|---|---|---|
| Record identity | Use a stable record reference | Prevent duplicate updates |
| Change handling | Apply approved field changes | Preserve system ownership |
| Failure handling | Record the failure and retry safely | Make recovery traceable |
Why this mattersClear contracts that reduce ambiguity between applications and delivery teams.
05
Reconciliation & quality
Plan validation
Define how the team will know the migrated experience is working as intended.
The work I did
- Specified checks for completeness, relationships, and field-level accuracy.
- Mapped operational reports to their underlying definitions.
- Documented exception reviews and acceptance criteria.
What I produced
- Reconciliation checklist
- Reporting comparison plan
- Acceptance and exception criteria
ILLUSTRATIVE MODULE / GENERIC EXAMPLE
Validation checklist module
| Check | Illustrative evidence | Decision |
|---|---|---|
| Record completeness | Compare expected and received records | Investigate unexplained gaps |
| Relationship integrity | Check valid customer associations | Resolve orphaned records |
| Workflow behavior | Walk through representative scenarios | Confirm acceptance criteria |
Why this mattersAn evidence-based way to assess readiness and identify gaps.
06
Sequencing & handoff
Prepare the transition
Turn the architecture into a staged implementation and operating roadmap.
The work I did
- Organized dependencies into a sequence the delivery team can execute.
- Documented cutover checkpoints, rollback considerations, and ownership.
- Defined how teams will use the new workflows and monitor exceptions.
What I produced
- Implementation sequence
- Cutover and rollback plan
- Team handoff and monitoring guide
ILLUSTRATIVE MODULE / GENERIC EXAMPLE
Transition readiness module
| Stage | Illustrative checkpoint | Owner responsibility |
|---|---|---|
| Prepare | Confirm mappings and prerequisites | Resolve open dependencies |
| Pilot | Review representative workflows | Record issues and decisions |
| Transition | Assess readiness and recovery options | Coordinate the handoff |
Why this mattersA practical roadmap from design decisions to a controlled transition.
02 / HOW THE PARTS CONNECT
Explore the thinking
behind the build.
01
Define the operating model
Map the source context, entities, and workflow requirements.
03
Plan the transition
Connect validation and acceptance criteria to a staged readiness roadmap.
02
Illustrative walkthrough of the design. Playback does not run a live workflow.Specify the contracts
Make data structures, integrations, and ownership explicit.
Evidence & scope +
The scope reflects Logan’s architecture and migration-planning work. This portfolio roadmap uses illustrative module examples; it does not reproduce the original manifest, company-specific configuration, operational counts, or source-system identifiers. Transition planning is not a claim that every rollout step has been completed.
AI INTEGRATION / CUSTOM TOOLS
AI access to business data
Connected AI assistants to business systems through purpose-built tools and data access.
MY CONTRIBUTION
Custom integration development
THE PROBLEM
An assistant needs reliable access to business context to answer useful questions.
WHAT I BUILT
Built MCP connections between assistants, tools, and warehouse data.
WHY IT MATTERS
Lets business questions reach the underlying information through a defined interface.
01 / EXPLORE THE WORKPROJECT EVIDENCE
02 / HOW THE PARTS CONNECT
Explore the thinking
behind the build.
01
Ask a business question
Start with a defined outcome, period, and reporting scope.
03
Validate the answer
Reconcile aggregate results and keep the supporting definitions visible.
02
Illustrative walkthrough of the design. Playback does not run a live workflow.Connect through MCP
Give the AI workflow a structured path to the relevant data tools.
Evidence & scope +
Configured Oxford Snowflake MCP successfully queried on September 9, 2026.
14 / 14
Close projectMULTICHANNEL ACQUISITION / A COMPANY-NEUTRAL MODEL
Google & Meta milestone optimization
Designed a modeled feedback system that makes setup completion the campaign’s optimization win.
WHAT THIS PROJECT DEMONSTRATES
Funnel analysis, milestone selection, CRM automation, and platform goal configuration: a system designed to acquire more setup-ready leads at a lower cost per setup.
PORTFOLIO SIMULATION
A self-authored operating model with $9M in synthetic media spend. All campaign figures and platform-style views are illustrative, not client results, live accounts, or screenshots from Google or Meta.
THE PROBLEM
Late revenue events delay feedback about the behavior acquisition should target.
WHAT I BUILT
Worked backward from outcomes, selected setup, and mapped CRM events to each platform.
WHY IT MATTERS
Measures cost per setup and lead volume while later revenue validates the goal.
THE MILESTONE FEEDBACK LOOP
Work backward to choose the goal. Feed it forward to optimize.
Illustrative workflow / no live data
A financial close tells us which earlier behaviors mattered. Setup becomes the selected success event: when its completion criteria are met, the platform receives an optimization win without waiting for the later sale.
01 / START WITH THE OUTCOME
Study eventual wins.
Join earlier CRM milestones to mature revenue outcomes. Find the behaviors that reliably precede valuable business.
02 / WORK BACKWARD
Choose setup.
Select a defined, verifiable setup milestone that balances predictive quality, event volume, and feedback delay.
03 / MOVE THE LEARNING GOAL
Setup is the optimization win.
Configure setup completed as the conversion the campaign should acquire. Later revenue validates the choice.
01 / THE LEAD MOVES FORWARD
Play the handoffSetup criteria met: record one optimization win
02 / THE AUTOMATION MAKES IT USEFUL
CRM webhook or scheduled change sync
01
Match the lead
Connect the CRM record to its campaign and available click identifiers.
02
Verify setup
Confirm the required setup behavior actually happened. Check consent and block duplicate milestone events.
03
Create the win
Create one setup-completed conversion. Attach a calibrated expected value only when the strategy calls for it.
04
Route and deliver
Send the setup event to its eligible platform route. Preserve event time, retry failures, and audit receipts.
Each event follows its eligible platform route
GOOGLE ADS
Setup completed / primary conversion
Data Manager API / enhanced conversions for leads
META ADS
Setup completed / CRM goal
Conversions API for CRM
03 / THE FEEDBACK INFORMS THE NEXT ROUND
Find more people who reach setup.
Setup feedback gives the selected goal earlier, more frequent examples of success. Evaluate improvement through cost per setup, setup volume, and the quality of the leads arriving.
Choose a milestone or play the handoff. Animation demonstrates the sequence, not processing speed.
The earlier win is intentional.
The strategy moves the optimization target from a late financial outcome to an earlier behavior backed by funnel analysis. The algorithm learns from setup completions while the business continues to track revenue.
Measure the same milestone over time.
Cost per setup is media spend divided by verified setup completions. Compare that measure across cohorts. A lower setup CPA than sale CPA reflects different denominators; it is not, by itself, an efficiency gain.
Keep checking the signal.
Track setup-to-revenue progression and later outcomes as volume scales. If setup becomes easier to trigger but less predictive of valuable business, refine the criteria or change the learning goal.
A chosen behavior, backed by outcomes.
Setup is the model’s explicitly defined earlier conversion milestone. Prior stage-to-win rates help select and validate it; an expected dollar value is optional for activation. An optimization win at setup does not book a financial sale.
THE MODELED BUSINESS CASE
Acquire the behavior that matters.
12 acquisition months / USD
Every cohort observed for 90 days
ANNUAL MEDIA SPEND
$9.00M
12 campaigns / 2 platforms
OPTIMIZATION WINS / SETUPS
17,042
Verified milestone completions
COST PER SETUP
$528.11
$9M divided by 17,042 setups
CRM LEADS GENERATED
75,740
$118.83 per CRM lead
More leads. More setup completions.
Monthly CRM leads and setup completions
Select a month for the exact figures. All amounts are generated by the model.
Q4 COMPARED WITH Q1
Cost per setup
−14.6%
Setup completions
+57.6%
Cost per lead
−6.2%
CRM lead volume
+43.5%
Spend grows 34.6%. Q1 and Q4 both use setup completion as the denominator: $578.44 to $493.95 per setup. Modeled improvements reflect budget, mix, and funnel assumptions, not a measured causal test.
01 / BASELINE
Start with eventual outcomes.
Join mature outcomes to earlier lead behaviors, compare progression, and identify a milestone with useful volume and shorter delay.
02 / DEFINE SETUP
Move the optimization win earlier.
Define setup criteria, validate the signal, and configure setup completed as the selected campaign conversion.
03 / VALUE
Learn from mature cohorts.
Estimate stage value from earlier outcomes, calibrate by campaign family, and keep realized revenue separate from predictions.
04 / SCALE
Expand within constraints.
Allocate toward stronger economics, cap retargeting and brand demand, refresh creative, and reduce underperforming competitor search.
Deliberately uneven.
The budget scales from $600,000 to $880,000 per month. Auction pressure and diminishing returns offset part of the improvement. Competitor search worsens and loses allocation; Instagram prospecting changes little. These are explicit scenario assumptions, not observed campaign incidents.
Later financial outcomes validate the choice of milestone: 2,338 modeled sales and $16.84M of modeled booked contract value. Those outcomes are separate from the 17,042 setup optimization wins.
THE BEHAVIOR BEHIND THE WIN
Reverse-engineer the goal from eventual outcomes.
One lead journey / six stage-entry cohorts
Thank you! Your submission has been received!
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Measure the journey. Choose the goal.
Setup completed is the optimization win in this model. Google uses a selected primary conversion action; Meta uses the supported mapped CRM goal. Later financial outcomes validate the milestone, while other stages remain measurable.
Never count the same revenue six times.
The cohort backsolve shows the same revenue from six stage-entry denominators. These values are not additive. Pipeline value uses each lead’s latest eligible state, and realized revenue is counted once per unique closed transaction.
Keep tomorrow out of yesterday’s model.
Prospective values use fixed, illustrative pre-period win-rate and deal-value assumptions. A production implementation would fit earlier mature cohorts, validate on later cohorts, and monitor calibration before activation.
THE DATA FOUNDATION
One durable model. Two activation paths.
Choose a layer to inspect its responsibility.
BUSINESS KEYS
Define the grain before the join.
Spend: platform + campaign + date. Lead: canonical lead ID. Milestone: lead ID + stage + first-entry timestamp. Revenue: unique transaction ID. Outbox: destination + lead + milestone version.
QUERY DESIGN
Move computation out of dashboards.
Pre-aggregate daily spend and cohort outcomes. Use date-pruned incremental models, selective clustering where it improves measured scans, and a late-arrival lookback with periodic reconciliation.
VALIDATION
Make errors visible before activation.
Enforce unique keys, test relationships and stage ordering, quarantine identity conflicts, and reconcile spend and transactions. An accepted API request is not proof of an attributed conversion.
Model assumptions, attribution, and technical references
Optimization definition: setup completed is the earlier goal, with one conversion per unique lead meeting the setup criteria. This synthetic model assumes setup occurs after qualification and before opportunity. The setup field is distinct from the won transaction field. Cost per setup is spend / setup; CPL is spend / leads; financial customer acquisition cost is spend / financial wins.
Scope. A synthetic high-consideration service acquisition scenario. The $9M covers media only. Revenue is modeled gross closed-won contract value within 90 days of lead acquisition; it is not cash collected, net profit, or a real advertiser’s revenue. All twelve cohorts have equal maturity.
Attribution. CRM leads use a single canonical identity and one deterministic last-eligible-paid-touch campaign within a modeled 30-day click window. Each transaction is counted once. Platform-style tables show CRM-reconciled custom columns, not the platforms’ self-attributed totals. Platform attribution windows and view-through reporting can differ, so cross-platform reported conversions should not simply be added.
Generation. A reproducible 144-row model spans 12 campaigns and 12 months. Budget totals reconcile to $9M. Channel mix, CPL, stage progression, and deal values have explicit trend and seasonal assumptions. Rounded lead and transaction counts drive every displayed ratio. This is a scenario, not a causal test or a promise of future performance.
Activation. Consent and permitted-use checks precede outbound events. Normalize and hash identifiers where required, preserve event occurrence time, use stable deduplication keys, and monitor delivery diagnostics. Google’s Data Manager API and Meta’s CRM integration require destination configuration and access; no connection is made by this portfolio.
Google: sending conversion events · Google: enhanced conversions for leads · Meta: Conversions API for CRM
Download the modeled campaign data