Product Owner, Growth (AI-First)

The Role
Belong's growth constraint is supply. Every homeowner who activates on the platform adds a
home to the network, creates a resident opportunity, and moves Belong closer to the profitability
inflection that defines the next chapter of the company. The homeowner funnel, from first
impression through signed agreement and activated listing, is the highest-leverage product
surface in the business.
Most growth product roles are about optimizing what already exists: faster page loads, shorter
forms, better copy. This role is about building something structurally different. Belong's
homeowner acquisition funnel is being rebuilt as an AI-native system: conversational intake
powered by LLMs, personalized onboarding that adapts dynamically to each homeowner's
financial profile, predictive scoring that routes the right lead to the right moment in the Advisor
workflow, and agentic follow-up that replaces manual sequences with intelligent, context-aware
outreach. The target is a funnel that learns, where every interaction generates signal that makes
the next interaction more likely to convert.
As Product Owner, Growth, you are the person building that system. You own the homeowner
acquisition and activation funnel end to end, from first contact to listed home. You ship in weekly
cycles, instrument everything, and hold conversion and experience quality simultaneously. This
role is for someone who understands that growth at Belong is not a marketing problem. It is a
product problem, and the product is increasingly an AI system.

Examples of What You'll Own
The AI-native intake and qualification layer.
The first interaction a homeowner has with Belong, whether via belonghome.com, a paid
channel, or a referral, is where trust is either established or lost. You will build conversational
intake flows powered by LLMs that qualify, capture, and begin converting leads in real time.
These are not chatbots with decision trees. They are context-aware systems that understand
the difference between a cashflow-positive homeowner who wants yield optimization and a
cashflow-negative homeowner who needs a path to profitability, and adapt the conversation, the
framing, and the call-to-action accordingly. The Cashflow Lens is not a marketing concept. It is a
segmentation variable that must be detected early and carried through every subsequent
product interaction.
Personalized onboarding and trust architecture.
A homeowner considering Belong is anxious. They are considering handing over their most
valuable asset to a platform they found online. Conversion at this stage is not a UX problem. It
is a trust architecture problem. You will design onboarding sequences that adapt dynamically
based on homeowner attributes: property type, cashflow profile, prior rental history, risk signals,

and behavioral signals from in-session activity. You will use LLMs to generate personalized
content, market analyses, improvement ROI estimates, comparable listings, that makes the
value proposition concrete and specific to their home, not generic.
Predictive lead scoring and Advisor routing.
Belong's Advisors are the trust-critical human touchpoint in the homeowner funnel. Their time is
finite and high-value. You will build the predictive infrastructure that scores every lead on
conversion likelihood, property quality, and fit with Belong's ICP, and routes leads to Advisors
with the context they need to have the right conversation immediately. You will work with data
science to train and evaluate these models, with RevOps to deploy them into the Salesforce
workflow, and with Sales leadership to validate signal quality against actual close rates.
Agentic follow-up and nurture sequences.
Most leads do not convert on the first contact. Today, nurture is a sequence of templated emails.
The target state is an AI agent that monitors lead behavior, page views, document opens, return
visits, session signals, and generates contextually appropriate, personalized outreach at the
right moment, with the right frame, without a human initiating every touchpoint. You will define
the agent's decision logic, build the context retrieval pipeline, instrument the output quality, and
iterate on conversion impact week over week.
Funnel instrumentation and the learning loop.
An AI-native funnel without rigorous instrumentation is a black box. You will build the
measurement architecture that makes every conversion decision traceable: which intake flow
variant produced the lead, which scoring model routed it, which agent-generated touchpoint
influenced the next action, which Advisor framing closed it. You will design the feedback loops
that push conversion signal back into model evaluation, prompt improvement, and scoring
recalibration. The funnel gets smarter every week or it is not an AI-native funnel.
The activation gap: agreement to listed home.
Signing the agreement is not growth. A listed home is growth. The conversion from signed
agreement to activated listing is a product problem with high leverage: homeowners who do not
complete inspection scheduling, who abandon the improvement process, or who sit in the
pipeline without a live listing represent real lost revenue. You will own the product layer that
closes this gap, including AI-assisted improvement planning, proactive homeowner
communication anchored to their cashflow profile, and predictive identification of homeowners at
risk of churning before listing.

The AI Stack You Will Work With
• LLM-powered conversational intake with real-time lead qualification and cashflow profile
detection
• Personalized content generation using property-level market data, comparable listings,
and improvement ROI modeling
• Predictive lead scoring models trained on conversion, property quality, and ICP signals
• Agentic follow-up workflows with behavioral trigger logic and context-aware generation

• Retrieval-augmented generation for Advisor preparation: the right context, surfaced at
the right moment before the call
• A/B testing infrastructure applied to AI-generated content variants, not just static copy
You will define what this system does. Engineering and data science will build it with you.

What Success Looks Like
90 days: The funnel is fully instrumented from first click to activated listing with conversion rates
and drop-off points visible at each stage. An AI-assisted intake flow is in production and being
tested against the baseline.
6 months: Lead-to-listing conversion is measurably above baseline. AI is integrated at a
minimum of 3 funnel touchpoints with documented conversion impact per touchpoint. Advisor
routing is scored, and the correlation between score and close rate is being tracked.
Year 1: The majority of homeowner outreach between first contact and agreement signing is
AI-generated, with human Advisors focusing exclusively on trust-critical call moments. CAC on
the supply side is trending down. Time-to-activation is compressing quarter over quarter.

Example KPIs You Will Be Held To
• Lead-to-listing conversion rate (the primary number)
• Cost per activated listing
• Time from first contact to listing live
• AI-assisted funnel touchpoint conversion impact, measured per touchpoint
• Advisor routing accuracy: scored lead close rate vs. unscored baseline
• Experiment velocity: instrumented tests shipped per month
• Homeowner CSAT at onboarding and inspection phases (the constraint: conversion
gains cannot come at experience cost)

Who You Are
AI systems builder, not AI enthusiast. You have shipped LLM-powered product features in
production. You understand prompt engineering, retrieval quality, latency tradeoffs, output
evaluation, and model feedback loops. You think about AI systems the way a statistician thinks
about models: with explicit assumptions, known failure modes, and a measurement plan built
before launch.
Growth obsessed, experience constrained. You understand that conversion rate without CSAT
is a local maximum. Belong's homeowner retention is a direct function of the expectations set

during acquisition. You optimize the funnel with that downstream constraint live in your head at
all times.
Quantitatively rigorous. You build experiments with proper hypothesis structures. You distinguish
between statistical and practical significance. You know when a metric is being gamed. You
make decisions with incomplete data and document the reasoning explicitly.
Trust architect. You understand the psychology of a homeowner considering Belong. Anxiety,
loss aversion, and the weight of asset delegation are the forces working against conversion. You
design for those forces, not around them.
Relentlessly shipping. You do not disappear for a quarter. You have something in production
every two weeks. You measure it. You decide what to do next. You ship again.

What You Bring
• 3 to 5 years of product experience with direct ownership over growth funnels in a B2C or
marketplace company
• Demonstrated track record of driving CAC down and conversion up through product
decisions, not marketing spend
• Hands-on experience shipping AI-powered product features, specifically LLM
integrations, conversational flows, or agentic workflows, in a production environment with
measurable conversion impact
• Proficiency with experimentation frameworks, funnel analytics, and causal inference in
messy real-world data
• Experience building or evaluating predictive scoring models in a growth context is a
strong advantage
• Prior work in residential real estate, fintech, or marketplace supply-side growth is a
meaningful plus