Digital Products — Target Customer Hypotheses¶
Every customer description below is a hypothesis, not a confirmed persona. No interviews, surveys, or market data back these descriptions as of this writing. They exist to give backlog items (../../portfolio/product-backlog.md) a plausible "who is this for" without pretending that research has already happened. Any future document that treats these as validated should cite the research that validated them.
Why hypotheses, not personas¶
A conventional "persona" document implies market validation (real interviews, real data) behind a named, detailed customer profile. This venture has not done that research yet. Writing detailed fictional personas with invented ages, incomes, and quotes would create false confidence. Instead, this document describes customer segments and the problem shape they're hypothesized to have, deliberately left coarse until research narrows them.
Segment hypotheses¶
Personal finance segment¶
Hypothesized customer: Individuals or households making a specific, consequential financial decision or trying to build an ongoing financial habit — retirement timing, debt payoff, college savings, tracking net worth, evaluating a rental property.
Hypothesized problem shape: These customers are typically underserved by either (a) generic advice content with no calculation tool attached, or (b) financial advisor/software tools that are expensive, require an account, or are overkill for a single decision. They may be comfortable with spreadsheets but not with building formulas themselves.
Confidence: Unresearched. Assumed based on the general popularity of financial planning templates in template marketplaces, which is itself an unverified observation, not a cited data point.
Home and lifestyle segment¶
Hypothesized customer: Homeowners or renters managing a recurring household-management burden — maintenance schedules, a renovation, an inventory, a move, emergency preparedness.
Hypothesized problem shape: These are often infrequent or seasonal tasks where the customer doesn't want to build a system from scratch each time, and where a guided/structured tool reduces the cognitive load of remembering what to track.
Confidence: Unresearched.
Small business segment¶
Hypothesized customer: Owners or operators of small businesses (roughly solo to ~20 employees, unconfirmed) who need operational visibility (cash flow, KPIs, pricing, sales pipeline, project profitability, team capacity) but don't have or want a full software subscription for it.
Hypothesized problem shape: These customers may already use spreadsheets informally and are hypothesized to want something more structured without moving to a SaaS tool that requires onboarding, per-seat pricing, or ongoing commitment.
Confidence: Unresearched.
Marketing and operations segment¶
Hypothesized customer: Marketing practitioners (in-house or agency) and operations professionals who need planning, forecasting, or governance tools for campaigns, budgets, KPIs, and measurement — potentially at a more sophisticated level than the other three segments.
Hypothesized problem shape: This segment may skew toward mid-market or agency-side professionals who already think in frameworks and want tools that reflect functional rigor (taxonomy governance, measurement planning) rather than general-audience simplicity. This is the least "consumer" of the four segments and may need a different research and distribution approach.
Confidence: Unresearched. This segment may in practice require more direct outreach/interview-based research than a marketplace-observation approach, given the more specialized subject matter.
How these hypotheses should be used¶
- Backlog items should reference the relevant segment hypothesis, not invent new customer detail inline.
- Any product that reaches the research stage should replace the relevant hypothesis
with actual findings in that product's specification
(
products/<slug>/), and should update this document if the findings materially change the segment-level understanding. - No document in this venture should present these hypotheses as confirmed personas, and no fabricated data (ages, incomes, search volumes, quotes) should be added to them.