💡 Universal hive data import and migration toolkit for switching beekeepers

[github-actions[bot]]

Summary

Provide seamless data import from competing beekeeping apps (HiveTracks CSV export, Apiary Book JSON, HiveLog exports, BeeKeepPal) and bidirectional export in open formats (CSV, JSON, PDF reports). Reduce the #1 switching barrier — years of accumulated inspection history locked in another app — by making migration effortless. A guided migration wizard walks new users through upload → column mapping → validation → import during onboarding.

Market Signal

The 2026 beekeeping app market is fragmenting: HiveSense, HiveLog AI, HiveTracks, Apiary Book, BeeKeepPal each have loyal user bases with years of accumulated data. No app offers import-from-competitor tooling. In every SaaS category, data portability has proven to be a critical adoption accelerator — CRM, project management, and note-taking tools all saw adoption inflection points when they shipped one-click import. HiveTracks has been operating since 2010, meaning some beekeepers have 15+ years of inspection data locked in their platform. HiveLog AI and HiveSense are newer but growing fast, creating a generation of beekeepers who will eventually want to consolidate or migrate.

User Signal

The PRD includes FR53 (data export) but not data import. The architecture specifies CSV/JSON export but does not address inbound migration. Data lock-in is consistently cited in app review comments as a reason beekeepers stick with suboptimal tools — users won't abandon years of hive records even if a better app exists. The off-season (winter) is when beekeepers evaluate new tools, making import capability a critical acquisition feature.

Technical Opportunity

The database schema (users, apiaries, hives, inspections, observations, media) maps cleanly to the data models of most competing apps — all track fundamentally the same entities. HiveTracks exposes CSV export with known column structures. Import adapters follow the same ExternalSignal adapter pattern already in the architecture — a parser per source format that normalizes data into Broodly's domain types. A migration wizard in the onboarding flow (Expo Router) guides users through upload → auto-detected column mapping → user confirmation → validation → import with progress feedback.

Assessment

Dimension	Score	Rationale
Feasibility	high	CSV/JSON parsing is straightforward. Schema mapping between apps is well-defined. Architecture's adapter pattern is reusable.
Impact	high	Removes the #1 switching barrier. Eliminates cold-start problem for new users. Enables competitive displacement of established apps with inferior UX.
Urgency	high	Needed before go-to-market. Beekeepers evaluate new apps during winter downtime (Oct-Feb). Import capability must be ready for the 2026-2027 off-season acquisition window.

Adversarial Review

Strongest objection: Reverse-engineering competitor export formats is brittle — they can change at any time. Imported data quality will be lower than native Broodly data, potentially degrading recommendation accuracy.

Rebuttal: Start with the 3 most popular apps that offer CSV/JSON export (HiveTracks, Apiary Book, HiveLog). CSV column mapping is user-confirmable during import — the wizard shows detected mappings and lets users correct them. Data quality flags on imported records (e.g., source: imported, missing: observation_type) ensure the recommendation engine can weight imported vs native data appropriately. Even partial import (apiary names, hive counts, inspection dates) dramatically reduces the cold-start problem.

Suggested Next Step

Download and analyze the export formats of HiveTracks, Apiary Book, and HiveLog AI. Map their data models to Broodly's schema and build a proof-of-concept CSV import adapter with column auto-detection and user-confirmable field mapping.