Traffic doubled, sales flat
Website traffic has doubled over the last quarter but sales have not moved. The team has been pushing more paid acquisition but conversion is dropping and the founder is worried they are chasing the wrong thing.
Eight realistic problems across commercial, public-sector, mission-led and advisory work. Each one shows what Dog Bot would sniff, fetch and warn against before you commit to an answer.
Revenue, conversion, churn, margin and growth.
Website traffic has doubled over the last quarter but sales have not moved. The team has been pushing more paid acquisition but conversion is dropping and the founder is worried they are chasing the wrong thing.
Customer churn is rising despite strong new signups. Net revenue is flat. Activation looks healthy in the first week but cancellations spike around month two and the team is debating discounts vs onboarding fixes.
Statutory duty, public value, demand and legitimacy.
A public service needs to reduce temporary accommodation demand but political pressure is intense. Spend is overrunning, families are stuck in unsuitable placements, and elected members want a visible response before the next committee.
A public service has rising complaints, long backlogs and unclear ownership across two directorates. Frontline staff are overwhelmed and each team blames the next handoff.
Beneficiary impact, funder evidence, mission drift.
A charity programme is popular with beneficiaries but funders want clearer evidence of impact. The team has rich anecdotes and weak outcome data, and the next funding round is six months away.
A social enterprise is growing quickly but risks drifting from its mission. New revenue streams are profitable but only loosely connected to the beneficiary group, and the board is starting to ask uncomfortable questions.
Pre-engagement problem definition, scope and ownership.
A company wants portfolio rationalisation support but has not defined what success means. Different executives describe the brief differently and the board appetite for divestment is unclear.
A client wants an AI strategy, but their real problem may be process, data quality and governance. The sponsor is excited about tooling and the operating teams quietly say nothing will work until the basics are fixed.