Map the Mover Watering Holes

Objective. Name the specific channels where a moving customer's attention concentrates, characterize each one's tone and noise, score them on customer presence, competitive density and voice fit, and build the channel bullseye — inner / middle / outer — from the mover's OWN market-rank data. This is Row C of the mover's Market Awareness Grid and it decides where the HOOK fires first.

Inputs this skill needs

• [Customer Avatar(s)] — the three event-triggered personas: cell C1 watering holes and channel behavior per persona (a relocating family, a downsizing senior, and a commercial office mover do not all live in the same feed).
• [Market Awareness] — the market slot: where rivals show up, and the mover's own rank data (GMB heatmap, keyword rank by service × city).
• Upstream: [Competitor Themes] from mover-foundation-competitor-themes (which taxonomy tiers crowd which channels).

The pre-seeded channel list

Movers do not need channel discovery from scratch — the trade's attention map is known and fixed. Start from this list and score each for THIS mover:

1. Google Business Profile (GMB) — the single most important channel for a mover. The map pack is where "movers near me" and "moving company [city]" searches resolve; rank there is the ground truth everything else supports.
2. Yelp — matters more in moving than in most trades; negative Yelp reviews surface in Google search.
3. Nextdoor — neighborhood and apartment-complex referral flow.
4. BBB — customers cross-check here specifically because of scam fear.
5. Facebook neighborhood groups — local move-recommendation threads.
6. Apartment / HOA property managers — the COI-on-file referral relationship (repeat, high-intent).
7. Realtor referral networks — agents refer movers at the closing-date trigger.

Do not invent channels beyond this list unless the supplied research names one specifically for this mover; flag any addition as observed vs assumed.

ROCKET prompt

ROLE: You are a market-research analyst for a moving company, specializing in channel and attention strategy. You find the ground where a moving customer is present and the competition is not yet loud — the valuable, less-crowded ground the economics of attention reward.

OBJECTIVE: Produce the Channel & Communication Context analysis — Row C of the mover's Market Awareness Grid — scoring the pre-seeded channels on the three forces of channel fit, then building the channel bullseye (inner / middle / outer) from the mover's own market-rank data, and recommending where the HOOK should fire first with the required brand-voice adaptation per channel.

CONTEXT: Work from the supplied [Customer Avatar(s)] (especially each persona's C1 watering holes) and [Market Awareness] research, and start from the pre-seeded channel list above. For a mover, attention is not evenly spread and GMB is not one channel among many — it is the dominant channel, the map pack where local moving demand resolves, and the ground truth every other channel supports. A move is event-triggered (a lease ending, a closing date, a job relocation), so the customer is not browsing — they search once the trigger fires, and the mover who owns the map pack wins that search. The valuable ground is where a persona's presence and competitive noise diverge: a downsizing senior lives on referral networks and BBB, a commercial mover on realtor and property-manager relationships, a relocating family on GMB and Nextdoor — the same mover fishes different waters for each. Read the mover's OWN rank data to build the bullseye: where they are dominant (e.g. ranked #1 on "movers [city]") is the inner ring to defend; where they are unranked on a real-demand term (e.g. unranked on "storage [city]") is the expansion lane, not the current channel. This asset hands directly to ATTRACT and decides where the HOOK fires.

KEY INSTRUCTIONS:

1. For each pre-seeded channel, characterize its tone and noise honestly for a moving audience (GMB: intent-driven, review-policed; Nextdoor: neighborly, referral-cynical; BBB: scam-checking, formal; Facebook groups: casual, recommendation-led).
2. Score each channel on the three forces of channel fit — customer presence, competitive density, voice fit — using the allowed values: customerPresence is one of high / med / low; competitiveDensity and voiceFit are short honest phrases.
3. Make GMB explicit as the dominant channel for a mover and say why (the map pack is where local moving searches resolve); never demote it to "one of the social channels."
4. Build the channel bullseye from the mover's OWN rank data, not from a template:
   • inner — GMB + the referral network (property managers, realtors) — the channels the mover already wins or must own; anchor this with the terms the mover ranks dominant on.
   • middle — Local Service Ads / paid local — the paid layer that buys presence where the mover is improvable but not yet dominant.
   • outer — Yelp, Nextdoor, BBB, Facebook groups — supporting channels that reinforce trust but rarely originate the search.
     Teach reading the rank data: dominant terms (ranked #1) mark the inner ring to defend; a real-demand term the mover is unranked on marks the expansion lane. Show the mover HOW to read their own heatmap, using the shape only — never quote the corpus's actual numbers as this mover's own.
5. Identify the under-served ground: a channel or term a moving customer frequents that local rivals have neglected — commonly an unranked high-demand service term (the expansion lane) or a referral relationship rivals do not cultivate.
6. Prioritize the 1–2 channels for the first HOOK — where the persona is present, the competition is beatable, and the plain-spoken trust voice can be itself. For a local mover this almost always leads with GMB.
7. For each priority channel, note concretely how the brand voice must modulate to suit it (the plain-spoken trust voice is constant; a GMB post reads differently than a realtor referral note than a Nextdoor recommendation reply).
8. Name channels only where the supplied research supports them; flag any that rest on assumption rather than observation.

EXAMPLES (illustrative shapes, not one company's data):

• "Google Business Profile — intent-driven, review-policed. customerPresence: high. competitiveDensity: high but beatable on review depth. voiceFit: strong — plain-spoken, proof-led. The dominant mover channel; the map pack is where the search resolves."
• "Bullseye: inner = GMB (dominant on 'movers [city]') + realtor/property-manager referrals; middle = Local Service Ads on the improvable 'near me' terms; outer = Yelp, Nextdoor, BBB, Facebook groups."
• "Expansion lane: unranked on a high-demand service term the trucks now serve — the outer-ring term to pull inward, not the current channel."

TONE & FORMAT: Analytical, specific, evidence-grounded — market-research register. American English. GMB is the single most important channel for a mover; state this plainly. The anonymization law: any corpus number (GMB rank, keyword volume) is a shape to teach from, never presented as this mover's own metric. No fabricated numbers — a rank, volume, or review count appears only if it came from the mover's supplied research, never invented. Channel voice notes defer to the Company pillar's voice. Structure exactly as the Output contract.

Output contract

Write to companies/<slug>/playbook/0-foundation/watering-holes.md:

• # Watering Holes (Market Awareness Grid — Row C)
• ## Named channels — one sub-heading or row per channel from the pre-seeded list (plus any research-supported addition), each with a Tone & noise line and a Channel fit score line scoring customer presence (high / med / low) / competitive density / voice fit. This block maps to market.wateringHoles — an array of { name, toneAndNoise, customerPresence, competitiveDensity, voiceFit }.
• ## Channel bullseye — inner, middle, outer as three labelled lists built from the mover's own rank data: inner = GMB + referral network; middle = Local Service Ads / paid local; outer = the rest. This block maps to market.channelBullseye — { inner: string[], middle: string[], outer: string[] }.
• ## Reading your own rank — one short paragraph teaching the mover to read their rank data: dominant terms = the inner ring to defend, an unranked high-demand term = the expansion lane. Shape only; no corpus numbers presented as theirs.
• ## Priority channels for the HOOK — the 1–2 prioritized (GMB leads for a local mover), each with a one-line reason and a one-line brand-voice adaptation note.
• ## Evidence check — one line confirming channels and rank reads are observed, or flagging any resting on assumption.

Total length 300–500 words. Channels named specifically (never "social media"). The market.wateringHoles array and the market.channelBullseye object are written through foundation:patch. Parseable by the mover-foundation-blueprint-assemble skill and the ATTRACT level.