Scales with volume; ~30 min per influencer confirmed
Ops Communication
1–2 hrs
1–2 hrs
Gets faster once GM relationships are established
Content Review & Reporting
1.5–2 hrs
1.5–2 hrs
Lag of 3–7 days after visit; overlap with prior week
Admin / CRM / Tracking
0.5–1 hr
0.5–1 hr
Tracker hygiene, rate logging, client updates
Total per active market / week
7–11 hrs
8.5–13 hrs
For 2–3 active markets running simultaneously
💡 Steady-state estimate: Running 2–3 active markets per week at a pace of 3–5 influencers across those markets, expect ~10–16 hrs/week total. At full programme maturity (11 locations cycling), this could reach 18–22 hrs/week — closer to a 0.5 FTE in practice.
Recommended weekly volume
4–6
Influencers total per week, spread across 2–3 active locations. This keeps quality high and comms manageable without burning through the database or overwhelming any one site.
Locations active per week
2–3
Rotate through the 11 locations on a rolling basis. Each location gets one active "influencer week" roughly every 4–5 weeks, with NYC getting more frequent rotation given the larger pool.
NYC vs. other markets split
60 / 40
Start heavier in NYC where the database is ready and relationships exist. Gradually shift to 50/50 as non-NYC markets are onboarded and local influencer pools are built out.
Ramp timeline
8 wks
Weeks 1–3: NYC-only execution. Weeks 4–6: add 1 non-NYC market per wave. Weeks 7–8: full 2–3 market rotation live. Prevents ops strain on Boqueria's restaurant teams.
Why not more per week? Each confirmed influencer touch requires coordination with a real restaurant team — table holds, FOH briefing, day-of logistics. Overloading a single location in one week risks poor hospitality and weak content. Spreading 4–6 across 2–3 sites keeps each visit feeling intentional and gives the site team breathing room.
Why not all 11 locations at once? New-market sourcing is 30–60% more time-intensive until you've built a vetted local list. Launching all markets simultaneously would spike hours to 30+ per week with no process groove, high error rate, and inconsistent influencer quality across markets. Phased rollout also lets you prove ROI in NYC before scaling budget.
A 12-week view of the phased ramp: NYC-only for weeks 1–3, one non-NYC market added per wave through weeks 4–6, then a full 2–3 market rotation from week 7 into steady state. Bars show which workstream is active each week per market — solid = the primary focus that week, faded = ongoing rolling activity. The bottom row tracks total hours consumed.
Sourcing Outreach & Booking Visits & Content Ongoing / rolling
Hours track the rollout, not a flat retainer. Weeks 1–3 sit at the low end (7–10 hrs) while only NYC is live. The peak lands around week 6 (~17 hrs) when NYC is rolling and two new markets source at once — the deliberate, controlled spike that phasing exists to manage. (Launching all 11 markets together would push 30+ hrs with no process groove.) From week 7 the programme settles into a ~12–14 hr/week steady state for a 2–3 market rotation.
Suggested 4-week rolling rotation across 11 locations. NYC locations appear more frequently; non-NYC locations are introduced progressively. This is a template — adjust based on Boqueria's seasonal priorities or openings.
Influencer tier guidance: For a restaurant programme, micro-influencers (5k–50k followers) with a local, food-focused audience consistently outperform macro accounts on conversion and authenticity. Aim for ~70% micro, ~25% mid-tier (50k–200k), ~5% aspirational/media for brand lift. Gifted visits for micro; negotiate paid or hybrid for mid-tier and above.
Hours without AI
10–16
Per week at 2–3 active markets. Sourcing and admin are the biggest time sinks.
Hours with AI assist
6–9
AI handles profiling, shortlisting, first-touch drafts, checklist review, and reporting summaries.
Efficiency gain
~40%
Reduction in billable hours — absorbed as margin, competitive pricing, or capacity for more locations.
Phase
Without AI
With AI
How AI helps
Still needs human
Sourcing — New Markets
3–5 hrs
1–1.5 hrs
Auto-pull by location + category, engagement scoring, fake follower flagging
Final fit judgment — does this person feel right for Boqueria?
Sourcing — NYC
2–3 hrs
45–60 min
Database already exists — AI re-scores and re-ranks against current brief
Relationship context, past performance gut check
Outreach & Booking
2–3 hrs
1.5–2 hrs
Personalised first-touch drafts at scale, follow-up reminders
Negotiation, tone calibration, relationship management
Ops Communication
1–2 hrs
1–2 hrs
Minimal — comms are short and human by nature
All of it. FOH relationships are irreplaceable.
Content Review
1.5–2.5 hrs
1–1.5 hrs
First-pass tag/handle/hashtag check, brief compliance flag
Brand feel, tone, whether content actually looks good
~40% reduction in execution hours across the programme
Tools that do the heavy lifting
Modash, Phyllo, or Heepsy for database sourcing and scoring. Claude / GPT for outreach drafts and reporting summaries. A simple Make or Zapier workflow to auto-log confirmed bookings and post-visit metrics into a tracker. None of these require significant setup cost.
What this means commercially
The AI layer is an operational efficiency — it doesn't need to be surfaced to Boqueria. The benefit flows back as stronger margin on the retainer, the ability to absorb more locations without proportional headcount, or a more competitive monthly rate that makes the pitch easier to close.
💡 The irreducible human core: Relationship management, brand fit judgment, negotiation, and ops coordination with the restaurant teams cannot be automated. These are also the highest-value parts of the service — the things Boqueria is actually paying for. AI compresses the commodity work so that time concentrates on those moments.