Apollo BagelsMULTI-UNIT FOOD & HOSPITALITY

CATERING WAS STUCK AT 2%. NOBODY HAD TIME TO SELL IT.

A New York bagel group with lines out the door and a cult following 9 locations with 10 more opening. Retail runs the business: stores, limited-time drops, and a brand people cross boroughs for.

Catering was the proven-but-parked opportunity. Offices wanted it, Google was already an account, and nobody had time to sell it while the team opened stores.

grow
Apollo Bagels — a bag and a matcha handed over the counter

GOAL

The goal was to grow catering without hiring, turning proven demand into a real revenue line with no sales team. With 10 stores already in flight, nothing new could pull focus from that, so the team needed to stay on store openings. On top of that, Apollo Bagels wanted to prove the channel before staffing it, if catering worked, they'd hire behind the revenue instead of ahead of it.

We spent months talking about catering as an opportunity. Six weeks after launch, it was already a real line of revenue, without adding a single hire.”

Paras Jain

Paras Jain

Founder

Apollo Bagels

Every office

in New York reachable by the outbound engine

grow

10

new stores the team stayed focused on opening

grow

business map

  • SALESbottleneck

    Catering demand was proven and nobody was selling it. No sales team, no outbound function, and the third-party tools weren’t working.

  • OPERATIONSCONSTRAINT

    The team was fully focused on opening 10 stores. No capacity for a manual catering operation.

  • HIRINGCONSTRAINT

    With 10 store openings in motion, no sales hires were planned.

  • FINANCEOPPORTUNITY

    Store-level economics come together at month-end. As the group doubles its store count, per-store visibility becomes a daily need.

  • OPTIMIZE WHAT EXISTS
  • GROW NEW REVENUE
Chelsea Labs

THE OPPORTUNITY SHORTLIST

grow
  1. 1

    catering outbound eNgine

    Finds every office in New York, contacts them follows up, and hands warm orders to the store team.

  2. 2

    store-level p&l dashboard

    One daily view per store: sales, labor, food cost. Managers act the same day instead of waiting for month-end.

  3. 3

    new store prioritization

    Rank the next sites using existing store sales, foot traffic, and demographics.

  4. 4

    drop & collab identification

    Apollo runs limited-time drops. Pick the next drops and collab partners from social and sales data.

  5. 5

    social listening

    Mine mentions to find what drives demand spikes. Parked until it has number attached.

the result

Apollo Bagels — store dashboard
2% → 10%

revenue

Catering went from a side channel to a real line of business.

0 HIRES

team

No sales function was added. The engine does the outreach.

10 STORES

focus

The team kept opening stores while catering grew.

START HERE

DURABLE BUSINESSES, REBUILT FOR THE AI ERA

In two weeks, we map your business, uncover the highest-impact AI opportunities across your workflows and products, and give you a clear roadmap for what to build first.

Apply for an AI Audit