Choosing venues that actually convert (the playbook, teased)

We get one question more than any other from prospective operators: "which venues should I place stations in?" The answer is more specific than people expect — and most of the operating return from a charging network comes from getting this question right.

This is the public, teased version of our internal venue-selection playbook. The full version walks operators through it on the demo and on the kickoff call.

The principle: dwell time × phone usage

Two simple variables. Multiply them and you've predicted most of a venue's per-station performance.

• Dwell time: how long an average customer spends in the venue.
• Phone usage during that dwell: how actively the customer's phone is in use the whole time.

High on both axes = high rentals. Low on either = low rentals. It's that simple, and it's the variable that most surprises new operators when they look at their actual data after a few months.

Categories that consistently produce (yes)

These work across our networks. The pattern is the same: long sit-down, phone-heavy social use, predictable peak hours.

Hot pot / barbecue / shabu-shabu restaurants

The strongest single category. 45-minute waits during peak, 2-hour meals, photos of food, group chats coordinating, ride-hailing on the way out. Customers are visibly on their phones the whole evening, watching battery drop, looking for an outlet.

A well-placed station at a busy hot pot restaurant in any of our markets produces every single day.

KTV / karaoke venues

Multi-hour bookings, lots of phone use for song selection, photos, group chat. Phones run out before the night does. KTV consistently produces in our data.

Day spas and aesthetic clinics

Long appointments (1–4 hours). Members reading on their phones in lounges, charging while in treatment. Smaller volume than hot pot but higher per-customer value — and these venues care deeply about the on-brand amenity feel.

Hotels and boutique stays

Check-in waits, lobby dwell, room-charge-via-app integrations. Tier-2 in volume but very consistent.

Bars and lounges, peak hours

Peak nightlife produces. Off-peak is slower. Average is good if the venue has consistent peak.

Banquet halls, event venues, private clubs

Long events, captive audience, phone-heavy social dynamics. Lower density per week (events vary) but high yield per event.

Categories that struggle (no)

These don't produce, on average. Patterns of low dwell or low phone-during-dwell.

Coffee shops where customers stay 15 minutes

The customer is in and out before the rental decision even forms. Coffee shops are a chronic disappointment for new operators who place there because they had connections.

Fast-casual restaurants

Same problem. Order, eat, leave. Not enough dwell for the customer to consider a rental.

Convenience stores

The customer is in for 90 seconds. Wrong category.

Outdoor / unstaffed locations

The dwell is real but the station integrity (theft, weather, vandalism) becomes a real cost.

Pure retail (clothing, electronics)

Phone usage during shopping is incidental, not constant. Wrong fit.

Gray-zone categories (sometimes, depends)

These can work but require nuance.

Casual sit-down restaurants

Depends entirely on average ticket time. A 75-minute meal venue works; a 25-minute fast-casual doesn't. Walk the venue at peak before you commit.

Movie theaters

Long dwell, but phone use during the movie is socially discouraged. The pre-show wait works, the rest doesn't. Marginal.

Salons (hair, nails)

Long dwell, phones used moderately. Smaller volume than spas because client base is more transactional. Works in dense urban markets, less so in suburban.

Bowling alleys, arcades, escape rooms

Variable. The good ones produce. The pattern is "people who came to be together socially for an extended period."

The placement question inside a good venue

Even within a good venue, placement matters.

• Entry / waiting area is best in venues with waits (hot pot, KTV, popular bars).
• Lounge / hostess area for venues without waits but with long sit times (spas, hotels).
• Bar back-bar for bars and lounges.
• Reception for clinics and salons.

Avoid:

• Far corners customers don't pass
• Spots without line-of-sight from where the customer is sitting (they forget the option exists)
• Anywhere that creates a long walk from where they're rescuing a dead phone

How we coach venue selection

Our operator dashboard surfaces per-venue performance after a few weeks of operation. The pattern is usually visible by week 4:

• High-producing venues confirm the category fit
• Low-producing venues raise questions: is it placement? is it the wrong category? wrong neighborhood?

We have the calibration data from our own networks. New operators don't have to discover all of this from scratch — they inherit the pattern.

What "the playbook" actually contains (full version, for operators)

This article is the public version. The actual operator playbook adds:

• Specific category × city expected-rental-rate calibrations
• Pricing tier defaults per category
• Venue conversation scripts and the deck
• Agreement templates per venue type
• The "should I pull this station?" decision tree
• Anti-pattern catalog from our own deployments

You get all of it on signing.

Where to start

The categories above are the starting universe. Once you sign on as an operator, we walk through your specific city's strongest categories on the kickoff call — based on what's actually present and dense in your market.

Apply to become an operator and we'll walk through the full playbook with you.