Getting your drink into bars: finding and prioritising UK venues that fit

The method below turns a defined account universe into a practical pilot sequence, translated from the metrics page into Tuesday-afternoon actions. It assumes what every early brand has: a product, a phone, a small budget, and no national distributor yet.

Step one: write the venue brief before the venue list

One page, five lines, brutally specific: the venue type where your product is the obvious order (not "bars that might take it"), the price point the room must support (a £6.50 RTD doesn't live in a £7 cocktail room and vice versa), the city clusters that match your drinkers, the three named example venues per city that define "like this", and the serve story in one bartender-sized sentence. "Craft gin for good bars" is not a brief; "spirits-forward bars with a negroni-class program in Shoreditch, Northern Quarter and Bishopbriggs-equivalents, a stated per-bottle trade price and per-serve margin requirement" is. The brief's job is making the next two steps mechanical instead of hopeful.

Step two: build the universe from public data

The UK's venue universe is more knowable than it looks, and none of it costs a consultancy fee:

• The public register (local-authority licensing records, with access, fields and bulk-download availability varying by council and UK nation) can provide premises-licence information and conditions; do not assume it is a complete venue directory or includes every personal licence holder. The skeleton of your universe, with opening hours attached.
• Companies House filings for the groups (the ten-site regional operators worth a named pitch, and the ones with a drinks director you can find).
• The social layer: Instagram and the listing apps tell you which rooms actually run a cocktails program (posted drinks menu, guest-shift posts, the bartender tags that reveal who curates).
• The map layer: cluster by postcode against your drinker data (where your DTC orders and event list actually come from), because proximity to demand beats proximity to cool.

A bounded first research pass can produce a useful shortlist; record how many entries were checked and how long it actually took rather than treating a 500–2,000-row list as an automatic ten-hour result with a fit score against the brief. That score is the whole prioritisation; everything after is working it top-down.

Step three: the sequence that compounds

Pitch order matters more than pitch quality in the first hundred accounts. The sequence: anchor venues first (two or three per city from the brief's named list, the ones whose menus other bartenders read), accept honest terms to get them (they're buying the story, not the margin), then prove ROS weekly with rate-of-sale maths before expanding, because the second wave sells itself only when the first wave can be shown pouring. Then the follower cluster (bars within the anchor's postcode that match the brief — bartenders list what they see working two streets away), then the regional groups, whose buying decision is a spreadsheet and a tasting and moves faster than independents once one of their venues is already working with you.

The failure mode this sequence exists to prevent: 150 scattered listings sold one at a time, no city with critical mass, ROS diluted to nothing, and a sales story that can't be told because there's no anchor to point at. One city done properly is a case study; fifteen cities done thinly is a logistics problem.

The pitch itself, in one paragraph

A concise pitch should make the working serve and economics clear: what the product is in one sentence, what it does in a serve they already pour (spec card, on the bar, before the conversation), what it costs them and what it makes them per serve, and what you'll do that they can't (training, glassware, the guest-shift budget). Bring the spec before the story, bring the margin before the brand film, and leave the sample with the working spec card attached, because the bottle will get tasted on a slow Tuesday by whoever opened it, and that person is the account.

Turn a long list into a workable next step

Record venue name, address, licence information where relevant, format, menu evidence, observed price tier, date checked and the reason it fits. Keep an unknown field unknown rather than assigning a confident fit score to missing data. Contact details should be used in accordance with the applicable privacy and marketing rules; a public listing is not automatic permission for every type of outreach. Review closed venues and duplicates before counting reach. For a pilot, a smaller verified cluster with an owner for the next action is more useful than a large scraped directory whose opening status and commercial relevance nobody has checked.

FAQ

Method and assumptions

Venue-universe counts are approximations from publicly known licence and industry figures (tens of thousands of licensed premises; see our trading index for the pub subset), labelled indicative. The targeting method reflects standard drinks-distribution practice, not a study. No named venue endorses anything here.

Last reviewed 19 October 2026.