Short answer: selling lager through on-premise (bars & restaurants) is a five-step blueprint — segment, target, offer, execute, measure — run on data, not gut. Lager wins on velocity and availability, so the metric that matters is tap handles won and held, not shipments. Below is the blueprint, the KPIs, and where analytics earns its keep.
Lager is a volume business with thin margins: it’s won by being available, fresh and turning fast wherever the drinker reaches for it. The sales motion differs by market player, and for on-premise (bars & restaurants) the buyer is the owner, GM or beverage director — the motion is to win and hold tap handles and menu placement, where lager throughput and brand visibility are highest. This is one of the lager sales blueprints by channel.
The blueprint, step by step
- Segment — Split on-premise (bars & restaurants) by volume potential and fit so effort goes where the return is.
- Target — Rank the specific openings — the depletion gaps, resets, tap openings or authorisations — into a call list.
- Offer — Build the price-pack, program and incentive that fits this channel’s economics.
- Execute — Do the unglamorous work at the point of sale: calls, planograms, installs, displays.
- Measure — Close the loop on tap handles won and held and feed it back into next cycle’s targeting.
The metrics that matter
Steer on tap handles won and held, kegs per account per month, menu presence, draught quality (line cleaning), and staff advocacy. An account-propensity model ranks venues by their fit and likely throughput; draught-quality data keeps the beer you fought for tasting like it should.
The data and AI stack behind it
At scale this runs on a modern stack, not spreadsheets. Data engineering pipelines land depletions, scan and CRM data into a cloud lakehouse or warehouse — on AWS (S3, Redshift, SageMaker, Bedrock) or Azure (Fabric or Synapse, Azure ML, Azure OpenAI). On top, AI / ML runs the forecasting, account scoring and price-and-promo models; generative AI copilots draft account plans and answer questions in plain language; and a vector database (pgvector, Pinecone, Azure AI Search, OpenSearch) powers semantic search and RAG over account notes, distributor agreements and rep call history — so a rep can ask “what did we promise this account last quarter?” and get a grounded answer. The stack is the engine; the blueprint is the steering.
Where this blueprint breaks
The honest caveat for this channel: a tap handle you win but don’t maintain (dirty lines, slow turnover) pours flat, stale lager and costs you the brand — placement without quality follow-through backfires. The blueprint is a discipline, not a guarantee — it works when the measurement is real and the follow-through happens.
The bottom line
For on-premise (bars & restaurants), lager sales come down to availability and velocity, and the five-step blueprint keeps the team honest about both. Run it on tap handles won and held, link it to the channel overview, and let the data pick the next account.
Frequently asked questions
How do lager breweries sell through on-premise (bars & restaurants)? Run the five-step blueprint: segment on-premise (bars & restaurants) by volume and fit, target the priority openings, build the right price-pack and program offer, execute at the point of sale, and measure on tap handles won and held rather than shipments. Lager is a velocity game, so availability and turnover beat one-off sell-in.
What sales metrics matter most here? Track tap handles won and held, kegs per account per month, menu presence, draught quality (line cleaning), and staff advocacy. The common trap is steering on shipments instead of the metric that proves the beer actually moved.
Where does data and AI help in this channel? An account-propensity model ranks venues by their fit and likely throughput; draught-quality data keeps the beer you fought for tasting like it should.
Related: on- vs off-premise intelligence.
Part of the Sales Intelligence for Beverage track.