Most sales teams now use AI in some way. In Foodservice, the results depend on two things: choosing the right outlets, and having the right data about them. Here are six insights for sales and insights teams at Foodservice suppliers and brands.
Key Figures
Six Insights for Foodservice Sales Teams
AI in Sales Is Now the Norm, but Field Sales Is Behind
Most sales organisations already use AI. Field sales teams are behind: one in three do not use any AI tool. Teams that do use AI mostly use it for admin, such as emails and content. At the same time, an account manager spends more than one working day per week on admin and CRM entry.
The Value Is in Better Decisions, Not Less Admin
Using AI does not mean getting results from it. Only 23% of organisations see significant ROI from their AI agents. The companies that grow faster use AI to support decisions. Every account manager answers three questions each day: which outlets to visit, when to visit, and what to talk about. AI can help answer these with data instead of gut feeling.
Foodservice Changes Fast
Every year, about a third of Foodservice outlets open, close or change concept. Volumes are also under pressure: in the first half of 2026, Dutch restaurants and cafés sold fewer dishes and drinks than a year earlier, and revenue growth came mostly from higher prices (ING). An outlet list from last year is already partly out of date. In a market that is not growing in volume, choosing the right outlets matters more.
AI Is Only as Good as the Data Underneath
Most attention goes to the chat interface or the AI agent. But the value comes from the layers underneath: models that score and predict, and above all the data they use. Without an up-to-date and complete view of all outlets, even a good AI agent will give confident but wrong advice.
Public Data Explains Why an Outlet Fits Your Brand
AI can read public sources for each outlet: Google reviews, menus, websites, customer photos, social media and delivery platforms. This shows things a standard database does not, such as the type of guests, the occasion, whether there is a terrace, which brands are on the menu and the price level. Each outlet can then be scored on how well it fits your brand, with the reason behind the score.
Menu Data Shows Concrete Sales Opportunities
An example from Dutch dessert menus: guests already pay more for apple pie when it comes with a scoop of ice cream. Yet most outlets that serve apple pie do not offer it with ice cream. For an ice cream brand, this is a clear topic for the next sales conversation.
Source: Roamler analysis of Dutch dessert menus, May 2026.
Data helps you decide which outlets to visit, when, and with what offer. The account manager still makes the difference during the visit.
Foodservice Data and AI for Your Sales Team
Roamler combines a complete Foodservice outlet database with AI and a field sales app.
Foodservice Outlet Database
Around 250,000 Foodservice outlets in the Netherlands, complete, up to date and structured, with filters by segment, cuisine, size and location.
Menu Intelligence
Public menus turned into structured data: categories, products, prices and formats.
ICP Matcher
Scores each outlet on how well it fits your brand, with the reason and source for each score.
Outlet FinderBeta
Search and filter customers and prospects, build shortlists and share them with your team.
AI Agent in SalesmappBeta
Prepares each visit with customer context, opportunities and points of attention, and helps plan appointments.
See How It Works with Your Own Outlets
In a demo, we show you how Roamler data and AI can help your team choose the right outlets and prepare better visits. We use examples from your own categories and regions. Questions first? Contact Anthony Vu, Head of Sales, at anthony.vu@roamler.com.
Request a demo