DashLeads

    Restaurant attribute data: ask your own question of each outlet

    Restaurant attribute data answers a specific question about each venue, such as "has a terrace", "offers vegan options" or "serves draught beer"; DashLeads can add custom attribute columns to 20M+ venues and reads 5M+ of their menus. Ask the question in plain words and AI answers it for each outlet from menus, menu photos, venue photos and reviews, showing the rule and the evidence, so you find the venues that fit this campaign and are not on your list yet.

    Mock-up of an example AI assistant on a phone: a rep asks which bars to visit for a new gin, gets two top-fit cocktail bars, and opens one to see the three reasons it fits.
    20M+
    outlets that can carry custom columns
    5M+
    outlets with menu content read
    100+
    data points per outlet

    The trusted intelligence layer for teams selling to Hospitality & Retail

    AB InBev
    Heineken
    Carlsberg
    Coca-Cola
    Red Bull
    Suntory
    Labatt
    Audiogest
    AB InBev
    Heineken
    Carlsberg
    Coca-Cola
    Red Bull
    Suntory
    Labatt
    Audiogest

    Which bars have a terrace and serve alcohol-free beer?

    Many sales questions are not about the channel at all. A summer campaign needs venues with outdoor seating. A plant-based brand needs restaurants with vegan dishes on the menu. A craft beer rep wants bars that pour draught beer, and a pet food brand wants dog-friendly cafes for a sampling tour.

    No standard outlet list has a column for your question. So reps scroll through photos and menus venue by venue, or they skip the question and visit everyone.

    Custom attributes turn that question into a column. You ask it once, DashLeads answers it for each outlet in your workspace, and the answer becomes a filter like any other.

    Three kinds of custom column

    Most questions fall into one of three types:

    TypeWhat it flagsExamples
    Venue featureA physical or operational traitHas a terrace, pet friendly, music nights, sports on screens, late opening
    OfferingA product or service on the menuVegan options, serves draught beer, has a cocktail list, sells breakfast, offers alcohol-free beer
    Your classificationA category you define"Neighbourhood local", "Destination dining", "Student hangout"

    The answer is Yes, No or Unknown for a feature or an offering, and one of your labels for a classification. Unknown matters: it means the public sources did not show the answer, which is different from No.

    See the rule and the evidence, then tweak it

    A column you cannot check is a column nobody trusts. Each custom attribute shows two things:

    • The rule, in plain words. For "Has a terrace": the venue lists outdoor seating, or recent photos or reviews show seating outside. You read it, and if it is too loose or too strict you edit it.
    • The evidence per outlet. The line on the menu, the attribute on the listing or the review that mentions it, with the date it was seen.

    Change the rule, preview the effect on a handful of venues you know, then apply it to the whole workspace. Your attribute sits next to the channel, your segments and the lead score, a score from 0 to 100 against the account you describe.

    Worked example: a summer terrace list

    Take a beer brand that launches an alcohol-free beer for summer and wants bars in one city with a terrace and no alcohol-free beer on the menu yet. Two custom columns do it.

    VenueAreaHas a terraceEvidenceAlcohol-free beerEvidence
    Neighbourhood barCentreYesListing: outdoor seatingNoMenu, 3 weeks ago: no alcohol-free beer listed
    Cafe on the squareCentreYesReview, last month: "lovely terrace"YesMenu: a rival's 0.0
    Wine barCentreNoListing: no outdoor seatingNoMenu, 2 months ago
    Canal-side pubWestYesPhoto, last spring: tables outsideUnknownNo menu found
    BrasserieWestUnknownNothing seenNoWebsite menu

    The filter "terrace = Yes and alcohol-free beer = No" gives 210 bars in the city. The neighbourhood bar goes on Monday's visit list. The canal-side pub goes on the list with a note to check the menu at the door.

    Frequently asked questions

    What is restaurant attribute data?

    Restaurant attribute data is a set of specific facts about each venue, such as having a terrace, offering vegan dishes or serving draught beer, that you can filter on to build a targeted list.

    Can I create my own attributes?

    Yes, you write the question in plain words, such as "pet friendly" or "has a cocktail list". DashLeads shows the rule it will use, you adjust it, and the answer is added as a column on each outlet.

    How do I know an answer is right?

    Each answer comes with its evidence: the menu line, the listing attribute or the review that supports it, with the date it was seen. You can check any venue in one click.

    What does Unknown mean?

    Unknown means the public sources for that venue did not show the answer, for example a bar with no menu online. It is not the same as No, so keep Unknown venues on a list when the visit can confirm it.

    Where does the menu information come from?

    Menu content comes from public menus, menus in photos, outlet websites and delivery menus. Menus in photos are read, so what they list becomes searchable, and every menu keeps its capture date.

    Can I combine attributes with segments and scores?

    Yes, attributes, your own segments and the lead score are all filters and columns, so "Street food, has a terrace, score above 70" is one list.

    For sales leaders: the business case

    Custom attributes let each campaign target the venues it was built for, without a research project per campaign.

    • Campaign lists in hours. A seasonal or product-specific target list comes from one new column, not from weeks of desk research.
    • Better fit, fewer wasted visits. Reps visit venues that match the pitch: a terrace for a summer serve, a vegan menu for a plant-based product.
    • Rules you can defend. Every answer has a written rule and evidence, so a target list holds up in a planning meeting and can be corrected in minutes.

    Ready to see what you're missing?

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    1

    Define an ideal customer profile and select your test city

    2

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