Dotlas

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1.000.000+
F&B Locations
50+
Data Variables per Location
On This Page:
  • Overview
  • Datasets
  • Data Pricing
  • Data Reviews
  • Competitors
  • Learn More
  • Overview
  • Datasets
  • Data Pricing
  • Data Reviews
  • Competitors
  • Learn More

Dotlas Data Products: APIs & Datasets

Explore Dotlas’ datasets, databases, and data feeds.

Dotlas Pricing & Cost

Learn about Dotlas’ prices, subscription cost, and API pricing.

For our ongoing data services, we charge anywhere between $250-$1500 per month per city, depending on the city size.
If you’d like one-off datasets, please get in touch with us and we’ll quote you a price.

Dotlas’ APIs and datasets range in cost from $1,000 / month to $2,500 / purchase. Dotlas offers free samples for individual data requirements. Get talking to a member of the Dotlas team to receive custom pricing options, information about data subscription fees, and quotes for Dotlas’ data offering tailored to your use case.

Dotlas Reviews

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About Dotlas

Learn more about Dotlas’ data sources, use cases, and integrations.

Dotlas in a Nutshell

We’re a big data analytics and AI startup founded in 2021.

Headquarters
USA

Country Coverage

Asia (4)
Bahrain
Kuwait
Saudi Arabia
United Arab Emirates
Europe (18)
Austria
Belgium
Czech Republic
Denmark
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Netherlands
Norway
Poland
Portugal
Spain
Sweden
United Kingdom
North America (2)
Canada
United States of America

Data Offering

We provide very enhanced F&B (restaurants, cafés, bars, etc.) data.

  • Metadata
  • Contacts
  • Social profiles
  • Reviews
  • Menus
  • Other info
  • Photos

Let us know if you have a specific request that you don’t see us having, and we’ll try our best to fulfil it.

Use Cases

Data Sources & Collection

We gather information from over 100 sources and have a team dedicated to cleaning, aggregating, transforming, triangulating data across sources, (to verify authenticity), and collating it all together.

Key Differentiators

COMPLETENESS
We’re always increasing the number of variables per POI we have information for. If you have a specific request, don’t hesitate to ask!

ADAPTED TO YOUR DATA SCHEMA
We deliver the data according exactly to your data schema so that you don’t have to spend development resources in transforming it.

DATA FORMAT OF YOUR CHOOSING
The data is provided in whichever format of your choosing, be it XLSX, CSV, JSON, XML, etc.

DELIVERY METHOD OF YOUR CHOOSING
Whether it is S3 buckets, Google Spreadsheets, or through API consumption, we are very flexible in the delivery method.

FLEXIBILITY
We are very flexible, so if you have a request for an enhancement to the data we are offering that you currently do not see, just ping us and we will work with you to make it happen.

What are you looking for?

Nuno
from Dotlas is ready to assist you

Frequently asked questions about Dotlas

What does Dotlas do?

Dotlas helps retailers improve revenue and operations by delivering insights and advanced analytics. We gather, manage, and analyze retail data from hundreds of sources, powering use cases such as competitive intelligence, market analysis, brand protection, and pricing optimization, among others.

How much does Dotlas cost?

Dotlas’ APIs and datasets range in cost from $1,000 / month to $2,500 / purchase. Dotlas offers free samples for individual data requirements. Get talking to a member of the Dotlas team to receive custom pricing options, information about data subscription fees, and quotes for Dotlas’ data offering tailored to your use case.

What kind of data does Dotlas have?

Restaurant Data, B2B Contact Data, Restaurant Location Data, Retail Data, and Food & Grocery Data

What data does Dotlas offer?

We provide very enhanced F&B (restaurants, cafés, bars, etc.) data. Metadata Contacts Social profiles Reviews Menus Other info Photos Let us know if you have a specific request that you don’t see us having, and we’ll try our best to fulfil it.

How does Dotlas collect data?

We gather information from over 100 sources and have a team dedicated to cleaning, aggregating, transforming, triangulating data across sources, (to verify authenticity), and collating it all together.