List of Dry cleaners in Indonesia
Download the complete database of Dry cleaners in Indonesia. Our detailed B2B list consists of 8773 records with email addresses, phone numbers, contact details, social media profiles, and much more in one place. It is your one-stop place for all the essential details you need on Dry cleaners for lead generation and market analysis. When you download our Dry cleaners across Indonesia dataset, you get to achieve operational efficiency and achieve your desired outcomes.
- 8 773 Dry cleaners in Indonesia
- 6 208 Phone Numbers
- 11 Emails
Data updated on October 01, 2025
How to download the data of Dry cleaners in Indonesia?
As a B2B database provider, we offer a complete list of Dry cleaners in Indonesia at an affordable price. Our datasets are reliable, accurate, and up-to-date with timestamps. Download the complete list of Dry cleaners in Indonesia database in CSV format now. Get instant access to detailed data, including geolocation, contact information, and insights tailored to your needs.
Download Free Sample List of Dry cleaners in Indonesia
Still confused? You can get started with a free sample list of Dry cleaners in Indonesia. The sample Dry cleaners dataset covers all the key fields such as name, location, contact information, geolocation, and more. Our database covers 8773 Dry cleaners across the country. Download the sample instantly - No credit card required.
| Name | Rating | Review | Url | Phone | Address | City | State/Territory | Country | |
|---|---|---|---|---|---|---|---|---|---|
| Nani Laundry | 4.4 | 51 | Ubud | BA | ID | ||||
| Kendi laudry | 0 | 0 | Cibinong | JB | ID | ||||
| Sri Laundry Express | 0 | 0 | Kabupaten Buleleng | BA | ID | ||||
| laundry | 0 | 0 | Curug | BT | ID | ||||
| Rafanda laundry | 0 | 0 | Diwek | JI | ID | ||||
| DINA LAUNDRY | 4.3 | 3 | Kabupaten Aceh Besar | AC | ID | ||||
| JEEVES - Central Processing | 4.9 | 156 | Jakarta | JK | ID | ||||
| Farhid Laundry | 0 | 0 | Bandar Lampung | LA | ID | ||||
| Luthfie laundry | 5 | 1 | Bekasi | JB | ID | ||||
| Mario Laundry | 4.7 | 3 | Mamuju | SR | ID |
| Name | Name of the Dry cleaners. |
| Address | Full postal address, including street, city, state, and country. |
| Pincode | The postal code of the Dry cleaners location. |
| Phone Number | Dry cleaners location phone number. |
| Email Address | Associated email address of the Dry cleaners location. |
| Domain URL | Website URL of the Dry cleaners. |
| Facebook Profile | Link to the Dry cleaners Facebook Profile. |
| X (formerly Twitter) | Link to the Dry cleaners X (Twitter). |
| Instagram Profile | Link to the Dry cleaners Instagram Profile. |
| Snapchat Profile | Link to the Dry cleaners Snapchat Profile. |
| WhatsApp Account | Link to the Dry cleaners WhatsApp number. |
| TikTok Account | Link to the Dry cleaners TikTok Account. |
| LinkedIn Account | Link to the Dry cleaners LinkedIn Profile. |
| YouTube Channel | Link to the Dry cleaners YouTube Channel. |
| Image URL | Links to images for a visual representation. |
| Latitude & Longitude | Dry cleaners geo-coordinates for location-based services and targeted advertising. |
| City | The city where the Dry cleaners is located. |
| State | The specific state or region within the country where the Dry cleaners operates. |
| Country | The country, focused on Dry cleaners for this dataset. |
How many Dry cleaners are there in each state/territory?
| 165 Records | North Sumatra database list has 165 records |  |
| 129 Records | Bengkulu database list has 129 records | |
| 72 Records | Central Kalimantan database list has 72 records | |
| 305 Records | South Sulawesi database list has 305 records | |
| 64 Records | Southeast Sulawesi database list has 64 records | |
| 358 Records | Central Java database list has 358 records | |
| 256 Records | East Kalimantan database list has 256 records | |
| 208 Records | Jakarta database list has 208 records | |
| 116 Records | Riau Islands database list has 116 records | |
| 76 Records | North Sulawesi database list has 76 records | |
| 772 Records | Riau database list has 772 records | |
| 480 Records | Banten database list has 480 records | |
| 318 Records | Lampung database list has 318 records | |
| 56 Records | Gorontalo database list has 56 records | |
| 122 Records | Central Sulawesi database list has 122 records | |
| 121 Records | West Nusa Tenggara database list has 121 records | |
| 212 Records | Jambi database list has 212 records | |
| 245 Records | South Sumatra database list has 245 records | |
| 55 Records | East Nusa Tenggara database list has 55 records | |
| 197 Records | South Kalimantan database list has 197 records | |
| 76 Records | Bangka Belitung Islands database list has 76 records | |
| 177 Records | Aceh database list has 177 records | |
| 971 Records | West Java database list has 971 records | |
| 1.3K Records | Bali database list has 1 288 records | |
| 797 Records | East Java database list has 797 records | |
| 576 Records | West Sumatra database list has 576 records | |
| 399 Records | Special Region of Yogyakarta database list has 399 records | |
Number of states/territories in Indonesia without Dry cleaners
Buy Dry cleaners in Indonesia datasets Now!
Download this business data in adaptable formats. Right from CSV, Excel, and GeoJSON, to other notable formats, we are here to help with the desired format!
Reliable B2B Datasets For Digital Marketing & Lead Generation
Email Marketing
Business datasets provide accurate contact information, enabling personalized email campaigns. Boost your open rates and engagement, leading to more qualified leads.
Targeted Advertising
Utilize B2B datasets to launch highly targeted campaigns on Facebook Ads, Google Ads, and more. Deliver relevant ads that drive traffic and generate quality leads.
Cold Calling
Access to detailed sales datasets with contact numbers helps your sales team reach decision-makers directly. Save time and increase the chances of faster conversions effortlessly.
Access meticulously curated datasets for precise and reliable information.
Leverage industry-specific data to target your audience effectively.
Adaptable data solutions that grow with your business requirements.
