Snapbizz Consumer Transaction Data of FMCG Products - POS Data India
# | Store_ID |
Store_Name |
Metro_City |
Invoice_ID |
Bill_date |
Date |
Month |
Week |
Hour |
Barcode |
Local_Item_Code |
Item_Description |
Centralized_Description |
Manufacturer_Name |
Category |
Sub_Category |
Quantity |
Selling_Price |
Total_Amount |
MRP |
Bill_Amount |
Loose_Item_Flag |
is_credit |
Pincode |
Zone |
Market_Cap |
Payment_Mode |
Payment_Type |
||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1 | xxxxxxxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxx | xxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxxxxxx |
2 | xxxxxx | Xxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxx | xxxxxx | xxxxxxx | xxxxxxx | Xxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | xxxxxx | Xxxxxxxx | Xxxxxxx | Xxxxx | xxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxxxxx | xxxxxxxx | Xxxxxxxxxx | Xxxxxxxx |
3 | Xxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxx | xxxxxxx | xxxxxxxxx | Xxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxx | xxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxx | xxxxx | Xxxxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxx | xxxxxx | Xxxxxxxxx | xxxxx |
4 | Xxxxxxxxxx | xxxxxx | xxxxx | xxxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | xxxxx | xxxxxxxx | xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxxx | xxxxxxxxxx | Xxxxxx | xxxxxxxxx | Xxxxx | xxxxx |
5 | xxxxxxxxx | xxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxx | xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxx | Xxxxxxxx | xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxx | Xxxxx | Xxxxxxx | Xxxxx | Xxxxxx |
6 | Xxxxx | Xxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxxx | Xxxxxx | Xxxxxxxxxx | Xxxxxx | Xxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx | xxxxx | Xxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxx | Xxxxxxxxxx | xxxxxxxxx | Xxxxx | Xxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxxx | Xxxxxxxx |
7 | Xxxxxxxxx | xxxxx | Xxxxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | Xxxxxx | xxxxxx | xxxxxxxx | xxxxxxx | Xxxxx | Xxxxxxxxx | Xxxxx | Xxxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | xxxxxxx | xxxxxxxxxx | xxxxxx | xxxxx | Xxxxxxxxxx |
8 | Xxxxxxxxx | xxxxxxx | Xxxxxx | Xxxxx | Xxxxxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx | xxxxxxx | xxxxxxxxxx | Xxxxxx | Xxxxxxxxx | xxxxxxx | Xxxxxxxx | xxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxxxx | Xxxxxxx | xxxxx | xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxxx | xxxxxxx |
9 | Xxxxx | xxxxxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxx | Xxxxxxxx | Xxxxxxxxxx | Xxxxxxx | Xxxxxx | Xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | Xxxxx | Xxxxx | Xxxxx | Xxxxxxx | xxxxx | xxxxxxxxx | xxxxxxx | Xxxxxxx | xxxxxx | xxxxxxxxxx | xxxxxxxxxx | Xxxxxxx | xxxxxxxxx | Xxxxx |
10 | xxxxxxx | Xxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxx | xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | Xxxxxxx | xxxxxxxx | xxxxx | Xxxxx | Xxxxxxxx | xxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxxxxx | xxxxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx | Xxxxxxx |
... | xxxxxxx | Xxxxxxxxxx | xxxxxxxx | Xxxxx | xxxxxxxxxx | xxxxxxxxxx | xxxxxx | xxxxxxxx | Xxxxxxxx | xxxxxx | xxxxxxxx | xxxxxx | Xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxxxxxxx | Xxxxxxxxx | Xxxxxxx | xxxxxxxx | Xxxxxxx | Xxxxxxxxxx | Xxxxxxxxx | xxxxxxxxxx | xxxxxxx | Xxxxxxxxx | xxxxxxxxx | xxxxxxxx | xxxxxxxxx | xxxxx | Xxxxx |
Data Dictionary
Attribute | Type | Example | Mapping |
---|---|---|---|
Store_ID
|
Integer | 11613 | |
Store_Name
|
String | GANESH STORE BW | |
Metro_City
|
String | Mumbai | |
Invoice_ID
|
String | 11613-1118013392 | |
Bill_date
|
String | 02/01/2019 11:47:45 AM | |
Date
|
String | 01/02/2019 | |
Month
|
String | 19-Feb | |
Week
|
String | W4 | |
Hour
|
Integer | 11 | |
Barcode
|
Integer | 8901491503051 | |
Local_Item_Code
|
|||
Item_Description
|
String | LAYS HOT SWEET CHILLI POTATO CHIPS 25 GM PLS | |
Centralized_Description
|
String | LAYS CARIBBEAN HOT & SWEET CHILLI 26 GMS | |
String | LAYS | Brand Name | |
Manufacturer_Name
|
String | PEPSICO INDIA | |
Category
|
String | SNACK FOODS | |
Sub_Category
|
String | NA | |
Quantity
|
Integer | 1 | |
Selling_Price
|
Integer | 10 | |
Total_Amount
|
Integer | 10 | |
MRP
|
Integer | 10 | |
Bill_Amount
|
Integer | 10 | |
Loose_Item_Flag
|
Boolean | f | |
is_credit
|
Boolean | t | |
Pincode
|
Integer | 400074 | |
String | Maharashtra | State Name | |
Zone
|
String | West | |
Market_Cap
|
String | Mumbai | |
Payment_Mode
|
String | CASH | |
Payment_Type
|
String | CREDIT |
Attribute | Type | Example | Mapping |
---|---|---|---|
Invoice ID
|
10263-2019008096 | ||
Item Descriptiom
|
Atta | ||
Centralized Description
|
Aashirvaad Shudh Chakki Atta 5 Kg | ||
Total Amount
|
500 |
Description
Country Coverage
History
Volume
500 million | records |
Pricing
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Frequently asked questions
What is Snapbizz Consumer Transaction Data of FMCG Products - POS Data India?
Snapbizz’s FMCG Consumer Transaction Data is your gateway to comprehensive consumption analysis, enabling you to unravel trends and make informed decisions. Discover the pulse of the market and propel your strategies forward with the power of precise data insights.
What is Snapbizz Consumer Transaction Data of FMCG Products - POS Data India used for?
This product has 5 key use cases. Snapbizz recommends using the data for SKU level grocery data, Invoice level retail sales fmcg Data, Consumer Sales Data, POS Sales Data, and fmcg Data for competitor analysis. Global businesses and organizations buy Point-of-Sale (POS) Data from Snapbizz to fuel their analytics and enrichment.
Who can use Snapbizz Consumer Transaction Data of FMCG Products - POS Data India?
This product is best suited if you’re a Medium-sized Business, Enterprise, or Small Business looking for Point-of-Sale (POS) Data. Get in touch with Snapbizz to see what their data can do for your business and find out which integrations they provide.
How far back does the data in Snapbizz Consumer Transaction Data of FMCG Products - POS Data India go?
This product has 5 years of historical coverage. It can be delivered on a monthly, quarterly, yearly, and on-demand basis.
Which countries does Snapbizz Consumer Transaction Data of FMCG Products - POS Data India cover?
This product includes data covering 1 country like India. Snapbizz is headquartered in India.
How much does Snapbizz Consumer Transaction Data of FMCG Products - POS Data India cost?
Pricing information for Snapbizz Consumer Transaction Data of FMCG Products - POS Data India is available by getting in contact with Snapbizz. Connect with Snapbizz to get a quote and arrange custom pricing models based on your data requirements.
How can I get Snapbizz Consumer Transaction Data of FMCG Products - POS Data India?
Businesses can buy Point-of-Sale (POS) Data from Snapbizz and get the data via S3 Bucket and Email. Depending on your data requirements and subscription budget, Snapbizz can deliver this product in .csv and .xls format.
What is the data quality of Snapbizz Consumer Transaction Data of FMCG Products - POS Data India?
Snapbizz has reported that this product has the following quality and accuracy assurances: 100% real time data. You can compare and assess the data quality of Snapbizz using Datarade’s data marketplace.
What are similar products to Snapbizz Consumer Transaction Data of FMCG Products - POS Data India?
This product has 3 related products. These alternatives include Snapbizz FMCG Financial Data POS Transaction Data, ClearScore Dataset Individual Tickers UK Consumer Transaction Data 1.4m users., and Granular Consumer Transaction Data Ecommerce Data for Emerging Markets. You can compare the best Point-of-Sale (POS) Data providers and products via Datarade’s data marketplace and get the right data for your use case.