Logistics
18 columns
200 rows
8 formats

Smart Retail Shelf Stock Analytics

This dataset provides detailed, event-level logs from IoT sensors and cameras monitoring shelf stock levels, product movements, and replenishment activities in digital retail environments. It enables comprehensive analysis for inventory optimization, loss prevention, and operational efficiency, making it invaluable for smart retail management and real-time analytics.

last updated 20 Aug 2025
by GoMask

The brief that made it

Real-time shelf stock monitoring and inventory optimization

Sample rows

preview · 8 of 200 rows · all 18 columns

log_idstring	event_typestring	stock_quantityinteger	product_categorystring	store_idstring	shelf_idstring	sensor_idstring	product_idstring	product_namestring	event_timestampdatetime	replenished_quantityinteger	movement_directionstring	movement_quantityinteger	sensor_typestring	sensor_statusstring	operator_idstring	location_zonestring	image_urlstring
LOG000001	stock_level	18	snacks	STR001	SHF01	SNSR-A1	PRD2001	Crispy Chips	2024-06-21T08:15:23	blank	blank	blank	weight_sensor	active	blank	zone_1	blank
LOG000002	replenishment	blank	beverages	STR002	SHF14	SNSR-B3	PRD2002	Lemon Soda	2024-06-21T08:47:09	36	blank	blank	RFID	active	OPR001	zone_2	blank
LOG000003	movement	blank	health_food	STR003	SHF23	SNSR-C2	PRD2003	Protein Bar	2024-06-21T09:03:12	blank	out	2	camera	active	blank	zone_3	https://images.srshelf.com/move/0003.jpg
LOG000004	stock_level	9	beverages	STR004	SHF35	SNSR-D1	PRD2004	Sparkling Water	2024-06-21T09:29:45	blank	blank	blank	RFID	error	blank	zone_4	blank
LOG000005	replenishment	blank	confectionery	STR005	SHF41	SNSR-E2	PRD2005	Milk Chocolate	2024-06-21T09:46:07	12	blank	blank	RFID	active	OPR002	zone_5	blank
LOG000006	movement	blank	beverages	STR006	SHF56	SNSR-F1	PRD2006	Organic Tea	2024-06-21T09:58:20	blank	in	1	camera	active	blank	promo_zone	https://images.srshelf.com/move/0006.jpg
LOG000007	stock_level	54	health_food	STR007	SHF61	SNSR-G3	PRD2007	Nut Mix	2024-06-21T10:02:17	blank	blank	blank	weight_sensor	active	blank	zone_6	blank
LOG000008	replenishment	blank	snacks	STR001	SHF02	SNSR-A2	PRD2008	Salted Pretzels	2024-06-21T10:15:29	3	blank	blank	other	active	OPR003	zone_1	blank
LOG000009	stock_level	0	condiments	STR002	SHF15	SNSR-B4	PRD2009	Tomato Sauce	2024-06-21T10:23:34	blank	blank	blank	RFID	error	blank	unknown	blank
LOG000010	movement	blank	beverages	STR003	SHF24	SNSR-C3	PRD2010	Energy Drink	2024-06-21T10:34:51	blank	left	7	camera	active	blank	zone_3	https://images.srshelf.com/move/0010.jpg
LOG000011	stock_level	27	health_food	STR004	SHF36	SNSR-D2	PRD2011	Fruit Bar	2024-06-21T10:49:03	blank	blank	blank	weight_sensor	active	blank	zone_4	blank
LOG000012	replenishment	blank	beverages	STR005	SHF42	SNSR-E3	PRD2012	Black Coffee	2024-06-21T11:07:14	80	blank	blank	RFID	active	OPR004	cafe_corner	blank
LOG000013	stock_level	0	blank	STR006	SHF57	SNSR-F2	PRD2013	blank	2024-06-21T11:18:22	blank	blank	blank	weight_sensor	error	blank	unknown	blank
LOG000014	movement	blank	health_food	STR007	SHF62	SNSR-G4	PRD2014	Granola	2024-06-21T11:22:37	blank	right	4	weight_sensor	active	blank	zone_6	https://images.srshelf.com/move/0014.jpg
LOG000015	stock_level	120	beverages	STR008	SHF75	SNSR-H2	PRD2015	Peach Juice	2024-06-21T11:37:48	blank	blank	blank	RFID	active	blank	zone_7	blank
LOG000016	replenishment	blank	snacks	STR001	SHF03	SNSR-A3	PRD2016	Veggie Chips	2024-06-21T11:41:02	2	blank	blank	RFID	inactive	OPR005	zone_1	blank
LOG000017	stock_level	1	beverages	STR002	SHF16	SNSR-B5	PRD2017	Green Tea	2024-06-21T11:55:25	blank	blank	blank	weight_sensor	active	blank	zone_2	blank
LOG000018	movement	blank	snacks	STR003	SHF25	SNSR-C4	PRD2018	Oat Cookies	2024-06-21T12:09:11	blank	unknown	1	camera	active	blank	zone_3	https://images.srshelf.com/move/0018.jpg
LOG000019	stock_level	44	health_food	STR004	SHF37	SNSR-D3	PRD2019	Berry Yogurt	2024-06-21T12:15:22	blank	blank	blank	RFID	active	blank	zone_4	blank
LOG000020	replenishment	blank	beverages	STR005	SHF43	SNSR-E4	PRD2020	Classic Cola	2024-06-21T12:29:33	230	blank	blank	RFID	active	OPR006	zone_5	blank

What the 200 rows show

from the 200-row sample

11.5median stock_quantity
3sensor statuses
4sensor types
5movement directions
8stores
15location zones

event_type200 rows by value

stock_quantity100 rows, in bands of 100

Median 11.5, from 0 to 1,000.

product_category180 rows with a value · 20 left blank

beverages68
health_food46
snacks37
condiments16
confectionery13

18 columns by typefrom the column list below

string 14
integer 3
datetime 1

Columns

18 columns in three groups

blueprint · 18 columns
column	type	description	example
Text 14 columns
`log_id`	string	Unique identifier for each sensor or camera log entryunique	LOG000001
`store_id`	string	Unique identifier for the retail store8 stores	STR001
`shelf_id`	string	Unique identifier for the shelf within the store	SHF01
`sensor_id`	string	Unique identifier for the IoT sensor or camera device	SNSR-A1
`product_id`	string	Unique identifier for the product being tracked	PRD2001
`product_name`	string	Name of the product	Crispy Chips
`product_category`	string	Category of the product (e.g., snacks, beverages)5 categories · optional	snacks
`event_type`	string	Type of event logged (stock_level, replenishment, movement)stock_level · replenishment · movement	stock_level
`movement_direction`	string	Direction of product movement (in, out, left, right, unknown)in · out · left · right · unknown · optional	out
`sensor_type`	string	Type of sensor or camera (weight_sensor, camera, RFID, other)weight_sensor · camera · RFID · other	weight_sensor
`sensor_status`	string	Operational status of the sensor (active, inactive, error)active · inactive · error · optional	active
`operator_id`	string	Identifier for the staff member responsible for replenishment (if applicable)optional	OPR001
`location_zone`	string	Zone or section of the store where the shelf is locatedoptional	zone_1
`image_url`	string	URL to the image captured by the camera (if available)optional	https://images.srshelf.co…
Numbers 3 columns
`stock_quantity`	integer	Number of product units currently on the shelf at the time of the event0 or more · optional	18
`replenished_quantity`	integer	Number of product units added to the shelf during a replenishment event0 or more · optional	36
`movement_quantity`	integer	Number of product units moved during a movement event1 or more · optional	2
Dates and times 1 column
`event_timestamp`	datetime	Date and time when the event was recorded	2024-06-21T08:15:23

Use it for

A logistics dashboard
Stock_quantity by event_type and a breakdown of product_category. Excel, Power BI or Tableau.
What pattern can you find in 200 rows?
A class exercise
Hand out the rows and one question. Everyone works from the same 200 rows.
Logs200
LOG00000118stock_le…
LOG000002replenis…
LOG000003movement
A software demo
Believable logs with store_id, shelf_id and sensor_id to fill a screen in front of a buyer.

This dataset200 rows18 columns

Yours1,000 rows18 columnslocation_zone: UK only

blueprint · smart-retail-shelf-stock-analytics

Behind this dataset

Same schema. As many rows as you need.

These 200 rows came out of a blueprint — 18 columns with generation rules behind each one. Open it in Data Factory to retune a column, add your own, wire in foreign keys, and run it at the size you actually need.

Rules it was built with

Item ID and shelf location mapping
Time-stamped restock events
Flag stockouts and overstocks
Synthetic anonymization

Rows1,000 rows10,000 rows100,000 rows1,000,000 rows

Open the blueprint in Data Factory

1 credit per row. Preview 20 rows free. Buy rows for the full run.

Exports: CSV, JSON, JSONL, Parquet, SQL, Excel, TSV, XML
Licence: yours to use, including commercially
API slug: smart-retail-shelf-stock-analytics

What should your data show?

No signup. No card.

Sample rows

What the 200 rows show

Columns

Use it for

A logistics dashboard

A class exercise

A software demo

Make it yours.

Same schema. As many rows as you need.

More in Logistics

What should your data show?