Retail Analytics
Retail analytics refer to the process of examining consumer demand, supply chains, and inventory levels by looking into data. Businesses use often various data types like transactional and behavioural data e.g to optimise their product pricing according to the season.
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Retail Turnover
by MBI Geodata
0 Data volume varies for every country worldwide
100% Coverage varies by country
249 countries covered
Retail Turnover / Globally consistent and comparable
Retail shop sales data
by Automaton AI
2K Images
1 country covered
Data of a retail shop of all the sales data for the predictive analytics (Tabular data)
Retail Centrality
by MBI Geodata
0 Data volume varies for every country worldwide
100% Coverage varies by country
240 countries covered
Retail Centrality Index describes the ability of an area to pin the Retail Spending of its population and of other areas’ population down to the local retail...
MBI Geodata
Based in Germany
MBI is a data company with a key focus on building global consistent and comparable datasets. Preferred data provider & partner to leading IT & GIS companies...
worldwide
globally consistent
strict & continuous controls
Lifesight
Based in Singapore
Lifesight is a data & analytics company specializing in customer intelligence. We collect, enrich and distribute high quality online and offline consumer beh...
Event per Day
Consumer Profiles
Brands Tracked
DDS Digital Data Services
Based in Germany
• Spatial Data
• Cloud Services
• Software & Tools
• Consulting
Worldwide
Independent
flexible
Frequently Asked Questions about Retail Analytics
Learn everything about Retail Analytics. Understand data sources, popular use cases, and data quality.
What are retail analytics?
Retail analytics relates to the effort that provides analytical insights on past and future store performance by looking in to vast amounts of data. Such insights are crucial e.g in marketing and procurement decisions.
What data do retailers need?
The data types used in retail analytics vary. For example, pricing data is often used to optimise product prices to reflect the competition, whereas in marketing, behavioural data can be used to group customers behavioural targeting.