- Oleksandr Leshenko - Resident Architect, Data Modeling
- Datapunkt BI possibilities
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Operational Analysis of Retail - Dashboard
Overview
An operational analysis of retail provides us with an oversight for how all of our stores performed throughout the year. In here we can see all of our stores and their locations, their revenue through the year and how much growth they have experienced in comparison to last year, how much growth we experienced in every region, what product category sold the most, average customer load through the day and week. This will help us get the general picture of how our business is doing.
For this BI solution we propose using Datapunkt BI Analytics. Conducting this analysis will help us understand current trends across all of our stores.
Goals
Make an easy to understand dashboard, so we could see the current trends across all of our stores.
Objectives
These objectives will help us reach our goal:
- Prepare the dataset based on the data received from stores
- Investigate in which regions we have stores, and how many of them we have
- Investigate which product category bring the most profit
- Analyze revenue across all stores
- Analyze growth across all stores and regions
- Analyze the average load across whole week and throughout the day
KPI Architecture
| Objectives | KPIs | Measures |
|---|---|---|
| 1. Map of all stores | Geo location of every store | In which regions there are stores, and their amount per region |
| 2. Revenue by product category | Revenue by product category | How much we made in a year in every product category |
| 3. Store revenue | Annual revenue by the store | Revenue of every store throughout the year |
| 4. Growth | Revenue growth percentage | Revenue growth percentage in comparison to last year in every store and region |
| 5. Customer load per hour | Amount of customers per hour | How many customers have visited the store on average every hour throughout the week |
| 6. Customer's Sankey diagram | The flow of customers per day | How many customer have visited the store on average on every day of the week |
