BI Analytics
Create a reliable, easy access analytical source to elevate your decision-making process
Eliminate assumptions and be confident in your decisions
1
Quickly identify current issues at the location & find best-fitted solutions
2
Identify level of potential for the Point of Sale
3
Receive extensive reports about a product, category, brand, store segment or retailer
4
Monitor any metric dynamic in comparison with the previous periods
![laptop](https://ailet.com/wp-content/uploads/elementor/thumbs/laptop-qdh9344ikw82fr5wl2pl4659s8g523nt6ispa2r99y.webp)
![laptop_2](https://ailet.com/wp-content/uploads/elementor/thumbs/laptop_2-qdh9344ikw82fr5wl2pl4659s8g523nt6ispa2r99y.webp)
![laptop_3](https://ailet.com/wp-content/uploads/elementor/thumbs/laptop_3-qdh9344ikw82fr5wl2pl4659s8g523nt6ispa2r99y.webp)
![laptop_4](https://ailet.com/wp-content/uploads/elementor/thumbs/laptop_4-qdh9344ikw82fr5wl2pl4659s8g523nt6ispa2r99y.webp)
- Identify OSA metrics execution by store, retailer, category, product or product segment
- Identify which retailer contributes the most to overall OSA
- View OSA progression ranges by location
- Identify store visits without assortment matrixes
- Determine average share of shelf for the category/brand/product/store
- Identify in which category brands holds a maximum or minimum share of shelf
- Compare your Share of Shelf with ones of your competitor
- Identify which retailer contibutes the most to overall OOS
- Identify which products are Out of Shelf most frequently
- Identify the reasons for lack of assortment
- Identify users with highest OOS at locations
- visual representaion of the stores that have met the KPI requirements
- comparing the results of metric compliance of all the POS
- Evaluate the potential of the Point of Sale
- calculating the space occupied by a category at location
- comparing the share of category of your product & of your competitor
- calculating the value of category size based on historical data (AVG, median, MAX, Min)
- calculating planned Share of Shelf value
- displaying store visit information on the map by user, store, region
- all the visit details are grouped in tables for a more comprehensive view of the store visits
- "Geo-tag error" metric
- detecting visits done in less than 5 minutes
- detecting POS with 100% Share-of-Shelf
- detecting photos done from the screen-monitor
- identifying users with too many or too little photos during visits
- detecting users violating the rules of taking a picture during the visits
Take a photo of the shelf and receive detailed analytics for every SKU, product category, brand or Point of Sale
- Embedded or Customized dashboards
- Analytical data detailed according to the client needs
- 24/7 access to your data
- Easy to use interface with all your data analytics in one place
- Pre-installed Data visualization tools
- Seamless data import process
![](https://ailet.com/wp-content/uploads/2023/03/Typeailet-16.webp)
![setting setting](https://ailet.com/wp-content/uploads/elementor/thumbs/setting-qdh93449blk25maebkruf33t7j3w7e8isv6ryv9148.webp)
at the location
Identify problem retailers and outlets with low OSA, OOS, SOS
![mizing_time_and_boos mizing_time_and_boos](https://ailet.com/wp-content/uploads/elementor/thumbs/mizing_time_and_boos-qdh93449blk25maebkruf33t7j3w7e8isv6ryv9148.webp)
Quickly identify locations, retilers with lowest metrics, define the problem and take corrective actions
![setting setting](https://ailet.com/wp-content/uploads/elementor/thumbs/setting-qdh93449blk25maebkruf33t7j3w7e8isv6ryv9148.webp)
at the location
Identify problem retailers and outlets with low OSA, OOS, SOS
![mizing_time_and_boos mizing_time_and_boos](https://ailet.com/wp-content/uploads/elementor/thumbs/mizing_time_and_boos-qdh93449blk25maebkruf33t7j3w7e8isv6ryv9148.webp)
Quickly identify locations, retilers with lowest metrics, define the problem and take corrective actions
![analytics-2 analytics-2](https://ailet.com/wp-content/uploads/elementor/thumbs/analytics-2-qdh93449blk25maebkruf33t7j3w7e8isv6ryv9148.webp)
Identify the reasons for assortment absence (e. g. virtual stock-out, blocked shipments from retail outlets, insufficient ordering, etc.)
![Scalability_(1) Scalability_(1)](https://ailet.com/wp-content/uploads/elementor/thumbs/Scalability_1-qdh93449blk25maebkruf33t7j3w7e8isv6ryv9148.webp)
Get the facts on breaches of agreements with retailers (absence of the key assortment in your stores)
![analytics-2 analytics-2](https://ailet.com/wp-content/uploads/elementor/thumbs/analytics-2-qdh93449blk25maebkruf33t7j3w7e8isv6ryv9148.webp)
Identify the reasons for assortment absence (e. g. virtual stock-out, blocked shipments from retail outlets, insufficient ordering, etc.)
![Scalability_(1) Scalability_(1)](https://ailet.com/wp-content/uploads/elementor/thumbs/Scalability_1-qdh93449blk25maebkruf33t7j3w7e8isv6ryv9148.webp)
Get the facts on breaches of agreements with retailers (absence of the key assortment in your stores)