Calibrate & fix brand performance across sales mix via
smart analytics
How quick and easy is it for you to
get brand analytics answers across channel, brand, category and
partners for ...
Ever get the feeling, that while you have the data, but the
right answers keep eluding you?
Wrestling with the right brand
performance answers across channel, brand, category, partners and
price?
Some typical brand performance analytics that are available,
include:
What is selling and what is not?
What is your current sales mix across brand, channel,
category and partner?
Which partners are heavily influenced by discounts?
Targets vs actuals across zones, channels, brands,
categories and partners?
Which brand sells better in which zone?
Which category sells better in which zone?
Which SKU sells better in which zone?
Where to place low-priced items?
Where to place high-priced items?
Top locations by Cancellations?
Top locations by Returns?
Did all your Min Offer Price exceptions have prior
approvals?
MRP brackets sales analysis - across zones, categories
and brands
Sales Mix over time for Brands and SKUs?
What are the trends for low-priced items across zones,
brands and time?
What are the trends for high-priced items across zones,
brands and time?
How does JetFerry.ai help with brand
performance analytics?
Without having to learn queries or APIs, you get brand
analytics all in one-place with multi-level, multi-dimensional
drill-down to help you get a massively deep understanding. Here
are just some of the answers you can get ...
Current sales trends across brand, channel, category,
zone and price
Current sales mix across brand, channel, category and
SKUs
Discount price analysis across channel, zone, brands,
categories and SKUs
Targets vs actuals across zones, channels, brands,
categories and SKUs
What are the trends for low/high-priced items across
zones, brands and time
MRP brackets sales analysis - across zones, channels,
categories, SKUs and brands
Cancellations break-down by location, brands, channel and
category
Returns break-down by location, brands, channel and
category
