About ShelfRadar
We built ShelfRadar to help D2C founders win on Quick Commerce.
Agentic intelligence to help improve revenue growth
in Qcom
Quick Commerce revenue growth is possible when inventory, ads and discounts are all orchestrated at the exact same time frame. If even one over or underachieves, targets will be missed and cost overruns happen. ShelfRadar helps you hit your targets.
Quick Commerce revenue growth is possible when inventory, ads and discounts are all orchestrated at the exact same time frame. If even one over or underachieves, targets will be missed and cost overruns happen. ShelfRadar helps you hit your targets.
We built ShelfRadar to help D2C founders win on Quick Commerce.
About ShelfRadar
We built ShelfRadar to help D2C founders win on Quick Commerce.
Quick Commerce revenue growth is possible when inventory, ads and discounts are all orchestrated at the exact same time frame. If even one over or underachieves, targets will be missed and cost overruns happen. ShelfRadar helps you hit your targets.
We built ShelfRadar to help D2C founders win on Quick Commerce.
Our goal is simple:
Our goal is simple:
We want to help brands achieve their goals by abstracting away the reams of data in Quick Commerce and help them focus on what needs
to be done today.
We want to help brands achieve their goals by abstracting away the reams of data in Quick Commerce and help them focus on what needs to be done today.
We want to help brands achieve their goals by abstracting away the reams of data in Quick Commerce and help them focus on what needs to be done today.
Our goal is simple:
Our goal is simple:
ShelfRadar is a natural language answer engine that helps you make better decisions that ultimately improve your P&L. We built this first for ourselves to help drive better outcomes for brands we worked with in Quick Commerce.
ShelfRadar is a natural language answer engine that helps you make better decisions that ultimately improve your P&L. We built this first for ourselves to help drive better outcomes for brands we worked with in Quick Commerce.
In Qcom, it’s easy to be overwhelmed by the volume and velocity of data across 3000+ dark stores in 200+ towns, across 6 platforms, across your 40+ SKUs in 4 categories, new ad formats, new deal/discount formats. The number of metrics and normalizing across platforms etc is a daily challenge.
In Qcom, it’s easy to be overwhelmed by the volume and velocity of data across 3000+ dark stores in 200+ towns, across 6 platforms, across your 40+ SKUs in 4 categories, new ad formats, new deal/discount formats. The number of metrics and normalizing across platforms etc is a daily challenge.
ShelfRadar solves this by using agentic AI to do the heavy lifting of generating the analysis plan, normalizing the data, selecting the right elements to focus on and generating the plan that will help you move the needle.
ShelfRadar solves this by using agentic AI to do the heavy lifting of generating the analysis plan, normalizing the data, selecting the right elements to focus on and generating the plan that will help you move the needle.
ShelfRadar is powered by a context layer that normalizes the data across each platform and ensures you get accurate, reliable answers to power your decisions.
ShelfRadar is powered by a context layer that normalizes the data across each platform and ensures you get accurate, reliable answers to power your decisions.
Backed by
ShelfRadar’s parent company, Punt Partners is backed by leading internet founders and marketing leaders in India.
Backed by
Backed by
KUNAL SHAH
KUNAL SHAH
ANUPAM MITTAL
ANUPAM MITTAL
DEEP KALRA
DEEP KALRA
ASHISH HEMRAJANI
ASHISH HEMRAJANI
KUNAL SHAH
KUNAL SHAH
KUNAL SHAH
ANUPAM MITTAL
ANUPAM MITTAL
ANUPAM MITTAL
DEEP KALRA
DEEP KALRA
DEEP KALRA
ASHISH HEMRAJANI
ASHISH HEMRAJANI
ASHISH HEMRAJANI
ARIHANT PATNI
ARIHANT PATNI
ARIHANT PATNI
PHANINDRA SAMA
PHANINDRA SAMA
PHANINDRA SAMA
SARBVIR SINGH
SARBVIR SINGH
SARBVIR SINGH
AAKRIT VAISH
AAKRIT VAISH
AAKRIT VAISH
RAVISH RATNAM
RAVISH RATNAM
RAVISH RATNAM
RAJESH JAIN
RAJESH JAIN
RAJESH JAIN
ASHISH GUPTA
ASHISH GUPTA
ASHISH GUPTA
ANAND JAIN
ANAND JAIN
ANAND JAIN
SURESH KONDAMUDI
SURESH KONDAMUDI
SURESH KONDAMUDI
KUNAL SHAH
KUNAL SHAH
KUNAL SHAH
RAVISH RATNAM
RAVISH RATNAM
RAJESH JAIN
RAJESH JAIN
ASHISH GUPTA
ASHISH GUPTA
ANAND JAIN
ANAND JAIN
SURESH KONDAMUDI
SURESH KONDAMUDI
KUNAL SHAH
KUNAL SHAH
ARIHANT PATNI
ARIHANT PATNI
PHANINDRA SAMA
PHANINDRA SAMA
SARBVIR SINGH
SARBVIR SINGH
AAKRIT VAISH
AAKRIT VAISH
KUNAL SHAH
KUNAL SHAH
ANUPAM MITTAL
ANUPAM MITTAL
DEEP KALRA
DEEP KALRA
ASHISH HEMRAJANI
ASHISH HEMRAJANI
title:What
[Target word or phrase]
Try ShelfRadar.ai for free
Claim an early spot in ShelfRadar’s beta program for our 30 day challenge! We will drive Rs. 1L in savings within 30 days either through improved availability, pricing, ad or cost optimization.
title:What
[Target word or phrase]
Try ShelfRadar.ai for free
Claim an early spot in ShelfRadar’s beta program for our 30 day challenge! We will drive Rs. 1L in savings within 30 days either through improved availability, pricing, ad or cost optimization.
title:What
[Target word or phrase]
Try ShelfRadar.ai for free
Claim an early spot in ShelfRadar’s beta program for our 30 day challenge! We will drive Rs. 1L in savings within 30 days either through improved availability, pricing, ad or cost optimization.
title:What
[Target word or phrase]
Try ShelfRadar.ai
for free
Claim an early spot in ShelfRadar’s beta program for our 30 day challenge! We will drive Rs. 1L in savings within 30 days either through improved availability, pricing, ad or cost optimization.
title:What
[Target word or phrase]
Try ShelfRadar.ai for free
Claim an early spot in ShelfRadar’s beta program for our 30 day challenge! We will drive Rs. 1L in savings within 30 days either through improved availability, pricing, ad or cost optimization.