AI-Powered WhatsApp Sales Assistant
Budget: ₹12,500 – ₹37,500 INR
SHREE SHIVAM – AI SALES incharge
Functional Requirement Document (Phase 1)
Objective
Create an AI-powered sales coaching assistant that monitors designated WhatsApp DSR groups, analyzes daily sales reports, and automatically posts personalized coaching, recognition, and leaderboard messages.
Users
Sales Executives / FCs
Store Managers
Brand Managers
Directors
Input Source
WhatsApp Groups
Example Groups:
IZOD DSR Group
UCB DSR Group
US Polo DSR Group
Sales staff continue posting DSRs in the current format.
No change in employee reporting behavior.
System Workflow
Step 1
Monitor selected WhatsApp groups continuously.
Step 2
Identify DSR messages.
Example:
Store Name: Raipur
FC Name: Mukesh
Today's Sale: 58184
MTD Sale: 445406
Target: 400000
Step 3
Extract and structure the data.
Store = Raipur
FC = Mukesh
Daily Sale = 58184
MTD Sale = 445406
Target = 400000
AI Analysis Engine
System should calculate:
Daily Metrics
Daily sales
Quantity sold
MTD sales
Target achievement %
Stock productivity
Classification
A+ Performer
A Performer
B Performer
C Performer
Based on configurable business rules.
Automatic Coaching Comments
For every valid DSR:
Generate a personalized response.
Examples:
High Performer:
"Jai Shree Krishna Mukesh ji. Excellent month closure. You have exceeded your target and demonstrated strong execution. Keep this momentum going."
Medium Performer:
"Jai Shree Krishna. Good effort. Focus on improving customer conversion and increasing average bill value."
Low Performer:
"Jai Shree Krishna. Significant opportunity remains. Tomorrow let's focus on trials, customer engagement and complete-look selling."
Comments must be:
Unique
Non-repetitive
Positive but performance-oriented
Aligned with Shree Shivam culture
Daily Leaderboard
At configurable time (e.g. 10 PM)
Generate:
1Store of the Day
2 Runner Up
3 Best FC
4 Most Improved
5Tomorrow Focus
Post automatically in the group.
Recognition Triggers
Automatic recognition messages:
Target Achieved
When MTD >= Target
3 Consecutive Strong Days
Most Improved Week
Highest Daily Sale
Highest Quantity Sold
Director Summary
Every morning:
Send summary to designated management WhatsApp group.
Include:
Store Ranking
Brand Ranking
Top Performers
Stores Requiring Attention
Target Achievement %
Data Storage
Store all extracted DSR data in:
Google Sheets (Phase 1)
Database (Phase 2)
Historical data must be retained.
Admin Controls
Admin should be able to:
Add/remove groups
Modify coaching rules
Modify leaderboard logic
Enable/disable auto replies
Set posting times
Technology Preference
WhatsApp Monitoring
OpenAI API
Google Sheets
Make.com or equivalent automation platform
Cloud hosting
Success Criteria
No change required in current DSR process.
Automatic AI response within 1–3 minutes of DSR posting.
Daily leaderboard generated automatically.
Director summary generated automatically.
Minimum 95% DSR recognition accuracy.
End of Phase 1 FRD.
One important addition
Ask the developer to build "humanized randomness."
If Mukesh posts 30 DSRs in a month, the system should not keep saying:
"Excellent work, keep it up."
Instead it should rotate between:
Recognition
Coaching
Challenge
Question
Appreciation
Comparative insights
That single feature will determine whether employees see it as a real coach or just another bot.
Functional Requirement Document (Phase 1)
Objective
Create an AI-powered sales coaching assistant that monitors designated WhatsApp DSR groups, analyzes daily sales reports, and automatically posts personalized coaching, recognition, and leaderboard messages.
Users
Sales Executives / FCs
Store Managers
Brand Managers
Directors
Input Source
WhatsApp Groups
Example Groups:
IZOD DSR Group
UCB DSR Group
US Polo DSR Group
Sales staff continue posting DSRs in the current format.
No change in employee reporting behavior.
System Workflow
Step 1
Monitor selected WhatsApp groups continuously.
Step 2
Identify DSR messages.
Example:
Store Name: Raipur
FC Name: Mukesh
Today's Sale: 58184
MTD Sale: 445406
Target: 400000
Step 3
Extract and structure the data.
Store = Raipur
FC = Mukesh
Daily Sale = 58184
MTD Sale = 445406
Target = 400000
AI Analysis Engine
System should calculate:
Daily Metrics
Daily sales
Quantity sold
MTD sales
Target achievement %
Stock productivity
Classification
A+ Performer
A Performer
B Performer
C Performer
Based on configurable business rules.
Automatic Coaching Comments
For every valid DSR:
Generate a personalized response.
Examples:
High Performer:
"Jai Shree Krishna Mukesh ji. Excellent month closure. You have exceeded your target and demonstrated strong execution. Keep this momentum going."
Medium Performer:
"Jai Shree Krishna. Good effort. Focus on improving customer conversion and increasing average bill value."
Low Performer:
"Jai Shree Krishna. Significant opportunity remains. Tomorrow let's focus on trials, customer engagement and complete-look selling."
Comments must be:
Unique
Non-repetitive
Positive but performance-oriented
Aligned with Shree Shivam culture
Daily Leaderboard
At configurable time (e.g. 10 PM)
Generate:
1Store of the Day
2 Runner Up
3 Best FC
4 Most Improved
5Tomorrow Focus
Post automatically in the group.
Recognition Triggers
Automatic recognition messages:
Target Achieved
When MTD >= Target
3 Consecutive Strong Days
Most Improved Week
Highest Daily Sale
Highest Quantity Sold
Director Summary
Every morning:
Send summary to designated management WhatsApp group.
Include:
Store Ranking
Brand Ranking
Top Performers
Stores Requiring Attention
Target Achievement %
Data Storage
Store all extracted DSR data in:
Google Sheets (Phase 1)
Database (Phase 2)
Historical data must be retained.
Admin Controls
Admin should be able to:
Add/remove groups
Modify coaching rules
Modify leaderboard logic
Enable/disable auto replies
Set posting times
Technology Preference
WhatsApp Monitoring
OpenAI API
Google Sheets
Make.com or equivalent automation platform
Cloud hosting
Success Criteria
No change required in current DSR process.
Automatic AI response within 1–3 minutes of DSR posting.
Daily leaderboard generated automatically.
Director summary generated automatically.
Minimum 95% DSR recognition accuracy.
End of Phase 1 FRD.
One important addition
Ask the developer to build "humanized randomness."
If Mukesh posts 30 DSRs in a month, the system should not keep saying:
"Excellent work, keep it up."
Instead it should rotate between:
Recognition
Coaching
Challenge
Question
Appreciation
Comparative insights
That single feature will determine whether employees see it as a real coach or just another bot.
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