The Monday Morning Crisis

A retail executive faces declining revenue.
Watch how Tower transforms chaos into clarity.

Scroll to begin the story
Chapter 1

Revenue Down 15%

Sarah, a retail VP, discovers a troubling trend in her weekly report. Sales are dropping, but she has no idea why.

Traditional BI tools show her what happened, but not why or what to do.

Monthly Revenue
$2.4M
โ†“ 15% vs last month
Chapter 2

Tower Connects the Dots

Within minutes, Tower connects to all data sources and begins analysis.

Tower
๐Ÿ“Š
Sales CRM
๐Ÿ›’
E-commerce
๐Ÿ“ฆ
Inventory
๐Ÿ“ˆ
Analytics
๐Ÿ‘ฅ
HR Data
๐Ÿ’ฐ
Finance
๐Ÿ”
Analyzing patterns...
๐Ÿง 
Identifying correlations...
๐Ÿ’ก
Generating insights...
Chapter 3

AI Thinks Like You Do

Tower's agentic AI doesn't just process dataโ€”it reasons about it.

  • โœ“ Cross-references inventory levels with sales drops
  • โœ“ Correlates staffing changes with regional performance
  • โœ“ Identifies seasonal patterns and anomalies
Chapter 4

Three Types of Intelligence

Tower delivers descriptive, predictive, and prescriptive analyticsโ€”all automatically.

๐Ÿ“Š

Descriptive

What happened?

Root Cause Found

West Coast stores experienced 40% inventory stockouts in key categories during peak season.

40% Stockout Rate
๐Ÿ”ฎ

Predictive

What will happen?

Forecast

If unaddressed, revenue will decline an additional 8% next quarter, impacting $1.8M in sales.

-$1.8M Projected Impact
โšก

Prescriptive

What should we do?

Recommended Actions
  • 1. Increase inventory by 60% for top 10 SKUs
  • 2. Reallocate staff to West Coast stores
  • 3. Launch targeted promotion campaign
Chapter 5

Dashboard Created Automatically

In minutes, not weeks. No BI team required.

Regional Performance
Inventory Status
40%
Top Actions
๐ŸŽฏ Increase inventory
๐Ÿ‘ฅ Reallocate staff
๐Ÿ“ข Launch campaign
Predicted Revenue
+$2.1M
Time to insights:
0min
Chapter 6

From Insight to Action

Sarah clicks "Execute Recommendations" and Tower automatically:

1
Creates purchase orders
For 60% inventory increase in top SKUs
โœ“
2
Notifies store managers
Automated alerts with staffing recommendations
โœ“
3
Launches marketing campaign
Targeted promotions in affected regions
โœ“
4
Schedules follow-up reports
Weekly monitoring and adjustment recommendations
โœ“
โšก Executing Actions...
โœ“ Connected to inventory system
โœ“ Purchase orders created (45 SKUs)
โœ“ Staff notifications sent (12 managers)
โœ“ Campaign launched via marketing platform
โœ“ Monitoring dashboard deployed
Chapter 7

Three Weeks Later

The numbers speak for themselves

๐Ÿ“ˆ
+23%
Revenue Recovery
West Coast stores back to peak performance
โฑ๏ธ
8 min
Time to Insight
vs 6 weeks with traditional BI
๐Ÿ’ฐ
$2.8M
Revenue Saved
Projected annual impact

Revenue Recovery Timeline

Tower Deployed Week 1 Week 4 Week 7

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