How teams use propin
How teams use propin
How teams use propin
to drive real sales execution
to drive real sales execution
to drive real sales execution
From bottlers to fintech, see how we help teams prioritize the right leads, optimize routes, and increase conversion in the field.
From bottlers to fintech, see how we help teams prioritize the right leads, optimize routes, and increase conversion in the field.
Case 1: Turn thousands of potential merchants into daily executable routes
CPG / Beverage Bottlers
Context / Problem
Bottlers have massive territory coverage challenges:
Millions of SMBs, but low visibility on which ones matter now
Sales reps visit based on habit, not data
Low conversion from visits → sales
What Propin does
Identifies high-probability merchants using geospatial + behavioral data
Prioritizes daily routes (WhatsApp-ready)
Filters “noise” → only actionable opportunities
Results (real pilot benchmarks)
+20% higher “Lead OK” rate vs benchmark
+68% increase in proposal rate
+77% increase in close rate
~3x lift in Leads → Sales conversion
What this unlocks
→ More sales per rep, without increasing headcount
→ Faster territory expansion with lower CAC
→ Data-driven execution (not dashboards—daily actions)
Case 1: Turn thousands of potential merchants into daily executable routes
Context / Problem
Bottlers have massive territory coverage challenges:
Millions of SMBs, but low visibility on which ones matter now
Sales reps visit based on habit, not data
Low conversion from visits → sales
What Propin does
Identifies high-probability merchants using geospatial + behavioral data
Prioritizes daily routes (WhatsApp-ready)
Filters “noise” → only actionable opportunities
Results (real pilot benchmarks)
+20% higher “Lead OK” rate vs benchmark
+68% increase in proposal rate
+77% increase in close rate
~3x lift in Leads → Sales conversion
What this unlocks
→ More sales per rep, without increasing headcount
→ Faster territory expansion with lower CAC
→ Data-driven execution (not dashboards—daily actions)
CPG / Beverage Bottlers
Case 1: Turn thousands of potential merchants into daily executable routes
Context / Problem
Bottlers have massive territory coverage challenges:
Millions of SMBs, but low visibility on which ones matter now
Sales reps visit based on habit, not data
Low conversion from visits → sales
What Propin does
Identifies high-probability merchants using geospatial + behavioral data
Prioritizes daily routes (WhatsApp-ready)
Filters “noise” → only actionable opportunities
Results (real pilot benchmarks)
+20% higher “Lead OK” rate vs benchmark
+68% increase in proposal rate
+77% increase in close rate
~3x lift in Leads → Sales conversion
What this unlocks
→ More sales per rep, without increasing headcount
→ Faster territory expansion with lower CAC
→ Data-driven execution (not dashboards—daily actions)
CPG / Beverage Bottlers
Case 2: Choose the right locations with real-world behavioral data
Retail & QSR Expansion
Context / Problem
Expansion decisions rely on:
Static demographics
Broker intuition
Limited understanding of who actually moves in the area
What Propin does
Combines mobile movement data + store performance
Benchmarks candidate locations vs top-performing stores
Simulates cannibalization and demand potential
What we’ve done
Mapped competitor networks (Nike, Puma, Skechers, etc.)
Identified high-traffic zones aligned with target customer profiles
Delivered standardized location scoring across countries
Impact
→ Higher hit rate on new store openings
→ Faster expansion decisions
→ Reduced reliance on manual tools (Excel / MapInfo)
Case 2: Choose the right locations with real-world behavioral data
Context / Problem
Expansion decisions rely on:
Static demographics
Broker intuition
Limited understanding of who actually moves in the area
What Propin does
Combines mobile movement data + store performance
Benchmarks candidate locations vs top-performing stores
Simulates cannibalization and demand potential
What we’ve done
Mapped competitor networks (Nike, Puma, Skechers, etc.)
Identified high-traffic zones aligned with target customer profiles
Delivered standardized location scoring across countries
Impact
→ Higher hit rate on new store openings
→ Faster expansion decisions
→ Reduced reliance on manual tools (Excel / MapInfo)
Retail & QSR Expansion
Case 2: Choose the right locations with real-world behavioral data
Context / Problem
Expansion decisions rely on:
Static demographics
Broker intuition
Limited understanding of who actually moves in the area
What Propin does
Combines mobile movement data + store performance
Benchmarks candidate locations vs top-performing stores
Simulates cannibalization and demand potential
What we’ve done
Mapped competitor networks (Nike, Puma, Skechers, etc.)
Identified high-traffic zones aligned with target customer profiles
Delivered standardized location scoring across countries
Impact
→ Higher hit rate on new store openings
→ Faster expansion decisions
→ Reduced reliance on manual tools (Excel / MapInfo)
Retail & QSR Expansion
Case 3: From “visit everything” to “visit what converts”
Traditional Trade / Distributors
Context / Problem
Reps cover territories blindly
No prioritization of stores with real potential
High operational cost per visit
What Propin does
Scores every store in a territory
Identifies whitespace (new opportunities)
Optimizes routes based on conversion probability
Typical Outcome
→ 2x productivity per sales rep
→ Lower cost per visit
→ More structured and scalable sales execution
Key shift
From coverage → to precision selling
Case 3: From “visit everything” to “visit what converts”
Context / Problem
Reps cover territories blindly
No prioritization of stores with real potential
High operational cost per visit
What Propin does
Scores every store in a territory
Identifies whitespace (new opportunities)
Optimizes routes based on conversion probability
Typical Outcome
→ 2x productivity per sales rep
→ Lower cost per visit
→ More structured and scalable sales execution
Key shift
From coverage → to precision selling
Traditional Trade / Distributors
Case 3: From “visit everything” to “visit what converts”
Context / Problem
Reps cover territories blindly
No prioritization of stores with real potential
High operational cost per visit
What Propin does
Scores every store in a territory
Identifies whitespace (new opportunities)
Optimizes routes based on conversion probability
Typical Outcome
→ 2x productivity per sales rep
→ Lower cost per visit
→ More structured and scalable sales execution
Key shift
From coverage → to precision selling
Traditional Trade / Distributors
Case 4: Acquire the right merchants, not just more merchants
Fintech / POS Acquisition
Context / Problem
Huge funnel of SMBs (millions)
Very low signal on who will actually convert
High CAC due to inefficient field sales
What Propin does
Filters high-intent merchants from massive datasets
Prioritizes acquisition routes
Aligns field teams with data-driven targets
Results
86% “Relevant Leads” vs ~70% benchmark
1.7x–3x lift across funnel stages
What this means
→ Same team → more merchants acquired
→ Better unit economics per merchant
-
Case 4: Acquire the right merchants, not just more merchants
Context / Problem
Huge funnel of SMBs (millions)
Very low signal on who will actually convert
High CAC due to inefficient field sales
What Propin does
Filters high-intent merchants from massive datasets
Prioritizes acquisition routes
Aligns field teams with data-driven targets
Results
86% “Relevant Leads” vs ~70% benchmark
1.7x–3x lift across funnel stages
What this means
→ Same team → more merchants acquired
→ Better unit economics per merchant
Fintech / POS Acquisition
-
Case 4: Acquire the right merchants, not just more merchants
Context / Problem
Huge funnel of SMBs (millions)
Very low signal on who will actually convert
High CAC due to inefficient field sales
What Propin does
Filters high-intent merchants from massive datasets
Prioritizes acquisition routes
Aligns field teams with data-driven targets
Results
86% “Relevant Leads” vs ~70% benchmark
1.7x–3x lift across funnel stages
What this means
→ Same team → more merchants acquired
→ Better unit economics per merchant
Fintech / POS Acquisition
-
Case 5: Find high-performing locations before your competitors do
Vending & Route-Based Businesses
Context / Problem
Location selection is manual and slow
Missed opportunities in high-traffic areas
Inefficient routes for operators
What Propin does
Detects high-footfall, high-fit locations (offices, gyms, etc.)
Prioritizes installation opportunities
Optimizes service and sales routes
Impact
→ Faster network expansion
→ Higher revenue per machine
→ Better route efficiency
Case 5: Find high-performing locations before your competitors do
Context / Problem
Location selection is manual and slow
Missed opportunities in high-traffic areas
Inefficient routes for operators
What Propin does
Detects high-footfall, high-fit locations (offices, gyms, etc.)
Prioritizes installation opportunities
Optimizes service and sales routes
Impact
→ Faster network expansion
→ Higher revenue per machine
→ Better route efficiency
Vending & Route-Based Businesses
Case 5: Find high-performing locations before your competitors do
Context / Problem
Location selection is manual and slow
Missed opportunities in high-traffic areas
Inefficient routes for operators
What Propin does
Detects high-footfall, high-fit locations (offices, gyms, etc.)
Prioritizes installation opportunities
Optimizes service and sales routes
Impact
→ Faster network expansion
→ Higher revenue per machine
→ Better route efficiency
Vending & Route-Based Businesses
Case 6: Understand visitor behavior beyond foot traffic
Shopping Malls / Airports
Context / Problem
Limited visibility on who visits, not just how many
Difficulty personalizing tenant mix and experiences
What Propin does
Analyzes visitor origin, behavior, and patterns
Identifies high-value audience segments
Supports tenant mix and commercialization decisions
What this unlocks
→ Better leasing decisions
→ Higher tenant performance
→ More personalized experiences
Case 6: Understand visitor behavior beyond foot traffic
Context / Problem
Limited visibility on who visits, not just how many
Difficulty personalizing tenant mix and experiences
What Propin does
Analyzes visitor origin, behavior, and patterns
Identifies high-value audience segments
Supports tenant mix and commercialization decisions
What this unlocks
→ Better leasing decisions
→ Higher tenant performance
→ More personalized experiences
Shopping Malls / Airports
Case 6: Understand visitor behavior beyond foot traffic
Context / Problem
Limited visibility on who visits, not just how many
Difficulty personalizing tenant mix and experiences
What Propin does
Analyzes visitor origin, behavior, and patterns
Identifies high-value audience segments
Supports tenant mix and commercialization decisions
What this unlocks
→ Better leasing decisions
→ Higher tenant performance
→ More personalized experiences
Shopping Malls / Airports
Give your team a live
Give your team a live
data-driven map
of your market.
data-driven map
of your market.
You already know your customers and your numbers. Let Propin bring the outside world into that picture — so your reps stop guessing, your managers stop firefighting, and your territories grow systematically.
You already know your customers and your numbers. Let Propin bring the outside world into that picture — so your reps stop guessing, your managers stop firefighting, and your territories grow systematically.