Geographic Market Insights

What if you could identify, at a ZIP code level, exactly where your best customers live and where your next "best markets" are emerging? That’s what we set out to do this quarter with a geospatial analysis 🌎 for one of our clients. Part 1: Geo-Spatial Analysis (partner KnoWhere Analytics) Part 2: Incrementality Testing (partner Stella | Growth Intelligence) 𝗧𝗵𝗲 𝗴𝗼𝗮𝗹 𝘄𝗮𝘀 𝘀𝗶𝗺𝗽𝗹𝗲: 👉 Identify ZIP codes across the US with 𝙪𝙣𝙧𝙚𝙖𝙡𝙞𝙯𝙚𝙙 𝙨𝙖𝙡𝙚𝙨 𝙤𝙥𝙥𝙤𝙧𝙩𝙪𝙣𝙞𝙩𝙮 👉 Build a smarter pool of high-potential customers to make Q4 as impactful as possible Here is how it works ⬇️ 𝗜𝗻𝗽𝘂𝘁𝘀: ▪️ 2-3 years of customer data (Shopify, BigCommerce, etc) ▪️ 2020 & 2023 Census data (population, income, demographic data) ▪️ Custom Development Index derived from federal imagery and national atlas datasets 𝗢𝘂𝘁𝗽𝘂𝘁𝘀: 🔵 National coverage, ZIP code-level scoring system broken into 3 groups & 3 tiers (e.g. Strong Tier 1, As Expected, Opportunity Tier 2) 🔵 General Targeting Score (GTS) - a full ranking of all zip codes within the nation and propensity for sales 🔵 Full range of high resolution maps and clickable KML files for Google Earth to aid visualization 🌎 (see image attached) 🔵 Key Audience (sales drivers) variable importance list 𝗧𝘂𝗿𝗻𝗶𝗻𝗴 𝗗𝗮𝘁𝗮 𝗜𝗻𝘁𝗼 𝗗𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀: Once the model runs, it tells you which variables are most correlated to your customers - because this is independent of surveys, ad platform data, and other information, the result is an independent validation of current understanding of the audience, and provides unique insight into consumer qualities. Maybe it’s ZIPs with more renters, and maybe it’s zips with a certain range of renters to buyers. Maybe it’s higher education levels or higher income clusters. The result is the ability to see your customer DNA, geographically mapped across the U.S. 𝗛𝗼𝘄 𝗪𝗲 𝗨𝘀𝗲𝗱 𝗜𝘁: That’s where things get fun. For this client, we identified 1.6K ZIP codes classified as “Opportunity” areas. Those zip codes were match markets to our top-performing ZIPs, but they were underindexing with sales. Next, we took those 1600 zip codes and ran an incrementality test across Meta and YouTube. Then we used Stella to measure lift. There are many tests for this model and data which can be tested and applied: ▪️Use the Opportunity ZIPs for out-of-home or direct mail testing ▪️ Double down on your strongest ZIPs for customer acquisition and retention during promo 𝗔 𝗻𝗼𝘁𝗲 𝗼𝗻 𝘁𝗵𝗲 𝗱𝗮𝘁𝗮 𝗶𝘁𝘀𝗲𝗹𝗳: Our end goal was to find 𝗼𝗽𝗽𝗼𝗿𝘁𝘂𝗻𝗶𝘁𝘆 𝗺𝗮𝗿𝗸𝗲𝘁𝘀 to better direct ad spend. And while we’re always trailing real data, we think because demographic structures shift slowly; relative differences between ZIPs remain meaningful. If you’re interested in Google Ads, or about running one of these analyses, feel free to connect with me. Banfana, Stella | Growth Intelligence

This visualization offers a powerful snapshot of average monthly salaries across the world in 2025 and it reveals far more than simple income rankings. At first glance, the familiar narrative appears intact: global financial hubs and advanced economies dominate the upper end of the wage spectrum. Cities in North America, Western Europe and parts of Asia continue to command the highest nominal pay levels. However, the real value of this graphic lies in what sits beneath the headline numbers. One of the most striking insights is the disconnect between salary levels and lived prosperity. High wages in cities such as New York, San Francisco or London are often offset by extreme housing costs, healthcare expenses, also taxation. In contrast, several emerging or secondary markets show more modest salaries but deliver stronger purchasing power, higher savings potential, improving quality of life. Income, in isolation, is an incomplete measure of economic wellbeing. The visualization also highlights structural shifts since 2020. Certain cities have experienced significant cumulative wage growth over the past five years, while others have stagnated or declined in real terms. These movements reflect deeper forces: post-pandemic labor rebalancing, remote work adoption, demographic pressures and divergent monetary policies. Salary growth is no longer guaranteed by geography alone. From a talent perspective, this has major implications. Employers competing globally must recognize that compensation strategies anchored solely to „top-tier” cities may no longer be optimal. Meanwhile, professionals are increasingly evaluating opportunities through a broader lens - factoring in cost of living, flexibility, taxation, and long-term stability rather than headline pay. Another notable takeaway is the increasing fragmentation of the global labor market. The gap between the highest- and lowest-paying cities remains substantial, but mobility (both physical and digital) is reshaping how value is created and captured. Skills, not location, are becoming the primary currency, even if location still influences outcomes. Ultimately, this graphic underscores a critical truth: salary data is most meaningful when viewed in context. Policymakers, business leaders, and individuals alike must move beyond surface-level comparisons and focus on sustainability, affordability …and real economic opportunity. The global workforce is not just getting paid differently, it is being valued differently. Understanding where those shifts are happening is essential for anyone making decisions about talent, investment or career direction in the years ahead. Graphic by Visual Capitalist

🎯 The Power of Geo-Targeting in Search Arbitrage Success 🌎💰 Search arbitrage is all about driving paid traffic at a lower cost than the revenue it generates. But here’s a game-changer: geo-targeting. Not all locations perform the same. A $0.10 CPC in one state could be $1.50 in another, and conversion rates can be even more unpredictable. If you’re running arbitrage campaigns without a geo-specific approach, you’re leaving money on the table. 📍 Why the U.S. Market is Different? The U.S. is a high-value but competitive market. Advertisers bid aggressively, and user behavior varies state by state. A campaign that thrives in California might burn cash in Texas. 🔹 USA = High Ad Costs, High Monetization Potential 🔹 Other Countries = Lower Ad Costs, Lower Monetization But even within the U.S., not all states are equal. This is where state-by-state targeting comes in. ⚠️ How Often Should You Change Geo-Targeting in the U.S.? On Facebook (Meta Ads), the worst mistake is running the same geo-targeting for too long without optimizing. 📊 The rule of thumb? Rotate and test every 2-5-10 days. 🚀 Pro Tip: If CTR or conversions drop, pause low-performing states and test new ones. 🌎 Best Niches & State-Specific Insights Different states have different user behaviors, incomes, and ad costs. Some niches explode in specific regions while failing elsewhere. ✅ California – Tech, Solar Energy, Luxury Real Estate ➡ High-income users, but expensive clicks. Great for high-ticket offers like EVs, SaaS, or premium real estate leads. ✅ Washington – Eco-Friendly Products, Software, Finance ➡ Strong tech presence (Seattle), eco-conscious audience. Good for fintech, green energy, and investment niches. ✅ Texas – Home Improvement, DIY, Insurance ➡ Huge demand for roofing, HVAC, and auto insurance. Lower ad costs than CA, but massive scale potential. ✅ Florida – Retirement, Healthcare, Travel ➡ Older population. Great for Medicare ads, real estate, and travel offers. ✅ New York – Luxury, Finance, High-Ticket Services ➡ Expensive but profitable for B2B, legal, and wealth management niches. 🔥 Final Takeaway: Let the Data Guide You Don’t stick to one state blindly. Let CPC, conversion rate, and ad revenue dictate your next move. 💡 Actionable Steps: ✅ Start broad (test multiple states). ✅ Pause underperforming regions after 5-10 days. ✅ Scale in states with low CPC & high conversions. ✅ Always A/B test state-specific ad creatives. Geo-targeting isn’t just a setting, it’s a scaling strategy. If you’re still treating all U.S. traffic the same, it’s time to rethink your approach. 🚀 Have you experimented with geo-targeting in arbitrage? Drop your insights below! 👇 #SearchArbitrage #DigitalMarketing #FacebookAds #GeoTargeting #GrowthHacking #AffiliateMarketing #AdOptimization

It’s clear—tons of brands are diving into OOH for the first time, and I get it: it’s not the easiest medium to figure out. It's complicated. It's fragmented. Every week, I get questions from marketers asking where to start, how to start, and most importantly, how to choose the right market. Choosing the right locations can feel overwhelming, but it doesn’t have to be. With the right data, you can make informed decisions that drive real impact. Here’s how to do it: First-Party Data: Tap Into Your Own Insights: *Shipping Addresses: Start with your top customers. Where are your biggest orders coming from? These regions are your prime candidates for OOH. *CRM Data: Map out where your repeat buyers are concentrated. Loyal customers are already brand advocates—you want them seeing and sharing your campaign. *Loyalty/Subscription Data: If your recurring revenue is strong in cities like Denver or Portland, focus your efforts there to amplify your brand presence. Social Engagement & Sentiment: *Where is your brand already gaining traction? Analyze social media data to identify areas with high engagement or organic mentions. These are often strong candidates for market expansion. *Geotagged posts can also show you where customers are naturally talking about your brand—leverage those locations for your campaign. Mobile Ad ID (MAID) Data: Track Audience Movement: *Use anonymized MAID data to map where your target customers live, work, and play. This data lets you visualize commuter patterns, weekend habits, and hotspots where your audience is most active. *For example, if your audience commutes from the suburbs into downtown, prioritize placements along major commuter routes or near transit hubs. Competitor Insights: *Research where similar brands are running their OOH campaigns. If they’re heavily focused on one region, ask yourself why. Are you missing an opportunity? *Competitor analysis can also help you avoid oversaturated markets and find untapped areas where your audience is underserved. By combining these layers strategically, you’re not just placing ads—you’re creating a campaign that connects with your audience in the moments that matter most.

Here's a surprising reality: while a significant majority, around 25%, of organizational data possesses a geospatial element, it's estimated that less than 2% of businesses are truly capitalizing on its potential for deeper understanding. 🤯 Ever feel like you're navigating your business decisions with a blurry map? 🗺️ You're not alone in dealing with the challenge of location data. 𝐓𝐡𝐞 𝐫𝐞𝐚𝐥 𝐩𝐫𝐨𝐛𝐥𝐞𝐦: 👉 The core issue lies in the complexities often associated with harnessing location data. For many organizations, extracting meaningful insights from geographically referenced information can be a significant hurdle. 👉 Siloed systems, data format inconsistencies, and the sheer scale of geospatial datasets often make comprehensive analysis a time-consuming and resource-intensive process. This can prevent businesses from effectively understanding spatial relationships in customer behavior, logistical efficiencies, or risk distributions. 😫 𝐓𝐡𝐞 𝐬𝐨𝐥𝐮𝐭𝐢𝐨𝐧: However, progress is being made in making this valuable data more accessible and actionable. A recent blog post from Google Cloud highlights how CNA, a prominent insurance provider, is addressing this challenge by leveraging BigQuery for its geospatial analytics needs. 🚀 By centralizing their diverse location data within BigQuery and utilizing its specialized geospatial capabilities, CNA has been able to streamline complex analyses and gain new perspectives. This allows them to visualize geographical patterns in risk, optimize resource allocation based on location intelligence, and develop a more nuanced understanding of their customers through a spatial lens – all within a scalable and efficient data environment. ✨ 𝐖𝐡𝐚𝐭 𝐝𝐨𝐞𝐬 𝐭𝐡𝐢𝐬 𝐭𝐫𝐞𝐧𝐝 𝐦𝐞𝐚𝐧 𝐟𝐨𝐫 𝐨𝐫𝐠𝐚𝐧𝐢𝐳𝐚𝐭𝐢𝐨𝐧𝐬 𝐢𝐧 𝐠𝐞𝐧𝐞𝐫𝐚𝐥? 𝐓𝐡𝐞 𝐩𝐨𝐭𝐞𝐧𝐭𝐢𝐚𝐥 𝐛𝐞𝐧𝐞𝐟𝐢𝐭𝐬 𝐚𝐫𝐞 𝐬𝐮𝐛𝐬𝐭𝐚𝐧𝐭𝐢𝐚𝐥: 👉 More Informed Decision-Making: Accessing location-aware insights can lead to more strategic and operationally sound choices. 🧠 👉 Identification of Opportunities: Uncovering previously unseen market segments and tailoring offerings based on geographic context can unlock new potential. 💰 👉 Deeper Customer Understanding: Gaining insights into customer behavior, preferences, and needs based on their location can lead to better engagement. 📍 👉 Increased Responsiveness: The ability to quickly analyze spatial patterns allows for more agile responses to changing conditions. 💨 Ultimately, the evolution of data warehousing platforms to seamlessly integrate advanced geospatial analytics represents a significant step forward. It moves location intelligence from a specialized domain to a more accessible and integral part of organizational analysis. Follow Omkar Sawant for more. #GeospatialAnalysis #Data #Insights #Cloud #Analytics #Trends #BusinessIntelligence

Closed a deal in the US in 3 months. Same deal in Europe? 9 months. Asia? 14 months with relationship dinners first. Geographic sales strategies aren't optional - they're existential. What closes deals in New York kills pipeline in Tokyo. Regional Sales Execution Breakdown: 🇺🇸 USA: Speed-Driven Fast decisions, single owner 3-6 month cycles Tools: Salesforce, ZoomInfo 🇪🇺 Europe: Consensus-Oriented Committee-driven buying 6-12 month cycles (30-50% longer) Tools: HubSpot, Cognism 🌏 Asia: Relationship-Led Hierarchy approvals Slow start, fast close after trust Tools: Zoho, QCC, Leadzen.ai Geographic execution requires strategic alignment with regional buying behaviors, not harder work. Where does your team see geographic friction? Share insights below 👇

A recent report from BNY Mellon delves into key insights across major markets and geographies: (1) Global Growth: The US displays signs of slowing growth, yet remains resilient compared to Europe and China, which encounter more challenges. (2) Inflation Trends: While there is a gradual moderation overall, persistent services inflation prompts central banks like the Fed and ECB to maintain cautious policies, potentially delaying anticipated cuts. (3) Equities: US equities continue to exhibit strength, with emerging markets offering selective investment opportunities. (4) Fixed Income: Bonds, particularly investment grade and short duration ones, become more appealing due to higher yields. (5) Commodities: Energy markets experience volatility driven by supply constraints and geopolitical risks. (6) Currencies: The dollar maintains its strength driven by rate differentials, while emerging market currencies face ongoing pressure. For more detailed insights, refer to the attached document.

At Gallup Pakistan Digital Analytics we have created GIS map of businesses in Pakistan comibining various data sources. Spatial analysis of business distribution is not just a visualization exercise—it reveals where opportunities lie. By identifying clusters of commercial activity as well as areas with limited business presence, we can highlight: Underserved Communities: Pockets of population where residents lack convenient access to shops, service providers, and small enterprises. Growth Potential: Locations with strong demand but fewer businesses—a clear signal for entrepreneurs to step in. Urban Planning Insights: Authorities can better plan infrastructure (roads, utilities, markets) to support balanced economic growth. Competitive Advantage: Business owners can evaluate saturation vs. gaps, guiding smarter decisions about where to expand. More can be found here : https://lnkd.in/dveirH6B

Amazon DSP just got a major upgrade — and it’s all about finding where your next customers are🚀 At Nashville unBoxed, Amazon Ads dove into Geographic Insights & Activation (GIA) — a new DSP feature designed to help advertisers uncover and activate growth in under-penetrated markets. Here’s a look at the key core concepts… 1️⃣ Find Untapped Regions – GIA highlights areas where category demand is strong but your brand share is low, using Amazon’s first-party retail signals. This can be activated through AMC! 2️⃣ Act Fast in DSP – You can apply geo-based bid adjustments directly in the Amazon DSP console — no heavy setup, just smarter spend. 3️⃣ Deeper Insight with AMC – Integrate GIA with Amazon Marketing Cloud to blend sales data, audience insights, and performance by region. 4️⃣ Simplified Optimization – GIA surfaces actionable geographic retail signals (via Amazon’s Sales Index) and makes local activation frictionless. 5️⃣ New-to-Brand Growth – The goal is simple: expand into high-potential geos, boost new-to-brand customers, and drive incremental sales efficiently. 6️⃣Creative efficiency - you can then use these locations to create ad specific headlines for each region through REC. No heavy overhaul , just plug and put and watch your ad adapt based on customer location! With geographic data and DSP activation finally connected, advertisers can move beyond the baseline geo targeting available in the current UI and target where the next wave of growth lives. #unboxed #amazonunboxed #amazon #amazonads #dsp #amazondsp

Supply Chain KPI Deep Dive #5: Geographic Performance Analysis   #Formula: SUMIFS([Total Sales Value], [Location], Location Name) #Revenue Distribution Insights:   Top Performers: • Kolkata: $842K (28.88%) - Market leader • Chennai: $725K (24.86%) - Strong growth • Mumbai: $585K (20.07%) - Metro market   Key Observations: • Top 3 locations = 73.8% of total revenue • Bangalore (9.69%) = expansion opportunity • Delhi (16.50%) = moderate performance Focus on leveraging geographic performance data to tailor your supply chain strategy by location. Prioritize resources and marketing efforts in top-performing markets like Kolkata and Chennai, while identifying growth opportunities in developing regions like Bangalore. Regularly monitor revenue distribution across locations to balance expansion and operational efficiency effectively.