How to Do Site Selection Using Alternative Data

Why traditional site selection is no longer enough

Traditionally, retailers chose store locations based on a mix of gut instinct, drive-time maps, and a handful of demographic indicators. But this approach is falling short as consumer behavior fragments across digital and physical channels.

Today, the most effective real estate teams combine alternative data sources to understand how people shop, where their spending is shifting, and which markets still hold room for growth.

Whether you’re a national retailer, a landlord, or a private equity-backed brand building your first fleet of stores, using alternative data can be the difference between entering a high-performing market or opening in one that looks good on paper but under-delivers in reality.

Start with Market Share Trends

Understanding your brand’s market share trajectory is the first step toward smart site selection. Instead of focusing solely on foot traffic or raw visit counts, analyze how much of total category spend your brand is capturing — and how that share is changing relative to competitors.

For example:

• If your market share in Chicago is 3% of total activewear spend and it’s been rising for four consecutive quarters, you may have brand momentum strong enough to justify an additional store.
• Conversely, if a market’s share is flat or declining even as category spend grows, it might indicate saturation, brand fatigue, or underperformance relative to peers.

Market share trends, especially when derived from transaction-level data, offer a clear, quantitative picture of competitive strength that traditional demographic data can’t capture.

Analyze Neighboring Comps

One of the most overlooked aspects of site selection is understanding neighboring comps.

Alternative data allows you to benchmark yourself by:

• Sales mix (e.g., what % of total spend in the area goes to restaurants, apparel, electronics, etc.)
• Category overlap (are your core customers already frequenting nearby complementary or competitive retailers?)
• Consumer migration patterns (how far are customers traveling to shop in this zone versus others?)

A cluster with thriving experiential and food tenants, for example, can create a gravitational pull that boosts cross-shopping and dwell time; corridor dominated by discount chains might attract a completely different psychographic profile.

Demographics and Psychographics

Demographics tell you who people are. Psychographics tell you why they buy.

Using segmentation systems and audience creation tools, you can understand the lifestyle orientation of a trade area, whether it’s defined by “Young Professionals” chasing status brands or “Middleburg Managers” prioritizing value and convenience.

This kind of profiling goes deeper than income and age. It allows you to match your brand positioning with the personality of a neighborhood. A boutique fitness brand, for instance, might discover that a suburb with median income of $120K still under-indexes for their target segments.

Integrating psychographic insight into your site selection process helps refine where you open and how you think about merchandise.

Online vs. In-Store Spend

Understanding what percentage of spend in your category happens online vs. in-store is crucial for evaluating brick-and-mortar opportunity.

In some categories, like electronics or specialty apparel, online share can exceed 50% in certain metros, meaning physical retail must serve a discovery or experience function. In others, like home furnishings or luxury apparel, the in-store channel still dominates, making local presence critical for capturing market share.

Transaction-based datasets can break this down by zip code or DMA, showing where customers still prefer to buy in person.

If your goal is omnichannel growth, the sweet spot is often a market where in-store share remains high but e-commerce penetration is rising. That’s a signal of healthy retail engagement, and an opportunity to build stores that complement, rather than cannibalize, digital sales.

Category Trends

No two markets evolve the same way. Category-level spend growth can vary dramatically by region, and understanding those nuances helps prioritize where to expand next.

Alternative data can show you, for example:

• Health & wellness spend rising 12% year-over-year in Austin while flatlining in Phoenix
• Premium dining spend up 8% in the suburbs of Atlanta but declining downtown
• A rapid shift from traditional apparel to athleisure in secondary Midwest markets

These insights reveal areas where consumer behavior is actively moving toward your brand’s category. Overlaying this trend data with psychographics and market share analysis gives you a 3D view of opportunity: where people are spending, what they’re buying, and whether they align with your core customer.

The Future of Site Selection

Foot traffic still matters, but it’s no longer enough, often missing the full picture. Device panels undercount visitors, misclassify venues, and struggle to connect physical visits to actual spend.

That’s why retailers are turning to transaction data to validate their decisions. Sales data shows realized. intent not just footfall. The most sophisticated real estate teams now blend the two and they enable more precise forecasting and stronger internal alignment when advocating for new sites.

In the next wave of retail real estate, stories will be backed by verified consumer behavior including real spending, real market share, and real alignment between shopper and site.

When every brand is chasing the same limited retail whitespace, those with better intel are going to avoid mis-steps and win the right deals.