Why are retailers using human mobility data?

Retailers are utilizing human mobility data to make informed decisions about store locations, operations, and staying ahead of their competitors. Here's how mobility insights are transforming the industry:

• Boosting Store Performance: Foot traffic data helps optimize staffing schedules and store layouts.
• Improving Market Analysis: Identify areas for expansion and avoid market saturation.
• Understanding Customer Behavior: Track visit frequency, duration, and shopping patterns.

Key metrics retailers should focus on:

1. Customer origins: 63% of shoppers choose stores close to home or work.
2. Visit frequency: Tracks loyalty and repeat visits.
3. Traffic flow: Identifies peak shopping hours and seasonal trends.
4. Customer overlap: Reveals where shoppers also spend money, helping refine competitive strategies.

How mobility data impacts retail:

• Retailers using location analytics see up to a 34% improvement in location strategy returns.
• Seasonal and event trends: Events like holidays or local activities can drive foot traffic spikes.
• Competitive insights: Heatmaps and customer movement tracking reveal competitor advantages.

Mobility data is reshaping retail by offering actionable insights that improve customer experience, optimize operations, and increase sales. With tools like geospatial analytics, businesses can adapt to shifting consumer behaviors and maintain a competitive edge.

Core mobility metrics for retail

Data-driven companies are 23 times more likely to attract new customers and six times more likely to keep them. How? By using mobility metrics to shape store operations, marketing strategies, and competitive positioning. These metrics lay the foundation for understanding the dynamics of retail competition.

Customer origin and visit Patterns

63% of shoppers choose stores based on proximity to their home or workplace. That makes understanding where your customers come from a game-changer for store placement and marketing. Our footfall data captures customer movement trends, helping businesses identify high-value areas. Here's how specific metrics can drive decisions:

For example, in Portland, summer 2024 events like Coraline's Curious Cat Trail increased weekend foot traffic by 11-14%. This type of data can help retailers time promotions to maximize impact.

But understanding customer origins is just the start. Analyzing where your customers overlap with competitors can unlock even deeper insights.

Customer overlap analysis

Customer overlap analysis reveals where your shoppers are also spending their money.

A study of 27 stores found that factors like product assortment and the distance between stores significantly influence shared customer bases. Knowing this helps retailers fine-tune their strategies to outpace competitors.

Once you’ve mapped customer overlap, digging into when and how long customers shop can further refine your approach.

Peak hours and visit duration

Knowing when customers visit and how long they stay can dramatically improve store operations. Retailers who excel in workforce optimization have seen results like a 16% boost in in-store conversions, a 12% rise in customer satisfaction, and a 9% increase in employee on-floor time.

Here’s how these insights can be applied:

Retailers leveraging such analytics have reported a 15% increase in sales. By focusing on these core mobility metrics, businesses can make smarter, data-driven decisions that directly enhance their bottom line.

Time-based movement patterns

Understanding how customer movement varies over time can give businesses a serious edge. In fact, 89% of marketers using location data report increased sales.

Daily and weekly traffic flows

Retailers are now combining online and offline analytics to uncover patterns that help them fine-tune their weekly operations. By analyzing traffic flows across different timeframes, they can make smarter staffing and operational decisions.

Here’s a breakdown of how traffic patterns shift throughout the day and week, and what strategies work best:

With shopping-center vacancy rates at their lowest in 20 years — just 5.4% — it’s clear that in-store shopping remains vital. These daily and weekly trends lay the groundwork for understanding larger seasonal and event-driven shifts.

Seasonal and special event impact

Beyond daily and weekly patterns, seasonal trends and special events play a huge role in shaping customer behavior.

Here are some key insights:

• Holiday Season Surges
  Retail sales spike during the holidays, with specific categories seeing predictable boosts. For example, jewelry and flower shops thrive in February for Valentine’s Day, while tech stores experience a rush in November during Black Friday.
• Special Event Influence
  Local events at malls can significantly drive both sales and customer engagement.
• Weather-Driven Trends
  Retailers that combine weather forecasts with visit data can better predict traffic patterns. One major chain noticed foot traffic peaked every 28–30 days, with promotional campaigns driving delayed spikes, typically peaking three days after launch. This insight allowed them to adjust staffing levels, cutting wait times and improving service.

To make the most of these seasonal patterns, retailers can:

• Plan inventory orders to match customer interest in seasonal merchandise.
• Use data analysis to uncover meaningful trends in foot traffic.
• Rely on historical data to anticipate future seasonal peaks.

As retail continues to evolve, adopting unified commerce strategies becomes essential for gaining a full understanding of the customer journey.

Competition Analysis Through Movement Data

Tracking how customers move between stores offers retailers valuable insights for planning and decision-making. By analyzing these patterns, businesses can uncover what gives competitors their edge. With the location analytics market projected to grow at an annual rate of 16.1% through 2030, using mobility data has become a key strategy for staying competitive.

Customer Movement Visualization

Heatmaps are a popular tool for retailers to visualize high-traffic areas and adjust their strategies on the fly. These visualizations highlight customer preferences and how they relate to competitor locations.

Retailers using these tools report better product visibility and increased sales. For example, Sephora used heat-mapping technology to study how customers interact with products. This led to noticeable improvements in both product visibility and sales.

These insights don’t just stop at individual stores. They also help businesses evaluate market density and spot opportunities for expansion.

Market density assessment

Foot traffic data plays a crucial role in analyzing market saturation and planning expansions. By mapping customer movement, retailers can make smarter decisions about where to grow next.

Here’s how some major brands are using mobility analytics:

• Walmart's Strategic ApproachWalmart studies customer traffic patterns to fine-tune store layouts and product placements, resulting in higher sales and improved customer satisfaction.
• Amazon Go's InnovationAmazon Go leverages heat mapping to enhance the shopping experience by improving customer flow and cutting down wait times.
• IKEA's Customer Flow AnalysisIKEA uses detailed movement data to design store layouts and product displays that align with customer behavior.

Price impact on store traffic

By combining movement data with pricing strategies, retailers can adapt quickly to shifts in the competitive landscape. Pricing has a direct influence on customer foot traffic, and smart retailers use data to stay ahead by:

• Monitoring competitor openings and adjusting promotions accordingly
• Timing promotions to align with peak traffic periods
• Refining pricing strategies based on neighborhood trends

For instance, a grocery chain tracked the opening of a nearby competitor. Using customer flow data, they launched targeted loyalty programs and local promotions to retain their shoppers. This kind of data-driven approach boosts both foot traffic and revenue.

Using mobility data effectively

Mobility data is reshaping how retailers make decisions. Businesses that embrace a data-driven approach see impressive results. When used strategically, mobility insights can deliver real, measurable improvements in critical areas:

Moving Forward with Geospatial Analysis

To stay ahead, retailers must refine their geospatial analysis capabilities. Echo Analytics transforms raw mobility data into actionable strategies, paving the way for smarter decisions.

The future of retail lies in sophisticated mobility analysis, and retailers have a golden opportunity to tailor their strategies. With location intelligence, businesses can ensure their strategies remain flexible and responsive to ever-changing customer behaviors.

FAQs

How can retailers use mobility data to choose the best locations for their stores?

Retailers can use mobility data to make better decisions about where to open new stores by analyzing foot traffic patterns, customer demographics, and the presence of nearby competitors. This data helps identify high-traffic areas and neighborhoods with strong potential, ensuring new stores are conveniently located and highly visible.

For instance, understanding where customers live, work, and shop provides valuable clues about locations that fit seamlessly into their daily routines. Mobility data can also drive targeted marketing efforts and refine inventory planning by predicting consumer demand based on real-time shopping habits. With these insights, retailers can streamline operations and deliver a more convenient and enjoyable shopping experience for their customers.

What metrics should retailers track to improve customer experience and boost sales?

To create a better shopping experience and boost sales, retailers should keep an eye on a few key metrics that offer practical insights:

• Customer Satisfaction Score (CSAT): This measures how happy customers are with their experience, highlighting areas that might need improvement.
• Net Promoter Score (NPS): A great way to gauge customer loyalty and see how likely they are to recommend the brand to others.
• Average Order Value (AOV): Tracks the average amount customers spend per purchase, shedding light on buying habits.

By keeping track of these metrics, retailers can get a clearer picture of what their customers want, fine-tune their strategies, and make smarter decisions that help them stay ahead in a competitive market.

How can analyzing customer overlap help retailers stay ahead in a competitive market?

Customer overlap analysis gives retailers a clear picture of the shared customer base between their business and competitors. With this knowledge, retailers can fine-tune their marketing efforts, tweak product selections, and design campaigns aimed at attracting shoppers who are already drawn to similar products.

It also highlights areas where competitors may be falling short, opening the door for retailers to fill those gaps and appeal to untapped customer groups. Using these insights, businesses can enhance customer connections, drive sales, and secure a stronger foothold in the market.