pass_by’s Enhanced Predictive Model Brings Industry-Leading Accuracy to Future Foot Traffic

Key Takeaways:

  • For the first time in the industry, pass_by has developed a proprietary AI model that can predict foot traffic with accuracy levels that match historical measurements.
  • The new AI model empowers retailers to make informed decisions based on reliable data, enhancing strategic planning and day-to-day operations.

The journey

Accurate foot traffic data is crucial for retailers to make informed operational decisions in today’s fast-paced retail environment. However, traditional foot traffic solutions have often relied heavily on location data, leading to noisy signals, siloed measurements, and accuracy issues. As a result, retailers have found it challenging to trust the data for important decisions, limiting its usefulness across various teams within their organizations.

Recognizing these challenges, pass_by introduced ground truth verified foot traffic data that integrates seamlessly with retailers’ existing in-store hardware sensors. This advancement provided a more reliable and comprehensive picture of customer behavior, addressing some of the limitations of legacy foot traffic solutions.

Retailers have been using foot traffic data for years, but the accuracy issues stemming from legacy providers have been a persistent problem. The feedback pass_by often heard from retailers is that it’s difficult to trust this data for important decisions, limiting how many teams within the retailers can benefit from it.

While ground truth verified foot traffic data was a significant step forward, the predictive data still left much to be desired.

Why Predictive?

Retailers need accurate predictive foot traffic data to plan effectively, but until now, there has been a discrepancy between the accuracy of the predictive data and the historical ground truth data.

Today, pass_by is addressing this issue with the release of its enhanced predictive modeling. This improved model significantly reduces the gap between predictive and historical ground truth data, providing retailers with predictive data that has up to 90% accuracy compared to the ground truth verified data.

Alfonso García de Corral, VP of AI at pass_by, explains:

Our team has worked diligently to develop a solution that provides retailers with precise and actionable insights, enabling them to optimize their strategies and stay competitive in the market.

pass_by’s enhanced predictive model opens up new use cases for retailers. Operational teams can now confidently incorporate foot traffic data into their demand planning models, and the data can be reliably filtered down to store teams for actionable insights. This enables retailers to move beyond the constraints of traditional foot traffic solutions and leverage data-driven insights in their decision-making processes.

pass_by has already begun showcasing this enhanced technology to select customers and partners and is eager to share it with the broader retail community. To learn more about how pass_by’s innovative solution can improve the way you understand and anticipate foot traffic trends, visit or contact the pass_by team for more details.

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James Ewen

James is the VP of Marketing at pass_by.

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