What is Data Version 2.0?

Placer is committed to constantly finding ways to improve the accuracy, quality, and reach of our insights. As part of this ongoing process, we launched a new data version on March 31st. 

Data Version 2.0 fundamentally improves the accuracy and granularity of Placer’s data, enabling us to produce a wide range of new features and capabilities while building upon our industry-leading reliability. It includes a series of significant enhancements to Placer’s ability to capture and attribute visits, including:

• The long-awaited addition of “short visits”, including visits as short as 1 minute in length, 
• Data extrapolation improvements,
• Optimized visit detection, 
• Improved employees and residents visits estimations,
• Accuracy improvements to Retail Sales, and
• Increased capacity to account for travel and tourism.

Importantly, all historical data from January 1, 2017 are updated as well, so that comparisons to previous time periods all use the same data perspective.

What changed?  How should I interpret the new data?

Data Version 2.0 impacts different reports to varying degrees: 

• Since it allows for more complete capture of property visits – including those visits with very short durations – Data Version 2.0 may yield data shifts in Visit Metrics and Rankings reports.  
• Reports that are based on True Trade Areas and relative metrics –– such as Demographics –– are less sensitive to changes in overall visit capture and therefore less likely to show data shifts.
• Data Version 2.0 significantly improves the accuracy of sales estimates across all categories covered in Retail Sales reports – especially categories with many short-duration visits, such as QSRs.  

When interpreting property reports, we recommend assuming a margin of error relative to the shift seen in the chains and industries that apply to specific properties. This can be found in the “Version 2.0” Labs report in the Labs section of the Placer platform, which shows chain-level visit metrics and dwell time using the new data version for all chains that are currently available within the platform.  For example, if the wider Grocery category is seeing a 5% increase in visits, one could consider a margin of error of a 5% increase on an individual grocery property.

Frequently Asked Questions

Q: What are the core data improvements that were introduced in Data Version 2.0?
A:  Data Version 2.0 includes the following improvements:

• Short visits capture - Placer reports now take into account short visits, starting from just 1 minute in duration, for every POI in every category.‍
• Foot traffic estimates accuracy improvements - Placer insights will now benefit from a variety of accuracy improvements, including a dynamic population model that enhances representativeness and accounts for population growth over time, more granular extrapolation calculations, measures to further prevent retroactive data distortion, improvements to our de-biasing model, and more.

‍Q: Were historical data updated as well? ‍
A: Absolutely. One of Placer’s standout attributes is that it is designed to reflect historical change in the physical world. This is especially important because our physical environment is constantly changing: stores, restaurants, malls and other POIs open, close, merge and move. Thus, all historical data from January 1, 2017 was updated with the new data version, so that comparisons to previous time periods all use the same data perspective.

Q: Is there be any data degradation?  Did the number of locations or chains decline? 

A: No. The new data version is better in every measure and increased reach while enabling the launch of a series of new capabilities. In fact, Data Version 2.0 results in an increase in the overall number of locations that may be analyzed within in-platform reports.

Q: How do you define a “short visit”? 

A: A short visit is any visit that is less than 10 minutes long.

Q: But what if I don’t want to count short visits?

A: Placer understands that not all visits carry equal significance in all use cases. Some brief visits, like a 3-minute stop at a gym or a 6-minute visit to a movie theater, may not be as relevant to your analysis.  To address this, we have introduced a customizable approach allowing for visit duration segmentation. 

All users have the flexibility to analyze visit data across different visit duration segments,  based on their preferences. To make it as simple as possible, we have provided a default "duration segment" defined on a per-category basis. This means that, per category, users see by default either all visits or, alternatively, visits with a duration of 10 minutes and above. For example, the default for movie theaters is “10 Min or Longer”, while the default for QSR locations is “All Visits”.

Q: Were my data feeds affected? 

A: Yes, data feeds were affected. All data feed customers have received communication directly from their customer success team with information relevant to their unique data feed setup. 

Q: What do I do if I have additional questions?

A: If you have any questions, please reach out to your Customer Success Representative and we will get back to you as soon as possible.

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