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"PiinPoint has become an integral part of my role as Retail Analyst at Cushman & Wakefield Waterloo Region. The platform allows me to put together professional looking reports and provide clients with the insights they need to make real estate decisions.
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I honestly don’t know how I would do my job effectively without PiinPoint."

Jessica McCabe, M.Ed.
Retail Analyst

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eBook

Evolution of Real Estate Network Planning in the Age of AI

Read eBook Now >

GeoAI Blog Series

A person in front of computers with Data, graphs and charts on their screen.

GeoAI Blog Series: Trouble in AI Paradise: Get the Data Right First!

It comes as no surprise that the absence of a focused data strategy centered on location intelligence is a significant hurdle to the practical application of AI to Real Estate planning. Real Estate executives and GIS experts agreed that in the absence of a holistic data strategy, the organization suffered from three typical roadblocks to leveraging AI effectively: 1) data silos within the organization - non-integrated spatial and other data sources, 2) missing data - incomplete consumer or real estate supply data, 3) acquiring unique sources of new data for competitive advantage.
Read Now >
Graphs showing a positive trend

GeoAI Blog Series: AI/ML Investments Reduce the Risk of Real Estate Planning Mistakes

The overwhelming perception from GIS and Real Estate Executives is that AI/ML technologies will have a profound effect on the speed and accuracy of producing sales forecasts, the measurement of cannibalization, and the ability to find white and gray (infill, repurpose) space opportunities in retail networks.
Read Now >
Code on a computer screen

GeoAI Blog Series: GIS and Data Science Don’t Speak the Same Language

The collaborative synergy among Analytical Teams - particularly between geographic information science (GIS) and data science (DS) teams - separates organizations that have an AI strategy and have invested in “Centers of Excellence” around data and machine learning operations (MLOps) from the rest. Read more on how to overcome this in your organization…
Read Now >

GeoAI Blog Series: Building Next-Generation Location Intelligence Tools

GeoAI is an emerging fast growing field of study and development enabling real estate and GIS professionals with next generation tools for market analysis and retail network planning.
Read Now >

GeoAI Blog Series: Trust and Transparency; Beating the “Black Box” Syndrome

One of the most pervasive barriers to adoption of AI/ML technologies in organizations is the inability for Executives and Leadership more generally, to “believe” or “trust” the outcomes from complex AI/ML model systems. Read more on how to overcome this in your organization…
Read Now >
Chicago City Skyline

GeoAI Blog Series: Increasing Efficiency in Real Estate Planning

One of the most popular values of leveraging AI technologies in organizations is focused on internal productivity and efficiency gains during the real estate analysis and approvals process.
Read Now >

GeoAI Blog Series

New blogs posted monthly. Stay tune with our Newsletter!

GeoAI Blog Series: Trouble in AI Paradise: Get the Data Right First!

It comes as no surprise that the absence of a focused data strategy centered on location intelligence is a significant hurdle to the practical application of AI to Real Estate planning. Real Estate executives and GIS experts agreed that in the absence of a holistic data strategy, the organization suffered from three typical roadblocks to leveraging AI effectively: 1) data silos within the organization - non-integrated spatial and other data sources, 2) missing data - incomplete consumer or real estate supply data, 3) acquiring unique sources of new data for competitive advantage.

Read More

GeoAI Blog Series: AI/ML Investments Reduce the Risk of Real Estate Planning Mistakes

The overwhelming perception from GIS and Real Estate Executives is that AI/ML technologies will have a profound effect on the speed and accuracy of producing sales forecasts, the measurement of cannibalization, and the ability to find white and gray (infill, repurpose) space opportunities in retail networks.

Read More

GeoAI Blog Series: GIS and Data Science Don’t Speak the Same Language

The collaborative synergy among Analytical Teams - particularly between geographic information science (GIS) and data science (DS) teams - separates organizations that have an AI strategy and have invested in “Centers of Excellence” around data and machine learning operations (MLOps) from the rest. Read more on how to overcome this in your organization…

Read More

GeoAI Blog Series: Building Next-Generation Location Intelligence Tools

GeoAI is an emerging fast growing field of study and development enabling real estate and GIS professionals with next generation tools for market analysis and retail network planning.

Read More

GeoAI Blog Series: Trust and Transparency; Beating the “Black Box” Syndrome

One of the most pervasive barriers to adoption of AI/ML technologies in organizations is the inability for Executives and Leadership more generally, to “believe” or “trust” the outcomes from complex AI/ML model systems. Read more on how to overcome this in your organization…

Read More

GeoAI Blog Series: Increasing Efficiency in Real Estate Planning

One of the most popular values of leveraging AI technologies in organizations is focused on internal productivity and efficiency gains during the real estate analysis and approvals process.

Read More

New Research from PiinPoint: “The Evolution of Real Estate Network Planning in the Age of AI” is now ready for download!

We spent the last four months of 2023 digging into the literature on Artificial Intelligence as it applies to the real estate strategy and planning of brick & mortar retail distribution. In addition, we conducted a series of executive interviews with Real Estate and Geographic Information System (GIS) professionals across a range of sectors. Here’s some highlights!

Where is the value in adopting AI?

  • Productivity: Increasing efficiency of the real estate analysis approvals process
  • Risk Reduction: Increasing accuracy of predictions and reducing investment risk
  • Customer Growth: Identifying emerging customer behaviour and new growth markets
  • Engagement: Optimizing operations to promote customer and employee engagement
  • Profitability: Creating new jobs for long term employment expansion

But with all the benefits, there are challenges and barriers to overcome in order for Real Estate professionals within retail organizations to realize the value:

  • Strategy: Not having an AI strategy
  • Data: Not having the right data!
  • Talent: Traditional GIS professionals and Data Science teams are siloed.
  • Process: Lack of trust and transparency of the AI/Machine Learning outcomes.

So what’s new coming down the pipe?

  • Building next-generation location Intelligence tools on a foundation of GeoAI
  • Research on Explainable AI is already gaining traction to address the trust and transparency issue.

As with all good research, we were left with some final questions for the future.

  1. Will AI Technologies reduce the need for brokers?
  2. Will AI Technologies reduce the need for dedicated GIS departments within retail organizations?
  3. Will internal Real Estate Teams be disrupted by GeoAI capabilities?
  4. Will the third-party SaaS GIS solution market be disrupted by internal GeoAI investments?

Conclusion: GeoAI will disrupt location Intelligence and real estate network planning as we know it - Are you ready?

Download your “ungated” copy of the ebook here and let us know what you think!