PECO, one of the nation’s largest owners and operators of grocery-anchored shopping centers, will utilize Spatial.AI’s Geosocial data to help inform business decisions.
Cincinnati, OH — November, 2019 — Spatial.AI today announced that Phillips Edison & Company (“PECO”), one of the nation’s largest owners and operators of grocery-anchored shopping centers, will utilize Spatial.AI’s Geosocial data to help inform business decisions. PECO is at the forefront of leveraging data to drive optimal performance at its properties resulting in enhanced leasing, merchandising and acquisition strategies.
Securing access to real-time information on location-specific human behavior, personalities and sentiment aligns with PECO’s “Locally Smart” initiative, which focuses on ensuring the company’s shopping centers resonate with the communities they serve.
“Through our partnership with Spatial.AI, Phillips Edison is able to employ dynamic analysis of robust data to capture the personalities of each unique community where we operate,” said Phillips Edison Chief Operating Officer Bob Myers. “In today’s evolving retail landscape, it’s helpful to have Geosocial data to have a better understanding of the types of tenants that will do well in our neighborhoods.”
Retail property owners and operators must be able to consistently identify the best tenants for their vacancies. To do this, they have to understand which businesses the community is most likely to support. Spatial.AI empowers landlords and retailers to make more informed decisions by leveraging Geosocial data, which combines location-based social media data with critical insights and analytics to capture the organic interests and personalities of a community. These observations have proven to be an effective indicator of which tenants will be most successful in a particular location, enabling leasing teams to optimize their merchandising strategies.
“Spatial.AI is excited to be a part of PECO’s forward-thinking strategies. PECO’s shopping centers are the heart of hundreds of neighborhoods, and their attention to the unique qualities of these communities is bringing the right retailers and restaurants to the right customers,” said Spatial.AI CEO Lyden Foust.
Spatial.AI captures publicly available Geosocial data and categorizes conversations—finding and labelling themes. Spatial.AI users see an index of how many people in any region are talking about nightlife, coffee or subjects related to motherhood, for example.
“We are a very data-driven company,” said Phillips Edison Senior Director of Data Science Brad Farris. “Different types of data are needed for our use cases because traditional demographic data provides us with an incomplete description of communities. Demos don’t accurately represent the rich textures of our customers’ preferences. However, Geosocial is helping to solve for this.”
Geosocial data is like hyperlocal market research: A massive number of people from a broad geographic distribution freely and organically contribute data over time. Spatial.AI data scientists then apply unsupervised machine learning, which analyzes the underlying structure of the information, to identify meaningful patterns and organize that data into usable social segments. Those segments allow customers to receive maps with quantifiable and actionable information about the people who live, shop and work in any given community.
For more on how Geosocial data can improve your business, visit www.spatial.ai.