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EP 63: A Data Driven Approach for Selecting Brick & Mortar or Pop-up Retail Store Locations w/ IdealSpot’s Bryan Eisenberg

2X eCommerce Podcast · with Bryan Eisenberg · February 9, 2016 · 54 min

Summary

This episode reveals how ecommerce operators can de-risk their physical retail expansion using cutting-edge data science. Bryan Eisenberg of IdealSpot explains how leveraging machine learning to analyze over 15,000 data points across demographics, psychographics, search, social, and traffic metrics can pinpoint optimal brick-and-mortar and pop-up locations. This data-driven approach replaces guesswork, significantly improving the success rate of new retail ventures by aligning strategy with deep consumer and market insights.

Key takeaways

Themes

retail & omnichannelai & automationanalytics & attribution

Topics covered

retail location intelligencebrick and mortar strategypop-up shopsmachine learning for retailsite selection analyticspsychographics in retailproduct content management

Episode description

Bryan Eisenberg is the Founder & CMO of Ideal Spot - a web-based, commercial real-estate mapping and analysis suite. IdealSpot helps retailers find their ideal retail location utilizing machine learning algorithms akin to retail location data analysis experts. Its machine learning algorithms utilizes deep learning analysis of over 15,000 data points such as demographics, psychographic, search, social, mobile, competitive, and traffic metrics for every location in a bit to significantly reduce the risks retailers face when choosing retail locations. Bryan is a recognised authority and pioneer in ecommerce, UX, online customer experiences and conversation rate. Bryan has worked with companies such as HP and Intel as well as is on the advisory board of several successful start-ups. He is 2-time best-selling New York Times and Wall Street Journal Author of the books: “Call to Action” and "Waiting for Your Cat to Bark" He a world leading and respected digital marketing expert. Message from Our Sponsors: This episode is brought to you by Salsify. As an online retailer or supplier, you are well aware that ACCURATE PRODUCT CONTENT drives more sales...However, as your store starts to scale the harsh reality is that maintaining product description content becomes more and more of a challenge to ecommerce teams.Enter Salsify...Salsify is a SaaS based product content management platform built specifically for online retailers and brand owners.I recently took Salsify on a test drive and here are the glaring advantages etailers stand to gain:- Your entire product catalog can be accessed by any department in a centralised hub,- There’s a workflow setup that ensures no fields go amiss when product data is published to multiple channels such as Amazon, your Google Merchant account or just directly to your ecommerce st

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Frequently asked about this episode

What does this episode say about retail & omnichannel?
Traditional retail location selection is fraught with risks; utilize data analytics to inform decisions rather than relying on intuition.
What does this episode say about ai & automation?
Leverage machine learning platforms like IdealSpot to analyze extensive data points (demographics, psychographics, search, social, mobile, competitive, traffic) for optimal site selection.
What does this episode say about analytics & attribution?
Apply data-driven location intelligence for both permanent brick-and-mortar stores and temporary pop-up shops to maximize impact and minimize risk.
What does this episode say about retail & omnichannel?
Recognize that online customer behavior insights (UX, conversion rates) can inform and predict the viability of physical retail spaces.
What does this episode say about retail & omnichannel?
Ensure product content management is streamlined with platforms like Salsify, especially when scaling, to maintain accuracy across all sales channels.

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