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Despite the hype that Amazon and other e-com sites receive, it is estimated that 94% of US retail sales still happen “In the Real World”. Yet precisely because brick & mortar businesses rely on their physical locations to drive sales, they often don’t have the same rich data sets available to online retailers. Worse, the data they do have is often siloed between different departments and in different databases. So they don’t connect the dots for potentially transformative insights into customer behavior, media vehicle effectiveness, cross-sell opportunities, or new approaches for dealing with competitors. This panel will discuss strategies and challenges in combining media, social, and sales data to improve understanding across an increasing number of online and offline data sets. We will present real-world examples of how multi-unit retail business are connecting store sales, media impression, and local social engagement data to drive actionable insights and real-world results.
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#DigitalBricks
How Data Can Help
Brick & Mortar Businesses
Thrive
Brad B McCormick Chief Digital Officer Moroch Adver5sing • Mul5-‐Unit Retail Marke5ng • Brand Adver5sing • Paid, Owned, Earned Media Integra5on
Chris Treadaway President & CEO Polygraph Media • Social Media & Big Data • Decision Driven Marke5ng • Author: Facebook Marke;ng, A Hour a Day
Dr. Edo Airoldi Associate Professor Sta5s5cs Harvard University • Media AHribu5on Modeling • Sta5s5cal Methodologies • AB Test in Complex Systems
Speakers
Retail Spends Most on Advertising
"Half the money I spend on advertising
is wasted; the trouble is I
don't know which half.”
-John Wannamaker New York Retailer
1874
Big Data to the Rescue?
The Vision
Store Sale & Transac5on Data
Localized Social
Media Data
Na5onal & DMA Specific Media Impression Data
Na5onal & DMA Related Economic & Local (i.e. Weather) Data
The Vision
Store Sale & Transac5on Data
Localized Social
Media Data
Na5onal & DMA Specific Media Impression Data
Na5onal & DMA Related Economic & Local (i.e. Weather) Data
BeHer Insights, BeHer Campaigns, BeHer ROI, Less Waste, Less CluHer
The Reality
Store Sale & Transac5on Data
Localized Social
Media Data
Na5onal & DMA Specific Media Impression Data
Na5onal & DMA Related Economic & Local (i.e. Weather) Data
The Reality
Store Sale & Transac5on Data
Localized Social
Media Data
Na5onal & DMA Specific Media Impression Data
Na5onal & DMA Related Economic & Local (i.e. Weather) Data
• Archaic POS Systems • Employee Era • Cadence & Timing of
Reports
• Frequency & Reach Duplica5on
• Changing Customer Habits
• Cadence & Timing of Reports
• User Opt-‐In • Outdated Bios • Loca5on accuracy • Loca5on at moment of
engagement
• Correla5on vs. Causa5on
• Cadence & Timing of Report
Store Sale & Transac5on Data
• Archaic POS Systems • Employee Era • Cadence & Timing of
Reports
Weekly Sales Reports, by DMA, By Store
Store Sale & Transac5on Data
• Archaic POS Systems • Employee Era • Cadence & Timing of
Reports
Week to Week vs. Comp Sale Analysis
Localized Social
Media Data
= Above Average Social Engagement
= Below Average Social Engagement
• User Opt-‐In • Outdated Bios • Loca5on accuracy • Loca5on at moment of
engagement
Real Time Social Engagement Segmented by DMA
Localized Social
Media Data
• User Opt-‐In • Outdated Bios • Loca5on accuracy • Loca5on at moment of
engagement
Weekly Fan Engagement Analysis By DMA
Localized Social
Media Data
• User Opt-‐In • Outdated Bios • Loca5on accuracy • Loca5on at moment of
engagement
Understanding DMA-specific Social Trends
Localized Social
Media Data
• User Opt-‐In • Outdated Bios • Loca5on accuracy • Loca5on at moment of
engagement
Programmatic Media Buys Initiated by Social Activity.
Na5onal & DMA Specific Media Impression Data
• Frequency & Reach Duplica5on
• Changing Customer Habits
• Cadence & Timing of Reports
Tracking Largest Ad Spend Against Changing Trends.
Na5onal & DMA Specific Media Impression Data
• Frequency & Reach Duplica5on
• Changing Customer Habits
• Cadence & Timing of Reports
Correlating DMA Media Dollars to DMA Transactions.
Na5onal & DMA Related Economic & Local (i.e. Weather) Data
• Correla5on vs. Causa5on
• Cadence & Timing of Report
How Weather Influencers Local Economic Activity.
The Vision – In Beta.
Questions?
#DigitalBricks
How Data Can Help
Brick & Mortar Businesses
Thrive
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