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JPK
Gro
up
Product Intelligence and Experience Summit
March 15-16 • San Francisco, CA
Next Generation Feedback: Extending Digital Analytic Methods
to the Physical World March 15, 11:30am
Widely considered one of the leading digital measurement experts in the world,
Gary recently launched a new venture focusing on digital analytics tracking and
strategies in the physical retail space. He previously led EY’s Digital Analytics
Practice from 2013-2016. EY acquired Gary’s previous company – Semphonic
– in March of 2013. As Semphonic’s President and co-Founder, Gary led
Semphonic’s growth over a 15 year period from a 2-person practice to the one
of the leading digital analytics practices in the United States. Voted the most
Influential Industry Contributor by the Digital Analytics Association in 2012, Gary
writes an influential blog (http://semphonic.blogs.com/semangel), has published
more than twenty whitepapers on advanced digital analytics practice and is a
frequent speaker at industry events.
View presentation online at:
www.jpkgroupsummits.com/attendee2
Gary Angel – Digital Mortar
THE TRUTH IS OUT THERE
Extending Digital Methods to the Physical World
Is the sun rising or setting on physical retail?
“…all channels will become blurred to the point of being
indistinguishable…[technology will enable] fantastic levels of
personalization and co-creation between retailer and
customer.”
Clare Rayner – Retail Champion
“No one has to go to a store anymore, we have to
want to go to a store. Understanding that simple
formula is the first step towards today’s physical retail
environment.”
Lee Peterson – WD Partners
“The future of retail lines in
technology enabled customer-
centricity.“
Paula Rosenblum – RSR Research
The future of retail hinges on being able to deliver better experiences.
The Omni-Channel Edge
Omni-channel is about USING physical stores as an ASSET to drive better experience.
Continuous improvement is the key to getting those experiences right.
And measurement is the key to continuous improvement.
1995 2016
What does Omni-Channel Involve?
One Customer…..Any Channel……....………….Great Experience
Measure and Optimize the Digital Experience
Measure and Optimize the In-Store Experience
Combine the two in Measurement, Operations
and Marketing
Measurement
Testing
Personalization
Continuous Improvement
Measurement
Testing
Personalization
Continuous Improvement
Combining Digital & Store
Segmenting across channel
Integrated Analytics
Driving the Experience
The store has been a black-box We count how many customers go in
We measure how much we sold.
The experience inside is a mystery
What engages and when does that sell?
Where do customers go?
Are areas of the store underperforming?
How much localization is necessary?
Is the staffing level appropriate?
Who are our best performers?
Until Now
Wi-FiData gathered by in-store Wi-Fi
access points track Wi-Fi
emitting device movements
within a networked space.
BluetoothConnected Bluetooth beacons
ping enabled devices and can
triangulate location with
sufficient beacon density.
Video CameraMultiple camera images, angles
and lenses are used to stich
together movement patterns,
activity and demographics.
New Collection Technologies have made the in-store journey MEASURABLE
A look at the Data
Measuring Physical Spaces
Imagine this was a Website
A customer journey might look like this…And, of course, we might want to know where they spent their time…
Science Fiction
Mystery
Calendar
Science Magazines
And it looks a lot like digital data!
Page Time
SFCat 5.35
MysteryCat 2.32
CalCat 1.59
SMagCat 6.12
We could map that to the merchandise….
The new world of in-store Journey Analytics
StoreWeb
Path Analysis Path Analysis
Functional Analysis Draws, Corridors, Impulse
Funnel Abandonment In-Store Funnel
Content Attribution Staff Performance
Associated Content View-based Market Basket
Opening up a lot of Customer Experience and Omni-Channel Analysis
And not just in retail
Fan Inferences
• Warmup interest
• Alcoholic beverage consumer
• End to end game viewer
• Taste for global cuisine
• Prioritizes convenience at half time
6:04pm on 1/18/17 (OKC): Enter East gate1
6:06 – 6:32pm: Watches warmup in section 1282
6:35 – 6:42pm: Browses team store3
6:44 – 6:58pm: Anchor Steam 6th Man Saloon4
6:59 – 7:19pm: Buys Banh Mi sandwich5
7:23 – 8:24pm: Sitting in section 2186
8:25– 8:39pm: Golden State Greats concession7
8:41– 9:44pm: Sitting in section 2188
9:44pm: Sitting in section 2189
9
8
7
6
5
4
3
2
1
Tracked in real time, simultaneously with thousands of other fans in an Arena.
Big Data Integration
Integrate Customer Journey Data with:
Point-of-Sale
Staff Detail
Store Layout
Weather
Event Data
Local and National Promotions
For comprehensive Customer Journey Analytics and Optimization
The omni-channel join
But what about the Omni-channel join?
Searching for the perfect Union
No one join strategy is sufficient1 Wifi connections create the potential for both stable MAC capture and email address collection and join.
Mobile Applications create an easy way to join digital signatures (potentially across desktop as well) with in-store journey behavior.
PoS integration provides a means of linking customers via loyalty programs and credit cards from the in-store journey to the full-account
2
Omni-Channel journey analysis
No one join strategy is sufficient
Behavioral cues can support immediate analysis and optimization
1 You can journey map and analyze customers who do returns to optimize the store experience and operations
You can focus on customers with store-pickup and measure strategies for placement, convenience and cross-sell
You can segment customers who “Showroom” by category, experience and long-term store loyalty.
3
Fine-grained time-based integration in a big-data
world
No one join strategy is sufficient
Behavioral cues can support immediate analysis and optimization
And data integration at fine-grained time increments is always an option
1
2
Correlating key data sources like PoS, Staffing and Category Engagement works very well when you can drive the data down to small time increments.
You can identify key operational gaps – times, places, and situations where you lacked staff or were overstaffed in ways that were predictable (with Weather for example).
And you parse the in-store funnel to understand how area engagement drives to purchase.
You must remember this…
Key Takeaways
Parting Shots
Technologies exist to fix that problem and measure in-store and other location-based experiences.
The join between physical data and digital data is (and will likely remain) challenging. It requires a multi-pronged strategy to achieve even partial success.
Digital methods provide the best paradigm we have for analyzing this new data set and optimizing experience.
The physical experience is the largest UNMEASURED and UNOPTIMIZED part of a typical customer journey.
THANK YOU