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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.

ContactGary.Angel@DigitalMortar.com

THANK YOU