The Five Best (& Uncommon) Practices for Unlocking Value in Customer Data to Drive Growth and Real Estate Strategy

Pitney Bowes Software

The Five Best (& Un-Common) Practices for Unlocking Value in Customer Data to Drive Growth and Real Estate Strategy

October, 2014

Al Beery - PBSGary Faitler - PBSDave Bolan - Rexall

Who we are…

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Since 1959, the PBS Strategy and Analytics division (formerly Thompson Associates & MapInfo) has

provided innovative research solutions and developed sophisticated sales‐forecasting models for

more than 1,600 clients in the retail, restaurant, and financial‐services industries.


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Let Pitney Bowes Software and Dave Bolan, Director of Analytics, Rexall Canada, share with you the five not-so-common best practices for unlocking the maximum analytic power from your data. It begins with leveraging data for powerful visualizations and reporting, thereby facilitating the creation of actionable information.

Pre-Cursor to this Webinar…

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Dave Bolan


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1.Harvest Your Data for Maximum Yield

2.Optimize Insight → Display and Report

3.Extract Meaning ~ Prepare for Action

4.Construct Tools for Forecasting

5.Build Bridges for Busting Silos


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1.Harvest Your Data for Maximum Yield

Harvest Your Data…

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2. Optimize Insight → Display and Report


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3. Extract Meaning ~ Prepare for Action

Use this slide for a Full-bleed image

Extract Trade Area Insight

What is the extent and

consistency of my store’s draw?

Extract a Clear Customer Profile

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Establish a general understanding of “Who is YOUR Customer?”Index clusters based on contribution to performanceCreate a uniform ‘effective’ household base for model development Identify demographic characteristics which correlate with sales

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Competitive Impact Quantification

The competitive analysis evaluates the competitiveness of each individual geography, so it is important to understand the type of competitive situation impacting each.

Types of Competitive Situations• Adjacent – competitor is in same center or across the street• Impacting – competitor is in a similarly advantageous/convenience position• Intercepting – competitor is more convenient to the census tract customers

CustomersCustomers

Adjacent

Intercepting

Impacting

Quantify Significance of Site Characteristics

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Site characteristic analysis measure model calibration against thepresence of site specific attributes as provided for all database stores.

Model Distance Decay Patterns

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Basic premise is that customers who are more conveniently served by the store will visit more frequently and thus contribute a higher annual volume


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4. Construct Tools for Forecasting

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5. Build Bridges for Busting Silos



Leveraging Results Across the Organization

Sample Range of Analyses:

• Data Visualization

• Trade Area Analysis

• Maturity Analysis

• Customer Profiling

• Competitive Assessment

• Site Attribute Analysis

• Site Forecasting

• Benchmarking

• Store Clustering

• Omni-Channel Analysis

• Target Marketing

Benchmarking Foundation• Performance varies by environment (e.g., market size and

density, competition, customer profile, synergies, etc.)

• The PBS model is best-fit to the client database, controlling

for measurable qualities within the environment that have

been statistically shown to drive store performance

• Benchmarking utilizes the value of the predictive model in

the context of goal-setting, which is often an arbitrary

process

• Actual store performance and model-predicted potential are

scored in decile, with (-5) being the lowest and (+5) being

the highest.

Benchmarking results should be measured against P&L metrics to determine the full

picture of viability

Store Benchmarking

Exceeding Potential

Not Meeting Potential

Store Benchmarking

Developing a national demand surface with pre-defined criteria, PBS can run a national supportable store analysis and provide the results at the market level

Supportable Store Estimation

• Interaction between brick & mortar stores with online sales

• How does saturation of brick & mortar impact my online

growth?

• Established markets v. greenfield markets

• What is the most appropriate assignment?

Omni-Channel Analysis

Recap – Interdepartmental Value

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Dave Bolan


Analyses to accounts for ‘roll-in’ acquisitions & impact of FTE doctors in associated clinics

Upcoming: Model adjustment for rebranding

Store clustering & benchmarking to support model

Renovation lift calculator

Partnership at a Glance


Flyer Optimization

Existing sales penetration Market-share

Potential – Trade Area only Competitive Intensity


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Q&A

Business

The Five Best (& Uncommon) Practices for Unlocking Value in Customer Data to Drive Growth and Real Estate Strategy