How to Effectively Use Shopper Analysis in Retail Business

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© CountBOX 2016

How to Effectively Use Shopper Analysis in a Retail Business

© CountBOX 2016

Retail Market Overview

Physical Stores vs. Mobile & E-Commerce

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Source: Mazedon Retail

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Source: Mazedon Retail

Retail Evolution

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What is Shopper Analysis?

What is Shopper Analysis?• Data collected and analyzed to create insights as to:• Who are the shoppers?• Where do they go in stores?• What do they buy?• How do they buy the merchandise?• How long do they stay in the stores or the online store?• How often do they shop at the store? (Loyalty)• When do they shop during the week?• When do they shop during the days of the week?• What seasons do they shop the most?

• When do they shop the least?

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Where does the data come from?• Main data sources:• Retailer

• Point of sale (POS) systems in bricks & mortar stores• Online store transactional data

• External data sources• Surveys

• Online • In-mall

• Observational data• Gathered in-store: 24/7/365

• Secondary data sources• Reports, third-party databases, etc.

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What POS shopper data is collected?• Purchase information

• Merchandise purchased in stores and online• From single “department”• From more than one “department”

• Size of transaction• Number of items purchased (UPT)• Dollars used in transaction (average receipt or dollars per transaction)

• Type of transaction• Credit• Debit • Cash (in-store only)

• Loyalty program usage

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Online Shopper Analysis

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Google Analytics

Google Analytics – Behavior

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Google Analytics – Age

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Google Analytics – Geography

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Google Analytics – Device Used

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Google Analytics – How Acquired

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Google Analytics - Website

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Summary: Online Shopper Analysis• Google Analytics provides the following information on

shoppers:• Base demographics• Shopper acquisition• Geographical dispersion of shoppers• Shopper movement through the online store

• Pageviews• Bounce Rate, etc.

• Analysis of online ad campaigns• Conversion rate of online ads

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In-Store Shopper Analysis

In-Store Shopper Analysis• Provides shopper and area analytics for retail stores/chains• The data includes:

• Who the shopper is: age, gender, ethnicity and mood• Where they go in the store or mall

• Area analytics• What they do in the store

• Shopper traffic distributions by time period• Dwell times• Occupancy

• Store analytics• KPI’s• Labor

• Marketing and advertising campaign analysis

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Unobtrusive In-Store Sensors

Door counting sensors:

Area counting sensor (WIFI)

Demographic sensor

In-Store Shoppers

Shoppers are key to retailers’ success …. do they know who their customers are?

(Surveys cannot provide shopper profiles at the store or mall level.)

In-Store Shopper Profiles Using facial recognition technology shopper profiles are created …

Shopper data is aggregated for composite shopper profiles that include: • gender, age, ethnicity and mood.

The shopper profiles are reliable as they come from a census of the store’s shoppers

How Does It Work?

Images Reviewed For Accuracy

Sample Shopper Profile Analyses

Customer Loyalty Using door sensors and WIFI sensors within the store or mall• Calculates the exact percentage of loyal customers• Assessments made by time periods, promotions or events

Customer Service & Satisfaction

Using WIFI analyses queue wait times are calculated• Customer satisfaction

is directly related to wait times• Longer wait times =

less satisfied customers• Compare average wait

times to company standards

Customer Engagement Area counting examines Customer Engagement

• Exact percentage of customers within areas of stores or malls

• Heat maps: represent high and low traffic areas within a venue

• Dwell time of customer in the store.• Longer dwell times =

sales

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Shopper Traffic by Week

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Store Traffic by Day of Week

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Store Traffic Distribution by Hour

Key Metrics With Retailer Data When you combine retailer data with shopper analysis data you create even more powerful measures:

• Conversion rate• Percentage of shoppers that make a purchase

• Value of each shopper• Total sales divided by number of shoppers per time period

• Shoppers to staff ratio• Number of shoppers per staff member on the sales floor

• Staff optimization • Scheduling staff to shopper traffic based on staffing constraints

• More scheduled during peak hours• Less scheduled during low traffic hours

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Store Conversion Rate v. Traffic by Day

Assess Marketing Campaigns and Events Lift in shopper traffic and sales for the campaign or event

• Shopper traffic analyses• Percentage increase• Actual increase in the number of shoppers• Track staff to shopper ratio

• Sales analyses• Percentage increase in sales• Actual increase in sales• Increase/decrease in sales per shoppers (shopper value)• Increase/decrease in conversion rate

• Assess any potential “lost” sales through:• Staff to shopper ratios• Decrease in conversion rate

Compare and contrast marketing campaigns and events:• Winners and losers• Assess any changes in shopper profiles that may occur during the

campaign or event

Additional Shopper Analyses

• Benchmarking of key metrics• Internal (company)• Industry segment

• Measuring and modeling of environmental factors• Impact of weather and weather events• Industry trends• Seasonality

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Summary: In-store Shopper Analysis• In-store shopper analyses provide the retailer with data on:• Who the customer is• When and where they shop in the store• How long they spend in line and in the store• KPI’s for store operations

• Conversion rate• Shopper value• Shopper to staff ratio

• Analyzing marketing campaigns and events

Conclusions• Shopper Analysis is invaluable in providing insights as to:• Who customers are• Where do they go • What they do• Both online and in-store

• This information is used to provide:• Key performance metrics to improve the business by focusing on the

customer• To prove their relevance, physical stores need to embrace shopper analysis

• Provide the right products at the right price in the right area with the right service levels

• Shoppers and customers are assets

© CountBOX 2016

© CountBOX 2016

Thank you!

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