Customer Data to Cash Register: Retail Analytics Close the Gap

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Information about Customer Data to Cash Register: Retail Analytics Close the Gap

Published on March 4, 2014

Author: Alteryx

Source: slideshare.net

Description

Join Alteryx & Mark Heckman, Principal, Mark Heckman Consulting and former VP of Marketing for Marsh Supermarkets to hear about the state of analytic adoption in the retail industry and the steps successful retailers are taking to put the power of data blending and advanced analytics directly in the hands of their data analysts, the people closest to the business problem. Attend the webinar to hear latest industry research on:

1) Top organizational inhibitors to wider-spread adoption of analytics

2) Highest potential analytical opportunities in retail

3) Steps leading retailers are taking to build analytical culture across functions

Customer Data to Cash Register: Retail Analytics Close the Gap © 2014 Alteryx, Inc. | Confidential

Speakers Ritu Jain Director of Industry Marketing, Alteryx Mark Heckman Principal, Mark Heckman Consulting Former VP of Marketing, Marsh Supermarkets Jimmy Garrett Sales Engineer, Alteryx © 2014 Alteryx, Inc. | Confidential 2

Agenda… 1. Current State of Advanced Analytics in Retail 2. Top Inhibitors to Wider-Spread Analytics Use 3. Steps Successful Retailers are Taking to Expand Usage 4. Real Life Case Examples © 2014 Alteryx, Inc. | Confidential 3

Showrooming/ Webrooming a Norm © 2014 Alteryx, Inc. | Confidential 4

Many Paths-to-Purchase © 2014 Alteryx, Inc. | Confidential 5

Inventory Distortion: A $800B Problem!! © 2014 Alteryx, Inc. | Confidential 6

4000+ and Counting! © 2014 Alteryx, Inc. | Confidential 7

Data is the Linchpin © 2014 Alteryx, Inc. | Confidential

Current State of Data-Driven Decision-making Source: RSR Research Benchmark Report 2014 – Retail Analytics Moves to the Frontline © 2014 Alteryx, Inc. | Confidential 9

Desired State of Data-Driven Decision-making Source: RSR Research Benchmark Report 2014 – Retail Analytics Moves to the Frontline © 2014 Alteryx, Inc. | Confidential 10

25+ Years of Retail Marketing Experience at Randalls/Tom Thumb & Marsh Supermarkets © 2014 Alteryx, Inc. | Confidential

Marsh Supermarkets….A History of Innovation and Industry Thought Leadership • 90 Stores, Central Indiana-Western Ohio…. • $ 1.1 Billion in Sales • First UPC Scanned in Troy, Ohio, 1974 Mark Heckman • Marketing Executive, VP of Marketing Until 2011 • Author, Industry Study and Harvard Business Case © 2014 Alteryx, Inc. | Confidential 12

Our Original Aspirations! • Weekly Targeted Programs to Select Shopper Groups • Desktop Targeting, Query and Reporting Tool • Standing Program for ―VIP‖ Shoppers • Create Personalize Experience on website • Expand Customer Specific Data into the Merchandising Arena • Category Growth • Store Layout • Assortment © 2014 Alteryx, Inc. | Confidential

Issues That I Faced Behind the Chair • Limited Use of Customer Data in Decision Making Process • Lots of Data, Several Data Silos, No Interaction • No Dashboard Access to Data • Little Co-operation or Data Sharing Between Departments • Insufficient Budget and Human Resources to Execute Data-Driven Programs • No Stated or Accepted Plan In Place to Enhance Data-Driven Positioning in the Enterprise © 2014 Alteryx, Inc. | Confidential

The Resulting Customer Data-Driven Roadmap Phase 1Discover Phase 2-Engage Phase 3- Involve Phase 4-Expand © 2014 Alteryx, Inc. | Confidential 15

Phase 1. Customer Identification • Created a Plan to Accelerate Data Access and Eliminate Reliance on IT for Data Pulls • Define Communication Options For Near Term and Future • Evaluate Shopper Engagement Options • Segmentation • Clubs • Geographies • Syndicated Appends • Determined Shopper Segmentation Approach © 2014 Alteryx, Inc. | Confidential 16

Phase 1- Customer Identification Shopper Segmentation ---Key Questions to Answer With Segments What is the true value of each segment to your business? © 2014 Alteryx, Inc. | Confidential Is the segment large enough to move the needle? How will we communicate to each segment? How effectively can the segmentation scheme be integrated into the core elements of the business?

Phase 1- Customer Identification- Shopper Segmentation Variables • Net Dollars per period shopped • Trips per period shopped Many customer segmentations stop at only 3 indicators of customer worth – Recency, Frequency and Spend… • Days Since Last Purchase • Periods Shopped (4wk, 13 total) • Avg. Net Dollars per Trip • # Departments Shopped • # Categories Shopped • Avg. % Discount • $ & % Spend on Front Page Items • $ & % Spend on PL • % Spend Weekdays • % Spend Weeknights • % Spend Daytime • % Spend Evening © 2014 Alteryx, Inc. | Confidential • % Spend Night • • • • • • • • • • • • $ & % Spend on Grocery $ & % Spend on Dairy $ & % Spend on Frozen $ & % Spend on Produce $ & % Spend on Deli $ & % Spend on Bakery $ & % Spend on Meat $ & % Spend on Non-food $ & % Spend on HBC $ & % Spend on AO Category relevancy Item relevancy

Phase 2- Increase Engagement - Linking Shoppers to Categories Each Shopper Segment’s Relationship with Categories and SKU’s Was Established. Categories were Defined for Each Shopper Segment According to the Categories ―Breadth of Appeal‖ and ―Spending Index‖ © 2014 Alteryx, Inc. | Confidential 19

Phase 3—Involve Merchandising and Operations Retailers need to combine traditional marketing and advertising activities with merchandising, each have assets needed by the other. As a transitional tool away from mass to a more targeted approach…..affinities to front page circular items are scored to better understand what the optimal mix of FP items to drive sales among key customer segments © 2014 Alteryx, Inc. | Confidential 20

Phase 3- VIP Mailer Results Department Level Impact We decided to focus several key offers in the Produce Department as many of the top shoppers in the segment communication indexed extremely high in Produce. The results were encouraging. Nearly 10% lift in the entire Produce Dept. and in 9 of the stores with very large Produce Departments, 20% Departmental Lift was experienced. © 2014 Alteryx, Inc. | Confidential

Phase 4---Solving Retail Problems with Customer Data Out of Stock Opportunity Store Level Weekly Weekly Store Sales $50,000 $100,000 $150,000 $200,000 $250,000 $300,000 $350,000 $400,000 $450,000 $500,000 $550,000 $600,000 Out of Stock % % Won't Sub Lost Sales 7.0% 40.0% $1,400 7.0% 40.0% $2,800 7.0% 40.0% $4,200 7.0% 40.0% $5,600 7.0% 40.0% $7,000 7.0% 40.0% $8,400 7.0% 40.0% $9,800 7.0% 40.0% $11,200 7.0% 40.0% $12,600 7.0% 40.0% $14,000 7.0% 40.0% $15,400 7.0% 40.0% $16,800 Chain Level Annualized Projected Improv. 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% Weekly Time Recovered Store Per. In $ Count Wks $140 100 52 $280 100 52 $420 100 52 $560 100 52 $700 100 52 $840 100 52 $980 100 52 $1,120 100 52 $1,260 100 52 $1,400 100 52 $1,540 100 52 $1,680 100 52 Chain Chain Annualized Annualized Ave. Gross Recoved $ at Gross % Margin Cost $728,000 26.0% $538,720 $1,456,000 26.0% $1,077,440 $2,184,000 26.0% $1,616,160 $2,912,000 26.0% $2,154,880 $3,640,000 26.0% $2,693,600 $4,368,000 26.0% $3,232,320 $5,096,000 26.0% $3,771,040 $5,824,000 26.0% $4,309,760 $6,552,000 26.0% $4,848,480 $7,280,000 26.0% $5,387,200 $8,008,000 26.0% $5,925,920 $8,736,000 26.0% $6,464,640 Out of Stock Prevention Department Specific Traffic Patterns In addition to providing a whole store look, Dwell Density and Traffic Flow can be produced to gain an understanding about how consumers move within a specific area of the store. Represents HUGE Incremental Dollars to Both Retailer and Brand. Customer Data Both Household Level and Not are Key Elements to Staying In Stock SKU Assortment Dwell Density & Traffic Flow Now is Frequently Driven by VIP and other Critical Shopper Segment’s Affinities to Categories and Products Store Layout Can Now be Refined and Adjusted to Leverage Traffic Patterns of Key Shopper Segments within the Store Confidential – Subject to PathTracker® license Dwell Density: Shopper distribution based on visits and time spent Traffic Flow: The arrows indicate the dominant traffic flow in the various areas of the store. The larger the arrow, the higher the percentage of shoppers who are moving in the same direction. © 2014 Alteryx, Inc. | Confidential Audit PathTracker® Sample Analysis Project #07912 Spring 2007 12 22

Technology Culture Organizational Inhibitors © 2014 Alteryx, Inc. | Confidential Source: RSR Research Benchmark Report 2014 – Retail Analytics Moves to the Frontline 23

The Current Approach to Insight FAIL Large IT Project © 2014 Alteryx, Inc. | Confidential Lots of Tools Many Months…

The Alteryx Approach All Relevant Data Packaged Market & Customer Data Enrich Report Analyze Blend Text Access, cleanse, and blend data with unique packaged data options © 2014 Alteryx, Inc. | Confidential Rapid design of predictive analytics with unique spatial understanding Consumerize the use of sophisticated analytics 25

Corporate Info. Customer Success Strong Foundation 165+ 300+ 95%+ Associates across North America & Europe Customers across the world Renewal rate Ranked “Visionary” by Gartner Leader in Data Blending and Advanced Analytics © 2014 Alteryx, Inc. | Confidential in Both ―Advanced Analytics‖ and ―BI and Analytics‖ magic quadrants 26

Our Retail Customers…. Big Box and Specialty Consumer Goods © 2014 Alteryx, Inc. | Confidential Grocery Restaurants

Results Speak… Marketing © 2014 Alteryx, Inc. | Confidential Merchandising Supply Chain Corporate

Recommendations 1. Ensure access of data, analysis and reporting to those that need the data, minimizing dependence on legacy systems and IT 2. Build cross- functional relationships and joint goals to ensure inter-departmental cooperation, tear down fiefdoms 3. Tie metrics and results of data-driven initiatives back to organizational goals -departmental sales, # of units, shoppers, etc. 4. Take small, iterative steps with data-driven programs, gaining quick wins -- and use those wins to build executive support, promote data-based culture © 2014 Alteryx, Inc. | Confidential 29

Questions? © 2014 Alteryx, Inc. | Confidential 30

Key Terms • • • • • • • • • • • • • • • Retail Analytics Customer Analytics Customer Loyalty Merchandising Planning Demographic Analysis Customer Data Customer Scorecards Multichannel Analysis Big Data Analytics Big Data Analysis Predictive Analytics Data Blending Advanced Analytics Data Artisan Data Analyst © 2014 Alteryx, Inc. | Confidential • • • • • Alteryx Mark Heckman Marsh Supermarkets Ritu Jain Alteryx Analytics Gallery 31

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