inspire 2014 – consumer reports: making data analysts self-reliant to claim a seat at the table
DESCRIPTION
Consumer Reports generates over 1.8 million surveys annually to help them evaluate products for their publications. But survey data is notoriously difficult to use. In this session you will find out how Alteryx enabled Consumer Reports to replace the tedious process of reformatting survey data with an automated process, and view the results in Tableau. Case studies will reveal how Alteryx is used to provide asset tracking for the items they test, for SEM data, and to determine which product categories drive the most interest from their subscribers. Previously, analytic insight was confined to people who could write code, but you will find out how Alteryx is giving analysts “a seat at the table.” Michelle Leonard, Senior Research Associate, Consumer ReportsTRANSCRIPT
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Making Data Analysts Self Reliant
Michelle LeonardSr. Research AssociateConsumer Reports
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Multi-Media Organization
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Our Challenge
Content Creators(Testers)
CRO.org
TVPrint Pubs
Digital
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Goal
TV
Windows
SUVsCrib
s
Smartphones
Meat
Dryers
Identify Top Performers
Identify Best Distribution Channel
CRO.org
Digital
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Project Challenges
New Way of Thinking• Faced reservations about the approach & its implications• Intense debate on what variables to consider
High Stakes• Reallocating resources could impact jobs and the organization’s success
Enormous Task• No road map – data & critical thinking
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Consumer Perspective
Rate Ourselves
• Is the information we provide valuable to our subscribers?
Financial Perspective• Are we producing content that will grow our subscriber base?
Mission Perspective• How well does our content support Consumer Report’s mission?
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Consumer Data
Disparate Data Sources
• Monthly surveys for each media channel• Web traffic & orders• Household spending (3rd party data)
Financial Data (Revenue & Expense)
• Employee salaries (Time spent testing) • Testing & Test Sample Costs• Media channel specific costs
Mission Perspective• Internal assessment of each content category
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First step, analyze major sources independently
Disparate Data Sources
Web Data
PrintSurvey
s
Finance
Data
3rd PartyData
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Monthly Surveys
Readership
• Measure article level performance• Data collection challenges (survey length, multi-topic articles) • Data analysis challenge • (Show Tableau Dashboards)
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Needed An All-in-One Tool
• Handle survey data• Manipulate Data• Join & normalize disparate data sources
• Manage Data• Handle high file volume
• Analyze Data• Scale conversion and statistics
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Survey Data
• Process monthly survey files• Join survey results with a product classification file• Ability to store answer and answer labels separately• Analyzing results
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Next step, join & analyze major sources together
Disparate Data Sources
Web Data
PrintSurvey
s
Finance
Data
3rd PartyData
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Join Data Sources
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Product Hierarchies
Dealing with the different content category hierarchies • For example, one source might
report data at an “SUV” level whereas another source reports data at a “Large luxury SUVs” level
• We used Alteryx to proportionally allocate data from each source to same level.
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Convert Scales
We also used Alteryx to convert each data source to a 1-5 scale…
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Metrics
• Impact• Revenue • Reach• Value
Established four key metrics
Tableau Dashboard
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Challenges with Alteryx
• Finding it hard to follow complicated work stream • Certain tasks are easier in Excel• Input parameters (Alteryx/Tableau connection)
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Next Steps
• Determine when to use Alteryx vs. Tableau• Improve streams • Test/refine metrics• Develop accuracy reports
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THANK YOU!