inspire 2014 – consumer reports: making data analysts self-reliant to claim a seat at the table

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Making Data Analysts Self Reliant

Michelle LeonardSr. Research AssociateConsumer Reports

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Consumer 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

Print

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!