Unlocking the value of customer data
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Transcript of Unlocking the value of customer data
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Unlocking the Value of Customer Data
June 20, 2013
Presented By:Robert J. MooreCEO, RJMetrics
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I. Enabling Data-Driven Decisions
II. Making Data-Driven Decisions
Contents
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Enabling Data-Driven Decisions
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Single Version of the Truth
SYMPTOMS
“How do your team members get consistent
data-driven answers to their business questions?”
• Static deliverables (e-mail attachments, printed reports)
• Human roadblocks to data (usually technical)
• Online (internet or intranet) access point
• Individual logins and “sandbox” environments
SOLUTIONS
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Accuracy
SYMPTOMS
“Is the output correct?”
SOLUTIONS• Incorrect data
• Doubts about correctness of data
• Auditability
• Ties back to source data
• Public access to business logic assumptions
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Communicate Priorities
SYMPTOMS
“What metrics actually matter in a sea of options?”
SOLUTIONS• Inefficient use of time in
dashboarding environment
• Conflicting KPIs by team
• Centralized messaging
• Dashboard sharing
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Reduce Maintenance Burdens
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SYMPTOMS
“What keeps the system up-to-date and working properly?”
SOLUTIONS• Stale data and buggy features
• Increased burden on tech team
• Leverage platforms
• Test and iterate
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Making Data-Driven Decisions
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Marketing ROI
Know what your customers are worth.
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January 2010April 2010July 2010
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Shifting Marketing Spend
“We’re able to isolate small, long-tail sites that have ROI that is 16x what some of the larger sites provide. And we can find these at scale.”
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Direct Marketing
Identify individual marketing targets based on behavioral indicators.
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Direct Marketing
Acknowledge high-value customers
Retain at-risk customers
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Merchandizing and Pricing
Stock your shelves with data.
Most analyses we can run to determine a high-value customer can also be used to identify high-value products:
– Cohort Analysis
– PLV Growth Over Time (Product Lifetime Value)
– Correlation to High-Value Customers
– Value by Category/Vendor/Margin
– Churn Analysis by Product (SaaS)
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Merchandizing and Pricing
Studied the relationship between price points and their demand curve, leading to drastic margin improvements across their product mix.
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High-Confidence Forecasting
• Future behavior of existing base– Individually model each customer cohort for out
months– “Peer” cohorts are an excellent indicator of future
behavior
• Full lifecycle behavior of new customers– Varying marketing spend across different channels
can yield different long-term behavioral predictions– Data can inform both performance projections and
expected acquisition costs
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Raising Capital
• Investors and acquirers are more data-driven than ever.
• Simplify due diligence by communicating KPIs and answering data-driven questions using your centralized dashboarding system.
• Investors ask data-driven questions for a reason – go looking for skeletons in your own closet.
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Raising Capital and Board Reporting
• Fab.com ran a $40MM fundraising process by steering all potential investors through an RJMetrics dashboard
• Have control over presentation of your own data, answer obvious questions before they’re asked, and demonstrate awareness of your own key metrics
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Thanks!