Unlocking the value of customer data

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  • Hello everyone– I’m excited to spend some time with you this morning and want to thank SVB for putting so many members of the community in one room so we can talk about my favorite topic in the world: data.Up-front, I want to make it crystal clear that my intention here today is not to pitch you all on RJMetrics. The reason I’ve been asked to come speak is not because of what our product can do. It’s because of the more broad lessons we’ve been able to learn by building it and by working with literally hundreds of online businesses to help them extract value from their own customer data.To inform where these insights are coming from, let me tell you a little bit about what we do.
  • Unlocking the value of customer data

    1. 1. Unlocking the Value of Customer Data June 20, 2013 Presented By: Robert J. Moore CEO, RJMetrics
    2. 2. I. Enabling Data-Driven Decisions II. Making Data-Driven Decisions
    3. 3. Enabling Data-Driven Decisions
    4. 4. Single Version of the Truth “How do your team members get consistent data-driven answers to their business questions?” SYMPTOMS SOLUTIONS • Static deliverables (e-mail attachments, printed reports) • Online (internet or intranet) access point • Human roadblocks to data (usually technical) • Individual logins and “sandbox” environments
    5. 5. Accuracy “Is the output correct?” SYMPTOMS SOLUTIONS • Incorrect data • Auditability • Doubts about correctness of data • Ties back to source data • Public access to business logic assumptions
    6. 6. Communicate Priorities “What metrics actually matter in a sea of options?” SYMPTOMS • Inefficient use of time in dashboarding environment SOLUTIONS • Centralized messaging • Dashboard sharing • Conflicting KPIs by team
    7. 7. Reduce Maintenance Burdens “What keeps the system up-to-date and working properly?” SYMPTOMS SOLUTIONS • Stale data and buggy features • Leverage platforms • Increased burden on tech team • Test and iterate 7
    8. 8. Making Data-Driven Decisions
    9. 9. Marketing ROI Know what your customers are worth. $350 $300 $250 $200 $150 $100 $50 $0 January 2010 April 2010 July 2010
    10. 10. 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.”
    11. 11. Direct Marketing Identify individual marketing targets based on behavioral indicators.
    12. 12. Direct Marketing Acknowledge high-value customers Retain at-risk customers
    13. 13. 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)
    14. 14. Merchandizing and Pricing Studied the relationship between price points and their demand curve, leading to drastic margin improvements across their product mix.
    15. 15. 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
    16. 16. 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.
    17. 17. 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
    18. 18. Thanks!

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