how to find the customer retention secrets hiding in your data
TRANSCRIPT
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Why Retention Matters
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Top-performers grow significantly faster
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In part due to high acquisition
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Revenue from repeat customers
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Revenue from repeat customers
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Your customers are very different
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Building a Data-Driven Retention Strategy
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3 buckets of customers
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3 buckets of customers
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Your data-driven retention strategy
Channel analysis Getting the 2nd purchase Getting the 3rd 4th and 5th
Acquiring more loyal customers Retaining the most valuable customers
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How can I get more customers to make a second purchase?
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Getting the second purchase is tough
68% of customers will never purchase a second time.
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Step 1: Benchmark company performance
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+
Step 2: Identify problem areas
Customer Support Data
order #, order date
product #, SKU, size/type
order #, order date
OR
OR
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Product Analysis
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Step 3: Uncover the ideal timeframe for remarketing
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Step 3: Uncover the ideal timeframe for remarketing
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How can I get a customer to make a 3rd, 4th, 5th purchase?
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Good news! It gets easier
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Step 1: Evaluate the average time between order
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Step 2: Develop your purchase personas
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Case study: Dollar Shave Club
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How can I retain my most valuable customers?
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Step 1: Identify them
$ Spent
VIP customers
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Step 2: Track issues they are having
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Step 3: Discover what they love about you
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How can I acquire more loyal customers?
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Step 1: Identify the valuable campaigns/channels
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Step 1: Identify the valuable campaigns/channels
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Step 1: Identify the valuable campaigns/channels
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Step 2: Use your VIPs
Referral programs
Abandoned cart offers
Customer events
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How can I get to this data?
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Your 3 options
1
Spreadsheets
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Your 3 options
1
Spreadsheets
2
Build a solution
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Elements of an analytics stack
Data Integration
Data Warehouse
BI/Analytics
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#datastack
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Your 3 options
1
Spreadsheets
2
Build a solution
3
Buy a platform
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100% Build Build + Buy 100% Buy
Pros Maximum flexibility High flexibility Some flexibility
Cons Maximum engineering investment
Moderate engineering investment
Low engineering investment
What it is Build API integrations, warehouse, and analytics layer
Purchase the various components that are the best fit for your business
A complete data stack, easily configurable
Who is this right for?
Companies building data products (Spotify, Uber, Pinterest)
Companies with 5+ analysts, data scientists
Companies with <5 analysts, little engineering time
Examples In-house RJMetrics Pipeline + Looker, Mode, Tableau
RJMetrics CloudBI
Choose your data stack