How to Find the Customer Retention Secrets Hiding in Your Data

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

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

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

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

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

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

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

#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