Customer data quality: don't let inaccurate data stop you from acting
Customer data quality is never perfect. How to judge whether data is good enough for the decision at hand, triage the flaws, and act without fooling yourself.
Category
Customer Analytics
Lifetime value, retention math, control groups, data quality, and measurement that holds up in a board meeting.
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Customer retention rate: are you measuring it correctly?
Customer retention rate looks like simple arithmetic, yet two teams get two answers from one database. Five decisions hide in the definition; here is the fix.
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Is customer lifetime value a waste of time? Only when misused
Customer lifetime value is a forecast, not a measurement. When it wastes a CX team's time, when it earns its keep, and how to build a number you can defend.
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Measuring customer experience with control groups: how to hold out
Control groups in customer experience measurement are the honest way to show a change caused a result. How to hold out without A/B tools, and what breaks it.
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Can't the IT department do my customer analysis? Who should own it
Customer analysis is a question-asking job, not a query. Why it belongs with whoever owns the decision, what IT should own instead, and how to split the work.
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Customer experience measurement: is your program worth the effort?
Customer experience measurement decides whether a program survives year two. Rule 7 of no-excuses CX: three questions, a comparison group, one page a month.
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Customer lifetime value strategy: grow your business, no excuses
A customer lifetime value strategy turns the seven no-excuses rules into arithmetic: estimate value by segment, build a value-at-risk table, act on it.
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Using lifetime value in a short-term environment: leading indicators
Customer lifetime value leading indicators show up inside a quarter. How to find them, validate them against old cohorts, and turn them into value at risk.
