This course contains the use of artificial intelligence.

Customer analytics is usually taught as a tour of a tool. Here is the platform, here is the report, here is the dashboard. It leaves the impression that the problem was software.

The tool will calculate what you asked and show what you look at

Neither of those is the hard part. Analytics starts with a question and ends with a decision, and a dashboard does not supply either one. That is why so many teams have excellent reporting and no answers: nobody framed the question precisely enough for a number to settle it, and nobody decided in advance what they would do differently depending on the result. So this course is built around four questions rather than four screens. Who are these people and how do the groups differ. What happens to them, step by step. Why do they leave. And what is each one worth.

What this course covers

Forty-two lessons. The function that deals with customers daily: its key indicators — net promoter score, satisfaction, customer effort, first-contact resolution — an audit built on journey mapping, service strategy and the choice between omnichannel and self-service, team management, process automation with service level agreements, metrics and feedback analysis, difficult customers and escalation, and where service technology is going. Then journey design as a method: why poor experience is expensive, stages and touchpoints, the map itself, channel choice and tone, support material, personalisation, question design for research conversations, feedback platforms, satisfaction and response-time metrics, predicting drop-off, and analysing free-text feedback with language models. Then the research craft: what a survey can and cannot answer, study types, question design and scales, whether open questions repay the analysis, fielding, the report, and the move from findings to a plan. Then the apparatus itself: framing the question, segmentation by characteristics and finding the insight inside a segment, lifetime value and return on acquisition spend, building and measuring the lifecycle, funnel analytics, performance analytics, churn and retention with intent to stay, key driver analysis, correlation in a spreadsheet, multiple regression with its interpretation, forecasting with trend lines, and experiment design with a control group. Then churn as a project: causes, measurement and breakdowns, costing the churn, the business case, the reduction programme, implementation and resistance, and proving it moved. Finally the revenue side: the end-to-end funnel through retention, where revenue leaks, acquisition cost against lifetime value, payback and expansion, the system of record, operational analytics, forecasting deal quality, and a ninety-day rollout.

Most on-screen examples use employee data, and here is why that works

Fourteen of the forty-two lessons are customer-side throughout. The other twenty-eight were recorded about a workforce: the journey block maps a candidate's path, the survey block runs employee studies, the analytics block is people analytics, the retention block reduces staff turnover. The substitution is a single noun. Segmentation by characteristics, a lifecycle map, a retention rate, lifetime value, key driver analysis, regression and a control group are statistics over a population — the method does not know what the population sells or buys. There is one genuine difference and it runs in your favour as a student: employee data is complete and customer data has holes in it, so learning the technique on a clean sample is easier, and the course says so rather than pretending otherwise.

Who is teaching this

I am Mike Pritula. I built the people system at Preply as it became a unicorn, and I have worked at Wargaming, iDeals and Alfa-Bank. More than 1.6 million students have enrolled in my courses across 185 countries, and over 150,000 specialists have gone through my programmes. I hold PHRi and SHRM-CP certifications and represent HRCI in more than ten countries.

What is included

• Lifetime access to all 42 lessons

• Active instructor support in the Q&A section

• A Udemy Certificate of Completion

• Working material: the segmentation approach, the lifetime value calculation, the journey map with stage questionnaires, the retention and intent measures, key driver analysis, the regression walkthrough, the experiment design, and the churn business case

• Regression, forecasting and experiment design taught in a spreadsheet rather than described

Where to start

Write down the question you would want a customer analysis to answer, then write down what you would do differently depending on the answer. If the second sentence is blank, the analysis will be too. Enrol now and start today.