Lesson 3: Planning a Customer Analytics Initiative

Question-and-answer flashcards covering the main concepts from the lecture notes on planning and executing a customer analytics initiative.

What are the four guiding considerations for planning a customer analytics initiative?

Access to the right data; Customer-level data; Analytics that focus on the customer; Getting buy-in.

Why is access to the right data important in a customer analytics initiative?

Because it's hard to increase purchase frequency, conversions, or favorable attitudes if you don't know what customers are buying, when they buy, or what they’re thinking; ensure the data exists or can be collected and analyzed.

What does 'customer-level data' mean in this context?

Identify transactions, revenue, and survey data for each customer, and roll this lower-level data up to product or company-level summaries as needed.

What does it mean for analytics to focus on the customer?

Analytics should be meaningful to customers across their journey, using metrics that reflect customer impact (e.g., satisfaction with outcomes rather than the number of calls answered).

Why is getting buy-in essential for a analytics initiative?

Because insights won’t drive change unless people who can alter the product, price, or experience are involved with data collection and planning.

When defining scope and outcome, what is the first step?

State the goals of the initiative with specificity (e.g., a 10% revenue increase for a product line over the next year).

When defining scope and outcome, what is the second step?

Write down the business questions you want to answer; start small, be specific, and itemize questions.

Give examples of questions customer analytics can answer.

Examples include: Which product feature should be added? What’s preventing online purchases? What labels should change in navigation? Why aren’t customers recommending a product and how to fix it? Who are the most profitable customers? How long until a repeat purchase occurs?

What are the key steps in identifying metrics, methods, and tools?

1) Look for metrics meaningful to customers (e.g., on-time arrivals vs departures). 2) Identify tools needed for data collection (e.g., surveys of existing customers).

What is Net Promoter Score (NPS)?

A market research metric based on a single question about how likely a customer would recommend a company/product/service to a friend or colleague.

How are NPS respondents grouped?

Promoters (9–10), Passives (7–8), Detractors (0–6).

How is NPS calculated?

NPS = % Promoters − % Detractors.

What do Promoters, Passives, and Detractors signify in NPS?

Promoters are loyal enthusiasts; Passives are satisfied but unenthusiastic; Detractors are unhappy and can damage the brand.

What does 'Findability' refer to in website UX?

The ease with which users can locate and access the content they need on a website.

What metric measures findability?

Findability rate.

What methods are used to study findability?

Tree testing and card sorting.

What tools support findability analysis?

Tree testing software; methods to invite prospective customers; methods to analyze the data.

What is tree testing?

A focused approach to evaluate a site's navigational structure and determine where users lose their way; reveals if important resources can be found.

Give examples of tree testing applications.

Online grocery store: find how to change delivery time slot or add a payment method; Bus service app: find next bus times.

What are the two budgeting considerations for a customer analytics initiative?

Software (scalable to the size of the organization) and Time (cost of software, services, and staff time).

What does the analysis phase involve?

Describing the current state of the customer (often by segment) and identifying root causes of problems or insights; using loyalty, satisfaction, and open-ended feedback.

What outcomes demonstrate improvement in the Improving phase?

Quantifiable improvements in metrics such as conversion rates, customer attitudes, revenue, and repeat purchases.

What should you consider when Controlling the Results?

Automatic reporting (dashboards/scorecards), documented data access processes, and having the right people and procedures in place (who analyzes, who is responsible, and who is impacted).

What should be documented regarding data access and analysis?

How to get access to the data, the methods used to analyze it, and the people responsible for analysis and decision-making.