Data Analysis

Collecting customer feedback is the easy part. Turning it into product changes, retention wins and cost reductions is where most programs stall. Here's the long-form guide — methods, tools, step-by-step process, plus the pitfalls that quietly waste twenty years of customer feedback investment.

Excel sits on every desktop and can do almost everything a stats package does — once you know which features to use. This one-hour on-demand webinar walks through the practical survey analysis workflow: designing the analysis plan, testing response rates, charting cleanly, testing significance, and finding the satisfaction drivers.

You're three minutes into the executive presentation and a senior manager is already attacking the sample size on slide one. It's the laziest way to dismiss customer feedback findings, and it's increasingly common. This one-hour on-demand webinar walks through what sample size actually means and how to defend your numbers without getting drawn into a stats argument.

Your inbox just delivered a stack of customer feedback — numbers, scales, paragraphs of free text, the lot. Where do you start? Qualitative or quantitative? Both have their place, and choosing wrong wastes the week. Here's the three critical differences, with examples, benefits, and where each shines.

Should NPS be reported by the date the survey went out, or the date the response came back? It feels like a small reporting decision — until the wrong choice quietly distorts your trend line for months. Here's the case for each side and why "received date" is usually the right answer.

What's a good survey response rate — 1%, 15%, 50%? It's the wrong question. What actually matters is whether you've got enough responses to draw a conclusion, and that's a different number for every situation. Here's how to calculate the response rate you actually need, with the maths shown.