The 3 Important Differences: Qualitative vs. Quantitative Analysis

bigstock-Brawl-2670840It’s Tuesday afternoon and you’ve just been handed a stack of customer feedback forms with a wealth of information and data to go through and analyse before Friday. You look at the forms; there are numbers, scales, and paragraphs upon paragraphs of commentary.

You pause for a moment and breathe. Where do you begin? What can you even do with all that information?

You want to get the best analysis possible – so the question is – Qualitative Analysis and Quantitative Analysis – which one is better?  Which will provide the best results?

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How Kmart knows you’re pregnant before your family does

This is a fascinating insight into the state of the art in triggered and reactive marketing. In a longish, but very good article, the New York Times provides some great case study material on how Target in the US identifies and targets, no pun intended, women who are pregnant BEFORE they buy any pregnancy related goods or services. With this head start on the competition they are able to generate excellent returns on their marketing.

Do you know any companies working at this level of sophistication? Let me know.

Here is the full article: How Companies Learn Your Secrets

 

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Do Your Customer Experience Initiatives Have These Flaws?

It seems to me that many customer experience initiatives are deeply flawed. They start out well intentioned but lack the right process improvement mindset to drive long term change.

The customer experience strategy that seems to be best practice at the moment is:

  1. Do some research on what people want: ask a focus group, run a survey, etc,
  2. Design “the best” customer experience based on the research.
  3. Test it in a limited way –asking people what they think, doing some usability testing (i.e. watching what people actually do either actually or via analytics) of your systems.
  4. Roll-it out.
  5. Relax

The critical part is that the design process (steps 1 and 2)  is run only once. Then, having agreed that it is perfect, just let it run. This is wrong. [Read more…]

Forecasting customer value when you don’t have a contract: Discrete transactions

This post is one in a series in which I summarize into actionable steps parts of the substantial body of work by Peter Fader, Bruce Hardie, et. al. in the analysis of customer bases. The relevant source papers are referenced at the end of the post.

In this post, we will focus on the bottom left quadrant of the Fader/Hardie customer relationship map (as I will refer to it). We will be examining situations where there is no on-going contract between the supplier and the customer and where the customer can only purchase at discrete time intervals.
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Calculating Retail Sales Forecasts, Customer Life Time Value, and other customer variables

This post is one in a series in which I attempt to summarize into actionable steps parts of the substantial body of work by Peter Fader, Bruce Hardie, et. al. in the analysis of customer bases. The relevant source papers are referenced at the end of the post. The details of the statistical models are deliberately excluded from this summary but can be reference in the source papers.

In this post, we will focus on the top left quadrant of the Fader/Hardie customer relationship map (as I will refer to it) . [Read more…]