<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Customer Segmentation |</title><link>https://annelizekrause.com/tags/customer-segmentation/</link><atom:link href="https://annelizekrause.com/tags/customer-segmentation/index.xml" rel="self" type="application/rss+xml"/><description>Customer Segmentation</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Thu, 24 Apr 2025 00:00:00 +0000</lastBuildDate><image><url>https://annelizekrause.com/media/sharing.png</url><title>Customer Segmentation</title><link>https://annelizekrause.com/tags/customer-segmentation/</link></image><item><title>Where Does a Snack Shop Actually Make Its Money? A Business Report in Google Sheets</title><link>https://annelizekrause.com/projects/snack-attack-shack-report/</link><pubDate>Thu, 24 Apr 2025 00:00:00 +0000</pubDate><guid>https://annelizekrause.com/projects/snack-attack-shack-report/</guid><description>&lt;p&gt;Snack Attack Shack is a fictional snack retailer from the Masterschool orientation challenge. The official submission was a group project, but my place in the Data Analytics track rode on my orientation results, so I also built a complete version of my own: the report I would want to read if the shop were mine, covering where the money actually comes from, which customers are drifting away, and what&amp;rsquo;s quietly rotting in the warehouse.&lt;/p&gt;
&lt;p&gt;The answers were concentrated ones. Twenty-five customers, 28% of the base, generate 69.6% of revenue; the top 25 products carry 68.2%. Regular customers drive 96.8% of everything, which makes the dormant segment a reactivation opportunity rather than a write-off. On the operations side: several products sat flagged for urgent reorder while discontinued items still held excess stock, and the carrier comparison split cleanly into a fastest option (Speedy Express, 8.6 days average) and a cheapest one (United Package, €8.76 average), which is a choice, not a problem.&lt;/p&gt;
&lt;p&gt;Everything runs in Google Sheets, from cleaning through loyalty segmentation (new, non-returning, dormant, regular) to AI-assisted demand and profitability forecasting. Two logs in the repository document the work end to end: every transformation from raw data to final numbers, and exactly where AI assisted, because analysis you can&amp;rsquo;t retrace is just opinion with charts.&lt;/p&gt;
&lt;p&gt;Read the
, or explore the
in Google Sheets.&lt;/p&gt;</description></item></channel></rss>