Personalisation in loyalty programmes can produce far more than discounts. According to a WIRED report by journalist Reece Rogers, McDonald's returned a 515-page dossier after Rogers exercised his California right to access stored consumer data. The file contained not just a transaction history, but a set of algorithmic predictions about how often he would eat at the chain, how much he would spend, and whether he would ever stop.
The 515-page dossier
Rogers requested the data through the McDonald's Privacy Rights Center site. A few days later, a file with the golden arches stamped across the top arrived by inbox. The report's intro explained: "This report contains specific pieces of personal information about you that were identified by searching McDonald's systems which contain information about our customers."
What the predictions show
WIRED published a table of the key forecasts. Rogers was expected to make 2.16 visits during the next six weeks, with an average order spend of $13.49 and a total predicted spend of $29.15. The report put his customer attrition likelihood at 0. It assigned him to customer group CV2, and identified two behavioural archetypes: "Food-Led Afternoon Snack" and "On the Go Lunch in a Rush". His most visited geographic location was San Francisco and Santa Barbara, with 61 visits. The top product ranked by recency, frequency and monetary value was Large Diet Coke, and the top product category was Wraps–Chicken.
| What McDonald's Calls It | What My Data Says | What That Means |
|---|---|---|
| Estimated Number of Visits During the Next 6 Weeks | 2.16 | How many times McDonald's expects me to return before mid-September. |
| Estimated Average Order Spend During the Next 6 Weeks | $13.49 | What McDonald's expects me to spend per order. |
| Estimated Total Spend During the Next 6 Weeks | $29.15 | My total predicted value to McDonald's, over those six weeks. |
| Customer Attrition Likelihood | 0 | Potential odds I'll stop being a customer. Ouch! |
| Customer Group Based on Historical Transactions | CV2 | McDonald's doesn't provide details about what this internal value tier means. |
| Most Transacted Occasion Type | Food-Led Afternoon Snack; On the Go Lunch in a Rush | My two behavioral archetypes based on past orders. |
| Most Visited Geographic Location | San Francisco, Santa Barbara (61 visits) | The main market where I eat McDonald's and how often. |
| Recency, Frequency, Monetary Derived Top Product | Large Diet Coke | The item McDonald's recommendation math ranks as my number one. |
| Recency, Frequency, Monetary Derived Top Product Category | Wraps–Chicken | The menu section McDonald's expects me to order from. |
The data behind the forecasts
Rogers wrote that the dossier contained every past transaction, every offer McDonald's sent him, and his accumulated loyalty points. It also logged every time he scanned a code for the returning Monopoly sweepstakes, including the prize he received. To make sense of the document, Rogers used a generative AI tool to extract key information, then verified the details against the original file.
Privacy experts weigh in
Jeff Chester, executive director at the Center for Digital Democracy, told WIRED: "McDonald's secret sauce is really commercial surveillance." Privacy experts Rogers spoke with said that while this level of detail may feel invasive, it is fairly standard for how large companies in America run loyalty programs.
McDonald's response
A McDonald's spokesperson told WIRED via email: "McDonald's takes data privacy and security seriously, and we take robust steps to safeguard customer information. Like many digital loyalty programs, we use information such as past purchases to provide a more engaging, personal customer experience—like delivering the most relevant deals, offers and messages. Our customers continue to have privacy choices available to them as outlined in our privacy statement."
What this means for enterprise technology leaders
The dossier gives technology decision-makers a concrete example of what a loyalty analytics system can output: a per-customer file with predicted visit counts, spend totals and attrition scores derived from transaction data. The report's own language — that the data was found "by searching McDonald's systems" — points to the database queries behind the dossier. The figures WIRED published — 2.16 expected visits, $13.49 average order spend, and an attrition likelihood of 0 — provide a benchmark for the kind of customer scoring that a major fast-food chain generates from loyalty purchases.
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