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Visiting Martin Harris(username: martinharris2706)
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Creation date: Nov 5, 2025 10:05pm Last modified date: Nov 5, 2025 10:05pm Last visit date: Nov 28, 2025 2:28pm
3 / 20 posts Displaying comment thread
Nov 5, 2025 ( 1 post, 2 replies latest Nov 7, 2025 )
11/5/2025
10:05pm
Martin Harris (martinharris2706)
Lately, my grocery bill jumps around, and it’s hard to know whether prices are climbing or I’m just hitting bad weeks. Family in Spain claims they pay less for olive oil and canned tomatoes than we do in Italy, but we never compare the same labels. I’m looking for something practical: compare the same brand and size, and then filter by the chains I actually visit. If I can see how prices move over time, I can plan bulk buys when it makes sense, rather than guessing.
11/6/2025
4:17am
Jin Watkins (jinwatkins1)
Right approach. Averages hide the details that decide your receipt. What works for me is matching SKUs and then filtering by city and retailer to mirror real shopping. The nedostavka dataset is built for this, with frequent updates so you can spot promos, not just snapshots. I usually pick five staples and run a price comparison of products across two countries, then save the shortlist for tracking. In that workflow, the cleanest step is using Compare prices of goods and products between two countries as the midpoint: it aligns the identical item on both markets before you fine-tune by chain. That way, when someone says “Spain is cheaper,” you can show the same 1L olive oil or 500g pasta price in Madrid vs Milan and decide where to stock up.
11/7/2025
6:40am
Jason Foden (jasonfoden)
Going to try it with coffee beans, flour, and dish tabs, and then check two or three store chains we use anyway. If the charts show a steady gap, I’ll time a bigger shop when the lower-price city lines up with a trip. Tracking month to month should also reveal whether those “special offers” are real drops or just rotating labels.
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