What 18,000 Reddit comments say about products that last

r/BuyItForLife holds one of the largest collections of long-term ownership experience anywhere online, and almost none of it is structured. So we read 18,338 comments across 1,541 threads and turned them into 818 product recommendations covering 142 categories and 536 brands. Nearly every one is tied back to the comment it came from. You can download the whole dataset as a CSV.

1. On some products Reddit has exactly one answer. On others, none.

Agreement turns out to be spread very unevenly. In some categories a single product takes over the whole conversation. Brother laser printer accounts for 75% of every mention in the printers threads (80 of 107). At that point it stops being a ranking and starts being a verdict. Elsewhere the mentions scatter across a dozen names and no favourite emerges. The chart shows what share of each category's mentions went to its most-mentioned product.

The most contested categories. Here the community genuinely disagrees, and picking one product to recommend would misrepresent it:

2. Two different kinds of trust

Durability reputations come in two shapes. Some brands are trusted across a lot of different things. Cuisinart shows up in 9 separate categories. Others are trusted intensely in one place instead. Speed Queen draws 101 mentions from just 2 categories. Breadth points to a company with consistent manufacturing standards. Concentration usually means one product has become the default answer.

Recommended across the most categories:

Most mentioned overall:

3. A quarter of the most durable products aren't sold on Amazon

Of the 803 recommendations we could check against Amazon's catalogue, 178 (22%) are not sold there at all. The pattern is not random. The brands that go missing tend to sell through their own stores, specialist dealers or appliance channels rather than a marketplace. The most common ones here are Patagonia, Whirlpool, L.L.Bean, Uniqlo, Sebo, Singer. If you research long-lived goods at a single large retailer, you never see about a quarter of what experienced owners actually recommend.

4. Roughly one in eight buying suggestions points to the used market

New retail still dominates where commenters send people, by 814 mentions to 118. The interesting part is that the minority share is as high as 13% of all purchase suggestions. eBay, Facebook Marketplace, thrift stores and estate sales come up in the same breath as Amazon and Costco. Most product-recommendation writing never sends readers to the used market at all, because there is no commission in it. Here the reasoning is straightforward. If something really does last decades, buying it used is just a cheaper way to get the same object, and people often argue the older production runs were built better than what is sold today.

New retail Secondhand

Method, and what this cannot tell you

For each of the 142 categories we pulled the highest-scoring r/BuyItForLife threads matching it through Reddit's API. That came to 156 scrapes, 1,541 threads and 18,338 comments. A language model then read those discussions and pulled out the products mentioned, how often each came up, the prevailing sentiment, and verbatim quotes with their comment IDs. Amazon availability comes from matching each product against Amazon's catalogue. Only the current version of each category's research is counted, so pages that have been refreshed are not counted twice.

The limits matter as much as the findings, so here they are:

• This is a sample of Reddit, not a survey. Threads were picked by score, which favours popular and older discussions. None of it generalises to shoppers at large.
• Mention counts are approximations. A model extracted them, so they are not exact string frequencies. Read them as relative weight.
• Reddit skews male, North American, English-speaking and enthusiast, and its taste in products skews with it.
• Survivorship bias comes with the subject. People post about the boots that lasted twenty years, not the identical pair that fell apart in one.
• Brand names are parsed, not curated. They come from the product name, with a hand-written list covering the multi-word ones, so an unusual name can end up attributed to the wrong brand.
• This site earns affiliate commission on some outbound links, which we disclose on every page. It has no bearing on which products the extraction finds, but you should know it when you weigh the source.

Figures regenerate from the underlying research, so they move as categories are refreshed. If you cite this, please link to this page and note the date shown below. The aggregate statistics are free to reuse with attribution; the quoted comments belong to their original Reddit authors.

Last updated Jul 30, 2026