A crowdsourced map of what codes as what.
Every points strategy eventually hits the same wall. Your card earns 3x on dining or 5x on groceries, but whether a given store actually triggers that bonus comes down to its merchant category code, and nobody tells you what that is up front. The network assigns the code, not the sign over the door. So a store that looks like a grocery can ring up as a superstore instead, a restaurant tucked inside a hotel can post as lodging, and a warehouse club sits in its own bucket that most grocery cards ignore. You usually find out which one you got after the statement posts, when the points are either there or they are not.
For years the only way to check ahead of time was to dig through forum threads. Someone on FlyerTalk swears a certain store codes as grocery, someone on Reddit says it stopped last year, and Doctor of Credit has a comment section three hundred replies deep. The information exists. It is just scattered across a dozen places and half of it is stale.
Swipe Smart is an attempt to put all of that in one spot. It is a crowdsourced database of datapoints. People report what they bought, which card they used, and what it actually earned, and everyone else can search it.
What it actually does
You look up a retailer and see the datapoints other people have submitted: the card, the category it coded as, and what it earned, filterable by card, category, and region. If you are about to drop a few thousand dollars somewhere to clear a minimum spend, or you want to know whether a store counts for your 5x quarter, you can see what other people got before you commit instead of gambling on it.
The other half is contribution. After a purchase you can add your own datapoint, and the community votes on whether the existing ones still hold up, which is the part that keeps the whole thing from rotting. It gathers reports the same way the forums do, pulling from FlyerTalk, Reddit, and Doctor of Credit, just organized so you are not reading three hundred comments to find the one that matters. It covers a handful of countries too, not only the US.
Where it helps, and where to be careful
The obvious use is gift cards and bonus categories. If a grocery store codes as grocery, buying gift cards there can turn a 5x grocery card into 5x on almost anything, and knowing that before you go is most of the game. Same idea for confirming a store lands in your dining or travel bucket before you route a big charge through it.
The thing to keep in mind is that a crowdsourced datapoint is exactly that, one data point. Coding varies by location, changes over time, and sometimes differs between two branches of the same chain. A report from a store in another state last year is a hint, not a promise. The votes and the volume help, but a single unverified entry is worth about what a single forum comment is worth, so treat it as a lead and confirm it with a small purchase before you lean on it.
None of that makes it less useful. It just means it is a map drawn by other travelers rather than the official one, and you read it accordingly. For something that is free and runs on donations, having these datapoints searchable in one place beats hunting through comment sections every time you want to know how a register is going to code you.