Liquor industry sales jumped 4.5% in the U.S. in 2016, and in America alone, alcohol is a $220 billion industry. It’s no surprise, then, that the app ecosystem for alcohol -- especially beer and wine -- is fairly robust.
You probably have some of your own favorites on the beer app side, including TapHunter, Untappd, and MyBeerNation. WineRing, Delectable, and Vivino are some of the top wine-searching and recording apps.
Vivino: helping us impress our friends via wine selection since 2011.
In fact, in late 2016 Untappd -- which amazingly had 3 million drinkers on it but was still being run part-time -- merged with NextGlass, a wine/beer identification app, and only then did the Untappd founders make it their primary job.
The relative (if not immediately financial) success of Untappd underscores the three main features of most drinking-related apps:
For a drinking app to work well for its users, it needs to offer these three things consistently. What else are wine and beer apps doing to keep mobile users engaged?
An additional important aspect is image recognition, so that an app user can take a picture of a label, store it (as discussed above), but also have the label itself bring up identifying characteristics of the beer/wine -- and maybe even link it to similar products. WineWoo, a wine lovers/recognition app, wanted to cover 80% of the French wine market within their app. For context, that’s somewhere north of 200,000 wine labels. They ultimately partnered with an enterprise image recognition software company to make it a possibility.
A similar note on execution: Vivino is the most-downloaded in the wine app category globally, and much of their scaling process was accomplished with freelancers, especially around UX, design, and image recognition needs. This makes sense: many of these companies are startups without an immediate revenue model before a strong user base is established, as you see with Untappd’s founders not going full-time for years. If you’re interested in building or bettering an alcohol app, consider that growth approach.
The clearest path to monetization for these types of apps is gaining more user data or partnering with local providers (wineries, brewpubs, liquor stores, etc.) This is illustrated by how Untappd worked with Bear Republic, a California-based brewery, a few years ago. Working with a digital agency, Bear Republic determined three interesting intersection points about the craft beer-drinking demographic:
This indicated there was some degree of brand loyalty, but most craft beer drinkers wanted additional exposure to options in the space.
Bear Republic partnered with Untappd to create a special badge for the release of one beer, Racer X. If you checked in drinking a Racer X from October to December, you could unlock it. The results:
The “special” nature of the unlock coupled with the ease of social share drove a lot of awareness about Racer X and boosted initial sales for Bear Republic. The partnership -- where the app helped connect an already-interested market (craft beer drinkers) with a potential provider (a brewery) -- is one major way for these apps to collaborate and monetize.
Some apps, like Signature Wine Club, allow users to research wine in-app, then order said wines from the comfort of their own home -- or gift wines to friends and family. Similar apps typically work with a variety of payment options and offer subscription models based on the amount of wine purchased in a given month. Drizly and Minibar are similar apps in this space. In most cases, they partner with local merchants and receive a cut of the order price. On the consumer side, it will drive up the price as opposed to doing it yourself -- but who wants to brave Friday night wine crowds in the rain or some such? Not us!
Remember NextGlass from above? Well, it showcases another aspect of these apps: when they work really well, they know your drinking preferences better than you do. Wait, what? Consider:
What makes NextGlass stand out is how it makes those recommendations. Unlike other recommendation apps, it’s not predicting what you’ll like based on similar brands or what other people say. Rather, it uses the actual chemical makeup of the drink. Trace Smith, the company’s chief operating officer, said that around 30,000 bottles of beer and wine have been tested for the app using a high-resolution mass spectrometer — a device that measures chemicals in a substance.
“Each bottle that we run through the mass-spec, we get over 20,000 individual chemical attributes. We’re looking at each of these bottles at a molecular level,” Smith told The Huffington Post during a phone interview. “We see the data of what they do and don’t like, and based on that info, we see what other bottles they’ll like.”
Thought Big Data was limited to stuff like spreadsheets and analysts? Nope. It literally is improving your happy hour. (Here's to you, Big Data.)
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