Three Ways to Find a Wedding Photographer, and Why Two of Them Suck
WORDS: Jim Kee
If you're getting married and you need a photographer, or any one of the other 20 services for your wedding, like a florist, DJ, caterer or venue, your prospects for finding one have definitely improved in recent years. Here are the three ways to find a service for your wedding, ranked from most primitive to most advanced.
135 years ago the yellow pages were invented, and for over 100 years, companies were listed alphabetically, which explains why there are so many more companies with names that start with "A" than any other letter in the alphabet. In 1997 a website listing wedding vendors launched to let users filter to choose their photographer's style ("artistic" or "classy"), distance ("within 5 miles" or "within 10 miles") or starting price range. Filtering is intuitive and we all use it all the time, but here's why it sucks.
Filtering gives the user the impression of control and choice, but in reality, the choices aren't meaningful because the filtering criteria are not what we would use to make a decision. We want to know if the photographer is good, if they are artistic, if they've screwed up other people's weddings. We want to know if they will be able to take charge and get the pictures we want, or if they are going to wilt under the mother-in-law's gaze. None of those are available. Instead we get to choose between "Modern" or "Dramatic." We can choose a photographer from within 10 miles or within 25 miles, as if that matters. It gives the shopper a false sense of control and absolutely zero benefit. Worse even, users are lured onto wild goose chases, switching over to individual websites, browsing at hundreds of wedding pictures until they realize that they've blown several hours. And, then just when the couple thinks they found a match, they discover that the photographer is booked for their date.
Netflix and Amazon pioneered "collaborative filtering," in which the user is identified, and then the "decision engine" looks for similar users and then recommends what those other users liked. Amazon is amazing at this, and it works great for books. You buy a dozen books on Amazon, and then Amazon understands: you like romance novels and biographies, so Amazon will recommend books in those genres that you haven't yet purchased. It's not a bad method. It can get fooled if you buy a book for someone else, or if someone else already bought you that book. It can get fooled if your preferences change, or if you're just a really unique individual who has eclectic tastes.
Collaborative Filtering would be an upgrade from what exists today for wedding websites, except that they would prefer not to use it. It would reduce the time that couples spent browsing their site and therefore the number of impressions that they can claim to have.
But, the bigger problem is that the decision engine is trying to guess and infer what you want instead of just asking. The decision engine is going through this roundabout process of trying to collect what other people like and batch them into groups, and then identify what group you are part of, and then make a recommendation. This is a technique that's good if you have lots of computing power but no personal attention from an actual human expert. An actual human expert, also known as a "wedding planner," would ask lots of questions and then make recommendations based on expert knowledge and familiarity with vendors in the market.
The current state of the art is the Prepaired approach. Start with a 30-year veteran in the wedding business like Tobey Dodge, author of The Other Side of the Aisle and planner of over 800 weddings. Distill all that knowledge into a massive algorithm. Quiz the couple on their preferences, tradeoffs, likes and desires. Then, do the same with every wedding caterer, florist, venue and photographer. Consider everyone's calendar, which vendors work effectively with which others. Then, present the couple with a Match Score for each one, showing the four available photographers with the highest probability of delighting the couple. And, this great tool will only get better as Machine Learning techniques refine recommendations.
The beauty of this system is that it's also the best possible world for the photographers (and caterers, make-up artists, and cake artists). Most of them are small businesses or individual proprietors. They have their own unique skills and styles, but they struggle to differentiate themselves from the sea of competitors that started yesterday with a $100 website, a dozen stock photos and an ad on a wedding website. Experienced professionals love the idea of an expert algorithm to help them find the couples whose wedding vision will fit their unique style and abilities.
To be fair to those more primitive methods, the Expert Algorithm method is a lot harder to implement. You need to learn a lot about everyone - the couple and the many photographers out there - and then you need to know what's important about matching them. That's the kind of thing that you only learn from decades of planning actual weddings. All that expertise is available by visiting Prepaired.com, currently in Los Angeles and soon in many more cities in the United States.