MATT MUSICK

Faris and I made this.

Tue, 31 Jul 2012 17:07:00 -0400

Faris and I made this.

I came across a blog post titled “The new ROI of social: Risk of...

Sat, 30 Jun 2012 17:15:00 -0400

I came across a blog post titled “The new ROI of social: Risk of Irrelevancy” a few days ago and it got me thinking. The post focuses on how some clients are hesitant to dive into social media.

Undoubtedly many brands risk some degree of irrelevancy by foregoing social, but the part of the post that interested me most was the following:

“Think of it this way: imagine that most of your existing customers suddenly began speaking a new language. What would you do? Would you insist they revert back to English in order to do business with you, or would you learn that new language?”

Apparently, a lot of people agree that social is a new language.

Sure, thinking of it that way, it’s a good point. The problem is that’s the wrong way to think about it. Social is not a new language. Social behavior has been around as long as humans have existed. Good thing, since otherwise we wouldn’t be here today.

A better comparison might be the printing press. It allowed a behavior that already existed to become much more efficient and effective.

Clay Shirky says in Cognitive Surplus, “Media is actually like a triathlon, with three different events: people like to consume, but they also like to produce, and to share. We’ve always enjoyed all three of those activities, but until recently, broadcast media rewarded only one of them.”

One way that the proliferation of social platforms might eclipse the printing press in impact is that while the printing press meant replication became simple and more books and pamphlets were distributed, you couldn’t respond through the same medium unless you too operated a printing press. With social platforms, anyone with a computer, a smartphone or a local library can respond immediately and on the same platform.

So no, social behavior is nothing new. Social platforms are just allowing this behavior to become more immediate, more efficient and more effective.

Recommendations inform almost all of our choices about what to...

Sun, 29 Apr 2012 18:45:00 -0400

Recommendations inform almost all of our choices about what to watch, read, listen to, eat or experience. They come from friends, an online review, a staff pick or even hearing a song on the jukebox at your neighborhood bar.

But there are so many levels of recommendations. There are those from friends, acquaintances, coworkers and sometimes from strangers through blog posts, articles, tweets, etc. How can anyone retain, let alone process and act on all of these?

Social recommendations didn’t start with Facebook, Twitter or Yelp or even with MySpace or Friendster. You’ve been sharing, accepting and weighing them since you could first communicate with your peers.

However, if you’re anything like me, you only follow through on a tiny amount of these recommendations. Why?

I believe the two main reasons are:

1. We don’t remember

2. We don’t care

We don’t remember because we’re busy. Never have we had as many options, and never have we been as connected with people and brands. Recommendations have already become impossible to keep up with.

As Faris Yakob so effectively puts it media space is growing as such an exponential rate that it is essentially infinite.

The same is true of content. As of January 2012, an hour of video is uploaded to YouTube every second.

It’s easy to see why we need recommendations. We cannot try everything ourselves.

We’ve always used the opinions of others to assist in decision making, and none are more important to us than our real-life connections.

Familiarity with our social groups makes recommendations from them more valuable to us than those of strangers. We rely on past experiences with our peers for reference, but that’s not the only reason. We’re not just attracted to people who share our tastes, we’re also attracted to the tastes of our friends. People naturally want to connect with others through shared culture and experiences.

Within a social group, we might think of one person as the foodie, one person as the music expert and another as the most fashionable. The biological reason for this is that we cannot store all this information individually. If we think of ourselves as mainframe computers, these social contacts act as external hard drives, storing information that we can access as needed.

So maybe I trust Jonathan’s opinions on music but not on food. There’s no reason for me to follow all of Jonathan’s recommendations but only the ones I care about, in this case music.

There are recommendation applications for just about everything –food, online video, books, music, you name it. Before you know it you could easily have 15+ apps and probably only check a few.

So why not create a universal recommendation application? Not just for locations (foursquare) or books (Goodreads) or movies (Rotten Tomatoes) or food (UrbanSpoon). Why not create an app that works for everything, even experiences?

Sure, there’s Yelp, but it doesn’t tie into how we naturally use our social connections to make informed decisions. I don’t know whether to trust a review from “Michael T.” because I have no experience with him to reference.

A couple of these comprehensive recommendation apps exist. Stamped, backed by Google and featuring a beautiful interface, has had trouble getting off the ground. Oink, the first project from Digg founder Kevin Rose’s new venture Milk, has already folded.

What each of these lack(ed), however, is in my opinion the most important feature – the ability to follow only select categories of a person’s recommendations.

Remember, I don’t care about Jonathan’s fashion sense or his favorite restaurants. I only want his music recommendations. If my friend Caroline and I generally agree on everything, I can follow all of her recommendations.

And these recommendations are waiting for me to check at my convenience. I don’t have to worry about remembering to watch that YouTube video Ryan IM’d while I was in a meeting.

This addresses both the “don’t remember” and “don’t care” issues.

I believe the first app to solve this and gain a sizable user base will make its creators and investors very wealthy.

Facebook knows the power of real-life relationships when it comes to advertising. That’s why its ad units let you know if a friend already likes something. Think about the power of a recommendation app that knows what you like, what you’re looking for and your physical location. Think about the potential to send highly targeted messaging to users depending on these criteria and other triggers (perhaps weather conditions or time of day) and the ability to include one-click purchases.

If my friend Christian recommends his new turntable, I can find where to purchase one locally. If it’s not available locally I can purchase it directly online and have it shipped to my door, all through the app.

If Michael recommends a record, I can download it directly from the recommendation through iTunes, Insound or Amazon.

If Kate recommends a movie, I buy tickets to see it in my local theater or download the film directly to my mobile device.

Monetization is not just built in, it’s an integral part of the experience. Ads are not just messaging but a convenience service for users.

Who will be the first to crack the recommendation nut? It would seem that one of the giants like Google or Facebook would have a leg up on everyone, but Google’s continued troubles with anything social (Wave, Buzz, Google+) and Instagram’s rise to a billion-dollar app in 17 months mean it could be just about anyone if the app and user base are right.

For one day last month Amazon offered $10 gift cards for $5....

Sun, 22 Apr 2012 17:50:00 -0400

For one day last month Amazon offered $10 gift cards for $5. Responding to an email chain about ROI, a coworker asked, “What’s the ROI on this? Looks like Amazon just gave me $5 for free.”

Now this was just a conversational email but it got me thinking. Obviously, Amazon didn’t “give” him anything. He didn’t have a five-dollar bill in his hands courtesy of Amazon. In fact, he’d just given Amazon $5. But this feeling of receiving a “free” $5 was undoubtedly shared by many others. Besides the fact that he’d received nothing from Amazon, there’s an enormous difference in the company giving away five million dollars (one million cards were sold) and foregoing five million dollars of potential income.

Of course, the very next email in this chain compared the Amazon card offer to Groupon. There are several problems with this comparison. Namely, Groupon deals are generally for a specific experience whereas Amazon sells almost every product on earth.

A discount on Amazon does not devalue the brand because Amazon sells everything. It also does not devalue the specific product you might purchase because the discount is associated with Amazon and not the item you purchase.

On the other hand, a Groupon discount is directly associated with both the brand (let’s say a restaurant) and its products (the meal you eat). Regardless of whether new customers enjoy their meal, they will mentally anchor the price of their experiences with the discounted price they paid.

Another error in the comparison is that Groupon is primarily marketed to retailers as a way to gain new customers. I don’t think this was Amazon’s primary intent. I’m not sure I know anyone who’s never made a purchase from Amazon. But because you don’t buy Amazon, you buy something Amazon sells, it doesn’t matter all that much whether you’re a new customer or an existing one.

For a restaurant, however, it does. Existing clientele can take advantage of a Groupon discount just like new customers can. The next time they consider returning, they’re going to have an anchor set at that lower price. Our brains are hardwired not with gains but with losses. This is called loss aversion, and the mental trick has been confirmed in numerous studies since the late 70s, when Daniel Kahneman and Amos Tversky first coined the term. In the example of our Groupon restaurant, this means most people will see the last meal not priced at a discount but the next meal priced at a premium.

This is why many gas stations charge a “discounted” rate for paying with cash. They’re really implementing a surcharge for paying with a credit card. Because the price is anchored at the more expensive of the two, drivers see it as a discount.

Amazon also knows that many of these cards will never be redeemed. A poll of Groupon buyers last September found that 22% of Groupons purchased were never used. I wonder if any of this group thinks Groupon gave them anything… The funny part is, this is really the only “free” money in the entire discussion. For every card that’s never used, Amazon pockets $5 for doing absolutely nothing.

But Amazon’s plan doesn’t even stop there. I purchased one of the cards, so I have $10 to play with, $5 of it being “free.” On the surface, it seems that I should just buy a $10 item. So I add that to my cart and start the check-out. Oh yeah… now I’ll need another $15 to reach the minimum price to receive the Super Saver shipping discount. No biggie; there are lots of things I need that I could buy from Amazon. Next thing I know, my cart totals $37.

Again, I don’t believe Amazon was after new customers. What they were after is purchases that you likely would have made elsewhere. And just maybe you’ll remember how convenient it is to order online and have things magically appear at your doorstep.

This reminds me… I have $10 to spend.