Instagram Direct and the crowded messaging space

Instagram found a place in our hearts as an app for broadcasting moments. Take a photo (or later a video) and share it publicly, and specifically, to people who follow you. Now Instagram wants us to use it for private sharing. Take a photo or video and send it to one person or a small group. Those are entirely distinct species of communication.

Convincing a userbase to break their ingrained behavior pattern and use an app for something completely different is a tough sell. And it’s a lot tougher if that “something different” is actually “something you can do elsewhere”.

If I want to share a photo with a few friends, I can text it, email it, or Facebook message it. These each let me get friends’ reactions and have a conversation around the photo. In fact, they’re all more flexible than Instagram Direct in that I can reply with another photo — the absence of that feature is my biggest gripe about IDG. It also suffers from a creation interface that’s too slow for sharing to such a limited audience. Filtering and adding a witty caption bog down the flow, making Instagram Direct too time intensive to be a rapid-fire visual communication tool.

And of course, if I want to private message someone a photo or video, I can Snapchat them. Snapchat has carved out a purpose and following with ephemerality — something that’s actually different. I can’t send a photo that disappears with any other major messaging service, so I go to Snapchat when I have something silly or racy to share.

So really, the problem is that Instagram Direct is too different from Instagram, and not different enough from everything else.
 

Good piece from Josh Constine on a key problem facing Instagram Direct.

Allowing video to be uploaded was a natural extension for Instagram. Instead of broadcasting photos, you were broadcasting video. It felt comfortable right away. 

Instagram Direct felt immediately strange. I'd never used Instagram as a one-to-one photo sharing tool, and the people I'd chosen to follow on the service were not ones I'd chosen with one-to-one sharing in mind. My Instagram graph is much smaller than my graph on other social graph services because I'd chosen who to follow based on who I wanted to see photo broadcasts from, and I think most people who follow me there were looking for my photo broadcasts as well. It will always be easier for me to share photos one-to-one through another app because my graphs are larger there and because, as Josh notes, the interaction flow is much faster.

I now use the following multitude of apps to message other people on an almost daily basis: email, Twitter, Twitter DM, Facebook, WhatsApp, Line, Snapchat, iMessage, SMS. One would think using so many different messaging apps would be annoying, that the shape of social graphs would see one of these services winning out through network effects.

But now that all of these messaging apps can easily piggyback off of my mobile contact book to easily find the people I already know on those services, the switching costs are very low. The interfaces are all easy to learn and largely equivalent (the other person's message in a chat bubble on one side of the screen, mine on the other side) so the learning curve is also negligible. Finally, since my phone sends me a notification anytime I receive a message through any of these services, I can launch any of the apps with one click and tap out a reply just as easily as I would on the next app.

For those reasons, It's not clear this has to be a winner-take-all space. That makes it challenging for investors in this area. If some other messaging app came along that was somewhat better and some of my friends flocked to it, I could switch in no time, and if for some reason one of these apps became unfashionable, I could delete it without too much regret.

Hierarchy of innovation

Nicholas Carr hypothesizes that we're seeing a stagnation in transformative innovation because we've shifted towards the top of a sort of Maslow's hierarchy of innovation.

As with Maslow’s hierarchy, you shouldn’t look at my hierarchy as a rigid one. Innovation today continues at all five levels. But the rewards, both monetary and reputational, are greatest at the highest level (Technologies of the Self), which has the effect of shunting investment, attention, and activity in that direction. We’re already physically comfortable, so getting a little more physically comfortable doesn’t seem particularly pressing. We’ve become inward looking, and what we crave are more powerful tools for modifying our internal state or projecting that state outward. An entrepreneur has a greater prospect of fame and riches if he creates, say, a popular social-networking tool than if he creates a faster, more efficient system for mass transit. The arc of innovation, to put a dark spin on it, is toward decadence.

One of the consequences is that, as we move to the top level of the innovation hierarchy, the inventions have less visible, less transformative effects. We’re no longer changing the shape of the physical world or even of society, as it manifests itself in the physical world. We’re altering internal states, transforming the invisible self. Not surprisingly, when you step back and take a broad view, it looks like stagnation – it looks like nothing is changing very much. That’s particularly true when you compare what’s happening today with what happened a hundred years ago, when our focus on Technologies of Prosperity was peaking and our focus on Technologies of Leisure was also rapidly increasing, bringing a highly visible transformation of our physical circumstances.

If the current state of progress disappoints you, don’t blame innovation. Blame yourself.

More on Vegas and yield

I wrote last week about learning from Las Vegas and its ability to maximize yield from its flow of visitors.

Recommended by Alexis Madrigal and Tyler Cowen, the book Addiction by Design: Machine Gambling in Vegas covers much of that topic and more in a really gripping fashion. Given how much time we all spend plugged into the internet through our devices now, it's a very timely and important issue. I'm about a quarter of the way through the book and am, pun intended, addicted.

New knee ligament

Doctors have discovered a new knee ligament, the anterolateral ligament. It doesn't seem possible that with years of medical research and millions of cadavers studied and knee surgeries performed that it would be possible to discover a new knee ligament, but there you go.

Whether a similar process occurs in living people who injure and don’t treat an A.L.L. — because they don’t know they have one — is unknown, Dr. Claes said, but is potentially the weightiest question raised by this new research. “We think that it’s quite likely many people who tear an A.C.L. also tear an A.L.L,” he said, and that lingering injury or weakness in this overlooked ligament could leave joints unstable.

But at the moment, that possibility is speculative, although Dr. Claes said that he and his colleagues had re-examined scans of some of the knees that they had operated on to repair A.C.L. injuries and identified concomitant A.L.L. tears in many of them.

He and his colleagues have begun planning and practicing surgical procedures for treating A.L.L. tears, but at the moment, so much remains unknown about the ligament, including whether it can heal without surgery.

I tore my ACL, MCL, and meniscus in one basketball incident, and now I'm wondering if I still have an ALL or if it's just dangling there. Someone should make sure Derrick Rose's ALL is in good shape.

Big data and price discrimination

Adam Ozimek speculates that Big Data might bring about more price discrimination.  First degree price discrimination has always been a sort of business holy grail, but it was too difficult to get enough information on the shape of the price-demand curve to make it so.

For some time now, though, this has no longer been the case for many companies, and in fact one company did try to capitalize on this: Amazon.com. I know because I was there, and the reason that was a short-lived experiment is a real world case study of how the internet both enables and then kneecaps this type of price discrimination.

Amazon, until then, had one price for all customers on books, CDs, DVDs (this was the age before those products had been digitized for retail sale). A test was undertaken to vary the discount on hot DVDs for each customer visiting the website. By varying the discount from 10% up to, say, 40%, then tracking purchase volume, you could theoretically draw the price-demand curve with beautiful empirical accuracy. 

Just one catch: some customers noticed. At that time, DVDs were immensely popular, selling like hotcakes, and the most dedicated of DVD shoppers perused all the online retail sites religiously for the best deals, posting links to hot deals on forums. One customer posted a great deal on a hot DVD on such a forum, and immediately some other respondents replied saying they weren't seeing the discount.

The internet giveth, the internet taketh away. The resulting PR firestorm resulted in the experiment being cancelled right away. Theoretically, the additional margin you could make over such price discrimination is attractive. But the idea that different customers would be charged different prices would cause such distrust in Amazon's low price promise that any such margin gains would more than offset by the volume of customers hesitating to hit the buy button.

Ozimek notes this: "The headwind leaning against this trend is fairness norms." What's key to this is that the internet is the world's most efficient transmitter of information, and while it enables a greater degree of measurement that might enable first degree price discrimination, it also enables consumers to more easily share prices with each other. This greater transparency rewards the single low price strategy.

It's not a coincidence, in my mind, that Apple fought for a standard $0.99 per track pricing scheme with the music labels while Amazon fought the publishers for a standard $9.99 pricing for Kindle ebooks. Neither Amazon or Apple was trying to profit on the actual ebooks or digital music retail sales (in fact many were likely sold at break-even or a loss), they were building businesses off of the sale of complementary goods. In the case of Amazon, which is always thinking of the very long game, there are plenty of products it does make a healthy profit off of when customers come to its site, and getting users to invest heavily into building a Kindle library acted as a mild form of system lock-in. In the case of Apple, it was profiting off of iPod sales.

In the meantime, second and third order price discrimination continues to exist and thrive even with the advent of the internet so it's not as if the pricing playbook has dried up.

A skeptic might counter: didn't Ron Johnson get fired from J. C. Penney for switching them over to an everyday low price model? Didn't their customers revolt against the switch from sales and coupons and deals you had to hunt down? 

Yes, but everyday low pricing isn't a one-size-fits-all pricing panacea (as I wrote about in reference to the Johnson pricing debate at J.C. Penney). For one thing, there is path dependence. Once you go with a regular discount/deal scheme, customers create a mental price anchor that centers on that discount percentage and absolute price. It's hard to lift an anchor.

J. C. Penney was trying to go from a heavy sale-driven pricing scheme to an everyday low pricing model, and that's an uphill, unmarked path. Only the reverse path is paved. It's not clear whether the switch would have worked in the long run. Johnson ran out of runway from his Board soon after he made the switch and revenues declined. 

Everyday low pricing tends to work best when you're selling commodities since those items are ones your customers can purchase many places online. At Amazon we were far more interested in dominating one crucial bit of mental math: what website do I load up first if I want to buy something? We were obsessed with being the site of first resort in a consumer's mind, it was the core reason we were obsessed with being the world's most customer-centric company. Anything that might stand in the way of someone making a purchase, whether it be prices, return policy, shipping fees, speed of delivery, was an obstacle we assaulted with a relentless focus. On each of those dimensions, I don't think you'll find a company that is as customer-friendly as Amazon.com.

Ultimately, customers have a hard time figuring out intrinsic value of products, they're constantly using cues to establish a sense of what fair value is. Companies can choose to play the pricing game any number of ways, but I highly doubt Netflix and Amazon will choose to make their stand on the first order price discrimination game. There are many other ways they can win that are more suited to their brand and temperament.

Still, the peanut gallery loves to speculate that Amazon's long term plan is to take out all of its competitors and then to start jacking up prices. A flurry of speculation that the price hikes had begun spun up in July this year after an article in the NYTimes: As Competition Wanes, Amazon Cuts Back Discounts. After the NYTimes article hit, many jumped on the bandwagon with articles with titles like  Monopoly Achieved: An invincible Amazon begins raising prices.

If you read the NYTimes article, however, the author admits "It is difficult to comprehensively track the movement of prices on Amazon, so the evidence is anecdotal and fragmentary." But the article proceeds onward anyhow using exactly such anecdotal and fragmentary evidence to support its much more certain headline. 

Even back when I was at Amazon years ago we had some longer tail items discounted less heavily than bestsellers. However, pricing the long tail of books efficiently is not as easy as it sounds, there are millions of book titles, and most of the bandwidth the team had for managing prices was spent on frontlist titles where there was the most competitive pressure. All the titles listed in the NYTimes article sound to me like examples of long tail titles that were discounted too aggressively for a long period due to limited pricing management bandwidth and are finally being priced based on the real market price of such books. Where in the real world can you find scholarly titles at much of a discount?

The irony is that the authors cited in the article complain their titles aren't discounted enough, while publishers ended up in court with Amazon over Amazon discounting Kindle titles too much. This is to say nothing of the bizarre nature of book pricing in general, in which books seem to be assigned retail prices all over the map, with the most tenuous ties to any intuitive intrinsic value. The publishers set the retail price, then Amazon sets a price off of the retail price. If the publishers wants the discount on their books to be greater they could just increase the retail price and voila! The discount would be larger.

To take another category of products, DVDs, soon after we first launched the DVD store, long tail title like Criterion Collection DVDs were reduced from a 30% discount to a 10% to 15% discount. But just now, I checked Amazon, and most of its Criterion DVDs are discounted 25% or more. If I'd taken just that sample set I could easily write an article saying Amazon had generously decided to discount more heavily as part of its continued drive to return value from its supply chain to customers.

Could the net prices on Amazon be increasing across the board? I suppose it's possible, but I highly doubt that Amazon would pursue such a strategy, and any article that wanted to convince me that Amazon was seeking to boost its gross margins through systematic price hikes would need to cite more than just a few anecdotes from authors of really long tail books. 

It will remain a tempting narrative, however, because most observers think it's the only way for Amazon to turn a profit in the long run.

However, that's not to say big data hasn't benefitted them both in extraordinary ways. Companies like Amazon and Netflix know far more about each of its customers than any traditional retailer, especially offline ones, because their customers transact with them on an authenticated basis, with credit cards. Based on their customers' purchase and viewing habits, both companies recommend, better than their competitors, products their customers will want.

Offline retailers now all want the same type of data on their customers, so everyone from your local drugstore or grocery store to clothing retailers and furniture stores try to get you to sign up for an account of some sort, often by offering discounts if you carry a free membership card of some sort.