From Ben Thompson’s post – “The State of Consumer Technology at the End of 2014″
While the introduction of the iPhone seems like it was just yesterday (at least it does to me!), we are quickly approaching seven years – about the midway point of this epoch, if the PC and Internet are any indication.4 I sense, though, that we may be moving a bit more quickly: the work/productivity and communications applications have really come into focus this year, and while the battle to see what companies ride those applications to dominance will be interesting, it’s highly likely that the foundation is being layed for the core technology of the next epoch:
- Wearables is a possibility, and it certainly seems that Apple is trying to accelerate the category with their ambitious Apple Watch rollout. However, no matter how good the Apple Watch is, I’m not sure it’s an epoch definer, especially if it cannot truly standalone
- Bitcoin is a definite possibility, particularly if there ends up being a “tick-tock” to epochs: device (PC), then protocol (Internet), device (smartphone), then protocol (Bitcoin). Blockstream, an attempt to create sidechains for non-monetary applications that run on top of Bitcoin, is particularly interesting in this regard
- Both of the mobile applications that I identified could be core technology for the next epoch: were Uber to become ubiquitous, could businesses be built on top of it? What would such an operating system look like? An out-there idea to be sure, but in the realm of possibility.
More likely is that the messaging services become so dominant that they render the underlying mobile platform unimportant. This too would be similar to the effect of the Internet on the PC: the biggest reason the Mac was able to make a comeback from near death was because the Internet – and web apps – ran everywhere. It didn’t matter what browser6 or OS was on your actual PC. Similarly, if all essential apps and servers are routed through your messaging service, then the underlying OS – whether iOS or Android – is increasingly irrelevant. In fact, I strongly believe this is the future in China in particular, one more reason why Apple is investing so strongly in non-tangible qualities like fashion.
In response, Fred Wilson offer’s his perspective on the core technologies critical to defining “What’s Next”:
Ben’s framework is roughly similar to ours but his conclusions are a bit different as follows:
1) I would substitute personal mesh for wearables
2) I would substitute the blockchain stack for bitcoin
3) I would bet on messenger as the next mobile OS over anything else. We have already seen that happen in China.
Originally posted on Gigaom:
“Disruption” is one of the most overhyped concepts of the last ten years. A Google Trend search for “disruptive innovation” shows a steeply rising graph, and you can hardly open a professional news website without reading stories about whole sectors being disrupted. Given that “business as usual” is apparently undergoing a profound transformation, how this will impact the people doing the actual work in our economy? One logical consequence is that the way people work and earn money will also radically change. How this will be different is a direct result of the new dominant organization model that is currently emerging.
What do YouTube, Airbnb, and bitcoin have in common that distinguishes them from CNN, Hilton Hotels, and the average bank? The answer is that the former are all platforms. We are witnessing the death of the decades-old industrial organization model, which is being replaced by the organization model of the…
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“Personal data isn’t property.
It’s as much a part of you as your eye color, the way your heart calms when you see beauty, and your world view.
It may not be inside your skin but that doesn’t make it any less you.
It is you moving through time and space. It’s you in action and asleep. It’s you interacting with people. It’s you thinking aloud and witnessing the world. It’s your backup brain, your legacy, your self.
It’s you. ”
Professors Vineet Kumar, Clarence Lee and Sunil Gupta have been working on understanding the economic dynamics of freemium pricing by looking at customer behavior; their co-authored paper and an article by Kumar in the Harvard Business Review shed light on how companies can maximize profit, get upgrades and encourage referrals.
In a recent interview, Kumar says he has found “patterns,” in the data, although he is reluctant to say they can draw actual conclusions. “The shape of the pattern may change a little based on the setting,” says Kumar. “But what I tried to draw is generalizable and applies to most freemium companies.”
As companies make decisions about how their freemium products are designed and priced, they should consider the following:
- When your product is not attracting enough new users, it means “your free offers are not compelling enough and you need to provide more or better features free.”
- When your product generates lots of sign-ups, but few decide to pay, it means “your free offerings are too rich and it’s time to cut back.”
- When customers don’t understand why they should upgrade, it’s going to be tougher to move people to the paid product. What to do? Kumar gives the example of LinkedIn LNKD -0.57%, where he says “the advantages of upgrading are murkier” than they should be. He believes the company could monetize more users if this was corrected.
- When your conversion rate is too high, you may not be attracting enough trials because “your free product is not very compelling, which will limit your potential acquisitions.”
- Early adapters are less price sensitive than later adapters. Rates of conversion from free to paid users vary over the life cycle of the product, with early adapters to the product probably converting at a much higher rate than later adapters.
- Companies will notice the pattern of a declining conversion rate — initially. When you have “an introduction of new features, the conversion rate starts picking up.” Kumar gives an example using Hulu. They probably see conversion rates increasing when they’ve “introduced a new show, or new episodes of a show that are in the premium version, not in the free. It’s not surprising when you have more of a value proposition from a consumer’s perspective it increases your upgrade probability.”
- Referral bonus programs – where current customers are rewarded for referring new customers– are effective, but if they are too generous, the program won’t encourage multiple referrals.
From James Surowiecki article titled – “In Praise of Efficient Price Gouging”
“In the four years since the car service Uber launched, it has been beset by criticism from myriad groups, including city officials annoyed by its sometimes cavalier attitude toward regulation and taxi companies annoyed by increased competition. Some of the harshest criticism, though, has come from an unlikely place: Uber’s own customers. Thanks to its reliance on what it calls “surge pricing”— meaning that during times of high demand, Uber raises its prices, often sharply—the company has been accused of profiteering and exploiting its customers. When Uber jacked up prices during a snowstorm in New York last December, for instance, there was an eruption of complaints, the general mood being summed up by a tweet calling Uber “price-gouging assholes.”
Uber’s algorithm (which it has been refining since 2011) is the company’s greatest asset and most significant innovation, allowing it to find the price that will attract drivers—whom, as independent contractors, it can’t order onto the road—without alienating customers.
The basic reality of Uber’s business model is that when people want a ride the most, it’s likely to be the most expensive. This will always be irritating, just as exorbitant prices for last-minute airline tickets are irritating. But over time, surge pricing will also become more familiar and less surprising.
Utilities are now starting to use dynamic pricing for electric power, which can help prevent blackouts at times of high demand and promote energy conservation more generally. A new startup called Boomerang Commerce, which is led by former Amazon engineers, has been helping online retailers set prices dynamically. Dynamic pricing is the future, even if the road to get there will be bumpy.”