Artificial intelligence (AI) is real, albiet maturing slowly. You experience it when you talk to Alexa, when you see a creepily-targeted online ad, and when Netxflix turns you on to Stranger Things. Oh yea, and that self-driving car over there is AI super-powered! AI is indeed cool, but many are scared about how it ultimatley may impact society. Stephen Hawking, Elon Musk, and even the Woz warned that "...artificial intelligence can potentially be more dangerous than nuclear war." In a nutshell, they are concerned about AI that may evolve to outsmart humans and kill people - a valid concern. But, I have another more terrifying concern that would likely be an insidious precursor to runaway, killer AI.
Container technologies allow enterprises to create highly differentiated apps and services faster, with better quality and geographic reach, to create compelling customer experiences. They have quickly become an important element of digital business transformation for EA pros because they promise faster software delivery, tremendous scale, higher resiliency, greater flexibility, and broader implementation options. Everything about enterprise app infrastructures, development styles, and architectures is changing, and containers play a key role in each area.
However, Forrester’s TechRadar™ for business technology infrastructure found that containers and container management technologies are still in the Creation stage, meaning that some container components and management tools are immature and changing quickly. Companies must navigate a complex landscape of technology components to build, package, and deploy containers. To help tech management pros accelerate cloud evolution, I’ve recently published a report with Dave Bartoletti focusing on the software landscape for each layer in a typical container management software architecture. Some of the key takeaways:
It’s Groundhog’s Day, when a sleepy landpig emerges from his little mancave and entertains questions from the press about astronomical phenomena!
As good a day as any to share a few content trends where we at Forrester expect to see considerable acceleration this year.
Here are your 6 content trends and one wannabe-trend that won’t trend in 2017.
The first megatrend
Direct-to-consumer pushes CPG out of the brand advertising comfort zone
Direct-to-consumer plays by the CPG giants, and even more so the CPG small guys, will put substantial pressure on brand marketers to invest in content and experiences that drive action. That means more content for richer websites, email programs, product documentation, and paid and unpaid executions. Mondelez’s made a $10 billion bet on this, and Unilever’s acquisition of Dollar Shave Club signals their interest in more direct subscription-driven sales.
What does it mean?
Digital agencies with strong content chops and some ecommerce nous will be the winners, as brand teams ramp up their direct marketing capabilities.
The second gigatrend Stunts and experiential executions set higher bars for hero and community content
Up until now, paid services like Netflix, Amazon Prime, and HBO have dominated US online video viewing, particularly for long-form, TV-style content. Uptake of ad-supported, TV-style online video has been slower; traditional TV providers control much of this content, and they’ve been cautious about making their programming available outside the lucrative TV bundle. Even if many viewers want to cut the cord, they may not follow through as they realize they cannot get all the content they want. YouTube, of course, has a massive ad-supported online video business that has been growing healthily according to our calculations. However, even YouTube falls short of Netflix in terms of downstream bandwidth consumption, and its estimated ad revenue is only a small fraction of traditional TV ad revenue. For online video ad spend to show meaningful growth, consumer-generated or web-only content won’t be enough. A truly robust online video ad market will require the migration of traditional TV content to digital platforms.
This migration appears to be gathering momentum. Recently, we have seen a number of developments that could drive the uptake of ad-supported online video and that indicate that 2017 could be the year when ad-supported online video starts to make a splash.
Live streaming captures younger eyeballs in particular. Millennials are the first to embrace streaming in all of its forms, appealing to marketers trying to capture fragmented audiences. Forrester’s Consumer Technographics(R) data reveals that 63% percent of Millennials (age 18-36) watch 5 or more hours of TV shows, films or video online. This is a significant percentage of their TV time so marketers must learn how to reach this audience outside of linear TV types of viewing.
The NFL’s proven content sweetens the package. NFL games garner high viewership and in a typical week dominate the top 10 most-watched shows, especially among the coveted 18-49 age demographic. And primetime programming, especially sports content, is one of the most popular conversation topics on Twitter.
In the days of old, not very long ago, release cycles were measured in years —organizations were using “on-time” and “on-budget" as the mantra for project efficacy. Business today is compelled to deliver business technology in cycles of hours, or days. Faster cycles render not only tradition “waterfall” processes and silo based IT obsolete, it also renders traditional metrics ineffective! These arcane metrics no longer deliver the visibility and granularity tech pros need to fine-tune their delivery capability. The mission has transitioned to rapidly deliver high quality, high value solutions. For all, this is a significant shift from the past, when the main points of focus were schedule, cost, and efficiency. Modern software metrics — speed, quality, and value — are based on continuous feedback from business partners and customers.
Apple announced its Q1 FY2017 earnings yesterday. They sold a lot of iPhone 7’s and beat sales estimates. More interesting to me though was the news on Apple Pay … the number of Apple Pay users tripled in the past year, with hundreds of millions of transactions and billions of dollars in purchases in the December quarter alone. This represents nearly 500% increase for Apple Pay transactions year-on-year!
Forrester data shows that 11% of online consumers have used Apple Pay. Among those, almost ⅔ use Apple Pay all the time or frequently when it is available.
For full disclosure, I love Apple Pay - especially using it on my Apple Watch.
(Timing markets has never been in my golden gut; anticipating technology relevance is. Watches and body cameras, for example, will never be mainstream, nor will drones or curved TVs. Ping me and I'll explain why. Or do this cosmo quiz to make your own prediction for consumer technology.)
As reported (and powerfully visualized by CB Insights), Unicorns are crowding the market. Look at the density of Unicorn logos starting in February 2014, three short years ago. It's astounding. Why this proliferation? Why now? Why so dramatic?
I believe three things have created and propped up the Unicorn valuations of tech startups:
If you're an investor, there's no place better to put your cash. The returns on real assets are small. The returns on exuberance (like big fancy new houses) can be large. So investors have lots of cash to place bets on startups that might just pop.)
The recent election, with a hoped-for impact of deregulation and infrastructure spending, left the market energized about the potential for growth. The market's up. So the potential for healthy exits and IPOs (even ones without a clear revenue growth model such as Snap's) is up.
We followed a rigorous, academic approach that started with the premise that improving CX drives customer loyalty. Using our Customer Experience Index (CX Index™) survey questions about customers’ loyalty to and spending with a particular brand and combining them with industry-level numerical assumptions, we answered the following question: How likely is a customer to stay with your brand, or spend more, or recommend you to others — and what would that be worth to your organization in dollars and cents?
For each customer, we calculated a loyalty-based revenue potential and a CX Index score. Calculating these numbers at the individual level allows us to track the relationship between CX and revenue throughout the entire range of CX Index scores and develop models to describe the nuances of how CX drives revenue in a particular industry. With these models, we can predict the revenue associated with a brand’s CX improving — or even deteriorating.
We tested several models to find the “shape” that best describes the data. We found that the relationship between CX and revenue potential tends to follow three main shapes:
Linear. CX and revenue move in lockstep. Whether you improve a poor experience, a mediocre experience, or a good experience, the impact on revenue will be the same.