Hyperscale Public Clouds: If You Can't Beat 'Em, Join 'Em

James Staten
With Amazon Web Services and Microsoft Azure now on greater than $2 billion annual run rates and expanding their application services nearly weekly, it’s starting to look tougher than ever for traditional hosters, enterprise cloud players and managed service providers to compete against them. When you just can’t see how to win, the better option might just be not to try.
 
That seems to be the new trend in enterprise cloud vendor strategies as evidenced this week in moves by Datapipe, Google, and VMware. These moves follow similar shifts in strategy taken by Accenture, Rackspace, and others in the past quarter. The strategies acknowledge a reality that is redefining what they hoped hybrid cloud meant.
 
That reality: Hybrid means Hyperscale +.  
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You Must Solve Two People-Shaped Content Problems

Ryan Skinner

The problems of content marketing apply to you as a marketer whether you’re actually practicing “content marketing” or not.

In any enterprise, there’s a New York Times-scale amount of content getting produced.[i] And your customers are hoovering up content (from a brand or otherwise, in many channels, interchangably) and making decisions based upon it.[ii]

That means you’re in the content business. And the more customers control the purchase path, the more marketers find themselves in the content marketing business.

Which means you will be dealing with the problems content marketing creates. Two of these problems are particular to marketing teams and governance. These are best explained with analogies:

The Menu Problem – How content gets conceived and planned

The Sausage Problem – How content gets made and delivered

The Menu Problem
Marketers don’t have much experience running editorial organizations. This is best reflected in the low percentage of marketers who report that they follow a content marketing strategy.[iii]

A strategy is necessary.[iv] And no one is taking the responsibility to make one.

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Rethinking Analytics Infrastructure

Richard Fichera

Last year I published a reasonably well-received research document on Hadoop infrastructure, “Building the Foundations for Customer Insight: Hadoop Infrastructure Architecture”. Now, less than a year later it’s looking obsolete, not so much because it was wrong for traditional (and yes, it does seem funny to use a word like “traditional” to describe a technology that itself is still rapidly evolving and only in mainstream use for a handful of years) Hadoop, but because the universe of analytics technology and tools has been evolving at light-speed.

If your analytics are anchored by Hadoop and its underlying map reduce processing, then the mainstream architecture described in the document, that of clusters of servers each with their own compute and storage, may still be appropriate. On the other hand, if, like many enterprises, you are adding additional analysis tools such as NoSQL databases, SQL on Hadoop (Impala, Stinger, Vertica) and particularly Spark, an in-memory-based analytics technology that is well suited for real-time and streaming data, it may be necessary to begin reassessing the supporting infrastructure in order to build something that can continue to support Hadoop as well as cater to the differing access patterns of other tools sets. This need to rethink the underlying analytics plumbing was brought home by a recent demonstration by HP of a reference architecture for analytics, publicly referred to as the HP Big Data Reference Architecture.

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More On New Video Consumption Behaviors

Jim Nail

The press coverage of my report "Making Sense of New Video Consumption Behaviors" -- and especially the number they highlighted that 46% of the "core" TV audience watches linear TV in a typical month -- raised a lot of questions (and skepticism!) on the Research Wonks list serve. I figure if they had those questions, others might, too, so here is the response I posted there:

"The media always looks for the headline-grabbing, shocking, number and the 46% watch linear certainly qualifies. I used this number in passing to set up the report so before I address the methodology questions, let me share the core conclusion of the report: consumer video consumption behaviors are different enough across generations that planners need to break out of past planning routines and account for these different behaviors. Toward the end of the report I say:

A goal of 100 gross rating points (GRPs) against an 18-to-49 audience is merely an average across this entire audience; if the placements are skewed to linear TV, it will likely deliver too many ads to the 35-to-49 segment and not deliver enough to the 18-to-34 group.

The 46% number doesn't comment on the number of hours, and the data we capture is very broad here, but even it shows that linear is still the larger number of hours.

In the report I say that linear is the “main dish” that must be complemented with “side dishes” like streamed sources and addressable plus “desserts” like professional short-form video to present a balanced video ad diet. (Yes, I really tortured that metaphor!)

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Can’t Stop, Won’t Stop: Commerce Platform Tech Spending Grows Unabated

Michael Yamnitsky

Behind every online sale is a set of software tools to manage the shopping experience and order process: the commerce platform.

The technology itself is nothing new. Commercial software packages for digital commerce have been around for 15 years or so. However, we’ve seen commerce-related technology investments accelerate over the past couple of years. Companies are replacing legacy systems from the early 2000s with modern platforms ready to meet the demands of mobile commerce and international sales, and the buyer pool is extending from retail to virtually every industry. 

The journey isn’t quite over. Forrester expects growth in commerce tech spending to continue unabated. According to our recent forecast, we expect the US market for commerce platform technology to nearly double over the next five years, growing from $1.2 billion in 2014 to nearly $2.1 billion by the end of the decade.

Peter Sheldon and I developed this forecast to help tech vendor clients identify and assess new market opportunities. For deeper insight into the target markets most ripe for growth, we segment spending projections by target industry (i.e., retail, wholesale, pharma) and quantify the shift from legacy (i.e., on-premises) to modern (i.e., SaaS/hosted) solutions. For more details, see the recent report we’ve published around the forecast results.

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Mobile BI Success: Having The Right Technology Helps, But Isn't Enough

Martha Bennett

Between 2012 and 2014, mobile BI adoption shot up: Forrester survey data shows that the percentage of technology decision-makers who make some BI applications available on mobile devices has nearly quadrupled, and the percentage who state that BI is delivered exclusively via mobile devices has risen from 1% in 2012 to 7% in 2014. While this clearly demonstrates that mobile BI is gaining traction, the actual mobile BI adoption picture is rather more nuanced. Our ongoing research and client interactions show that mobile BI adopters fall into three overall groups; some organizations

  • Really ‘get’ the transformational potential of mobile BI. They are the ones who understand that mobile BI is about much more than liberating reports and dashboards from the desktop. They focus on how data can be leveraged to best effect when in the hands of the right person at the right time. If necessary, they’re prepared to change their business processes accordingly. For those companies, mobile BI is an enabler of strategic goals, and deployment is a journey, not an end in itself.
  • Make mobile BI available because it’s the right thing to do, or they’ve been asked to.  Many of these organizations are reaping considerable benefits from their mobile BI implementations, and the more far-sighted of them are working on how to move from the tactical to the strategic. Equally, many are trying to figure out where to go from here, in particular if the initial deployment doesn't show a clear benefit, let alone return on investment. 
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Digital skills are the golden ticket in 2015

Martin Gill

It’s no secret that digital skills are in short supply. In fact, while some three quarters of executives tell us their firm now has some form of digital strategy (however rudimentary), a paltry 16% say they have the skills and capabilities necessary to deliver it. Even though the average eBusiness team’s staffing budget is growing year on year, finding the skills and capabilities to execute on a digital strategy is becoming harder and harder.

Our latest annual organizational and staffing backs this up. Our September 2014 Global eBusiness And Channel Strategy Professional Online Survey reveals:

  • eBusiness Teams Have An Average Of 95 Employees. The average eBusiness team has 95 team members. As would be expected, the larger the worldwide revenue, online revenue, or total employee count is, the larger the eBusiness team is.
  • Technology And Customer Experience Are Still The Hardest Roles To Fill. Technology, customer experience, and business analytics are the hardest jobs to hire for.  Additionally, technology and customer experience are the most outsourced, and technology is the most understaffed.  
  • The Digital Skills Gap Continues To Widen. Digital transformation brings an increased level of responsibility for eBusiness employees who are often leading the charge for company-wide transformation in addition to handling day-to-day operations. As all business becomes digital business, eBusiness teams will have an increasingly difficult time sourcing talent. 
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Time To Reset Your Knowledge Of Big Data Ecosystems In China

Charlie Dai

At the China Hadoop Summit 2015 in Beijing this past weekend, I talked with various big data players, including large consumers of big data China Unicom, Baidu.com, JD.com, and Ctrip.com; Hadoop platform solution providers Hortonworks, RedHadoop, BeagleData, and Transwarp; infrastructure software vendors like Sequotia.com; and Agile BI software vendors like Yonghong Tech.

The summit was well-attended — organizers planned for 1,000 attendees and double that number attended — and from the presentations and conversations it’s clear that big data ecosystems are making substantial progress. Here are some of my key takeaways:

  • Telcos are focusing on optimizing internal operations with big data.Take China Unicom, one of China’s three major telcos, for example. China Unicom has completed a comprehensive business scenario analysis of related data across each segment of internal business operations, including business and operations support systems, Internet data centers, and networks (fixed, mobile, and broadband). It has built a Hadoop-based big data platform to process trillions of mobile access records every day within the mobile network to provide practical guidelines and progress monitoring on the construction of base stations.
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Digital Initiatives Expose Gaps In Customer Analytics Capabilities

Michael Barnes

In my last blog post I outlined Forrester’s key customer insights (CI) predictions for 2015. Now I’d like to drill down into some of the key barriers to CI effectiveness we’re seeing among Asia Pacific-based organizations. This content was pulled from my recently published report, which Forrester clients can access here.

Core competencies of effective CI pros have typically centered on customer segmentation and campaign performance measurement. When extending these capabilities to digital marketing strategies, the goal is typically to enable more effective customer acquisition and onboarding by extending reach. In other words, digital innovation often simply means “better campaigns.”

But what happens once that process is complete? It’s not enough to have a world-class digital capability for acquiring new customers. Empowered customers expect the same type of seamless experience, improved efficiency, and heightened responsiveness in all subsequent interactions with your brand.

So why so many firms struggling to realize the full potential of customer analytics to effectively serve and retain their customers? I’ll give you four reasons:

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How To Win A Forrester Groundswell Award For Social Reach Marketing

Nate Elliott

We’re now accepting entries for the 2015 Forrester Groundswell Awards. This is our chance to recognize the very best social marketing programs from the past year, and we’d love to give an award to you for your best work. Our deadline for entries is February 20, 2015.

My favorite category is Social Reach Marketing — where we celebrate the best word-of-mouth and social advertising programs. If you used social media to reach new audiences and generated awareness, this is the category for you.

So what’s the key to winning a Forrester Groundswell Award for Social Reach Marketing? It’s not just a question of whether your word-of-mouth program or your social ads reached lots of people — you need to prove your efforts had a business impact on the people they reached.

Our 2014 winners in this category offer perfect examples:

  • B2C Social Reach winner Morningstar Farms increased favorability, trial, and intent to purchase. MorningStar Farms wanted to introduce its meat-free products to new audiences — a classic use case for social reach marketing. So they worked with House Party, Inc. to identify 3,000 influencers and sent them a "party pack" so they could host meat-free barbecues for friends and family. The social activity around the barbecues created a further 29 million impressions that reached 10 million people. But this program didn’t win an award just because it had big reach — it won because that big reach moved people closer to the point of purchase. Specifically, the parties themselves generated 128,000 trials of MorningStar Farms products, and the brand saw a 40-point lift in favorability and purchase intent from partygoers.
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