Chinese organizations should leverage the benefits of private cloud to address emerging requirements such as more agile technology services to improve customer engagement. However, determining which private cloud solution your company should choose is not a matter of size or market share. What’s most important is fit for purpose — your purpose. And that’s exactly what our The Forrester Wave: Private Cloud Solutions In China, Q1 2015 report helps you determine.
Charlie Dai and I spent the past six months identifying and evaluating the leading vendors in the private cloud space in China by scoring them against 24 criteria, grouped into three high-level buckets:
Current offering. A vendor’s position on the vertical axis of the Forrester Wave graphic indicates the strength of its current product offering. The key current offering criteria are cloud management and self-service access, service management and creation, automation capabilities, heterogeneity, contract terms and support, and cost.
Strategy. A vendor’s position on the horizontal axis indicates the strength of its go-to-market strategy. Forrester evaluates strategy with planned enhancements, strategic vision, third-party ecosystem, partnerships, and customer experience.
Market presence. The size of a vendor’s bubble on the chart indicates its market presence in China. Forrester evaluates market size via installed base and revenue.
CRM is the foundational building block that allows empowered consumers and connected employees to do business in ways we could not imagine just a few years ago. Historically, CRM strategies have focused around operational efficiency gains like reduced marketing costs, increased revenues from salespeople, shorter sales cycles, or better customer service productivity. Its no wonder that CRM is widely deployed in all companies – both big and small.
Every so often I check my blog stats to see what you, the reader, find most interesting - my goal is to continue to bring you great content in both my blog and my research. While I was looking back over my blog stats I thought you might like to see the top ten blog posts in case you missed any of them. But just how should I assess the top ten? Like all outcome metrics, this one is open to interpretation.
I could take the simple route and just count which posts have the most reads. But that would fail to take into account how many days it has been since the blog was published - it stands to reason that older blog posts might garner more reads. So a ranking based on the number of reads divided by the number of days the post has been online would yield a more accurate result in terms of most read post (See Table 1 - Top ten most read posts).
My colleague, Samantha Jaddou, who’s an analyst on the CX team covering the China market, is working on a report “The CFM Vendor Landscape 2015, China”. This report is to better help Forrester clients, particularly companies who operate in China, understand whom they should turn to to satisfy customer feedback management needs. She is in the middle of fielding a survey, which will be the research foundation for this report.
If your firm is interested in being included in this study to show your product and service capabilities in China in the CFM space, please consider one or both of the following:
The holiday season is one month behind us, and while the celebratory spirit has faded, the effects live on through the gifts we’ve exchanged. If you think the shiny new object you presented to your loved one had its greatest impact when she unwrapped its box, think again. Apart from the occasional toy tossed to the back of a closet, gifts may have a stronger influence on our long-term behavior and lifestyle than we might think —particularly when it comes to consumer electronics.
For example, according to Forrester’s Consumer Technographics® data, consumers who have received a tablet computer as a gift end up using traditional devices like laptops, desktops, and digital cameras less often. Qualitative insight from our ConsumerVoices Market Research Online Community reveals that sentiments of surprise and delight characterize the experience of these tablet recipients; regardless of their initial technology attitudes, most community members find the devices exceed their expectations and inadvertently change their lifestyle:
According to the National Retail Federation, consumer electronics stores saw more than $23.4 million in holiday sales in 2013 and even more by the close of 2014. However, the more interesting story is unfolding now, as consumers who have leapfrogged the purchase experience begin experimenting with —and embracing —their new devices.
Time spent on mobile is skyrocketing. Since about 80% of that time is spent on apps, many marketing leaders have quickly jumped to the conclusion that the only way to reach and engage their customers is through their own branded apps. Wrong! Here are five — often ignored — good reasons for marketing leaders to broaden their mobile approach beyond their own apps:
1. Branded apps are relevant. Yes, some of them (Starbucks, Nike, and many others) are success stories. But more often than not, branded apps don’t deliver real mobile benefits and engage only a small subset of customers. It's about time marketers connect their apps to their marketing and CRM systems to personalize and contextualize the brand experience. Marketers should launch fewer but smarter apps.
2. Apps offer real engagement opportunities. Yes, but only for a minority of apps, according to Forrester’s App Engagement Index. Several of the most engaging apps — Instagram, Pinterest, Snapchat, Twitter, and WhatsApp — either don’t have or only recently introduced mobile advertising offerings. Marketers must identify the overlap between the most engaging apps and the most popular apps among their brand’s customer base. Then they have to mix content and context to tell a story that is relevant to customers in their mobile moments. It will not be about ads but about sparking a conversation instead of broadcasting a marketing message. Marketers should select the most promising partners evolving their apps as marketing platforms.
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.
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.
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.
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!)