I recently wrote about the need for IT organizations to embrace SaaS to maintain relevance and help drive business value. This quarter, I’ve set my sights on IaaS. In my forthcoming report, “IaaS Adoption Trends In Asia Pacific”, I explain in detail why my advice remains the same.
Internal IT resistance to expanding IaaS usage based on security, data management, and availability/performance concerns are certainly valid. But project-driven, opportunistic IaaS usage will continue to grow across the region as business decision-makers rationally seek out public cloud-based services that meet needs not met by internal IT.
IT decision-makers failing to consider all service-provisioning options will see their credibility wane and their control usurped by the inevitable emergence of shadow IT, driven by clear business demand. On the positive side, as usage expands internally, I’ve already seen Asia Pacific organizations begin viewing IaaS as a mechanism to fuel innovation based on easy access to cloud-based compute resources. Put another way, IaaS supply is beginning to fuel increased demand.
Some key recommendations for encouraging IaaS-related innovation while minimizing risks:
I just finished my new report on the Agile testing tools landscape. I’ll point Forrester readers to it as soon as it publishes. But there are few things that have struck me since I took over the software quality and testing research coverage at Forrester and which I would like to share with you in this preview of my findings of the testing tools landscape doc.
My research focus area was initially on software development life cycles (SDLCs) with a main focus on Agile and Lean. In fact, my main contribution in the past 12 months has been to the Forrester Agile and Lean playbook, where all my testing research has also focused. Among other reasons, I took the testing research area because testing was becoming more and more a discipline for software developers. So it all made sense for me to extend my software development research focus with testing. But I was not sure how deep testing was really going to integrate with development. My concern was that I’d have to spend too much time on the traditional testing standards, processes, and practices and little on new and more advanced development and testing practices. After 12 months, I am happy to say that it was the right bet! My published recent research shows the shift testing is making, and so does the testing tool landscape document, and here is why:
“Search is often your last chance to keep a customer on your website before they go elsewhere to find the same product or content.” I love this quote (courtesy of the president of a digital agency). It shows us exactly why we should think of site search beyond its status as an IT-funded afterthought. Your customers need search in order to find a named item or piece of content. Or they rely on search because they can’t find what they need through the site’s menu structure. When looking to source site search solutions, organizations are faced with many options from mostly niche players and a few large vendors. How do you make sense of this? I recommend you begin narrowing the site search field by asking yourself these four key questions:
Do your existing tools have sufficient bundled search capabilities? Many web content management and eCommerce vendors have embedded open source search capabilities into their core product (e.g., IBM, Intershop, hybris, Ektron, Sitecore) and some have innovated search experiences based on the open source framework. This makes it potentially unnecessary to buy a standalone search solutions. But be careful. For some solutions, embedded search only indexes and processes customer queries. It doesn’t allow for more advanced search features like merchandiser consoles or business user support for different ranking models.
Good customer service is the result of the right attention to strategy, business processes, technology, and people management. This seven-part series focuses on customer service technology and explains the what, why, how, and when of the technology. Let’s start at the beginning: What is customer service technology?
The contact center technology ecosystem for customer service is a nightmare of complexity. At a high level, to serve your customers, you need to:
Capture the inquiry, which can come in over the phone, electronically via email, chat, or SMS, and over social channels, like Twitter, Facebook, or an interaction escalated from a discussion forum or a Web or speech self-service session.
Route the inquiry to the right customer service agent pool.
Create a case for the inquiry that contains its details and associate it with the customer record.
Find the answer to the inquiry. This can involve digging through different information sources like knowledge bases, billing systems, and ordering databases.
Communicate the answer to the inquiry to the customer.
Append case notes to the case summarizing its resolution and close the case.
The Obama 2012 campaign famously used big data predictive analytics to influence individual voters. They hired more than 50 analytics experts, including data scientists, to predict which voters will be positively persuaded by political campaign contact such as a call, door knock, flyer, or TV ad. Uplift modeling (aka persuasion modeling) is one of the hottest forms of predictive analytics, for obvious reasons — most organizations wish to persuade people to to do something such as buy! In this special episode of Forrester TechnoPolitics, Mike interviews Eric Siegel, Ph.D., author of Predictive Analytics, to find out: 1) What exactly is uplift modeling? and 2) How did the Obama 2012 campaign use it to persuade voters? (< 4 minutes)
This year’s Customer Experience Forum just wrapped up, and two days and 20 client meetings later I’m back at Forrester’s headquarters. I’ve had a moment to think about the questions clients asked me, and as an application development and delivery (AD&D) analyst, it was great to see that attendees were interested in bridging the customer experience strategy with their technology strategy and decision-making process.
When thinking about those issues, the top three questions I was asked during the forum included:
What vendor can help us support personal experiences? I got this question a lot, and each time I found myself repeating that moving to deeply contextual experiences isn’t solved by just one technology or one vendor. Many technologies (including those you may already have in place) support a contextual strategy, and they each work together to deliver a deeply contextual experience. These include (among others) tools like AB/multivariate testing; web content management; eCommerce platforms; recommendations engines; customer analytics; and site search. And when it comes to mobile apps, it’s not always a sourcing story as you’ll likely need to build applications that take contextual inputs into account (e.g. location).
I was intrigued to read in StorefrontBacktalk about Target’s plans to reduce its spending on IT. Apparently, investors warmed to the message, but most of our readers tell us that it’s not how much you spend, but how well you spend it that really determines whether investors see a good return on IT investment. In this research, we asked retailers which IT investments yield a quick financial return and which have the most potential to drive superior returns.
We found that pricing and promotion technologies can have a quick impact on financial performance and forecasting and that allocation and assortment optimization applications have the most potential to drive inventory turn and margin to generate favorable returns. Years ago, I heard of the brilliant success of retail entrepreneur Mike Ashley, which was attributed to his attention to assortment planning. However well you execute, you can’t make money in retail without a plan that ensures that the right merchandise is available in the right location at the right time and price.
We are re-running the survey to see how retailers’ views have changed. Please complete the survey to add your voice to our research (please be patient; it takes a little while).
Update/Correction: Target has told Forrester that, far from reducing IT spending, it actually plans to increase its IT initiatives in 2014. All the more reason to consider your own IT investment priorities!
This content also appeared in the June 2013 edition of CRM Magazine.
Web content management (WCM) software has been around nearly as long as the modern Web. This software enables technology pros to develop sites, lets content people create and publish, and helps marketers leverage online channels to engage customers and prospects.
Forrester’s recent research into this vibrant market confirms a fact that buyers of this technology need to be aware of: WCM has become an essential foundation for enabling successful digital experience efforts. And by doing so, it’s supporting one of the last things that corporations and brands can use to differentiate themselves.
Recently, vendors have put resources into expanding features, building, buying, or integrating with various things:
Visitor profile, segment, and targeting tools to deliver personalized content in context
Capabilities to develop and deploy mobile and social channels of engagement
CRM, email marketing, analytics, A/B testing, integrations, and tools
As businesses work to differentiate their products or services, grow the bottom line, and expand globally, they need to think seriously about the important role that their employees play in helping the business achieve successful outcomes. Businesses must invest in processes and technology to recruit and onboard the best people, address performance gaps with key learning activities, provide career development plans, and align pay with performance. Activities like human resource management (HRM) deployment in the cloud and the use of mobile and social technologies for HRM processes catapult HR to the cutting edge of innovation.
If you want to learn more about predictive analytics, you have to read Eric Siegel's new book as reviewed on my Intro To Predictive Analytics Reading List. Eric is a former Columbia University professor and the founder of Predictive Analytics World. I caught up with Eric at Predictive Analytics World in Chicago. Eric says that data “encodes experience” and that firms use predictive analytics to ferret out what it means — “Who will click, buy, lie, or die.” Watch to hear Eric describe it (< 3 minutes).