Tech Trends Archives

data overloadedThe Obama administration has apparently fallen in love with Big Data (especially yours) with its tracking of mountains of phone calls and Web data. But for business customers, the Big Data buzzword might actually slow sales.

Twice in one week I’ve heard customers or providers complain that Big Data is not what it’s cracked up to be. Meanwhile, market researcher Gartner reported that  confusion over the terms “analytics,” “BI” (business intelligence) and “Big Data” chopped growth in BI software sales from 17 percent in 2011 to seven percent in 2012.

Complaint #1 came from an attendee at the 2013 MIT CIO Symposium. Analyzing millions of patient records to assess someone’s chances of coming down with a disease was fine, he said.  But patients don’t have the time or skill to understand a complex chart with a pile of medical jargon, he said.  They just want to know their chances of getting sick.

Complaint #2 came from a post on the B2B Marketing blog. In it, Pamela Bath, who herself does “Big Data” analysis for marketers. She described how she recently took two cars to different dealers owned by the same chain, and got 13 voice mails asking if she was satisfied with their work. If Big Data and customer relationship management are so good, she said, why didn’t the dealership understand she was one customer and just call her once?

(For the record, “Big Data” means analyzing a large volume and variety of data coming in at high velocity. “Business intelligence” refers to the software and processes to analyze the data and present reports to users. “Analysis” means…all of the above, and more. See why everyone’s confused?)

Lesson One: Focus on the End User

I do a lot of writing for clients in the “Big Data” and it gets very techie very quickly. That’s because it’s a new area coping with huge technical challenges. Still, the business conversation around “Big Data” can quickly degenerate into which Hadoop distribution to use, horizontal vs. vertical sharding and extraction layers vs. integration layers.


Credit: Dashboard Insight

To keep business buyers interested in your “Big Data” product or service, explain who might use the analysis and how the results will look to them. Remember the “dashboards” (right) from the executive information system days with red, yellow and green lights showing what was going right and what was going wrong? The less technical the end user, the closer we should come to that simplicity.

And describe whether that end user is, for example, a sales manager facing an end-of-month quota, a pharmaceutical researcher looking for patterns in gene expression or a mid-80s diabetes patient with bad eyesight hoping to avoid yet another hospitalization. Each requires a different level of complexity, different flexibility in drilling into the data, and even different colors and type sizes.

You could argue this reporting format question is not specific to Big Data and you’d be right.  But Big Data gives you more ways to waste time with a flood of meaningless analysis, and gives vendors more temptation to get caught up in speeds and feeds rather than business cases. It’s our business as marketers to keep the conversation on track.

Lesson Two: Define the Business Process

You’re also not selling Big Data right if you’re not explaining where and how it fits into all the processes that make money for the business.

In Pamela Bath’s car dealership run-in, she complained marketers weren’t making the common-sense connections among their marketing channels that would tell them she’s one person, not two.  The dealership’s CRM system should have identified her as a single customer, she argued, while their call log system “should have kicked in to ensure dealerships don’t end up overzealously quizzing their clients.

“As marketers,” she said, “We need to focus more on the ‘little data’ that we already hold to get a clear transactional and demographic understanding of our customers, the permissions they have given us and their channel choice.”

Therefore, questions to address in your marketing material include:

  • “Which business groups are asking for this Big Data analysis, and why?
  • How will their analysis fit with that done by other units within the business?
  • Who decides what questions we’re asking and which results would be most relevant to the business?”
  • “Does the information we gather come from all the systems that are most relevant to the business?”
  • And (with an eye to government spying headlines) have we really thought through the privacy concerns?

Again, you could argue these questions could apply to generic data analysis or to any business function. But again, Big Data is so new and so…well, big, it gives you more room to hang yourself.

Marketing Roadmap

 Yes, highlight technical features like your stateful failover, self-healing clustering and automated compression.  But the decision makers who write the checks want to know who will use the data analysis and how Big Data helps the business. Answer those questions well, and they’ll think of you first when they have a technical need.

Is Big Data confusion turning off your prospects?

Author: Bob Scheier
Visit Bob's Website - Email Bob
I'm a veteran IT trade press reporter and editor with a passion for clear writing that explains how technology can help businesses. To learn more about my content marketing services, email or call me at 508 725-7258.

Steal This Idea: An App to End Sweatshops

Needed: An app to end sweatshops.

Aftermath of Bangladesh factory collapse.

While top retailers hang back over liability fears, the Bangladesh government lacks cars to even get inspectors to garment factories like the ones whose recent collapse killed 1,127 workers. Meanwhile, we consumers keep the system going because we like to save money. And, hey, how do we know where that shirt or jeans were made?

Meanwhile, social app developers let us share with an eager waiting world how far we jogged today. Webcams let us monitor our houses or nannies from work. RFID (radio frequency identification) tags let owners track the location of plastic shipping pallets lest they be chopped up by thieving recyclers.

If We Can Put a Man on the Moon…

If we can do all that, why can’t we use information technology, the Web and portable sensors to show customers, while they’re in the store, whether the shirt, jeans or whatever they’re looking at were made in a decent factory or a sweatshop?

Some studies have estimated that it would add as little as ten cents to the price of a piece of clothing to prevent disasters like building collapses. Would you pay that? Would you go further and spring for an extra dollar or Euro to add air conditioning and clean air?

Let’s say we’re real sports and make it the equivalent of $2US (about the price of the average Starbucks) to a piece of clothing or smartphone. Set aside $1 to improve factory conditions, and split the other $1 as additional profit between the factory and the retailer, just to keep everyone motivated.

Workers get better conditions, factories and retailers make more money, and we consumers get to brag about our generosity. The whole system is voluntary. It could also be a monumental PR and branding coup for the consulting, technology, retail and social media outfits that teamed up to make it work.

Oh, Yeah, the Details  

Some really smart people could come up with a more elegant way to do this. But here are some building blocks:

  • Embed a hard-to-remove RFID (radio frequency identification) tag or other unique identifier for the factory at which each piece of clothing was produced.
  • Create a mobile app that lets the customer scan the bar code or Google the factory ID and see real-time worker feedback about conditions. Services such as LaborVoices  and Labor Link already gather such feedback for retailers. Why not share it with consumers?
  • Create a “fair trade” certification process factories can voluntarily join, adding a fair-trade logo to their products if they choose. Vendors that want to go premium (and charge even more for their products) could set up Webcams in their factories showing consumers how well they’re treating their workers.
  • The customer decides how much to spend based on a reasonable level of information about the conditions under which the product was produced.

One small clothing company, Indigenous Designs, is already doing this on a small scale with QR codes.  Next, we need a large retailer, or clothing manufacturer, with the guts to do it on a large enough scale to make this a competitive necessity.

Not There Yet

 This system wouldn’t, of course, track suppliers further down the production line, like the farms that supply raw cotton, the mills that process it or those who make subassemblies (like shirt fronts and backs) for the factories.

 Then there’s the low-end of the consumer market, where customers may not want or be able to pay a premium for “ethical” products. And, yes, everyone from factory owner to global retailer to disgruntled factory workers will try to game the system. But the same social media sites that track complaints can also help uncover attempts to trick the system, just like with product reviews on the Web.

The more workers, factories and retailers participate, the more likely it is that most factories will, over time, get the reputations they deserve and most consumers will vote with their wallets. Best of all, this makes good working conditions an area where factories and retailers want to excel. (Free-market advocates may now applaud.)

All we need now are some smart, connected people in the technology, consulting, social media and retail industries to step up and get it done. Volunteers?

 Please feel free to pass this on to any clients or partners you think could help, and to claim it’s your idea.


Author: Bob Scheier
Visit Bob's Website - Email Bob
I'm a veteran IT trade press reporter and editor with a passion for clear writing that explains how technology can help businesses. To learn more about my content marketing services, email or call me at 508 725-7258.

Demystify DevOps — Or Else

DevOps? I thought you meant SPECIAL ops. Watch me collapse those deployment cycles...

DevOps? I thought you meant SPECIAL ops. Watch me collapse those deployment cycles…

Doing one thing at a time is so…nineties. We now have to do everything, all the time, like the guy texting as he walked past me into a ladies’ room in O’Hare Airport.

But that’s a different story.

The big emerging trend in IT multitasking is DevOps. It means combining what used to be the sequential tasks of creating an application (development) and keeping it running (operations.) Doing both in parallel should allow businesses to roll out new applications and services more quickly. That’s essential when a photo sharing site like Instagram needs to add 1 million users in 12 hours, users expect constantly updated mobile applications, and popular Web sites do continuous “A/B” testing to see if users like the scroll bar looking like this or like that.

 Beyond Process Change

 You might think DevOps is largely a “soft skills” story – how to get often warring development and operations teams to play nice. Development, after all, is paid to get cool new apps out the door quickly. Operations is paid to slow down and make sure they work right and are secure. And there are, indeed, plenty of good stories for marketers to tell about consultants who can do the necessary training and process change.

But it turns out there’s also a big technology story. Operations, after all, collects reams of log files and other data that track the operation of everything from Web servers to load balancers. By feeding that data back to the developers, in real time, they can tweak their applications and system architectures to avoid slowdowns, and adapt user interfaces based on what’s hot from the Web analytics that week.

This has raised the profiles of vendors such as Splunk, whose software monitors and analyses “everything from customer clickstreams and transactions to network activity to call records.” This can be used, among other purposes, “to debug and troubleshoot applications during development and test cycles.” Likewise, the CA LISA software suite from CA Technologies (one of my clients) simulates production environments to help multiple development teams work in parallel and manage test environments, another important part of the DevOps process,

Eschew Obfuscation 

So we know there’s a tech story to tell here. But in my conversation with vendors I’m finding some common challenges:

  •  Many customers either don’t know what DevOps is, or think it is hype. Define DevOps carefully and put it in context of related buzzwords like agile and open source. How you position all these trends isn’t as important as being clear in how they relate. Case studies of how DevOps has scaled securely in the real world will also help win over skeptics.
  •  Especially if you provide products or services on the data analysis side, make sure you explain exactly how you fit into DevOps process. This is a classic opportunity to define the conversation around an emerging market space by being first to explain it. (One sign of confusion: One of my clients described Splunk as a leader in the DevOps space, but Splunk itself doesn’t seem to agree, as a search for “DevOps” on their site yielded no hits.)
  •  Again, if you play in the data warehouse/data analysis/query tools space of DevOps, make sure you explain you’re analyzing machine data from the IT infrastructure, and not business data like when to put the beer next to the diapers to sell more of each. (A classic “Big Data” insight which, by the way, may have been ignored.)

So is DevOps real? Everyone from rocket scientist billionaires at social Web sites to somewhat staider outfits like the German Post Office say yes. Others will take more convincing. Ladies and gents, start your explanation engines.

Author: Bob Scheier
Visit Bob's Website - Email Bob
I'm a veteran IT trade press reporter and editor with a passion for clear writing that explains how technology can help businesses. To learn more about my content marketing services, email or call me at 508 725-7258.
Working at home

Marissa, we need to talk about this telecommuting thing.

I’ve been trying to ignore all the mindless coverage of Yahoo ordering all employees into the office so they can figure out how to save the company. But when Best Buy joined Yahoo in ending “telecommuting” something snapped.

All the “Is telecommuting dead?” headlines are a classic example of the media sucking the meaning out of an event, replacing it with an easy-to-understand “Who’s up, Who’s Down” story line.

Telecommuting isn’t dead. It won’t die until someone uninvents the Internet, the microprocessor and the telephone. It saves too much money in office space. It lets companies outsource too much work to cost-effective outside contributors. It’s too much of a perk for smart, hard-working employees who need to pick up their kids at 5:15 and can be trusted to make up the time later.

Telecommuting isn’t dead so much as it’s over. Whether employees should “work from home” is a 20-year-old argument that’s long ago been answered by the likes of outsourcing and, well, Mark Zuckerberg becoming a billionaire based on coding he did in his dorm. Today’s challenge is how to use today’s distributed technology and distributed talent to survive amid the sudden and tectonic market shifts that have Yahoo and Best Buy struggling for life.

Telecommuting: That’s So 90s

Telecommuting was coined in the late 80s or 90s as some pioneers began to, gee, let people work from home and dial into email over modems. Ironically, the technologies that made Yahoo and Best Buy big in the first place (search and home electronics) helped popularize telecommuting. The fact they can’t figure out how to get the most from remote workers might be part of their problem.

The very term telecommuting is kind of quaint. Nobody works only in the office these days. Between the recession and smart mobile devices, people need to and can work anywhere and anytime. Our employers and clients expect it and technology makes it possible.

Where a full-time employee works during the regular work day is only part of what makes successful companies tick. Your best developers might be in Indiana, India or Rumania. Your best customer service rep might work from their living room in New Brunswick. Your sales reps work out of their cars. These folks are remote because that’s the most cost-effective (and maybe the only way) you can get their services.

Culture, Not Cubicles

That doesn’t mean physical proximity isn’t important. We still need to do lunch, to have off-sites, to do group orientation meetings, to do boozy networking at trade-show receptions. And, yes, companies facing a life or death crisis need employees to run into each other in the hallway, lunchroom and (yes) bathroom for those random conversations that spark turnarounds. And, yes, they need the sense of shared purpose and connection only physical proximity can deliver.

But that doesn’t mean all hands have to be on the same physical deck at the same time all the time. Have a group you think can do great things? Give them a goal, some budget dollars for travel and let them (within reason) figure out for themselves when to meet and for what reason. Need key players in the office for more random availability and chats? Negotiate a schedule that respects their child-care (or parent-care) responsibilities.

Whatever you do, do it intelligently, and fairly. For example, Yahoo CEO Marissa Meyer could afford to build an in-office nursery for her child. Imagine a key product manager or developer kept from picking up their child due to a sudden in-office late afternoon meeting. They imagine their child left confused and wondering why their parent isn’t there, and see the CEO’s child next door in their nursery.

Next step: That employee is looking for an exit, and the more capable they are, the sooner they’ll leave. And that is no way to run a turnaround. Telecommuting (or not) isn’t the question or the answer. Good management is.

Author: Bob Scheier
Visit Bob's Website - Email Bob
I'm a veteran IT trade press reporter and editor with a passion for clear writing that explains how technology can help businesses. To learn more about my content marketing services, email or call me at 508 725-7258.

Marketing the Cloud? Get Ready to Step Up Your Game

Marketing cloud services. The cloud is hot, no matter how you define it. Just how hot the cloud is, and what it’s good and not so good for, was the focus of an interview I did with cloud application performance monitoring vendor Boundary the other week.

For marketers, the takeaway is that there’s no one “cloud.” The number and type of cloud services will continue to explode, and explaining the competitive differentiator for each type of cloud service and tool will become more important.

I’m curious to hear your take, as marketers and industry observers, on some of my observations. They included:

  • Continued growth of the cloud will be driven as much by agility as by cost savings.
  • The boundaries between infrastructure as a service, software as a service, platform as a service, and “You name it as a service” (security, management, storage, backup, etc.) will blur as providers slice and dice their offerings to meet the precise needs of just about any user.
  • The answer to “Is the public cloud safe/reliable enough?” is “it depends” on which private clouds you’re it comparing. A “too big to fail” bank should (we hope) be able to maintain an ATM network at least as solid as Amazon’s infrastructure. If you’re a struggling mid-market manufacturer cutting costs on the IT side, you might be better off trusting Amazon. Then, of course, there’s the difference between dedicated infrastructure in the cloud and a true, multitenant public cloud.
  • Look for consolidation at the top of the cloud service provider food chain and creative new business models from the bottom. At the high end, it’s all about economies of scale to fine-tune the delivery of jobs of servers, storage and network capacity most reliably and inexpensively. At the bottom end, startups with hot developers (with dreams of IPOs in their eyes) will leverage open source software to create “anything as a service” business model we haven’t dreamed of yet.
  • With the growth of open source software and frameworks, more and more cloud providers will build (a la Facebook and Google) more and more of the technology they need. This, of course, raises interesting questions about the future of the proprietary software vendors who pay many of our bills.
  • For customers, the first challenge is figuring out how to use cloud is determining which IT-related functions are “core” (and worth keeping inside) and what are “context” and worth buying as a service if someone else can do them better.


I ended on one of my hobby horses, which is that as great as the cloud is, local client devices like PCs with their own storage won’t go away anytime soon. Until I can instantly get reliable, high-speed Web access anywhere, anytime, I want the work I need to get done today on my local hard drive.

You can read the full interview here. I’m curious to hear whether you think it’s getting harder to market the cloud, and how you’re approaching it.

Author: Bob Scheier
Visit Bob's Website - Email Bob
I'm a veteran IT trade press reporter and editor with a passion for clear writing that explains how technology can help businesses. To learn more about my content marketing services, email or call me at 508 725-7258.

Survey Shows Big Data Pain Points

If you’re marketing hardware, software or services for “Big Data” – the analysis of very, very large datasets to uncover business opportunities – you should check out a recent column my colleague Larry Marion  wrote for Datamation.

In it, he wrote that “despite a decade of expensive deployments and a parade of innovative products” customers are complaining that Big Data tools are too backward-looking and not predictive enough, can’t handle unstructured data, and are too slow and hard to use by non-technical, business types.

Solving these technical problems is up to the engineers, not us marketers. But the concerns in this chart provide a handy list of “pain points” for you to highlight in your marketing content, and in your social media searches for prospects.

Beer and Diapers? Naaah!

This report comes on the heels of a recent post I wrote for CA Technologies’ Innovation Today blog warning that organizations “won’t do the tough work of cleansing and validating (their data) to make sure the insights they gather will actually be valid.”

And last summer I covered a panel discussion that talked not only about data quality, but the very human factor that companies often don’t trust Big Data insights because they don’t fit their preconceptions. (Remember the oft-quoted Big Data insight that customers who buy beer often also buy diapers? Professor Tom Davenport of Babson College told the panel the convenience store chain never stocked the two together because it didn’t believe the sales data.)

While the database, analytics and hardware folks tackle things like speed, data quality, data access and usability, vendors can tap their internal subject matter experts to write about process issues such as:

  • How does IT convince the business users of Big Data of the need to properly cleanse data, and then find the most cost-effective way of doing so?
  • How can IT forge closer bonds with business units so it can help understand what are the Big Data questions most worth asking – and spending money to solve?
  • Where are the hot new technologies in predictive analytics, which ones can be trusted, and what are cost-effective ways to try them out before putting big bets on their predictions?

Real or Hype?

All these are areas the sales force and Big Data consultants are probably already tackling, and have insights on, even if the engineering folks haven’t solved all the technical issues.

But all this is for naught if, despite all our marketing and posturing, Big Data is just not working for the vast majority of customers. Are concerns like those highlighted in this survey preventing, or just slowing, the insights promised by Big Data?

Author: Bob Scheier
Visit Bob's Website - Email Bob
I'm a veteran IT trade press reporter and editor with a passion for clear writing that explains how technology can help businesses. To learn more about my content marketing services, email or call me at 508 725-7258.

Content Marketing For Storage Hypervisors

You can’t engage and score prospects with content marketing unless that content is clear, improve and specific. One example is the “storage hypervisor” buzzword I uncovered while reporting a recent piece on Storage Orchestration for Computerworld.

Calling something a storage hypervisor implies it can deliver the same dramatic cost savings and flexibility as a server hypervisor. But looking under the surface, what is what your serious prospects will do, shows important differences between the two. Failing to clearly explain storage hypervisors throws away an opportunity to more closely engage your prospects and to score them based on what content they read.

Server vs. Storage Hypervisors

Server virtualization, for all its underlying wizardry, is fairly easy to understand. Take one physical server, which often runs at a fraction of its capacity, and split it into “virtual” servers that each work harder.  The hypervisor is software that juggles work among the virtual servers to assure work gets done efficiently. The customer buys fewer physical servers and spends less on real estate and power, the virtualization vendor sells some software. Everyone goes home happy.

In storage virtualization, the underlying technology is the same: A software layer that masks the makeup of physical storage devices. So is the aim: To make the best use of customer’s existing storage before they buy more. But looking more closely, things get more complicated.

In server virtualization, one physical device is usually split into multiple logical devices, each devoted to one application. Most storage virtualization does the opposite: Combine multiple physical devices in a single pool of storage that can be accessed by multiple applications.

Some storage “hypervisors” provide new ways for achieving this storage pooling, by (for example) virtualizing the storage servers that control the storage hardware. Other hypervisors virtualize applications such as back and deduplication to perform them more effectively. Some support only some forms of storage (block vs. file) or some uses cases (dev/test vs. production.)

All this makes storage hypervisors a more complex sell than server hypervisors. This is an opportunity to be the first among your competitors to a) educate your prospects and b) score how good a fit they are for your offering based on what they read.

Decision Points

You’ll get far more, and better qualified, leads for “storage hypervisors” by creating, and tracking the readership of, content that answers questions such as:

  • What you are virtualizing? Storage, storage servers, applications or a combination thereof?
  • Which usage scenarios do you target? : Production systems such as Web serving or on-line transaction processing, or infrastructure services such as backup and restore?
  • Which third-party storage tools do you support? Does the customer need to “rip and replace” their existing backup software to get the benefits of your virtualization?
  • How well do your storage hypervisors integrate with server hypervisors to efficiently scale the entire IT infrastructure up and down as application needs change?
  • Where does your storage hypervisor run? On a physical appliance, to maximize performance and interoperability? Or a virtual appliance, to maximize flexibility and reduce cost?

Answering questions like these clearly in your content marketing empowers you to qualify your storage hypervisor prospects based on which features and functions they choose to read about.

Author: Bob Scheier
Visit Bob's Website - Email Bob
I'm a veteran IT trade press reporter and editor with a passion for clear writing that explains how technology can help businesses. To learn more about my content marketing services, email or call me at 508 725-7258.

Cloud Framework Marketing a Murky Mess

Lesssee, the framework supports the APIs which support storage but not authentication...

In more than 25 years of technology reporting rarely ran into such chaos as I did reporting a recent story for Computerworld on open source cloud frameworks. Just about everyone worth talking to claims to have a framework; just about everything valuable calls itself a framework; and just because you have (or are) a framework doesn’t mean you don’t need another framework to get anything done.

Let’s start simple: A framework is a collection (or, if you prefer, library) of software that helps you do something. In the case of cloud frameworks, the objective is to develop, deploy and/or manage a cloud-based application. The “library” of enabling software that makes up a framework might include development, management and test tools, middleware to link the application to other cloud components such as databases, or APIs to make it easier to move applications among clouds.

A Pain in the PaaS and the IaaS

Some frameworks are designed for use with private clouds (those within a customer’s own data center.) Others are for public clouds, such as those hosted in multitenant (multiple customer) environments such as Amazon. Others are designed for “hybrid” clouds (a mix of public and private) except, of course, if by “hybrid” we’re talking about a mix of physical and virtual servers, as some vendors do.

Then, of course, there are cloud frameworks built at various levels of the “stack” that leads from the base hardware to the applications user see. Infrastructure as a service (IaaS) clouds help customers deploy servers, storage and networks; platform as a service (PaaS) platforms have all the tools needed to deploy actual applications. Each level of framework provides a different combination of price, agility, control and security. A customer might need one framework (such as OpenStack) to provision virtual machines, and another (such as Opscode Chef) to describe how those servers will be configured.

Confused yet? Consider that not all frameworks have all the pieces customers need to not only deploy but manage very large, complex applications over time. Some, such as Eucalyptus and Deltacloud, are APIs (application programming interfaces) aimed at making it easier to move applications from one cloud to another. But customers have found that without the ability to also move underlying services, such as data storage, from cloud to cloud these APIs fall short. If your framework can provide that (or you need another to do this work) say so.

Some have even built their own frameworks after being unable to find one that handled enterprise-scale requirements. These requirements include updating hundreds of applications, providing the strict levels of authentication needed for financial applications and discovering and reusing services such as security and data warehousing. If you can provide these services, these are big draws for enterprise customers.

Open Source or Not?

Many large organizations now see open source software (where the source code is freely shared and open to improvement by customers and others) as a safer choice than proprietary code, as long as they can get enterprise-level support. But whether a framework is truly open source and not tied to one vendor can be another mystery.

Some frameworks have a true open-source feel (geeky Web pages with no major company logos.) Other frameworks are backed with financial and technical help from big-name software vendors. Cloud Foundry, for example, is backed by VMware, while Red Hat’s Open Shift is based on Red Hat Enterprise Linux.

That big-name backing is often a plus, not a minus, to customers. But it raises another question in customers’ minds about just how committed the vendor, or partnership of vendors, is to open-source versus their own in-house products. Providing details like the number of developers you’re committing to open source, what modules or code you are contributing to the effort, and how open you are to new members joining the “community” and pitching in. Those are all questions I hear customers asking when considering open source frameworks.

Guess What I Am. Go Ahead. Guess.

Kudos to those who clearly explain what type of framework they are (the level at which they operate, what functions they do and don’t provide, and exactly what role commercial vendors play vs. the volunteer “community.” But others confuse customers with cute product names and high-level benefits such as “agility,” “flexibility” and “portability” without explaining whether or how these hold up under the scalability, manageability and security requirements of the real world.

To avoid being swept away in a flood of look-alike offerings, use my tried and true “fill in the blanks” formula to make your framework pitch more understandable:

               “(Product name) is a “(noun) that (verb, verb, verb.)

                The product consists of (noun, noun, noun.)

                 It is better than competitive products (adjective, adjective, adjective) because it (specific claim, specific claim, specific claim.)”

 And be sure to describe, clearly and up-front, how you meet the life cycle application demands of complex enterprise environments if you hope to serve that market.

Author: Bob Scheier
Visit Bob's Website - Email Bob
I'm a veteran IT trade press reporter and editor with a passion for clear writing that explains how technology can help businesses. To learn more about my content marketing services, email or call me at 508 725-7258.
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