finding ideas for marketing contentAre your pitches, blogs, videos, podcasts and white papers rehashes of vague buzzwords like transformation and digital?

To avoid pumping out “me-too” messaging, push yourself (and your in-house subject matter experts) to dig deeper and come up with specific, actionable advice for your potential customers.

One great example comes from a story about data analytics on the TechTarget publishing and marketing site. Don’t let the fact it is old (December 2013) stop you from reading it carefully. The subject (data as a corporate asset) is as fresh as ever. More importantly, this story shows how to take a common, even overhyped, topic and bring fresh, compelling insight to it.

The secret: Asking tough questions based on real-world experience with customers — the kind your sales, support and marketing staff get every day.

Five Meaty Questions

After describing the new (as of 2013) trend of older industries such as manufacturing using Big Data, the piece gets to the good stuff – a five question quiz one vendor asks CIOs to see if they’re serious about treating data as a corporate asset.  The questions include “Are you allocating funding to data, just as you would for other corporate assets?” “Do you measure the cost of poor, missing or inaccurate data?” and “Do you understand the “opportunity cost” of not delivering timely and relevant data to your business?”

While each question has a “marketing spin” (a “yes” answer makes them a better prospect) each is also valuable because they help a prospect understand the real-life challenges of implementing new technology.  Note that each question:

  • Drills beneath good intentions to coldly measure how committed a customer really is. (How much are you willing to spend on this new technology?”)
  • Talks about the non-technical issues that often derail IT projects. (Does this initiative have its own budget?)
  • And describes specific processes (such as measuring the cost of poor quality data and the “opportunity cost” of not delivering high quality data) that can improve how a customer implements the new technology.

Providing detailed insights like this helps establish you as a trustworthy, experienced technology provider and makes it more likely customers will listen when you come to them with a more product-specific pitch.

Finding the Nuggets

Now, how do you wring such insights from your sales, marketing or product support staffs? Whether the subject is Big Data, security, containers or any other buzzword of the week, ask them questions like:

  • How do you know a prospect is serious about our product or service rather than just going through the motions?
  • What are the non-technical factors (such as budget, corporate culture, office politics or management processes) that make implementation of our product succeed or fail?
  • What words, phrases or questions do you hear from a customer or prospect that tell you working with them will be a nightmare, or a pleasure?

The answers to these questions are your “raw material.”  Your next steps are to decide which of the answers are most valuable and relevant, flesh them out with real-world examples and follow up questions from your SMEs, and don’t publish until you can provide detailed, specific and actionable recommendations.

Do all that, and you’re not just another echo chamber in the IT hype factory. You’ll deliver usable, actionable content that will keep your prospects reading — and buying.

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.

My Kingdom for a Better Sales Pitch

bigstock-Man-Standing-On-Street-Is-Aski-132268082A political fund-raising call I got the other day ended very badly. No, not because I wound up screaming at the caller, or even because I didn’t contribute.

It ended badly because the organization almost lost my contribution by boring me with a bland, “one size fits all” script and forcing me to go on-line afterwards to contribute, rather than letting the caller easily send me a follow up email.

The same happens all the time with B2B sales campaigns. Here’s what went wrong and how voters, and customers, could more easily vote with their wallets.

The Rigid Sales Script

I got the political fund-raising call when I was 1) busy working and 2) out of the country and thus charged mega-bucks for every minute of phone time. I tried to tell the caller I was interested but couldn’t take the call, and even offered my email address as a sincere expression of interest.

But the telemarketer sounded completely confused and continued with what was obviously a pre-programmed spiel. I wound up, unfortunately, hanging up on him. The script from which he was working, and his call center system, probably wouldn’t let him easily grab my email and send a follow up note with an easy link to contribute.

I wound up finding the organization’s Web site and contributing, but someone less motivated wouldn’t have. In addition, my call will be recorded as a “hang up” (and a failure) rather than a success (by reminding me of an organization I chose to contribute to.) That makes it harder for this political organization to track the effectiveness of its call banks vs. email or other communication channels, or to link my contribution to the call.

The One Size Fits All Script

The second mistake was that the “sales pitch” began with a general, high-level reference to themes from the previous night’s convention coverage. But just as product pitches need to tell me exactly how the product will help me, this call never got specific. What would have been even more compelling would be something like this:

As you know, funding for the endangered sea turtle will be a critical issue in the next Congress.  Rep. Joe Kelp in Maine’s 2nd congressional district is head of the natural resources subcommittee that will vote on such funding early next year, and is in a tight race with his challenger, Harriet Treecutter. We need only another $125,000 to fund a targeted direct-mail campaign to the 30,000 swing voters who can keep Kelp in this important chairmanship and move this funding forward next year. We’re currently $78,000 of the way there. Will you move us forward with another $50 contribution? If so, we’ll update you in three weeks with the results of the campaign.

And how would the organization know I care about the sea turtle? That’s where all the Big Data, micro-segmentation of voters we keep hearing about comes in. If you know what I care about (as a voter or a tech buyer) tell me very specifically what my contribution (or purchase) will do based on my specific desires.

The Turn-Off Follow-Up

Since contributing, I get almost daily emails form this group with subject lines like “BRUTAL loss,” “DANGEROUSLY behind,” and (which I love) “you haven’t answered.” Even in this election year, the sky can’t be calling every day – and it’s not my job to answer unsolicited emails.

What might get more contributions out of me would be an update on the results of the previous voter turnout campaign I helped fund. Tell me how the polls have turned, how many committed voters you have registered, and exactly how you would use my next contribution to make more progress.

In the B2B world, effective follow up means finding out if the customer is using the product, getting value from it, and is aware of how specific add-ons or upgrades could make them more money. For solutions sold in the cloud, sellers can track usage patterns, social media comments and other feedback to tailor their follow-up to each customer, suggesting products and services geared to their specific needs.

But as both an IT customer, and an involved voter, I keep seeing clumsy, unfocused and just plain irrelevant offers. In these days of Big Data and personalized messaging, why can’t we do better?

Author: Bob Scheier
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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.

Making Health Insurance “Digital”  

digital health insurance

Spring brings two painful ordeals. One is doing my taxes, where software can at least help ease the agony.  The other is choosing a health insurance plan, from a provider that seems never to have heard of the “digital” revolution.

Among the many loose definitions I’ve seen of the “D” word in my work with clients are:

  • Putting the customer first
  • Making products and services easy, and even delightful, to buy and use.
  • Customizing products and services, using Big Data to understand and even anticipate each customer’s needs.
  • Being mobile-first, or at least mobile friendly.

So 1980s

Compared to this lofty vision, what do I get from my insurer every year? A thick wad of paper (not even an email notification it’s coming) full of dense charts, impenetrable jargon, and confusing pricing options. The only “personalization” is their recommendation of a replacement of my current plan, which is being discontinued.) The new plan is close to 20% pricier than my current plan, and is about the level of a modest mortgage. But there’s no guidance on what I’m getting for the extra money or how this compares to my current plan. There are several pages of “mapping” diagrams to compare the insurer’s former and current plans, but it’s a year since I’ve signed up and neither my insurance card nor my bill have the name of the specific plan I’m now enrolled in.

And despite the fact I have, for at least 15 years, purchased only individual plans, the insurer makes me sift through four pricing levels for each of their new plans: for an individual, a spouse, a child and a family. It’s just another level of confusion about a decision (“How sick or injured will I be in the next year?”) that I’m not very qualified to make.

It’s also not very insightful or customized, in an era when Netflix can track which Doc Martin re-run I last binge-watched, and Amazon recommends stuff for me to buy based not only on my purchases, but my browsing history, and the purchase and browsing history of millions of others.

This seems like a process, and an industry, ripe for takeover by someone that could harness Big Data, real-time customization and a friendly user interface to make health insurance comprehensible and truly customized. (Note to health care CEOs: I, and a lot of other folks, would probably pay a modest premium just for the peace of mind of knowing what we’re buying. Just think, also, what simplifying the process would do for your back-office administrative and customer service reps.

So what would a “digital” health insurance purchase process look like?

Personal, Customized, Easy

  • Make online the default, and easiest to use, channel for information about plans and the process of choosing one.
  • Provide instant chat with a rep who can view my account and medical history without endless authentication and approval processes.
  • Use Big Data analysis of individual purchase behavior and health, as well as of others in their cohort, to recommend a plan on each customer’s historic health care consumption and scenarios (low, medium and high probability) of care needed in the next year.
  • To make it even more customized and interactive, provide cost estimates reflecting the customer’s most recent activity. (“Based on our experience with patients with your age and symptoms, there’s a 20% chance that shoulder pain you saw us about last week will require surgery rather than ice and Tylenol. If so, here’s the projected out-of-pocket cost under each of our three recommended plans.)
  • Tailor benefits to each customer’s needs and histories. Don’t tout your smoking cessation programs if you know I haven’t smoked in 30 years, or offer me a low-cost health club membership if you just gave me a discount for installing a home gym.
  • Speaking of home gyms, why not give me a one-click option to link my smartphone pedometer to your fitness-tracking program and give me a monthly discount on my premium based on my exercise level?

In industry after industry, disruptors are blowing away old-school competitors by providing easier to use products and services that save customers money. As a totally disgruntled (can you tell?)  health insurance customer, I’m ripe for being disrupted right out of my current provider.

Any contenders out there?

Author: Bob Scheier
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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.

How Big Data Will Fail. Why That’s Good

Big Data marketing tips When clients ask for “thought leadership” white papers, they want  ideas that aren’t yet common knowledge and that will grab and keep readers.

Here’s some thought leadership about the hot topic of Big Data: It can do massive harm if you use it to ask the wrong questions, overload users with documentation, implement it with the wrong data or ignore common sense. Being first to guide your customers around these pitfalls can mean competitive advantage.

Big Noise About Big Data

Big Data – analyzing a greater volume, variety and velocity of data to make better decisions – will grow at six times the rate of the overall information technology market, reaching $41.5 billion in 2018, says market researcher IDC.

Businesses have sliced and diced data about everything from underground oil deposits to customer sales for decades. But the growth of the Internet, of devices linked to the Internet of Things and social media means more data to mine every day. The opportunities range from using location data to text coupons to customers based on their location in a store to using arrest records to predict where crimes are likely and prevent them with a heavier police presence. (Hello, Minority Report.)

So what could go wrong? At least three big things. Here’s how to use each of these minefields to show thought leadership and speed the benefits of Big Data to us all.

  1. Data for Data’s Sake

ICD-10 is the latest version of the codes used around the world to describe medical conditions, and is the basis on which providers get paid by insurers. The most recent version, which went into effect October 1, is much more detailed than the previous versions, with 70,000 codes for everything from parrot bites to getting sucked into a jet engine. While the extra detail may help health researchers, Bloomberg Business Week reports says it means huge amounts of unpaid paperwork for providers – time they could be spending with patients. Skeptics note the added complexity means a windfall for consultants and software companies happy to sort out the mess, and gives insurers an excuse to deny claims.

  Thought leadership: Big Data will only be cost-effective and gain the trust of customers if we         gather only the data we need, ensure data gathering doesn’t interfere with an organization’s prime mission and is used for good, not evil. Be proactive about addressing these issues in your marketing.

  1. Forgetting the End Customer

In industry after industry, practitioners are scrambling for data-driven rules that will assure them they are doing a good job. In education, for example, some claim that the more a teacher moves around the classroom, the better their teaching. Have you ever had a teacher who could keep a classroom spellbound while standing in one place, and others who bored you to tears while they paced all over the place? Another teacher pointed out that too much stimulation (like a teacher wandering around the room) might distract students with autism or other disorders. Our fixation with data can blind us to our own experience.

Thought leadership: Stress (as many analytic experts already are) the importance of working closely with business managers and front-line workers to understand what data matter in the real world. Focus on metrics that matter to the end consumer. In education, for example, don’t monitor the teacher, but the students, and whether they’re listening raptly or are tapping on their smartphones. In sales, customer service or app development, focus on the user experience, not just stats like system response time.    

3. People Aren’t Robots. Yet.

There may come a day when we’re always guided to rational decisions by embedded neural networks, but we ain’t there yet.

Consider the financial meltdown of 2007-2008, which almost sank the globe into an economic depression. Some experts did predict the crash, and there was data (such as overly inflated home prices and rising household debt) that pointed to trouble.

But some of the biggest dangers were neither reflected in the data or the analytic models acting on it.  They include the folly of home buyers taking on mortgages they couldn’t afford, the greed of mortgage issuers (or those who packaged those loans for resale) in hiding rising delinquency rates, or the temptation for credit scoring agencies (who get paid by big financial firms) to keep the bad news quiet.

Thought leadership: Don’t just admit that human factors defy Big Data analysis. Become a leader in explaining the limits of Big Data, and advising your clients on when to supplement it with focus groups, qualitative research and field experience that take the human factor into account.

Big Data is still in the “peak of inflated expectations” phase of what researcher Gartner Inc. calls the “hype cycle” each new technology goes through. Next up is Gartner’s “trough of disillusionment” as customers fall prey to Big Data mistakes like those I’ve described.

As we learn how to use Big Data right, we’ll enter the sunny uplands of what Gartner calls the “slope of enlightenment” and “plateau of productivity” for new technology. Generating, and promoting, insights into the proper uses of Big Data will get your company, or your clients, to that happy state first.

Author: Bob Scheier
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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.

Can We Lead With Value in 2015?

2015 trends B2B content marketing Another day, yet another lament about how lame business-to-business (B2B) marketing content can be.

The latest eye-rolling comes from Forrester Research, courtesy of a report in AdAge. It quoted Laura Ramos, a vice president and principal analyst at Forrester, on her review of 30 B2B Web sites in in the technology, software, investing, medical products, manufacturing and services industries.

She scored the sites on ten criteria, “ranging from a customer-centric home page to innovative use of video” Out of the 30 sites, only four passed. The biggest problem, says Ramos, “is that the majority of content talks about the company, what its products and services do and how many awards they’ve won, but doesn’t speak to the issues their prospective buyers are trying to solve.”

Funny, I was just blogging about how often this happens in case studies (and how to prevent it.)

Two of Ramos’ suggestions jumped out at me, one of which I agree with, the other I don’t.

Good: Lead With Value

Ramos talked up how offering usable content such as research and self-evaluation tools can engage the prospect and keep them reading by offering value. Two recent survey-based projects in which I took part show how this works.

One survey, done for Oracle on global cloud adoption trends found, among other things, that:

  • Traditional datacenter requirements, such as performance, service-level guarantees, application lifecycle management and integration, become more, not less, important in the cloud.
  • Frequent cloud concerns include migrating applications with very high performance, availability and security requirements; inability to easily migrate existing application data; lack of ability to manage/monitor or modify existing applications in the cloud; and inability to integrate with non-cloud applications.
  • There are intriguing differences between the workloads customers plans for public vs. private cloud (see below.)

cloud adoption trends

Or consider another recent survey in which I played a role, this for Dell on mid-market use of Big Data.

Its findings include:

·        The biggest drivers of big data success are IT/business collaboration, proper skills and performance management.

·        The biggest causes of failure are lack of IT/business cooperation and lack of tools and skills.

·        And that the most influential departments in big data projects are IT and sales/marketing.

Surveys like this let your salespeople lead by offering valuable help, not putting on a hard sell. By describing the actual state of the market, they can better frame the argument for your products and services. Finally, knowing what customers really care about helps you fine-tune your marketing message and strategy.

Not So Good: Saving the Client’s Bacon

While most b-to-b companies feature case studies on their websites, they don’t do a good enough job telling customer stories, Ms. Ramos said.

“The case studies were OK, but they weren’t really compelling. There are a lot of companies bragging about themselves, disguised as customer success stories, but they don’t feature people and their struggles and successes.” she says. “Companies need to show the things they really struggled with, where they failed, and then show redemption — everyone loves a story of redemption.”

Everyone, that is, except the legal and PR departments of the customer featured in the case study. .  What CIO wants to fess up to that, even if the near-disaster was (of course) their predecessor’s fault? And what legal or PR department would let them make such a confession, when it’s hard enough to get clearance for today’s vague “We’re very pleased with the job XYX did for us…” quotes?

One global services client struggling to describe the “real story” in their own case studies raised another objection: That the IT department itself is reluctant to paint itself as the hero that saved the rest of the company from disaster.

Finding satisfied customers in the business to consumer (B2C) space is one thing. If anyone’s found a way to tell the full “redemption” story for a named B2B customer, I’d love to hear it.

Author: Bob Scheier
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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.
Dell Big Data

Click to read the full report.

Is Big Data – the analysis of a very large volume of varied data coming in very quickly – only for big companies?

Not at all, according to a recent report we at the Competitive Edge Research Reports unit of Triangle Publishing (with whom I am associated) wrote for Dell Software  . The report summarized results of a survey it commissioned on Big Data usage among mid-sized companies (those with between 2,000 and 5,000 employees.) Eight out of 10 of the 300 respondents agreed that they need better data analysis to meet their business goals. Virtually all (96 percent) have one or more big data projects in place or are starting one.

The most frequent improvements cited by those who have already deployed Big Data are increased product quality, greater ability to identify and exploit business opportunities and a better understanding of customer requirements. Expecting 25 percent greater benefits in many areas over the next two years, respondents predicted their Big Data budgets will rise to an average of $6 million over the next two years.

So mid-size firms are hot for Big Data. Where do they need help, and what marketing messages will they respond to?

Opportunities: Consulting

Let’s start with what respondents identified as the biggest drivers of Big Data project success: IT/business collaboration, having the proper skills and performance management to gauge the effects of Big Data initiatives.

This opens up, obviously, a bunch of consulting opportunities. One is the never-ending issue of how to get IT and business to define and manage IT projects carefully enough to get business benefits from them. Specific consulting needs that jump out from the results include:

  • Educating and coaching users on data analysis tools to help them identify, find, cleanse and use the right subset of Big Data to solve their most pressing business problems.
  • Helping users and their peers in IT develop complete and accurate business requirements, so the data geeks know which data and analysis to focus on, and
  • Helping customers choose, implement and understand the results of performance management tools, so they can understand how well their Big Data projects are working and how to improve them.
  • General change management and management consulting to overcome historical suspicion between business and IT, reluctance of business units to share data and “siloed” ways of looking at the business that get in the way of Big Data insights.

Note the powerful, underlying theme I’m seeing in a lot of my work for service vendors: The need for a more “industrialized” approach to IT that delivers consistent, repeatable, measurable services. Any frameworks, best practices, templates or proprietary tools service providers can bring to the table are worth highlighting.

Opportunities: Products

The products customers said they need the most focus not only on managing huge quantities of data, but understanding it in real time and easily sharing the results in a form business users can understand. Specific hot interest areas include:

  • Real time processing of data and analytics.
  • Predictive analytics.
  • Data visualization.
  • Access to cloud-based services to provide anytime, anywhere access to data and applications at lower cost.
  • Data aggregation that spans multiple databases.
  • Big Data platforms such as Hadoop
  • Data dashboards (desktop self-service data integration).

Note also that respondents expect their need tools that cleanse data (remove inconsistencies and inaccuracies) to rise significantly in two years. This is also an attractive area for services, as data quality requires changes to processes as much as technology.

Who to Target, What to Say

Given that budget limits are among the top barriers to Big Data projects, your case studies should highlight how you helped customers meet their top goals. According to the survey, the top three were  ”improve product quality, seize business opportunities and speed decision-making,” followed closely by “obtain better and deeper understanding of customer needs,” “quickly respond to competitive threats or other inputs” and “improve effectiveness of our marketing programs.”

Our findings showed that IT is most involved in Big Data projects, but sales/marketing was a close second. This shows, again, the very pragmatic and business-focused approach the mid-market is taking to Big Data. So does the fact that data from customer/ CRM, sales, manufacturing, supply chain/logistics and corporate financial systems are the types of internal data respondents are most important to Big Data projects.

In building your Big Data marketing efforts, then, remember to focus on business as well as IT needs, and on how you can help produce repeatable and measurable business results. For more information on the report or our marketing services, please contact Larry Marion at Triangle at

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.

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.

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.