free hit counters

From the category archives:

Product Marketing

Big Data is getting really hot these days, and along with it, some of its pet terms.  One of those terms is “In Memory Analytics.”

All of a sudden EVERYBODY — be they providers of data warehouse appliances, OLAP tools, data visualization tools, or other business intelligence derivatives — are claiming to have “In Memory Analytics.”  Even if what they offer is not truly “in memory,” or (for that matter) not really “analytics.”

While I dislike marketing that is deliberately misleading,  I see how this situation developed.  A lot of customers have hopped on the bandwagon and are specifically asking for “In-Memory Analytics” by name.  But the thing is, no matter how they phrase it, the actual customer problem is not “I need in-memory analytics.”  Instead, the problem is “I want to analyze a my data with near-instantaneous response.”  Thus, vendors who have covered at least some part of this problem are inclined to just slap the “In-Memory  Analytics” label on their wares, so that they can at least be considered, even if the term is not technically accurate.

The actual definition of “In-Memory Analytics” is a specific technical approach to the instantaneous analysis problem — an approach where the entire dataset is pulled into the server’s RAM in order to greatly speed up analytic queries.

It works great, but In-Memory Analytics is not the end-all-be-all approach by any means.  It doesn’t deserve to be synonymous with “instantaneous analysis,”  because:

  1. Other technical approaches may also provide solutions to this problem.
  2. “In-memory” cannot solve the problem at all for larger data sets.

More color on the first point:  In the next few years, we’re going to see lots of new approaches and technologies that provide the user with instantaneous insight into large data sets.  For example, MPP data warehouses, Hadoop, MapReduce, and other technologies will combine and be refined to give the user (the analyst) instant understanding of their data – regardless of whether all the necessary data is “in-memory” or not.

And on the second point: no matter what, we will always want to analyze data sets that are larger than what can be stored in memory alone.  The amount of data in the world is growing faster than Moore’s law and memory capacity improvements.  (Don’t believe me?  Take your favorite “in-memory” analysis problem and add a requirement for LOTS of historical data.)  Further, for the foreseeable future, disk storage will continue to cost a tiny fraction of memory storage.  Right now, Amazon Web Services charges about $0.10 per GB on disk, while memory costs 240 times as much, about $24.00 per GB.  So, expect lots of situations where the entire data set is huge — so huge that most of it is on cheap disk and only the most frequently accessed data is in-memory.  In-Memory Analytics alone won’t cut it.

{ 0 comments }

In Silicon Valley, every company wants to produce white papers. They’re considered an essential part of marketing technology products, and they’re on the checklist for every product launch. Beyond the launch, Product Management and Product Marketing typically want to provide prospects and customers with a wide variety of white papers on product-related topics.

White papers have their strengths: you have several pages to describe your products, their benefits, and their underlying technology to an interested audience. Customers or prospects in the early stages of learning about your sector get educated about why their problems should be solved, different approaches to solving them, and how to evaluate these approaches. In the case of experienced customers, a good white paper can further establish your credibility and deliver convincing arguments about why your company’s approach is superior. Done right, white papers can be great marketing tools and often generate more qualified leads than any other source.

Unfortunately, though, companies often squander this opportunity. Most technical white papers are never read, even if readers actively sought them out. Typically, in the software industry, many readers stop reading part way through the first page, overwhelmed by verbose, jargon-filled content and wondering how it applies to them.

White papers can avoid this fate and be much more effective marketing tools if you 1) do some up-front thinking, 2) carefully craft your arguments and provide proof points, and 3) use a good writer.

In the case of point #1, up-front thinking, Sure Product Consulting asks clients who want us to write their white papers the following questions. Prior to our even bidding on the project.

  1. Why do you want a white paper?
  2. How should this white paper be different from your marketing collateral? Does it have different goals? A different target audience? Will it have different messaging? Different content?
  3. How should this white paper be different from your competitors’ white papers?
  4. What are you going to do with the white paper? Give it away at conferences? Offer it as a “freebie” to customers who subscribe to your monthly newsletter? Or just make it a website download for anyone who wants it?
  5. How critical is it that customers actually read the paper, digest it, and remember its main messages? (This may seem like a silly question, but you’d be surprised at how often the real goal is to collect email addresses instead of truly communicating ideas.)
  6. How will you measure the success of this white paper as a marketing tool? (Qualified leads generated? The customer’s ability to remember key messages? Sheer number of email addresses collected?)
  7. Why do you believe a white paper is the most effective method to reach your goals?
  8. How “neutral” do you want your paper to be? Neutrality increases your credibility. But it also means you must even-handedly discuss alternative ways to solve customer problems—perhaps even naming your competitors.
  9. If there is just one message you want readers to take away, what is it?
  10. What tone—informal or formal—should your white paper take? By “informal,” I mean using “you” and “we” and not worrying very much about dangling prepositions and split infinitives. In the software industry, most white papers refer to the company in the third person, rather than “we.” They talk about “customers,” rather than “you.” In our experience at Sure Product Consulting, most software companies prefer this more formal writing style, even though readers are more likely to actually read and retain the messages presented more informally.

If you get clear on these issues before you start to write, your white paper project will go much more smoothly. You might even eliminate a feedback round or two, which has been our experience. The result will be a better and more effective white paper.

{ 0 comments }

Writing a Product Evaluation Guide? Avoid These 3 Mistakes.

January 17, 2009

Today, enterprises and consumers alike, expect to try out your software (or online service – see note 1) hands-on before making a purchase decision.  Thus, the necessity of Product Evaluation Guides that: Get prospective customers up and running with your software as quickly and as easily as possible. Give positive, low-risk product experiences, so prospective [...]

Read the full article →

Forget Product Reviewer Guides. Instead, Do Product Evaluation Guides.

January 13, 2009

Once upon a time, as far back as 2004, enterprise software Product Marketing Managers and Product Managers spent time creating “Product Reviewer Guides.” These documents were intended to step technical journalists through the process of installing and using the product, all for the purpose of getting the journalist to write a smashing review of the [...]

Read the full article →