Year: 2013 (Page 6 of 7)

The Marketing Technology Landscape

May 13, 2013 / Frank Gilbane / 0 Comments

It’s no secret that marketing continues to increase spending on technology, which raises the question of which technologies they are spending on. The answer is “lots” – the marketing technology landscape has become much larger, more varied, and more complex. One sign is the evolution of some web content management systems to solutions for web experience management, web engagement management, digital experience management, etc., which involves integrating with marketing automation, predictive analytics, social and many other marketing tools and back end systems.

Not all this is new. In 1999 more advanced businesses were already integrating e-commerce, web analytics, personalization, and marketing automation, but it was much harder then and there were far fewer options. I hesitate to say it is easier now, but it is in many ways – the technology is much better and we have much more experience with it. What is certainly not easier is navigating the technology landscape which is extremely dynamic, and contains categories with too many vendors. Both CMOs and CIOs need a marketing technologist function in some form, and would certainly benefit from input from analysts, and a <plug> vendor and analyst neutral conference </plug>. The illustration below may be scary, but should be very useful. Thanks to Scott Brinker for first pointing this landscape out. Scott also has his own similar graphic.

MARKETING TECHNOLOGY LUMAscape from Terence Kawaja

The Gilbane Conference is growing!

May 5, 2013 / Frank Gilbane / 0 Comments

Some of you may have heard there is some exciting news with regard to The Gilbane Conference.

We have entered into a partnership with Information Today, Inc. to organize and manage future conferences in this 12-year-old series. As you may know, Information Today is the publisher of KMWorld and EContent magazines along with a host of other publications and websites. Information Today also organizes the KMWorld and Enterprise Search Summit conferences, so they are on familiar ground with respect to web content management, content marketing, social media, and many other related technologies.

Information Today also publishes CRM magazine and produces the CRM Evolution conference and exhibition, which will enable us to reach out to marketers and other customer-focused professionals.

We believe the synergies between The Gilbane Conference and Information Today will assist us in producing even better and more innovative conferences in the years to come.

The resources of a larger enterprise and the personal care and attention you’ve come to know at The Gilbane Conference are what you can expect this fall.

The next Gilbane Conference will be at the Westin Boston Waterfront, December 3 – 5, 2013. ~~We will be announcing the Boston venue and dates in the next week or two and~~ See the new Gilbane Conference website for more information where we will be posting additional details very soon. If you are not already on our mailing list for advance information you can signup using the quick form below.

Our theme this year is Content and the Digital Experience: Manage, Measure, Mobilize, Monetize, and we’ll be continuing our vendor and analyst neutral coverage of content, marketing, and digital experience technologies for enhancing both customer and employee engagement and collaboration.

We look forward to seeing you in Boston this fall.

We would love to hear more about your interests. You can tell us more by using our more complete form. Or send us a message.

Leveraging Search in Small Enterprises

April 5, 2013 / Lynda Moulton / 0 Comments

A mantra for a small firm or start-up in the 1970s when “Big Blue” was the standard for top notch sales and selling was we need to out-IBM the IBMers.

Search is just one aspect of being able to find what you need to leverage knowledge assets in your work, whether you are in a small firm, a part of a small group in a large organization or an individual consultant seeking to maximize the masses of content and information surrounding you in work.

My thoughts are inspired by the question asked by Andreas Gruber of Informations und Wissensmanagement in this recent post on Enterprise Search Engine Professionals, LinkedIn group. He posed a request for information stating: For enterprise search solutions for (very) small enterprises (10 to 200 employees), I find it hard to define success factors and it seems, that there are not many examples available. If you follow e.g. the critical success factors from the Martin White’s Enterprise Search book, most of them doesn’t seem to work for a small company – simply because none of them can/will investment in a search team etc.…

The upcoming Enterprise Search Europe meeting (May 14-16, 2013) in London is one focus of my attention at present. Since Martin White is the Chairman and principal organizer, Andreas’ comments resonated immediately. Concurrently, I am working on a project for a university department, which probably falls in the category of “small enterprise”. The other relevant project on my desk is a book I am co-authoring on “practical KM” and we certainly aim to appeal to the individual practitioner or groups limited by capital resources. These areas of focus challenge me to respond to Andreas’ comments because I am certain they are top of mind for many and the excellent comments already at the posting show that others have good ideas about the topic, as well.

Intangible capital is particularly significant in many small firms, academia, and for independent consultants, like me. Intensive leveraging of knowledge in the form of expertise, relationships, and processes is imperative in these domains. Intangible capital, as a percent of most businesses currently surpasses tangible capital in value, according to Mary Adams founder of Smarter-Companies. Because intangible capital takes more thought and effort to identify, find or aggregate than hard assets, tools are needed to uncover, discover and pinpoint it.

Let’s take the example of expertise, an indisputable intangible asset of any professional services. For any firm, asking expert staff to put an explicit value on their knowledge, competencies or acumen for tackling the type of problem that you need to have solved may give you a sense of value but you need more. The firm or professional you want to hire must be able to back up its value by providing explicit evidence that they “know their stuff” and can produce. For you, search is a tool to lead you to public or published evidence. For the firm being asked to bid on your work, you want them to be able to produce additional evidence. Top quality firms do put both human and technology search resources to work to service existing projects and clients, and to provide evidence of their qualifications, when being asked to retrieve relevant work or references. Search tools and content management methods are diverse and range from modest to very expensive in scope but no firm can exist for long without technology to support the findability of its intangible capital.

To summarize, there are three principal ways that search pays off in the small-medium business (SMB) sector. Citing a few examples of each they are:

Finding expertise (people): potential client engagement principal or team member, answers to questions to fulfill a clients engagement, spurring development or an innovation initiative
Retrieving prior work: reuse of know-how in new engagements, discovery of ideas previously tabled, learning, documentation of products and processes, building a proposal, starting point for new work, protecting intellectual property for leverage, when patenting, or participating in mergers and acquisitions.
Creating the framework for efficiency: time and speed, reinforcing what you know, supporting PR, communications, knowledge base, portraying the scope of intellectual capital (if you are a target for acquisition), the extent of your partnerships that can expand your ability to deliver, creating new offerings (services) or products.

So, to conclude my comment on Andreas’ posting, I would assert that you can “out-IBM the IBMers” or any other large organization by employing search to leverage your knowledge, people and relationships in smart and efficient ways. Excellent content and search practices can probably reduce your total human overhead because even one or two content and search specialists plus the right technology can deliver significant efficiency in intangible asset utilization.

I hope to see conference attendees who come from that SMB community so we can continue this excellent discussion in London, next month. Ask me about how we “ate our own dog-food” (search tools) when I owned a small software firm in the early 1980s. The overhead was minimal compared to the savings in support headcount.

E-discovering Language to Launch Your Taxonomy

February 28, 2013 / Lynda Moulton / 0 Comments

New enterprise initiatives, whether for implementing search solutions or beginning a new product development program, demand communication among team leaders and participants. Language matters; defining terminology for common parlance is essential to smooth progress toward initiative objectives.

Glossaries, dictionaries, taxonomies, thesauri and ontologies are all mechanisms we use routinely in education and work to clarify terms we use to engage and communicate understanding of any specialized domain. Electronic social communication added to the traditional mix of shared information (e.g. documents, databases, spreadsheets, drawings, standardized forms) makes business transactional language more complex. Couple this with the use of personal devices for capturing and storing our work content, notes, writings, correspondence, design and diagram materials and we all become content categorizing managers. Some of us are better than others at organizing and curating our piles of information resources.

As recent brain studies reveal, humans, and probably any animal with a brain, have established cognitive areas in our brains with pathways and relationships among categories of grouped concepts. This reinforces our propensity for expending thought and effort to order all aspects of our lives. That we all organize differently across a huge spectrum of concepts and objects makes it wondrous that we can live and work collaboratively at all. Why after 30+ years of marriage do I arrange my kitchen gadget drawer according to use or purpose of devices while my husband attempts to store the same items according to size and shape? Why do icons and graphics placed in strange locations in software applications and web pages rarely impart meaning and use to me, while others “get it” and adapt immediately?

The previous paragraph may seem to be a pointless digression from the subject of the post but there are two points to be made here. First, we all organize both objects and information to facilitate how we navigate life, including work. Without organization that is somehow rationalized, and established accordingly to our own rules for functioning, our lives descend into dysfunctional chaos. People who don’t organize well or struggle with organizing consistently struggle in school, work and life skills. Second, diversity of practice in organizing is a challenge for working and living with others when we need to share the same spaces and work objectives. This brings me to the very challenging task of organizing information for a website, a discrete business project, or an entire enterprise, especially when a diverse group of participants are engaged as a team.

So, let me make a few bold suggestions about where to begin with your team:

Establish categories of inquiry based on the existing culture of your organization and vertical industry. Avoid being inventive, clever or idiosyncratic. Find categories labels that everyone understands similarly.
Agree on common behaviors and practices for finding by sharing openly the ways in which members of the team need to find, the kinds of information and answers that need discovering, and the conditions under which information is required. These are the basis for findability use cases. Again, begin with the usual situations and save the unusual for later insertion.
Start with what you have in the form of finding aids: places, language and content that are already being actively used; examine how they are organized. Solicit and gather experiences about what is good, helpful and “must have” and note interface elements and navigation aids that are not used. Harvest any existing glossaries, dictionaries, taxonomies, organization charts or other definition entities that can provide feeds to terminology lists.
Use every discoverable repository as a resource (including email stores, social sites, and presentations) for establishing terminology and eventually writing rules for applying terms. Research repositories that are heavily used by groups of specialists and treat them as crops of terminology to be harvested for language that is meaningful to experts. Seek or develop linguistic parsing and term extraction tools and processes to discover words and phrases that are in common use. Use histograms to determine frequency of use, then alphabetize to find similar terms that are conceptually related, and semantic net tools to group discovered terms according to conceptual relationships. Segregate initialisms, acronyms, and abbreviations for analysis and insertion into final lists, as valid terms or synonyms to valid terms.
Talk to the gurus and experts that are the “go-to people” for learning about a topic and use their experience to help determine the most important broad categories for information that needs to be found. Those will become your “top term” groups and facets. Think of top terms as topical in nature (e.g. radar, transportation, weapons systems) and facets as other categories by which people might want to search (e.g. company names, content types, conference titles).
Simplify your top terms and facets into the broadest categories for launching your initiative. You can always add more but you won’t really know where to be the most granular until you begin using tags applied to content. Then you will see what topics have the most content and require narrower topical terms to avoid having too much content piling up under a very broad category.
Select and authorize one individual to be the ultimate decider. Ambiguity of categorizing principles, purpose and needs is always a given due to variations in cognitive functioning. However, the earlier steps outlined here will have been based on broad agreement. When it comes to the more nuanced areas of terminology and understanding, a subject savvy and organizationally mature person with good communication skills and solid professional respect within the enterprise will be a good authority for making final decisions about language. A trusted professional will also know when a change is needed and will seek guidance when necessary.

Revisit the successes and failures of the applied term store routinely: survey users, review search logs, observe information retrieval bottlenecks and troll for new electronic discourse and content as a source of new terminology. A recent post by taxonomy expert Heather Hedden gives more technical guidance about evaluating and sustaining your taxonomy maintenance.

Mobile development strategy – platform decision update

February 22, 2013 / Frank Gilbane / 1 Comment

Last April I suggested that evolving mobile platform market changes meant organizations needed to re-visit their mobile development strategy and said

“What has changed? To over simplify: Apple’s dominance continues to increase and is unassailable in tablets; RIM is not a contender; Microsoft is looking like an up-and-comer; and most surprising to many, Android is looking iffy and is a flop in tablets with the exception of the very Amazon-ized version in the Kindle Fire.”

Not surprisingly, things have changed again. Two major changes are that Samsung is now a major player, and Google has finally made progress in tablets with the Nexus 7 and the much improved Android “Jelly Bean” release. Amazon’s second Fire is also more robust. There are now real choices in tablets – personally I have an iPad, a Fire HD, and a Nexus 7, and I use all three of them, and for many purposes I just grab the closest. But businesses making a significant investment in a platform for development need to carefully evaluate its stability and staying power.

One thing that hasn’t changed is the debate among analysts over what the iOS and Android market share numbers mean – specifically, whether the larger and accelerating Android market share numbers threaten Apple’s dominance. At first glance it is natural to think that dominant market share signifies a safer bet, and indeed many analysts make this point. But it’s not so simple. Last year there was evidence that even though Android devices had a market share advantage, Apple devices accounted for much more total online activity – were used more – and it is probably safe to say that use is a requirement of product success.

More importantly, if you look at profit share, Apple continues to dominate. So the opposing view is that Apple may be the safer bet since for most values of company/product health, profit trumps revenue.

In “The Mobile Train Has Left The Windows 8 Platform Behind“, John Kirk, who doesn’t mince words, has no patience for the view that Android’s market share means it will squash Apple:

“According to Canaccord Genuity, Apple took in 69% of the handset (all mobile phones, not just smartphones) profits in 2012. Samsung took in 34%, HTC accounted for 1%…

No one not named Apple or Samsung is making any meaningful profits from the handset sector…

Many industry observers have the handset market all wrong. They opine that Andoid is destroying iOS. What is actually happening is:

With 69% of the profits, iOS is doing just fine. More than fine, actually.

Android destroyed every phone manufacturer not named Apple (BlackBerry, Nokia, Palm, etc.).

Samsung destroyed every Android phone manufacturer not named Samsung (HTC, Motorola, Sony Erricson, etc.).

Pundits like to predict the imminent demise of iOS, but those profit numbers say just the opposite. And even as Android’s market share has increased, iOS’s profit share has increased too. Market share is no guarantor of profits. This should be self-evident. But apparently, it’s not.”

Kirk follows up with more entertaining disdain for the “church of market share” at “Does the Rise of Android’s Market Share Mean the End of Apple’s Profits?“.

In terms of tablet market share,

“According to Canalys, Apple – despite being supply constrained – sold 22.9 million tablets for 49% share, Samsung shipped 7.6 million tablets, Amazon shipped 4.6 million tablets for 18% share, and Google’s Nexus 7 and 10, combined, shipped 2.6 million tablets.”

In conclusion,

“Only Samsung and Apple are competing in phones. Only Amazon, Google, Samsung and Apple are effectively competing in tablets. The mobile “train” has left the station and companies like HP, Lenovo, Dell and Microsoft are standing on the Windows 8 platform, watching it pull away.”

For more on Microsoft see Kirk’s full post.

Mobile platforms are still evolving and the coming proliferation of new device types guarantee that there will be continuous and substantial change made to those that survive. No one responsible for a mobile development strategy should wait almost a year to evaluate their current plan. Fortunately there is no shortage of useful platform data. It just needs to be interpreted critically.

Big data and decision making: data vs intuition

February 12, 2013 / Frank Gilbane / 2 Comments

There is certainly hype around ‘big data’, as there always has been and always will be about many important technologies or ideas – remember the hype around the Web? Just as annoying is the backlash anti big data hype, typically built around straw men – does anyone actually claim that big data is useful without analysis?

One unfair characterization both sides indulge in involves the role of intuition, which is viewed either as the last lifeline for data-challenged and threatened managers, or as the way real men and women make the smart difficult decisions in the face of too many conflicting statistics.

Robert Carraway, a professor who teaches Quantitative Analysis at UVA’s Darden School of Business, has good news for both sides. In a post on big data and decision making in Forbes, “Meeting the Big Data challenge: Don’t be objective” he argues “that the existence of Big Data and more rational, analytical tools and frameworks places more—not less—weight on the role of intuition.”

Carraway first mentions Corporate Executive Board’s findings that of over 5000 managers 19% were “Visceral decision makers” relying “almost exclusively on intuition.” The rest were more or less evenly split between “Unquestioning empiricists” who rely entirely on analysis and “Informed skeptics … who find some way to balance intuition and analysis.” The assumption of the test and of Carraway was that Informed skeptics had the right approach.

A different study, “Frames, Biases, and Rational Decision-Making in the Human Brain“, at the Institute of Neurology at University College London tested for correlations between the influence of ‘framing bias’ (what it sounds like – making different decisions for the same problem depending on how the problem was framed) and degree of rationality. The study measured which areas of the brain were active using an fMRI and found the activity of the the most rational (least influenced by framing) took place in the prefrontal cortex, where reasoning takes place; the least rational (most influenced by framing / intuition) had activity in the amygdala (home of emotions); and the activity of those in between (“somewhat susceptible to framing, but at times able to overcome it”) in the cingulate cortex, where conflicts are addressed.

It is this last correlation that is suggestive to Carraway, and what he maps to being an informed skeptic. In real life, we have to make decisions without all or enough data, and a predilection for relying on either data or intuition can easily lead us astray. Our decision making benefits by our brain seeing a conflict that calls for skeptical analysis between what the data says and what our intuition is telling us. In other words, intuition is a partner in the dance, and the implication is that it is always in the dance — always has a role.

Big data and all the associated analytical tools provide more ways to find bogus patterns that fit what we are looking for. This makes it easier to find false support for a preconception. So just looking at the facts – just being “objective” – just being “rational” – is less likely to be sufficient.

The way to improve the odds is to introduce conflict – call in the cingulate cortex cavalry. If you have a pre-concieved belief, acknowledge it and and try and refute, rather than support it, with the data.

“the choice of how to analyze Big Data should almost never start with “pick a tool, and use it”. It should invariably start with: pick a belief, and then challenge it. The choice of appropriate analytical tool (and data) should be driven by: what could change my mind?…”

Of course conflict isn’t only possible between intuition and data. It can also be created between different data patterns. Carraway has an earlier related post, “Big Data, Small Bets“, that looks at creating multiple small experiments for big data sets designed to minimize identifying patterns that are either random or not significant.

Thanks to Professor Carraway for elevating the discussion. Read his full post.

How long does it take to develop a mobile app?

February 9, 2013 / Frank Gilbane / 0 Comments

We have covered and written about the issues enterprises need to consider when planning to develop a mobile app, especially on choosing between native apps, mobile web apps (HTML5, etc.), or a hybrid approach that includes elements of each. And have discussed some of the choices / factors that would have an effect on the time required to bring an app to market, but made no attempt to advise or speculate on how long it should take to “develop a mobile app”. This is not a question with a straightforward answer as any software development manager will tell you.

There are many reasons estimating app development time is difficult, but there are also items outside of actual coding that need to be accounted for. For example, a key factor often not considered in measuring app development is the time involved to train or hire for skills. Since most organizations already have experience with standards such as HTML and CSS developing mobile web apps should be, ceteris paribus, less costly and quicker than developing a native app. This is especially true when the app needs to run on multiple devices with different APIs using different programing languages on multiple mobile (and possibly forked) operating systems. But there are often appealing device features that require native code expertise, and even using a mobile development framework which deals with most of this complexity requires learning something new.

App development schedules can also be at the mercy of app store approvals and not-always-predictable operating system updates.

As unlikely as it is to come up with a meaningful answer to the catchy (and borrowed) title of this post, executives need good estimates of the time and effort in developing specific mobile apps. But experience in developing mobile apps is still slim in many organizations and more non-technical managers are now involved in approving and paying for app development. So even limited information on length of effort can provide useful data points.

I found the survey that informed the Visual.ly infographic below via ReadWrite at How Long Does It Take To Build A Native Mobile App? [InfoGraphic]). It involved 100 iOS, Android and HTML5 app developers and was done by market research service AYTM for Kinvey, provider of a cloud backend platform for app developers.

Their finding? Developing an iOS or Android app takes 18 weeks. I didn’t see the survey questions so don’t know whether whether 18 weeks was an average of actual developments, opinions on what it should take, or something else.

Of course there are simple apps that can be created in a few days and some that will take much longer, but in either case the level of effort is almost always underestimated. Even with all the unanswered questions about resources etc., the infographic raises, the 18 week finding may helpfully temper somebody’s overly optimistic expectations.

How Long Does it Take to Build an App?

How Long Does it Take to Build an App? infographic by Angelina.

Launching Your Search for Enterprise Search Fundamentals

January 31, 2013 / Lynda Moulton / 0 Comments

It’s the beginning of a new year and you are tasked with responsibility for your enterprise to get top value from the organization’s information and knowledge assets. You are the IT applications specialist assigned to support individual business units with their technology requests. You might encounter situations similar to these:

Marketing has a major initiative to re-write all product marketing pieces.
Finance is grappling with two newly acquired companies whose financial reports, financial analyses, and forecasts are scattered across a number of repositories.
Your Legal department has a need to categorize and analyze several thousand “idea records” that came from the acquired companies in order to be prepared for future work, patenting new products.
Research and development is attempting to categorize, and integrate into a single system, R&D reports from an existing repository with those from the acquisitions.
Manufacturing requires access to all schematics for eight new products in order to refine and retool manufacturing processes and equipment in their production area.
Customer support demands just-in-time retrieval and accuracy to meet their contractual obligations to tier-one customers, often from field operations, or while in transit to customer sites. The latter case often requires retrieval of a single, unique piece of documentation.

All of these groups have needs, which if not met present high risk or even exposure to lawsuits from clients or investors. You have only one specialist on staff who has had two years of experience with a single search engine, but who is currently deployed to field service operations.

Looking at just these few examples we can see that a number of search related technologies plus human activities may be required to meet the needs of these diverse constituents. From finding and assembling all financial materials across a five-year time period for all business units, to recovering scattered and unclassified emails and memos that contain potential product ideas, the initiative may be huge. A sizable quantity of content and business structural complexity may require a large scale effort just to identify all possible repositories to search for. This repository identifying exercise is a problem to be solved before even thinking about the search technologies to adopt for the “finding” activity.

Beginning the development of a categorizing method and terminology to support possible “auto-categorization” might require text mining and text analysis applications to assess the topical nomenclature and entity attributes that would make a good starting point. These tools can be employed before the adoption of enterprise search applications.

Understanding all the “use-cases” for which engineers may seek schematics in their re-design and re-engineering of a manufacturing plant is essential to selecting the best search technology for them and testing it for deployment.

The bottom line is there is a lot more to know about content and supporting its accessibility with search technology than acquiring the search application. Furthermore, the situations that demand search solutions within the enterprise are far different, and their successful application requires far greater understanding of user search expectations than Web searching for a product or general research on a new topic.

To meet the full challenge of providing the technologies and infrastructure that will deliver reliable and high value information and knowledge when and where required, you must become conversant with a boatload of search related topics. So, where do you begin?

A new primer, manageable in length and logical in order has just been published. It contains the basics you will need to understand the enterprise context for search. A substantive list of reading resources, a glossary and vendor URL list round out the book. As the author suggests, and I concur, you should probably begin with Chapter 12, two pages that will ground you quickly in the key elements of your prospective undertaking.

What is the book? Enterprise Search (of course) by Martin White, O’Reilly Media, Inc., Sebastopol, CA. © 2013 Martin White. 192p. ISBN: 978-1-449-33044-6. Also available as an online edition at: http://my.safaribooksonline.com/book/databases/data-warehouses/9781449330439