David Amerland

marketing

  • It’s easier to explain how something works when it no longer does. The reason for this lies in an obvious fact. When everything works as it should we forget about the effects and tend to focus on the mechanics. Because the system in question delivers what it promises we take its function for granted. As a result the “what” is conveniently overlooked and we focus on the “how”. 

    Let it break down at any point however and suddenly we become acutely aware of what it is that it actually does. Email, which is terrific in the way it breaks up messages at the point of origin, transmits fragmented bits over the internet pipes and then reassembles the message at the point of the receiver is amazing until it stops. Then we suddenly realize just how huge a chunk of our business relies on emails getting through to us immediately. 

    It’s the same with cognitive computing and semantic technologies, terms that are increasingly interchangeable. When employed correctly cognitive computing (which employs Machine Learning) takes masses of raw data and turns it into usable information by assessing the importance of each piece in relation to all the other pieces around it and then weighs the importance of a cluster of connected data in relation to all the other, similar clusters found on the web. The result is that answers are produced that closely approximate what a person would be able to provide had he had access to all the world’s information and a brain the size of a planet. 

    Not As Easy As It Sounds

    What sounds easy to explain is hard to do. For a start the algorithms that do all this have an accepted fail rate that in the best case scenario is around the 5% globally. But the global accuracy picture does not take into account what happens when the data required to cross-check and cross-reference the veracity of the connections is not there. 

    To illustrate what I mean consider what happens when I turn up at a conference on Big Data and call myself a Data Scientist. Because I play to stereotypes and want to live up to expectations, I have the impressive name badge, the clipboard and the slightly odd professorial attire. To clinch the deal I have also a presentation running behind me and have paid 50 friends to turn up and tell everyone who I am. 

    In that environment I am a data point. My attire and presentation are my primary footprint and my 50, paid friends are my connections. Anyone entering that environment has no reason to suspect I am lying and no good reason to challenge me on what I am purporting to be. 

    But a Data Scientist is not a point of data that works in a vacuum. You would expect to at least find a business I am working with that independently verifies my expertise and title. A publication or two. A book maybe. At least one paper. Other publications, excerpts, comments, interviews and appearances that indicate that yes, I am who I say I am and I do what I say I do. 

    Should there be a doubting Thomas in the audience (and in this case he plays the role of a search engine bot) all he has to do is Google my name to find all the connections, reviews of my books, citations and mentions. 

    This is what cognitive computing does when it comes to information. Not only does a spider of some description check to see the complexity and veracity of the immediate web that the presence of interlinked data has created but it then checks to see its history across a much wider spectrum of information. 

    The 4Vs Rule

    Data has a life that is governed by the Big Data concepts of: 

    • Volume
    • Velocity
    • Variety
    • Veracity

    Taken as a whole all four of the 4Vs represent a living, breathing piece of data (or datum to be a little pedantic) which, once we get past the metaphorical phase, suggests that the data actually has impact. People are interested in it. It has relative importance and therefore it has some degree of existential truth (which is where the Veracity component comes in). 

    Lacking that (which is what happens in my closed-world example above) holes develop in the capacity of an algorithm to truly understand what is happening. Its assessment of the situation may show that it is a case where trustworthiness may be questionable but beyond that it cannot really suggest anything. 

    The weakness here is in the conjecture. While humans can very quickly draw from their understanding of society and its structures and the possible pitfalls and suggest a motive in the overt absence of evidence of trustworthiness, an algorithm can only present the next ‘best’ answer it has available and that usually is never good enough. 

    How Does Google Do Map Semantic Connections?

    Google used to use Google+ and the web at large to track individual posts, link them to websites and personal profiles, map sentiment in comments and compare it all with past profile activity and textbook ‘signature’ styles to see what is real, what is not and what is somewhere in between. It continues to do this across the wider web using machine learning technology to provide it with the only cost-effective means to do so. 

    Given the ability of computers to do everything faster and better and their capacity to never forget it is easy to imagine that there is an always-on, omniscient mega-machine keeping tabs on everything and everybody and assigning some kind of ever evolving numerical value to everything. Clearly, this is not the case. 

    The reason lies in both the amount of information that is released every moment on the web and the computational power required to keep tabs of it all. Even a company as big as Google requires some kind of shortcut to make sense of it all and those shortcuts lie in trusted entities. The problem is it takes a long time to develop trusted entities that are in the same class as say Wikipedia or the New York Times. With time this problem will be a little smaller though the amount of fresh data released on the web will only grow. 

    We Are The Final Link

    The final link in the very long chain of processes that make information be true or false on the web, is us. Ultimately our activities, shortcuts and transparency become key to maintaining veracity across the web and while we may not be quite to the point where everyone is accountable for their actions and feels responsible for what they post, by degrees we will get there. Particularly as the divide between online and offline is being continuously bridged, first by our mobile devices and now by the advent of virtual reality and augmented reality connections. 

    What Marketers and Businesses Need to Know

    There is good news in all this for both marketers and businesses. If you’ve already got a copy of SEO Help then you’re ahead of the game and are already reaping the benefits. If you haven’t however you need, at the very least to do the following: 

    • Create data-density to your online presence that at least matches your offline one.
    • Find an audience. That means that on the web you need to engage. Do not just broadcast.
    • Define your identity. If a guy selling cronuts can do it, anybody can.
    • Think like a publisher. In Google Semantic Search I explained how now, none of us have a choice. Just like opening up a shop forces you to become an expert on window displays, color psychology and lighting, operating on the web requires you to know what works in terms of text, pictures and video.
    • Be personable. If your ‘voice’ and identity do not come across then people are unlikely to want to engage with a blunt, corporate sounding machine.
    • Be real. Acknowledge faults and weaknesses and work to set them right. 

    These are minimum requirements and each takes a lot of effort to get right. But then again something that requires hardly any effort at all is unlikely to hold much value in the eyes of the beholder which means it will not really get you anywhere. 

     

  • The trust we place in beards 
    Next time you want to fast-track the trust of the members of a social network I’d advise you to invest on a beard. Grown, glued or photoshopped, a beard apparently has the magical ability to increase your trustworthiness quotient (QT) by several notches at once.

  • None understood the cost of value perhaps better than the Ancient Egyptians. The great Pyramid of Cheops (one of the seven wonders of the Ancient World) required ten years of construction and up to 40,000 workers at one stage for what is essentially a tomb to house the remains of a dead emperor.

  • In a world where everything is data, navigating to the right place, finding the right answer or matching the right pair (of anything) is always a search problem. Data only makes sense when it is networked, connected, indexed, analyzed, assessed, abstracted, categorized, organized and presented in relation to other data.

    The process is an endless rinse-and-repeat cycle where the metadata surfaced becomes semantically dense enough to become data in its own right, allowing further metadata to be extracted from it. 

    Let’s get practical. Apply all the theoretical abstraction I’ve written above to the usual “Morning!” Greeting between neighbors. The depth of the relational connection between them (are they good friends, or are they being civil to each other?) will reveal itself in the warmth of the candour of that one, single word, exchanged. Is one distracted, lost in thought? Depressed? Angry? Clipped tones, trailing endings, a pitch that’s so low as to be barely audible or too high and sounds like a whine can be used to analyze emotions. Is the sound harsh? The word spoken fast, like an expletive almost, or are the syllables, long-drawn out? The difference could spell out whether there is enmity in the relationship, hidden aggression or it’s a casual, social connection with no other overtones. 

    We’ve only used one word and that’s before we begin to analyze whether there is a male/female interaction involved or whether a regional or national accent comes into play. 

    This is exactly the kind of semantic analysis Google does with speech in order to help improve its understanding of spoken queries in search. Because speech is data, possessing it also allows the accumulation of knowledge which stems from a sense of how speech is broken down into discrete units, analyzed for content, context and importance and classified. This allows Google the ability to reverse-engineer the process and create human-like speech using a computer that can now use inflexion, pitch, rhythm and speed to denote warmth, friendliness and openness. 

    There are several important takeaways here: 

    • In a data-centric world search is everywhere, even if we do not actively call it search or have a sense of it as such.
    • Everything that has an effect is information. Information is data. Data is subject to analysis and classification. That includes relatively ethereal things like emotion and intent.
    • Once metadata accumulates it becomes substantial enough to be subject to further analysis and classification so it becomes data which gives rise to further metadata.
    • The process of labelling, classification and refinement can be continued ad infinitum unless there are clear boundaries marked by benefits vs costs which do not fully justify the reiteration.
    • Data always has value. Its value is always contextual. 

    As Google’s machine learning gets better and better its voice recognition and voice synthesis capabilities will exponentially improve. Machine learning is closely linked to exponential growth because of the way training sets of data are sampled and the algorithms are then recalibrated. Exponential growth, as the graph below illustrates, has a latency period after which change accelerates dramatically. In practical terms this means that once machine learning gets past a tipping point it begins to produce good results at an accelerated rate.     

    Exponential Growth in Machine Learning Accuracy

    Getting to the Very Core of Reality

    Marketing has never quite been about being real. It has always been seen as the means through which a stimulus is created which is then satisfied by the product or service that is being marketed. But that is, to put it mildly, manipulation. It plays on desires, needs and fears to create a false sense of urgency that will lead to a purchase before the potential buyer has had the chance to research anything, think things through or change her mind. 

    Semantic search promised to change all of this by creating entities which are based on identity. This generates data, that needs to be classifed and validated.

    Machine learning makes all of this faster and less costly which means that more and more can be done without increasing operating costs. 

    Fire hydrant voice search querySearch queries posed in natural language can be processed and matched against real world concepts and objects without going through the traditional ‘translation’ phase where we try to think what specific search terms might possibly describe those objects. The search query “Red cylindrical object used to fight fire” returns, without any hesitation, “fire hydrant” on Voice Search.

    One of the most specific areas where this takes place is voice search and voice interaction. Without a keyboard to input a search query we have no drop-down autosuggestions from Google. We also cannot always remember what we searched for two queries earlier so the very concept of search terms (or even keywords) becomes redundant. 

    The approach has two very significant effects: 

    • Natural language description frequently supplants exact search terms and, even a search methodology.
    • It often does not feel like search. (Google Now, Waze, Google Maps, YouTube, GMail and Google Photos) are examples where search technology is active in the background. 

    The video below on Google Voice and how it is put together beautifully explains some of the concepts:  

    What it really means is that everything a business, a brand or a person does online and offline now really matters. This concept of “data density” was first broached in SEO Help designed, very specifically to address issues of identity, brand values and entity formation as part of a business’ or a brand’s day-to-day activities. 

     Because everything is data and everything is beginning to be understood and indexed, creating the necessary semantically rich data density required to succeed in search has to be part of an incremental, sustained and sustainable process that weds brand identity and core values with brand marketing activities and brand voice. Of course, in a semantic web, from a presence point of view everyone and everything is, from a practical point of view, a brand.  

     

  • The attention Economy Runs on Trust

    The web has always been a publishing medium. As a matter of fact it’s the effect it had on the democratization of publishing that allowed ordinary people to produce content at will that has been a catalyst to dramatic change on many fronts.  

    When citizen-journalism is possible and content can be produced by anyone with a blog, a web cam and a digital camera (in any combination of the three) the gatekeeper role of content creators such as newspapers, magazines and big publishers becomes redundant. When content is created by so many, so fast, in so many different ways, indexing it requires more than just the ability to catalogue it. It needs context, importance, relevance and trustworthiness. 

    The wave of content that led to the explosion of Big Data on the web, became the reason that led us to sematic search. A clever means of organizing massive amounts of data so they do not overwhelm us semantic search (search, really, as semantic technology is powering almost every search engine) also changed the way we view the veracity of content. Used to taking advertising at face value, our response to it highly dependent on the inclusion of emotional triggers (playing heavily on our fears, concerns and worries) we now want content to talk to us using our language, addressing our real concerns, appealing to logic as well as emotion and connecting with us as real people, rather than faceless units in a potential audience addressed en masse by a cleverly crafted marketing message. 

    Branding, marketing, search engine optimization and content creation, then stopped being separate disciplines in the marketing toolbox, only passingly acknowledging each other. In the 21st century they have become a unified means of addressing the needs of the audience and a direct way of making contact with them. 

    A recent study by Chartbeat on the online news media data metrics showed that: 

     

    About 40% of visitors leave having spent fewer than 15 seconds engaged on the page — and yet the pageview is often viewed as the most important metric.

     

    It’s not enough to get someone to click. We have to get them to read.

     

    Chartbeat provides editorial reporting to 80 per cent of the leading digital publishers in the US, and in a further 60 countries globally, using its publishing tools to help editorial staff create engaging content and design sites so its statistics are based on sufficient data to sound a warning bell.  

    It’s All About Money

    Online news sites of course don’t just serve news. They also serve ads and it is these that the statistic posted above is actually killing. When the news content you create is barely sufficient to stop the eye for 15 seconds, you can guarantee that no one is looking at the ads you charge clients, to place on the site. 

    The fact that attention and engagement are better metrics than pageviews has led the Interactive Advertising Bureau’s European body to urge adoption of viewability as the basis for display ad transactions, giving a virtual greenlight for publishers and advertisers to start using ‘attention’ as a significant advertising currency.

    This is where trust comes in. News and content become compelling when it comes from a trustworthy source, has something relevant to say and presents it in a way that is very accessible. Making readers jump through hoops by separating a 500 word article into four pages so you can serve more ads and more pageviews (as an example) is neither the best way to grab their attention nor gain their trust. 

    So, what works? 

    • Transparency – by all means serve your needs as a publisher, eCommerce website, marketer but also acknowledge the fact that you care about your readers. Work hard to show you do. No one says business should not work hard to make money, but a business that resorts to the online equivalent of ‘dirty tricks’ in order to do so, fails to gain the respect of the audience it seeks to attract. 
    • Vulnerability – if you’re running a site you really need people to get there. Acknowledge that, then work to make their time on your site as productive as possible even to your own detriment. If an article can deliver its content in 200 words, beefing it up to 800 is a disservice to the reader. Yes, you want them to stay on your site and yes you want them to remember you and come back. Treat them like you would yourself. It’s the only way to gain trust and attention.
    • Value – Stop producing content for content’s sake. Yes, the web has turned us all into publishers but the content we produce now needs to truly work to justify the time it has taken to create. So take pride in your work, create content that says: “I am pouring my soul into this because I think it really matters” and then let your online audience do the rest.
    • Stop begging – Sites that ask you to share their content with action calls that actually say “Share this with all your friends” may feel clever because they are ticking the “call to action” box in creating content, but they are also annoying the hell out of those who want to make up their own mind on what to share and what not to. This includes those annoying pop ups that always have the equivalent of “Do the clever thing and subscribe to our newsletter/RSS/mailing list” in big red letters while smaller bold font gives you the option of saying: “I want to remain uninformed/stupid/in the dark” and not subscribe to whatever they’re offering. Really, that is so transparent it really turns people off.
    • Start leading – Don’t wait for people to find your site. Lead the online conversation on the issues that truly matter to your business by starting it, first. At the end of the day it is your business. If you don’t care enough to raise your voice, who will? 

     The web is changing fast. If you’re still using Google Analytics to count pageviews, maybe you’re not changing fast enough. 

     

    Additional Links and Sources

    Why Publishers are Killing Pageviews (White Paper)
    Defining and Measuring Digital Ad Engagement in a Cross-Platform World
    Digital Ad Engagement: An Industry Overview and Reconceptualization (White Paper)

     

  • Maybe the time has come to apply a new value system on transactions in our world.
    This is a thought experiment. My posts on SEO, social media and marketing, reach these days into realms which I would not normally consider. Such is the pervasive power of social media to disrupt traditional notions of value and the traditional ways of doing things that over the last eight weeks I have written in-depth, detailed posts covering parenting, obscure US legislature, the law-making process, the nomenclature of bread and whether our focus on common sense sometimes circumvents logic.

  • Every business understands the value in branding, but few get the values of branding. In presentations I’ve often discussed how branding now cannot be separated from other business considerations like search, content creation, a social media presence and the core values that make a business what it is. 

  • “Disruption is killing us.” I overheard this at a meeting recently. One Head of department to another. It’s marketing. 

© 2019 David Amerland. All rights reserved