big data

Of Digital Breadcrumbs and Black Swans

I don’t remember where I first heard ‘Digital breadcrumbs’, but I thought it nailed this blog’s raison d’être. Pages from a human being’s existence on this planet, to be read by himself later in time, and if humanity does get desperate, maybe even by a sociologist later. 😀 I came across the phrase recently again in this superb post on Farnam Street blog titled  “Big Data as a Lens on Human Culture.”

To quote from it, (originally from the book Uncharted: Big Data as a Lens on Human Culture) “At its core, this big data revolution is about how humans create and preserve a historical record of their activities. Its consequences will transform how we look at ourselves. It will enable the creation of new scopes that make it possible for our society to more effectively probe its own nature.” Indeed, GMail, Facebook, Twitter all have ‘permanent’ records of our conversations and activities. More

Brand, Marketing – 2014 and beyond

These are not really trends or predictions, it’s more a set of drivers and their impact on the domain of brand marketing.

Technology: Disruption is an abused word, but I think technology is the biggest disruption that marketing has experienced. Yes, it has been so every time a new medium cropped up, but this wave is special. In this largish bucket, I’m dumping everything from the Internet of Things (IoT, which, in addition to really smarter devices and spaces, will also, I hope, give the entire domain of social a reboot) to 3D printing (HP’s entry, scheduled for mid 2014, should push this further in the mainstream journey) to wearable tech/techsessories (Google Glass is the poster boy, though development is happening on various fronts) to Social TV. (a classic example of how social adds itself as a layer to existing media platforms and augments it)  I also add to this the advancements in devices – specifically mobile, which is already forcing marketers to quickly rework their strategy to adapt. The reason I used the word disruption is because by fostering a new kind of phenomenon like say, the collaborative economy, and getting ready to challenge traditional manufacturing, technology is going beyond its role as an enabler and changing brand experiences.

Marketing Technology: While the first point was about technology in a relatively generic sense, this is is about the application of technology and associated tools in the marketing domain. This is everything from marketing automation to web content management to advertising technology and so many, many more things which will probably make a move towards mainstream in 2014. This very popular image would give you a vastness of this domain. With the kind of data that phenomena like IoT and wearable tech will spew out, and the levels of customisation that customers expect, everyone, across domain would have to at least attempt Amazonian levels of efficiency.  Also, increasingly, technology will help us integrate offline with digital. (example)

We can scream buzzword, but big data exists, and we’re only taking baby steps towards harnessing it. I can already see the first levels of it in social media advertising, where intelligent tools and dashboards allow not just better and real time targeting but also better analytics on everything from planning to attribution, to aid decision making. Extrapolate this to multiple media platforms, devices, delivery channels within each and think of the possibilities. I think the domain will move much faster because of two reasons – one, the fragmentation of marketing channels and the impossibility of managing it with only manpower resources, and two, the marketer’s ROI obsession. To quote Scott Brinker, “software is the new fabric of marketing” I see the ‘big’ in big data moving on two paths simultaneously – qualitatively big that would help in personalisation, and quantitatively big that would help in scaling. (mass customisation for larger audience sets, better targeted)

Agile Marketing: Yes, we have borrowed it from the software development guys. No, it’s not really new, nor is it surprising because if marketing is getting a technology influx, it is only obvious that software processes might be a good way to approach marketing. Everything that I have written above will ensure that by design or not, marketers will increasingly be forced to adopt this methodology as the days of predictable media platforms draw to a close. In a dynamic business environment, where new platforms are popping up regularly, and even known platforms are changing their rules constantly, the only way to cope, let alone thrive, would be to run various simulations continuously,  iterate and develop incrementally, break silos and communicate effectively, and have flexible frameworks that can be more responsive to the speed of the change cycles.  What I hope to see this year – at least at an early stage – are software/tools that are customised to the requirements of marketing. But irrespective of that, get ready to sprint! (read more)

Promotainment: Roughly, the phenomenon formerly known as advertising. Thanks to everything above, creativity will need to be channeled differently. In YouTube’s top trends for 2013, three branded videos managed to capture a place for themselves. But this only covers part of the story. Mere entertainment will not be enough to bond with the consumer, for sufficient pull to happen, brands will have to define a purpose (business and beyond) that will resonate with consumers, and treat it differently according to contexts. These contexts could be platforms, locations, topical opportunities and a host of other things, with each experience adding to the perceptions of the consumer. Experiences and ‘content’ need to be created for each of these contexts, and brands need to reboot the way they handle communication. (The Making of a Content Brand) The other key player in this mix is privacy – everything from transience (eg. Snapchat) to the ‘negotiation’ with consumers on what information they share to get what benefit. Customisation as per contexts and audiences and yet cohesive within the larger purpose framework. Not an easy challenge. (A wonderful take on this, and more from Vyshnavi Doss – Brand Avatars)

Marketing Organisation: I came across the fascinating Big Shift concept and the three ‘waves‘ – foundation, flow and impact – only recently. The third wave is how organisations respond to the fundamental shifts in knowledge and the flow of information that are characteristic of the first two waves. While this is a larger institutional shift, its impact will also felt in the structure of the marketing organisation. Add to this, the transformation required for agile methodologies and a fundamentally different content marketing process, and the existing marketing silos have no choice but to evolve. Technologists, ROI drivers, specialists in different kinds of brand experiences – real time, real (offline) and otherwise, data wizards to analyse the tons of data streaming in, CRM folks, creative people and many more will be part of this new structure that realigns the marketing domain to fit the new business landscape dynamics. (a good illustration)

These subjects, and in my mind, one of its results –  social business – will form the majority of this blog’s content in 2014. We’re at the cusp of an extremely interesting era in brand marketing, thanks to radical shifts in pretty much everything happening around us – what I keep referring to as institutional realignment. Here’s to an exciting year ahead!

einstein

 until next time, have a wonderful 2014!

The questions in Big Data

In my last post that touched upon Big Data, I had mentioned how the seeming intent of Big Data is to synthesise actionable insights from processed and unprocessed information at touch points related or unrelated to the enterprise, and then use it to target consumers better. While this is probably true for the short-medium term, I read a wonderful perspective at GigaOm by Beau Cronin on its true potential – the path to building the equivalent of global-scale nervous systems. As I tweeted after I read it, it reminded me of something I’d written a couple of years back before I’d heard of #BigData – if we could actually use data to go beyond that to answer life’s profound questions. Before we go into the subject, here’s a nice video by OgilvyOne titled “Big Data for smarter customer experiences” (via) though it’s skewed more towards the experience rather than the data.

Beau Cronin has mentioned several possibilities this would give rise to, and the post made me think if something like the hive mind concept would mesh into it as well – a sort of hybrid neural network. He has also pointed out the hurdles we would face while we get there – gathering, processing and conversion into actionable insights, and how phenomena such as priming,expectations, and framing matter so much in how we perceive our physical and social environments. In essence, a fascinating read.

I was particularly intrigued by framing, and began thinking about it in the context of the unstructured data – tweets, posts, mails, videos – that is a major component of Big Data. The fundamental question being – is it unstructured because we’re framing it ‘wrong’? Based on the enterprise’ intent and not the users’? Ironically, I couldn’t frame the questions right until I met the ever-brilliant S, who has always maintained that the answer is easy to find once the question has been framed right. He has developed (Tulpa -to build or construct in Tibetan – is the concept he enlightened me on while we were discussing semantics) something that at a rough level mashes the MECE principle with Frame Semantics and the entity-relationship model. There’s IPR involved, so no more beans shall be spilled, but as always, I learned much from the conversation.

In essence, structure can definitely be derived from what we currently call unstructured data, provided we frame the queries right. I can intuitively begin to understand that in the era of data abundance, the only way we can make sense of all of it is by focusing on an intent that is derived from a common purpose, so that the sources of data (users) will be more open to help solve the challenges of data collection. The processing and inferences that follow would yield the best results when the right questions are asked. I have a feeling that the questions asked by a business in an earlier era might not cut it.

until next time, role models

Brands and the Personal API

Lifestreaming and I go way back, at least 5 years. 2008 was when I wrote about it first, though the experiments had started earlier. Most of the services I’ve mentioned in the post are now defunct, but my interest in the subject never waned. From the perspectives of memories mentioned in that post to speciation to brands using their lifestreams to build communities around it, I have had several thoughts on the subject. That’s why I found this post at GigaOm, which was about Foursquare co-founder Naveen Selvadurai sharing data logs from his life (weight, sleep, activities) and hoping developers would hack his ‘personal API‘, very very interesting. There have been stories about people and the tons of lifestreaming data they have amassed, but I had never heard of an API, and therefore consider it pioneering work.

Pioneering, less because of the novelty, and more because I think it has the potential to become mainstream, and even, the default paradigm of creation and consumption. Since the engagement @ scale framework refuses to let go of me, I immediately thought of the personal API in that context. With technological advances, I think it’ll become easier to create one’s own APIs and you can see several companies mentioned in the GigaOm post that are working on it. So I’d hope that its evolution is as fast as (or faster than) that of self publishing (on the web) which about a decade back was a relatively complex thing to do. So, in essence, we’re talking about huge amounts of data that are being generated and captured by individual users, and this is only going to be accelerated thanks to phenomena like wearable technology.

The current way of looking at Big Data is to synthesise actionable insights from processed and unprocessed information from touch points related or unrelated to the enterprise. As I’d mentioned in my presentation (on engagement @ scale) this is then used to target users better or drive more efficiencies.  They don’t really operate at the higher levels of community/meaning/purpose. Now think of the personal API and the data it holds. What if we looked at this individual streams of ‘Big Data’ not from the enterprise’ perspective but from the user perspective? What if brands created platforms that  would allow people to upload data that they choose to so that the brands could solve their needs better? Like I wrote in my ‘maker’ post, with massive technology leaps happening in areas like 3 D printing, there are tremendous opportunities for co-creation. Brands could even aggregate data from these individual streams to find need gaps and package that for a larger market. In fact, I’d say that this is probably what Nike+ is doing already.

But the real story is that these personal APIs could give great insights into the individual’s purpose in life, his priorities – in short, his life’s narrative. It gives brands the window to latch on to the narrative that they can identify with, and create value and meaning in the individual’s life. I think that’s what brands originally strove to do!

Update: Thanks MJ, for pointing me to the Nike+ Accelerator!

until next time, AP”I”

PS: Over at Soylent, they’re creating the nutritional equivalent of water, an ubiquitous ‘meal’ that is customised for body types. Funding? Kickstarter of course! :)

@ Social Business Summit

I was quite thrilled to be invited to speak at the Mumbai version of the Dachis Group’s Social Business Summit – not just because of my awesome co-speakers, but because this is a platform that has seen the likes of Tony Hsieh and John Hagel earlier this year! To confess, a little nervous too, since (as my friend Kavi Arasu, whom I met for the first time after years of knowing him online, put it) I was going to ‘open the batting’! But in the end, it did turn out very well, judging from the audience reaction. Here’s my presentation – The Currencies of Engagement @ Scale, with a talk flow right below since slides with Yoda and Spock could seem way out of context in the subject of Engagement @ Scale.

The currencies of engagement @ scale

It was a fantastic experience – the crowd, perspectives of co-speakers, meeting Gaurav, Haroon, Nadhiya for the first time outside of Twitter, catching up with Gautam, Sumant, Sanjay and Ideasmith, and being introduced to a whole bunch of people that I hope to be in touch with.

But my biggest thrill was in getting this platform to share my ideas on an evolving domain that I am passionate about, and being appreciated by the likes of Jeff Dachis and Michael Jones. It was both exhilarating, and humbling.

 

A few photos here, though my expressions make it seem more like ComicCon or a theatre workshop! :O

I also wrote a more elaborate post at Medianama. Do take a look.

until next time, #SBS2013 #ftw :)

With great data…

LinkedIn’s article curation is improving very well in my case. What I particularly like is the dash of serendipity in the list. One of the articles I recently read was “Are we all being fooled by Big Data?” Though it is less to do with business per se and is skewed towards economic forecasting, it does make for a very interesting read.

Gartner’s 2013 Strategic Technology Trends has Strategic Big Data as one. In fact, I’d also add ‘The Internet of Things’, ‘In Memory Computing’ and ‘Actionable Analytics’ (also in the list) as related items, as a source, enabler and application respectively. While Big Data has been talked about for a while now, and has seen applications as well, I am not sure how accessible it is to the majority of organisations and brands. In essence, is it ‘mainstream’ enough? (I see organisations struggling to link existing data) Are there frameworks being built that will aid analysis and action across various functional domains – ways to nimbly access and use contextually relevant ‘packets’ from troves?

Probably 2013 is when we will see things moving. But there’s something about data that worries me. This has come from my own experience as well as from the things I have read/heard. And that’s where the organisation’s intent becomes important, because you can find data to validate most anything! This is all the more significant because with improving technology, the volumes of data will have the potential to help brands shift paradigms and disrupt the status quo. But it can also be used for strategic/tactical blunders. As the saying goes “If you torture data long enough, it will confess to almost anything

All of this reminds me of social media. The hype, the evangelism, the tools and so on. And just like social, Big Data has in it the ability to amplify the inherent nature of the enterprise.

until next time, think big

Differentiate or die?

I’m close to finishing “A Clash of Kings” – Book 2 of George R.R. Martin’s “A Song of Ice and Fire”. Pages 879-913 has lists of houses and characters. The lists will continue to expand in the next book, I’m reasonably sure, and I will probably have to spend Rs.200+ and buy this app. Many fantasy superstars have existed before GoT – Potter, LOTR, but this is the first time I have been immersed in one. Generally speaking, works of fiction are unique, and yet, such is the abundance and the related scarcity of time that there are choices to be made. So why GoT? Mostly courtesy the huge buzz the TV series generated on my various timelines. Let me now shift the story to brands, where abundance and time scarcity takes an even worse toll.

The title of this post comes from an article in FT. Without getting into the author’s bias/(vested) interest, I think he has a point when he says that the increasing focus on efficiency is stifling innovation and on the other side making consumers ‘number and dumber’.  On the business side, why bother with niche audiences when access to large sets of consumers through databases and mass media (now social media too) is much easier. On the consumer side, larger tribes are easier to find in the search for belonging. Of course these are generalisations, and I’ll be the first to admit that there are exceptions.

In the case of mass brands solving mass needs/wants, functional benefits are increasingly becoming a commodity. In an earlier age of information scarcity and relatively unfragmented media, differentiation could be as simple as just being visible. The story is different now, though the recent turn of social towards media would indicate that only the channels have changed. But IMO, there is a high chance that this trend will prove to be shorter than the reign of mass media, and true differentiation will evolve from a user perspective after everything from product to design to communication to experience has become a commodity. Arguable. :)

Increasingly, brands are using social media to target better, and that’s how platforms are selling their users too. I wonder if/how many brands at this stage are attempting to make their stories personal to the user. Different social platforms offer different contexts – in the way they are designed, in how users consume them, in terms of the need they satisfy, in terms of devices they are best suited for etc. Think of how Facebook, LinkedIn, 4sq, Twitter, Pinterest, Instagram, Path and the other services you use fit into your lives. Yet how many brands are trying to fit themselves into these contexts? Yes, we’re still in the early days of Big Data, but how much of investments are brands making in this as opposed to say, better FB targeting? What do you think – is it a scalable form of differentiation? Is it because of the pull towards familiar forms and templates of communication (read targeted mass advertising) that brands are loathe to walk this long path?

until next time, differentiation by integration?

Bonus Read: The Future of Storytelling

Until the customer is king..

Instagram just released v3.0. One of the biggest changes in this version is the introduction of Photo Maps, which quite obviously, plots your photos on a map. The default is opt-in, not opt-out, though they’ve done their bit to give the user control over data.  I updated despite reading this Wired article on the privacy implications and the bug that briefly exposed private photos!

I’d written my first post that referred to Big Data recently, and the day after that, I read this very interesting post that talked about various applications including an algorithm that can identify cities based on their unique architectural elements and other distinguising characteristics. But a few weeks earlier, WSJ had an interesting post that talked of how large corporations see big data as a means to get personal with customers using information gathered by placing tracking files in people’s browsers and smartphone apps without their knowledge—so they can be stalked wherever they go, with their “experiences” on commercial websites “personalized” for them. The post describes not just its real world analogies but practices as well, and predicts a future where the user will declare your own policies, preferences and terms of engagement—and do it in ways that can be automated both for you and the companies you engage. An entire ecosystem across apps and corporations built in a consumer centric fashion.

But as the post itself admits, the move toward individual empowerment is a long, gradual revolution. Until then, we need to define our own limits of sharing, fully understanding that it is a give and take. Not just what and where, but whom too – since all it takes a RT or a ‘Share – Public’ for something shared in a close circle to go public. How much of privacy would I give up to open myself to opportunities, or get an experience that is tailored to my needs and convenience. On the other side, a modern corporation needs to understand the choice the consumer is making and use the information to not just provide genuine value, but also make it easier for both entities to adapt to the rapidly changing landscape.

until next time, kingmakers

Data: Growing up

The Facebook story might be facing rough weather, but that hasn’t stopped the social network from pushing out new and interesting things. It launched “Page Post Targeting Enhanced” – features that make it a media platform offering sharper slices to marketers (easily) by allowing filters based on gender, interests, relationship status etc. It has also rolled out Facebook Stories that highlights “people using Facebook in extraordinary ways”. Venture Beat has a very smart take on how this can be the future of news by intersecting two of the most interesting contexts – location and interest. As a media platform, one can imagine the advertising potential.

Twitter already has local (city specific) trends, though, from experience, many people seem to think that they’re viewing national trends when Twitter is actually showing them local trends. Twitter already has Promoted Tweets and is enhancing features that allow better targeting.

Media buying in the age of traditional media consisted of a plan being prepared (and negotiated) after evaluating the reach, cost and other parameters of various options across platforms – print, OOH, TV, Radio etc. The (reach) data has always been contested, and the (post) measurement is more of a myth than reality. New media platforms, on the other hand, are significantly better in terms of transparency and in addition, have better native and 3rd party tools for self publishing, distributing and measuring. The data is one click away from the marketer. After a certain tipping point of reach that these media achieve, traditional media would be forced to provide this level of accessibility, and then, IMO, the value provided by media agencies would be reduced significantly, as tools would make it easier for the marketer to plan real time and measure too, across platforms.

In essence, data that the marketer needs, to make informed choices on the why/what/how/when of platforms, is easily becoming available.  The data that really needs to be converted into information is now flowing in the reverse direction – from the consumer and his actions across platforms to ______. And this data is not just for marketing, its use is across the board and affects product, customer care, operations, technology and so on. It is Big Data, the players are evolving, and the next stage in this ever changing game has begun.

until next time, don’t worry, it’s already a buzzword. 😉