Deep Learning, Personalization & Privacy

These three - Deep Learning, Personalization and Privacy are indeed oxymorons.  The fact that when they come together for contextualization, relevance and differentiated customer experience - privacy takes a back seat!  When Privacy takes centre stage, then Deep Learning & personalization take a backseat! The real question, is from a customer point of view, can they work in harmony? How do companies use them effectively?

What deep learning can do is well documented. When you listen to this talk by Jeff Dean on Large scale deep learning at Google, you will realize the power of its capability. The most important difference you will see is how Google has embedded that in its products and services.This then brings the issue of privacy to the center of the debate, as this is the data of the customer that Google analyzes & monetizes. However, when it comes to the synergy between Deep learning and personalization, all the data that is used to understand this customer, effectively means personalization can be done like never before. So, the next time you walk-in to your favorite store, or your bank, or your online store, or your health care provider - the personalization possibilities thro' virtual assistants can create a phenomenal experience to the customer. Hence, if deep learning helps customers make their life simpler, then what's the problem with privacy? I think if this is done with the permission of the customer, then puts to rest the debate.

However, this has a lot of learning for the other industries - as the customer pays and owns their products, unlike Google where products are sometimes used for free. Take for example an automotive brand - the applications of deep learning, personalization is phenomenal. With most cars fitted now with navigation systems and telematics devices, the data this can throw about the customer, their driving habits into their automotive platform is phenomenal. The driving habits, the engine data, travel data, innovative use of public data all represent great deep learning application opportunities for the automotive brands to drive personalization & differentiation. Here, privacy is something of little consequence or debate as any assisted customer service will only enhance the customer experience. The same goes with banks - where the usage of the mobile app, online banking, payment apps, shopping data  thro' credit cards, public financial data etc. will only create opportunities for deep learning applications and personalization for enabling personalized financial solutions.

The question really is not will they but they will have to do it soon.


Software vendors as data vendors - How will convergence, interplay & privacy make a difference?

Last week, we saw Microsoft announcing the acquisition of Linked-In for US $ 26.2 billion. With the acquisition of Linked-In, Microsoft now has access to over 400 million accurate profiles of professionals from Linked-In across the world. Over the last year or two, I have been seeing this trend where large software vendors like Salesforce.com acquiring Jigsaw and Oracle acquiring Blue Kai, who predominantly own data. So, this got me to think, what are the implications one can expect or must see over the next few years with these kind of trends?

Meanwhile, I was also reading an interesting article written by Sangeet Paul Choudhary in his blog, where it is mentioned how Linked-In was trying to get into the enterprise CRM space but lacked the infrastructure & tools( post written by Myk Pono) and Sangeet's view on how Microsoft can take advantage of this acquisition but lacks the understanding of network & data layers.

The key questions that came-up to me was - What does it take for a software vendor to work  & behave like a data vendor or as a platform player? Also, how can all these data seamlessly flow into Microsoft's strategy of leveraging its Enterprise CRM, Windows, Azure, gaming business etc.?

To understand & appreciate this, first we need to look at some of Google's acquisition of DoubleClick, Andriod etc. way back in 2007 & 2004 which made a huge difference to their platform strategy. As Google transformed itself from a search to an online advertising platform, many of these acquisitions made sense - with Android becoming the defacto mobile OS platform while still Microsoft was managing Nokia as a Mobile Phone company and not as a platform.This led to the death of Nokia as a mobile phone brand, as Microsoft thought of it like a licensing business(which is their DNA) more than a mobile computing platform. 

If Microsoft needs to take advantage of Linked-In's acquisition & their data, then - the transformation of Microsoft as a platform company is critical. For example,they need to look at  Office365 as a central platform or a hub is critical. This free & paid subscription based platform must leverage the 400 million Linked-In professional's data for their own personal devices & computing services- Home PCs, mobiles, gaming consoles etc. This then can change the game for Microsoft. However, if we look back at history, neither Hotmail or Nokia was leveraged to its full by Microsoft due its software vendor thinking. Microsoft will have to change its strategy & execution this time.

The next most important question was the issue of Privacy. What is the sanctity of privacy information owned by Linked-In & do the limited or full permissions that was given to Linked-In by these 400 million professionals, hold good for Microsoft too or how does Microsoft use these in its platform intelligently without diluting any of the privacy issues that may arise? For this, the permission-based sharing professional community that Linked-In nurtured, needs to thrive, without advertising as the primary revenue driver unlike other online platforms like Google, Facebook etc.

For software vendors to transform & think like data vendors, it forces, disruptive platform thinking from them. It requires a services, community, subscription & marketplace mindset with a strong interplay between them. Only time will tell if Microsoft is able to make this mindset shift but transform they must, if they need to play this game on the web for a leadership position.


Marketing in "micromoments" in a post digital world

I was reading an interesting update on Forrester Marketing 2016, where companies & marketers were asked to take cognizance of micromoments. I don't disagree fundamentally with this theory but I was thinking how do marketers prepare & adapt to this new paradigm.

One of the top questions that came to my head was - How do marketers really identify these micromoments? In an increasingly walled garden world of Facebook, Google, Twitter, Amazon- many customers' micromoments are happening, as I write this, in different digital platforms independently. Not only that, there are ever so many billion micromoments that happen offline in a customers' life and how do marketers make sense of it?

My premise is that it is now increasingly becoming  O2O(Offline-to-Online & Vice-versa) world, marketers need to look at this very differently. Here's my view of how this should be looked at:

Intent-driven micromoments - Some digital platforms naturally fit into intent-driven micromoments. For example, Google is a great example of a digital platform where "billions of intents" are searched by customers. People don't search for a product, they search for a need.They can be searching for a home, for a restaurant, for a car, for a college education, for naming a baby to be born, comparing a product to be bought, for a holiday etc. etc. In a customer's buying cycle - the trigger, consider & search- happens here. Marketers need to find a way of dominating "intent-share" at these micromoments.

Sharing-driven micromoments - Google, as a platform, does not naturally fit into this micromoment as customers don't share their moments there. A digital platform like Facebook fits here far more beautifully & perfectly. It is not difficult to see people sharing their convocation photos during the current season, their holiday, their child's birthday, their family get-together etc. etc. Sharing-driven moments provide opportunities for marketers to blend brands with their customer's life needs and see how they can be a part of these different micromoments. Marketers need to find ways of dominating "sharing-driven moments" & align it with their brand's storytelling.

Experience-driven micromoments - Some digital platforms like Twitter, Facebook, blogs fall here as customers share their experience - good and bad - here. For example, tweeting about poor govt. services is becoming a norm and governments globally are encouraging this. The same is with product performance, customer service, product support etc. where again experiences are largely drive this micromoment and is shared with world outside.  This micromoment can be a new business opportunity for a competing brand and retention opportunity for the incumbent brand. Again, marketers need to find ways of dominating "experience-share" micromoments.

The above are largely only online micromoments but as a marketer, one needs to find offline micromoments, which they can own,  that are contextual in the households they have been bought again & again. Be it thro' embedded IoT & other "service-led" mindset transformation platforms, marketers need to find new solutions here. 

Finally, in this battle for the customer & the micromoment, the other question to be asked is, who owns the data of the micromoment & privacy related issues need to be addressed very carefully by marketers. Doc Searls, in his book talks of intent casting,  where customers play a role in sharing their intent and brands then need to play a reverse role of fulfilling the micromoment.

Managing the customer micromoment is far more complex & deep than one can think of. And marketers need to rapidly innovate to gain share of this micromoment in their customer's life thro' relevant platforms and contextual marketing.