The Gold Rush Movement of Smarts, Sensors, and All Things Connected!


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Decoding the New World of ‘Internet of Things’

It’s not so new now so I am sure all of you are plugged-in to some extent with this mega movement called ‘Internet of Things’. In simple terms, it is connecting any device you can think of to the internet with an on-off button, and can be managed via a mobile app. So from your daily coffee-maker to an airplane or an oil-drilling machine, any of these can become ‘smart’ when you want them to be.

Although Gartner estimates that by 2020 over 26B devices will be connected to the internet, there’s a prediction that if ‘things’ include people then this number might be over a 100B! So really it is machine connecting to machine, machine connecting to a person, or a person connecting to a person.

Here’s a beginner’s guide definition that I really like: “The broad idea behind these buzzwords is that a whole constellation of inanimate objects is being designed with built-in wireless connectivity, so that they can be monitored, controlled and linked over the Internet via a mobile app.

IoT Technology Gartner Hype Cycle and Future Direction

All of you know about the technology hype cycle from Gartner. The triggers, inflated expectations, trough of disillusionment, enlightenment and then finally productivity. With IoT, we are evidently at the inflated expectations and at the tip of that.

With hardware becoming a commodity, machine learning algorithms coming mainstream, software advancing and cloud becoming ubiquitous, it is prime time for IoT. But which way it is going to go? That really depends on how the industry does with it. There are various moving parts including standardization, security vulnerabilities, and intelligent systems to manage data.

Source: Gartner

The Mechanics and Architecture of ‘Internet of Things’

There’s an overwhelming amount of information around how all of this works! But here’s a simplistic world view and a few definitions without getting into any complicated jargons. First there is the communications layer say wireless radios – these allow devices to connect to the internet and to each other. Some familiar standards are Wi-Fi, NFC, RFID etc.

Second, there are things, sensors and hubs. Things are things, so your coffee maker, the airplane and the oil-rig are all things. These things communicate via sensors that are agents used to transmit the data from these things/devices. So data around movements, temperature, weather, location and behavior are transmitted via micro-chips through the things to somewhere.

And that somewhere is cloud. So third is cloud services or a cloud platformthat stores and analyzes data in the cloud so people can see what’s going on and based on certain recommended steps, people can take action on their mobile app. This platform processes and churns all the data to deliver valuable intelligence. Intelligence that will be used to solve industry specific needs. All of these components are interlinked via secure gateways.

All of this together can be called an Internet of Things (IoT Platform) which provides and standardizes languages for apps and devices to communicate with each other. So far so good? If this is confusing the watch this video, I think IBM has done a phenomenal job of decoding the mechanics. Nothing better than visual content. For those of you who want to do some digging on the IoT architecture, here’s a great video from Microsoft Services.

https://www.linkedin.com/pulse/api/edit/embed?embed=%257B%2522request%2522%3A%257B%2522originalUrl%2522%3A%2522https%3A%252F%252Fwww.youtube.com%252Fwatch%253Fv%3DZMHQu_X0Ijk%2522%2C%2522finalUrl%2522%3A%2522https%3A%252F%252Fwww.youtube.com%252Fwatch%253Fv%3DZMHQu_X0Ijk%2522%257D%2C%2522images%2522%3A%255B%257B%2522width%2522%3A480%2C%2522url%2522%3A%2522https%3A%252F%252Fi.ytimg.com%252Fvi%252FZMHQu_X0Ijk%252Fhqdefault.jpg%2522%2C%2522height%2522%3A360%257D%255D%2C%2522data%2522%3A%257B%2522com.linkedin.treasury.Video%2522%3A%257B%2522width%2522%3A854%2C%2522html%2522%3A%2522%253Ciframe%2520class%3D%255C%2522embedly-embed%255C%2522%2520src%3D%255C%2522%252F%252Fcdn.embedly.com%252Fwidgets%252Fmedia.html%253Fsrc%3Dhttps%25253A%25252F%25252Fwww.youtube.com%25252Fembed%25252FZMHQu_X0Ijk%25253Ffeature%25253Doembed%26url%3Dhttp%25253A%25252F%25252Fwww.youtube.com%25252Fwatch%25253Fv%25253DZMHQu_X0Ijk%26image%3Dhttps%25253A%25252F%25252Fi.ytimg.com%25252Fvi%25252FZMHQu_X0Ijk%25252Fhqdefault.jpg%26key%3D03fb819bf74246bf972444a07b738ad0%26type%3Dtext%25252Fhtml%26schema%3Dyoutube%255C%2522%2520width%3D%255C%2522854%255C%2522%2520height%3D%255C%2522480%255C%2522%2520scrolling%3D%255C%2522no%255C%2522%2520frameborder%3D%255C%25220%255C%2522%2520allowfullscreen%253E%253C%252Fiframe%253E%2522%2C%2522height%2522%3A480%257D%257D%2C%2522provider%2522%3A%257B%2522display%2522%3A%2522YouTube%2522%2C%2522name%2522%3A%2522YouTube%2522%2C%2522url%2522%3A%2522http%3A%252F%252Fwww.youtube.com%2522%257D%2C%2522author%2522%3A%257B%2522name%2522%3A%2522TechEd%2520North%2520America%2522%257D%2C%2522description%2522%3A%257B%2522localized%2522%3A%257B%2522en_US%2522%3A%2522This%2520session%2520will%2520give%2520a%2520brief%2520overview%2520of%2520what%2520IoT%2520is%2520from%2520the%2520perspective%2520of%2520an%2520Architect%2520within%2520Consulting%2520Services.%2520We%2520will%2520look%2520at%2520what%2520kinds%2520of%2520projects%2520we%2520are%2520getting%2520involved%2520in%2C%2520what%2520those%2520projects%2520look%2520like%2520in%2520reality%2C%2520the%2520kinds%2520of…%2522%257D%257D%2C%2522title%2522%3A%257B%2522localized%2522%3A%257B%2522en_US%2522%3A%2522Architecting%2520the%2520Internet%2520of%2520Things%2522%257D%257D%2C%2522type%2522%3A%2522video%2522%257D&signature=ATpSb8jLwkQQuWiAN15jSdE53OgY

Source: Microsoft Azure Team

The Possibility of IoT in Every Application

As part of the growing IoT movement, there are two distinct segments that have emerged: the consumer and the industrial side of IoT. McKinsey has two broad categories for IoT applications – Information and analysis, automation and control. Information analysis mostly focused around tracking human behavior, enhancing situational awareness, and driving sensor-driven decision analytics. Automation and control is mostly focused on process optimization, resource consumption and autonomous systems.

Here are a few great infographics that will explain themselves. But this is just the tip of the iceberg. There’s a lot more stuff that’s waiting to get connected.

Source: IoT analytics and McKinsey

New Possibilities for Solution Architects and a Growing Market in the Making

Taking the cue from Microsoft’s presentation, and the infographics above, there’s a huge market opportunity out there for not just creating an IoT smart bulb product but also architecting a brilliant IoT best practice/solution approach for an organization.

According to IDC, the worldwide market for IoT solutions will reach $7.2 trillion in 2020. The leading industry practices would be around utilities, insurance, agriculture, factory, automobiles and more. There’s a lot of thought leadership around these solutions by systems integrators already. There will be need for a new mindset to address the new challenges with data, scale, security and device proliferation. But it might be about relearning some of the best practices for the brave new IoT world and ride the hype cycle.

Some awesome IoT read references:

https://www.wired.com/insights/2014/11/the-internet-of-things-bigger/

http://www.mckxinsey.com/industries/high-tech/our-insights/the-internet-of-things

https://www.gartner.com/doc/3299317?refval=&pcp=mpe

http://blogs.wsj.com/cio/2015/06/02/internet-of-things-market-to-reach-1-7-trillion-by-2020-idc/

https://www.gartner.com/doc/3316617?srcId=1-3931087981

http://blogs.wsj.com/cio/2015/06/02/internet-of-things-market-to-reach-1-7-trillion-by-2020-idc/

http://www.computerworld.com/article/2488872/emerging-technology-explained-the-abcs-of-the-internet-of-things.html

Good luck out there!

To learn more about me, visit – www.organicmarketing.live

Machine Learning and Predictive APIs: Driving All Experiences Intelligent and Digital


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The Experience Driven Economy: Understanding Your Customer’s Psyche

You’ve heard of digital transformation and how it is ‘transforming’ the customer experience (CX). Products now are focused on enhancing the ‘CX’ to drive bigger and better conversions. Take e-Commerce for example, it is not just about building a site to transact. Online shopping has become a lot more personalized and targeted. Marketplaces like Amazon know me and are tracking my ‘buying behavior’ and psychographics pretty diligently.

Based on all my previous clicks and buys, they ‘predict’ what I want and make the appropriate recommendations. They are tracking my abandoned cart behavior to see why I did not complete the cycle. They are making some fair predictions on how much I am willing to pay for something based on heuristics and not just the fair market price. This is something that Apple has mastered, all you iPhone7, 8, and 9 fanatics will agreeJ.

Taking it one step further, this experience has to be consistent across all your channels – mobile, web, wearables, TV, appliances, and other connected devices (think consumer IoT). This is what the omni-channel movement is all about. There’s a vast ecosystem of tools, platforms and ‘clouds’ that are trying to drive several of these moving parts forward and below is a view of that.

The Science of This Experience: Small and Big Data is Driving the Future

Now, let’s get into the HOW of this experience. Although it seems quite simple, there’s a huge science and approach behind it. And here’s where the industry crossed the chasmfrom natural to what we call artificial intelligence to predict human behavior. This journey however like in Maslow’s hierarchy begins with data. And, all of this is driven by Machine Learning.

In simple terms, Machine learning is the ability for the computer to program without any ‘explicit programming’. Take for instance the search criteria kids shoes. Every time I query kids shoes I get the same related search/recommendation. But if I programmed this a little differently to include or show results from top sellers in this category and limit it to only 2, I might get different results each time because the top sellers vary. I might also program to include related categories like kids socks or kids snow boots depending on the season.

Anyways, the global point here is this: this is an iterative process! First, all the data around customer behavior is collected and analyzed and there are a LOT of tools driving these analytics – KissMetrics, Google Analytics, Adobe Experience Cloud, Crazy Egg, RJ Metrics, Clicky and several others. Once the analytics are in, it is all about making the right hypotheses, creating the fuzzy codes and iterating to drive larger conversions. Hope you’re with me so far?

Machine Learning in Marketing: A Shift in Mindset

We’ve established that data is key for applying Machine Learning to marketing and especially e-commerce marketing. We’ve also figured how you can collect this data through various advanced tools.

But now, it is about creating the right models via Machine Learning and NLP (Natural Language Processing) to drive the top and bottom line for your business. Let’s investigate that a little bit. This exercise is also known as ‘data modeling’ and it is slightly complex when there’s a larger data set. It all begins with attributes and assigning scores to them, just like in the marketing automation system where we assign lead scores.

For example, we want to know if Padmini is interested is buying an iPhone7, for lack of a better product. We then evaluate people like Padmini who have made similar purchases to see if they have bought an iPhone7. We assign scores or points to each click that they make and then determine that if the score was above a certain threshold, then we conclude that Padmini would make an iPhone purchase most likely.

Now, once we determine that hypotheses, we target and recommend an iPhone7 to her on every page when she arrives by designing some predictive APIs. Although the model is explained quite simply, it is not. And that is why big data scientists are priced items in the market, to figure out the ‘nuances’.

Good luck out there and stay tuned to hear some more machine learning stories from me.

Have Fun!

Visit www.organicmarketing.live to learn more about me.

The Fascinating World of DevOps: A Phenomenon That Has Changed and is Changing How Software is Built and Delivered!


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Everyone’s talking about DevOps as a growing movement in software. For those of you who are not familiar, here’s a Wiki kind of definition (by me, as I understand it, after probing a few folks) – the DevOps culture narrows the chasm between development and operations, as it relates to software, with a goal to enable faster and efficient software delivery.

Emergence of DevOps as a New Approach to Software Development

All of you are familiar with the SDLC or software development lifecycle. Code – Build – Test – Package – Release – Configure – Monitor. Each stage of the software lifecycle will require a certain set of tools to execute that cycle flawlessly.

Development and operations sides were two different functions within the IT organization before the evolution of DevOps. Operations mostly dealt with compute, hardware, network requirements, and security policies, while software development focused on the building and managing applications. But Development had to interact and conflict with Operations to make software happen. This overhead would usually derail or delay software development efforts.

With the emergence of this new type of technology stack however, developers now have access to tools that will automate a ton of operative behavior, allowing them to focus on the core, which is building and managing the application and its functionality. Result – faster, better, and more software to simplify our lives.

The Interlinkage Between Agile and DevOps: Tracing the Evolution and Reason for DevOps

In the fascinating world of software, there are several “isms”, activities, paradigms, frameworks, disciplines, standards, and of course, tool sets. Core activities begin with gathering the requirements, designing and building to them, testing and then monitoring them.

You could use different models or paradigms such as traditional software engineering, waterfall, agile, or lean with methodologies such as SCRUM or Kanban. And of course, you could pick from a large stack of tools to undertake software delivery.

But let’s talk a little bit here about why DevOps at all? Why was there a need to automate some of the software development operational functionality? It all began with a need for agility and flexibility in software development. And why a need for agility? Because quality software was needed faster, and hence it needed to be released faster, reliably faster, to deliver the value to customer who is demanding it.

Consider mobile apps, and how fast they need to be released to compete for a customer’s mindshare to ensure optimal downloads? Ubers, Snapchats, Facebooks, Twitters, and many many many more need to release new features @ the speed of light to keep a tab on that mindshare. Now do the math!

Developers started using continuous integration approaches to achieve continuous delivery of this type software. Today, in some sense, DevOps is powering or accelerating THAT continuous delivery with an ecosystem of collaboration and automation tools, makes sense?

Making a Case for DevOps with Continuous Delivery for Any Time, Any Device Business Applications with the DevOps Ecosystem

As mentioned, applications need to move at the speed of light. And, as we move beyond mobile to wearables, and other IoT devices, these applications need to be even more uber fast. From simple transaction centric applications to innovative, early stage idea driven apps, the DevOps philosophy can cover the entire spectrum with its flexible ecosystem.

New Relic has a DevOps  tool set guide that outlines this ecosystem brilliantly. From OS, infrastructure, and virtualization layers to containerization, database, configuration, test, build, delivery, monitoring, and optimization, there’s a large DevOps tool network to tap into.

Depending on the software and its scale, a combination of these tools could be used with a team that understands how to use these tools, and/or with an integration partner who is familiar with the stacks. It is clear that to solve complex software build problems, a single tool will not be sufficient. And your software teams will have to intelligently mix ‘n’ match the DevOps stack.

If you’ve any interesting DevOps stories, share here….

Have Fun!

The CMO’s Dream Stack


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Marketing is about the force behind it. And most of it today is driven by emerging and incumbent technology. Very recently, I read a post on why we all should bet and invest on marketing technology than ads and others. In most recent interactions within marketing circles, the same question comes to the fore.

This post is an inspiration from a question that someone asked me last week – what is your dream marketing stack, all things considered? Which marketing tech stack do you think is built to succeed, what is hot out there?

There is no straight forward answer here but there’s definitely a heck lot of innovation to improve the marketing experience. And as I mentioned in one of my earlier posts, this is only the beginning. We’re seeing some ongoing consolidation in this space with the acquisition of marketing automation tools such as Pardot, Eloqua, and Marketo by Salesforce, Oracle, and private equity firms. And, we’ll continue to see a lot M&A activity with a one-stop-shop/single sign-on mindset.

One of the biggest challenges today is to manage diversified stacks and keep track of them. So consolidation and bringing everything together into one platform is going to be the future of lean marketing – as I see it.

Here’s a primer on SlideShare of tools and technology I’ve used and would like to use. I’ve tried to segment the marketing experience down into finer platform stacks. I’ve used almost 90% of this stack across several organizations. But the idea is to have a  seamless implementation with a good data science team in place.

CMO_Marketing_Stack

Data-Driven Marketing Attribution Models: Go Beyond the Gut to Make Your Marketing Decisions and Performance Stronger


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The Transition from Subjective to Objective

Marketing measurement has gone through a significant shift in the last decade.  The genesis of marketing technology has pretty much led this change from pure gut-driven to almost pure data-driven measurement. We can measure everything in marketing today, really.

Not just email campaign and web traffic, but content performance and customer experience as well. And, I believe that we are still seeing the tip of the iceberg. We’re going to see a lot more disruption here with big data driven analytics tools to do the crunching.

I think I covered this in my previous blogs somewhere, marketing today boils down to bringing in ‘leads’. All brand awareness, social media, campaigns, PR, and content need to bring in people to sign up for your product and engage/connect with you holistically. And, we’ll need to measure which of these activities are making the most sense for your business. 

Marketing Science and Measurement Principles

Marketing automation has taken over big time and in a nice way. I’ve seen startups invest in marketing automation as a mandatory measurement yardstick. With folks likePardot, Hubspot and Marketo bringing significant disruption with new features everyday to make marketing attribution simple.

From having run marketing at various startups, here are a few of my own semi-attribution models which I am a fan of. I would like to evangelize these to every startup trying to measure marketing performance. The pure definition of attribute modeling is more complex than this. Linear modeling, multichannel modeling and a lot more, and with a lot more metrics. That is a topic for another blog.

  • Lead Funnel science – This is the science that helps to track the lifecycle of the lead. From unqualified to marketing qualified to sales qualified to opportunity to closed won/lost. Pardot has an out-of-the-box report to track this and literally shows the conversions at each step of the funnel with a lifecycle report. SF.com has custom report capabilities that helps to configure this report. And there’s a huge App Exchange system within SF.com which has tons and tons of these requirements answered. This is a weekly report that every marketing/sales sync needs to run – imperative!
  • Performance Marketing Science – Everyone’s doing digital marketing now. Guzzling money down the pipe for those LinkedIn, Google, and Twitter ads. Rings a bell I suppose? But there’s digital campaigns and then there’s digital campaigns. The latter being a more educated and intelligent approach. Now, there are tons of tools to track your competitors, keywords, your competition’s ad spend, the backlinks, Google’s crawling science and what not. We know that marketing budgets are limited, but it’s well worth the money to invest in one of these investigative tools. I am a big advocate of Spyfu, especially when you are in the process of setting up your digital campaigns and doing the initial groundwork. There are several other tools out there including SEO Moz, SEM Rush, GA and others which do provide some level of visibility.
  • Content Science – I coined this term, not sure if it was used before in any marketing circles. Because content today is a science. It has a structure, a pattern, it can be measured and of course, absolutely optimized. We know all about SEO, so I am not going to go there. As marketers, we bow to the SEO lords and follow their direction to make ourselves visible across channels. The biggest influencer I have to say and admit is backlinks – the driver of all traffic. So, backlinks, backlinks, backlinks in your content. Moving beyond SEO, there are a few more layers to this science. These measure the ‘real’ impact of content. Usually, marketers measure impact from distribution channels, like social shares etc. But how do you know if your content is grabbing mindshare? How are people really engaging with your content? To track this, you need to start looking and moderating the comments on these pieces and assess the number of downloads. And, you do this consistently to measure the ‘long-term’ impact of different pieces of content. You’re going to see more writings from me on content science.

Data-Driven Marketing Efficiencies: Debug the Approach to Drive Bigger Results

Data has transformed the face of marketing in many ways. And each type of campaign has different measurement metrics. But data has resulted in driving marketing more holistically, including marketing design. No more ‘this is how I want to do it’ monopolies.

But, to make sure that the data-driven strategy works, your marketing approach needs to go through a continuous battery of tests, debugged, and debugged more. You might not reach a zero-defect stage ever but can get close to that to validate and evangelize your approach within marketing circles.

Good luck out there!

Startup Culture – A Tightrope Walk to Create a Balance that Thrives


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A Foundational Element That Steers the Startup Sails

If you’re in the Silicon Valley, you’ve heard this term ‘startup culture’ quite frequently in your circles. Innovative, cool, entrepreneurial, lean, ‘Ideo like’, flexible, collaborative, driven etc. are some of the adjectives used. Now, this term has percolated across other parts of the world where innovation and ideas are seeding – India most notably comes to mind. Among several things that decide and determine the path a startup takes, the evolution of its culture is perhaps one of the most significant ones.

But, honing a culture goes beyond Friday happy hours, team lunches, and birthday celebrations. It is something deeper. It is about ingraining those core values in every team member. The core values that will guide your startup through thick and thin. The big questions is – who dreams up these core values and how do these percolate across to every individual?

It is not simple, especially now, when we are working with global teams. Each of these teams have a different cultural mindset. But from experience, companies have crossed these chasms and some very elegantly at that. Based on that, there are a few isms, the startup culture mantras so to say which sail the ship through rough storms and still waters. Let’s explore!

Eliminating Dilution with The Inevitable Growth

We talked about core values and a person who actually dreams these up. Most times in a startup, these emerge from the the founding team. When a few people decide to quit their high paying corporate jobs to work on something they are passionate about, that is the founding value. A value that honors passion, entrepreneurship, innovation, ideas, and hardshipJ.

Anyways, the point is, that startup’s culture emerges there. The seeds are sown that early in the game and everything else builds on that. At this point, it is almost mandatory for the founders to carve these out on their walls, like doctrines. These are the principles by which the remaining team will be hired, driven, and coached.

So far so good, as long as you have a 3 people team, sharing home lunch. The challenge begins with the fourth hire. The core values that the founding members used to sow the seeds will now have to be passed on – in-tact.

The Five Tenets to Preserve the Founding Culture

There’s no formula for this but there are a few approaches which have worked better than others. This by no means is a preaching of principles but just best practices that have emerged from my experience. And of course, I would love to hear yours.

First, hire slowly and carefully. I believe that this is the single most important factor in building a strong team. Most times, it is 80% personality and culture-fit and only 20% skill. Yes, it is true. Skill you can teach, but attitude is usually quite tough. Focus more on personality centric questions, and structure tests to ensure that the team member can thrive in your operating environment. I have to make a confession here that I was not the best judge of people, it took a few iterations to learn this and I am still learning (sometimes the hard way). But once you have this skill in the bag, this becomes the single most essential thing to have.

Second, treat the new entrant as a founding member since you are still building the structure. Be open, be transparent (commonly used wordJ), be vulnerable. You are still an idea trying to find its market, still trying to build a structure that will work, still learning. You believe that your idea can disrupt and change the industry and that goal should drive every new entrant.

Third, and this is the perhaps the most important one, don’t analyze everything everyday! Because, results take time and it is usually following the law of averages that result in bigger things. When you analyze everyday, there’s collateral damage for lack of a better phrase. You create a lot of mistrust for yourself in other people and their capabilities. And you overthink every business outcome and action. This results in irrational biases and might hinder good decision making. But, it doesn’t mean you don’t act when required based on all the data you have. This is most definitely the most critical tight rope walk by far.

Fourth, take the time to celebrate. Whether it’s big or small moments. This is the time when people connect, when bonds are formed, when you exchange your life stories and learn from them. This is also the time to rethink core values, what they mean to all of you, and why sticking to them is the most important thing for your emerging business.

Fifth, always have a plan B. Needless to say, that businesses cannot thrive on indispensability. There might be situations that might hit us from the left field. Always prepare for that stuff to come and have a plan of action to deal with them.  This might be contrary to some of the initial predicament about treating all initial entrants as founders or having 100% belief in and passion for the idea.

However, with time, you will realize that as you build and scale with your new entrants hiring more new entrants, the situation sets are large. And, some will demand more coverage than others. But this should not deter you from building a rock solid culture.
Have Fun! And, good luck out there.

Finding Your Co-Founder – The Yin and the Yang Formula.


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Why Finding Your Love is More Important than the Product Idea?

In my previous blog, I talked about how your product idea can scale once it picks up market momentum with the ‘right’ product-market fit. That is about the idea. Consider this, what if your idea was not worth it? What if things did not go as well as you thought they would? What if you just want to abandon it and go to the next one?

You need a partner in crime. A person who can be your sounding board, with whom you can share your deepest fears about the product. A person with whom you have zero ego-clashes, who is your best friend, and who is on the same wavelength, at least most times. This person will then also be called, the Co-Founder.

And why do you need this person? Because, this is the person who cares about the journey with you. He/she wants to reach the destination but only with you! He would not care to go there if you were not part of this initiative. Sounds a little dreamy. Let’s see if we can make it a reality.

Quite a few thought leaders like Guy Kawasaki and others have shared their words of wisdom on  choosing the right partner. And there are Co-Founder labs such as these,these, and these where minds meet. There are entrepreneur’s club such as TiE and Y-Combinator and there are suggested methodologies. But this hunt goes deeper than that and there is a science and an art, and everything in between to this when you are trying to land with the right Co-Founder for your business.

Looking for Your Love in the Right Place!

You most definitely can Wikipedia, Quora, or Reddit your way and read blogs to find your founder. There are also ‘how to find a Co-Founder for dummies’ series over the web. But there is also a first principles way of doing this.

My Co-Founder is My Best Friend Usually, successful partnerships are a byproduct of association. The longer you know the person, the more comfortable you are. That is why, you will see old friends starting things together. Most times, this is the most optimal model. Sometimes, time and situations might test these relationships too. The stronger ones will float and the weaker ones will not.

It would be hard to deduce why these can survive hardships better but they just do. One possible analysis is they’ve both seen a lot of life together. They’ve married at the same time, brought up kids pretty much together. So the foundation of trust is quite deep rooted, and ordinary externalities cannot shake it so easily. It is usually as personal as that. P.S. – true in case of women friends too…although there will be some ruffling of feathers. As long as you leave it at that:-). 

My Co-Founder is My Better Half Sometimes, only sometimes (a huge disclaimer on this one), a husband and wife can make a great team. The wife usually brings in a lot of soft skills along with core subject matter expertise. In my experience, couples who have started ideas and businesses together have known each other for a while, just like old friends. Or, they just have an unexplained chemistry and understanding.

They are close, but also know to draw boundaries based on how their personalities have come together. Most recently, I have been visiting a restaurant owned by a wife and husband in partnership and in having more detailed conversations, this premise is validated.

The Limitless Generation

My Co-Founder is My Work/School Buddy – This is all the second wave millennials out there who connect very quickly and deeply with a few people. They cross cultural chasms very quickly and establish a very interesting wavelength. They hang out, discuss ideas, argue, criticize, but establish a very cool working relationship. And when things don’t work out, they part ways without much baggage.

I’m seeing a lot of more of these bud across the board and their ideas are certainly refreshing and new, especially in the B2C space. Some of these ideas we would not consider as viable ones with our limited understanding of the generation and their needs. Seeing them work in action, with passion, and so in-the-game, it does feel like this is the new normal and we’ll all need to adjust to it across cultures in the years to come.

The Yin and The Yang: Foundational Start-Up Elements

First things first, the business idea and the founding team have to match. And, this is generation agnostic.  If you’re doing something in mobile gaming and have guys from enterprise security trying to run it, it won’t work. That said, nothing is carved in stone, and there are start-ups which have scaled and succeeded with unrelated founding teams by following lean models.

But going back to Guy Kawasaki’s words of wisdom, the Yin and the Yang matter. First, they need to both dream the same dream and commit to it. Second, they need to bring the complementary skills. One brings core technology skills, and the other brings core people skills. One brings the business acumen, and the other brings the innovation mindset. Third, they both need to understand the numbers, financials, and profitability involved – no excuse.

In Conclusion

But no matter which path you choose, make sure you’re on it with someone who will enjoy it with you. Because, it is always, only about the path and how you travel. If you get there, great, and if you don’t, you still made the journey worth it. So take the time, calibrate and recalibrate before hopping on to that wagon. And, all this won’t change for the second wave millennials, you guys!

Your Turn!

It would be very interesting to hear your story, if you care to share it? How and with who did you find your start-up? What were your learnings?

Have Fun!

Visit www.marketingmatters.space to learn more about me.

Scaling Integrated Marketing Efforts – Perspectives for the Modern Enterprise


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Transition from a Cost to a Revenue Unit

Marketing is tough, I don’t think any marketer can deny that. And, as you scale up the value chain to lead the pack, there are some very imminent challenges. The fact is, Marketing was, and still is perceived as a cost center.

Traditionally, it was responsible for driving awareness and brand identity. But now, it is being redefined, and you’ll come across terms like ‘data-driven’ marketers or better still, ‘revenue’ marketers. With the influx of automation and analytics software, it’s becoming fairly easy to make logical deductions about customer and prospect behavior and forecast marketing spend in key areas.

Gartner’s 2015 Spend Survey highlights key strategic challenges that integrated marketers usually come across:

1)Turning marketing from a cost center to a revenue center and impacting the top line.
2)Keeping customers and prospects engaged and happy.
3)Managing and learning from competition constantly.

From being in business for a while and having seen enterprises function, I have seen this stuff in action. And, from that experience, here are some of the major tactical hurdles.

These basically trickle down from Gartner’s strategic survey, but go a level deeper.

1)Driving top line conversion through digital marketing programs.
2)Creating and distributing engaging content through marketing programs.
3)Tracking performance and analytics to fine tune campaign strategy.
4)Integrating across multiple systems of record within marketing.
5)Identifying the right set of tools to project manage marketing right.

Content – The Key Driver of All Integrated Marketing Initiatives


There might be many catalysts that push the marketing engine forward, but the biggest is and has always been good content. Agree or not, consistent content that drives engagement and which can be measured effectively defines the trajectory of good marketing. A well-written blog or case study, an engaging video or infographic, a good thought leadership paper with a definitive call to action, all these drive the right audience, higher conversion, and more marketing success. So before defining anything, a good content strategy might be the right place to start.

Here’s an infographic created by a key member of my team around content marketing challenges today.

So far, so good. So then, does it all boil down to just churning good content? If that was the case, then all good content would be geared up to convert, and all other principles of marketing including running effective programs around this content could be ignored. Because, the content should be able to speak? Yes?

The answer unfortunately is negative. Good content is a necessary but not a sufficient condition. There are several other disparate elements which need to be integrated to create a cohesive marketing program.

Building New Efficiencies with Integrated Marketing

Assuming that you have good content, you would need to build in several other layers to develop a cohesive, integrated marketing strategy. Some of the key principles to keep in mind:

1)Think beyond just creating good content. Content is king and queen, but it all starts there. This ‘good’ content needs to be found easily, on the web, on social networks and through other inbound marketing efforts. To make this content make rounds, it is essential to optimize and enrich it. It is important that it complies with industry standards and is backed up with appropriate keywords, images, videos. When it’s less content, the process can be manual, but with scale, the need for a sophisticated platform without much human intervention becomes very essential.

Here’s an interesting insight from one of my team members on how to scale good content.

2)Think beyond silos. All elements of marketing need to talk with each other. From marketing automation and CRM to analytics and CMS, all systems of record need to be hyper integrated, with a two-way flow of information. This is the key trait for every data driven marketer – to be able to make the systems talk and learn from it. A well designed email campaign would be a great case in point. This email campaign could be designed in an automation software such as Pardot or Marketo, it would be sent to prospects visiting the website which is on a CMS like WordPress. These prospects would be scored based on their interactions and the detailed analytics could be tracked on a system like BrightEdge.

3)Think scale, but without compromising on quality. If some pilot works, it will be essential to think about taking it to the ‘next level’ and establishing a plan of extension. And when you’re doing this, it is best to leverage the power of sophisticated tools/software to do this efficiently. My previous point about thinking beyond silos and running an integrated mechanism will become critical here. But when choosing software, it is also important to customize it to your needs. And as easy as it may sound, you need ‘able’ hands to take care of this.

4)Think content intelligence. This is a big one. Especially today, where people are consuming tons of content across multiple channels – web, mobile, tablet and wearable device. It is important to analyze user behavior, flows, and patterns todetermine the right go forward strategy. It is also important to understand the responsiveness and usability of this content across all channels to build the right traction.

Have Fun!

Visit http://www.marketingmatters.space to know more about me.