Posts Tagged ‘rand schulman’


Big Data: What Augmented Reality and Artificial Intelligence Have in Common

Written by Rand Schulman. Posted in Marketing Strategy

I’ve been writing a lot lately about how data is driving the new marketing Four Ps of people, process, purpose, and platform. We’re gathering mounds of data these days. Yet, it’s true that our ability to collect the data far exceeds our ability to analyze and socialize it. And it will get more difficult until we fundamentally have the data-driven people who can tackle the basic issues of understanding it and making it relevant. The newest technology that I present below will make it even more critical that we address these issues now.

Since my last writing in this column I’ve experienced two big data moments: the first, with augmented reality (AR), and the second, how something as pervasive as your mobile calendar becomes an artificial intelligence (AI)-based data application.

For one of my clients, a major telecommunications company, I attended the Augmented World Expo in Santa Clara two weeks ago. I’m working with them to apply metrics to AR. For those who don’t know, AR technology uses computer vision and object recognition information about the surrounding real world and allows the user to become interactive, and to digitally manipulate the views through the mobile phone camera lens. The technology’s been around for a few years, but this year it seems to have crossed the infection point of ecosystem and user adoption.


Google Glass is a good example of an AR application (note my picture).

My aha moment: AR applications are able to collect a tremendous amount of data from the real world. They can “see” – view objects of interest, things like a building, a cereal box (its size and shape), a logo, toys, games, furniture and rooms, and autos. They can also “record” user-generated and behavior-based engagement metrics like duration and depth.

For an analytics guy like me, this is the Holy Grail, as I can now collect and analyze zettabytes of data about user engagement metrics within our very personal mobile devices. They can also collect what I call qualitative metrics. I can see what the user sees, I can feel her intent, and I can record camera motion – direction and angles, object engagement, colors, facial features – and marry that information with basic conversion information like share buttons, couponing, or with loyalty programs. I can test and optimize.

Now, let’s marry this to profile data about one’s preferences. Interesting, huh? Some say scary. We need to apply the new Four Ps.

In essence, the real world, like a page, becomes a trackable series of events where we can now deploy our digital analytics tools. Truly, analytics for the real world. In the last two weeks I’ve spoken with many Fortune 100 companies all working on AR products across sectors – automotive, hotel, entertainment, and financial services. Early research suggests unbelievably good conversion results. This topic will be a continuing theme of mine in this column.

My second big data confirmation moment came at the announcement of Tempo (smart calendar application) closing a large Series A funding round last week.

Tempo was incubated at SRI, the guys who developed Siri, based on AI. To learn, AI needs big data. In just a few months since its launch, Tempo has analyzed terabytes of calendar data, and was built to understand and learn from this data. It is now one of the top iPhone productivity applications (after only four months) and I’m proud to have worked as a consultant to the company.

According to Tempo CEO Raj Singh, “We enhance massive amounts of data, and the calendar serves as the perfect framework because it has real context. It knows you, what you’re doing, and where you’re going. This is the future of ‘big data’ engineering – to push the AI down into the individual bits of your calendar.”

Tempo is an app that will understand who you are. Tempo is mining individual bits of data and connecting dots that otherwise would have been trapped. Over time, it will utilize this contextual data to do more than just build a smarter calendar. The data will actually anticipate your needs, making plane or restaurant reservations all based on personal contextual data.

And based on this personal data, Tempo’s goal is to evolve into a full-bore virtual assistant and move beyond a calendar. It wants to create a pervasive assistant that anticipates your actions by processing reams of public and private user data. Tempo wants to be able to make suggestions on when you should leave for that meeting, based on real-time traffic conditions, and make suggestions for your route and where you should meet and eat. Even what you might talk about and actions you need to take.

What both of these applications have in common is using data and personalization to drive new contextual and anticipatory experiences. Data-driven AR-based apps will share and enhance what you see. Data-driven AI-based apps will help define what you do, when, how, and why you do it.

This is surely a brave new world. Let’s embrace it rather than hide from it. To do this we need to think out-of-the box. Let’s understand our new set of Four Ps where we empower these new capabilities with data-driven people, who can define data-driven process, for our new platforms, and who can most importantly define data-driven purpose. It’s only going to get more challenging and the time is now!



Marketing’s New Rules

Written by Rand Schulman. Posted in Digital Marketing

During the last few years I’ve had the opportunity to meet lots of marketing executives during my travels. I hear the same storyover and over and a pattern is emerging that I’ve tried to address in this post.

The marketing profession is always changing and we know that the “Mad Men”-style era of advertising that favored creativity over analytics is gone. Some see this move from creativity to data-driven actionabilty as two distinct and separate disciplines. I don’t, and they’re not. It’s critical that we learn these new rules.

Rule No. 1: Merge Your Left and Right Lobes

The new marketer needs to be multi-talented, using both left and right brain functions. Those who can shift seamlessly between these two lobes will give their products the best chance for success. These days we need to be part artist and part data scientist to excel. We need to be both analytical and creative – truly a content engineer.

Rule No. 2: Creativity Without Conversion Equals Zero

It’s the same both online and offline. We need to sell products, and to do that we need to communicate and convert, both with micro and macro conversions. Today it’s critical that we create compelling content for a pre-defined business purpose. And if you don’t agree with me, you’re really only writing for yourself, so save it for your diary.

Rule No. 3: Learn the New Marketing Four Ps

Remember the old marketing Four Ps: product, promotion, place, and price? Well, there’s a new set of Four Ps today, driven by mobile: people, process, purpose, and platform.


It’s not about Math Men, Mad Men, or Sexy Data Scientists. As we know, roles and responsibilities across the business need to realign and meet the needs of our new paradigm. There’s now a direct line between, and often a single person who owns acquisition marketing, conversion marketing or “on-boarding,” and product user engagement, as volumes of data drive outcomes very quickly – sometimes in less than a day.

“Gamers” drove much of our notion of app engagement around user experience in the mobile world. Apps just had to be good and a crappy app would die a quick death. Fast fail. And since so many users at any given time were using a game, we could let the “law of large numbers” drive our decisions and we learned a lot about user behavior and retention rates in mobile applications. Zynga is, after all, an analytics company masquerading as a gaming company, and it clearly taught us a lot about app engagement over time.


As we are moving toward one person owning all three levels of responsibility for acquisition, conversion, and retention (more like a producer in the game world), we now need to evolve our processes about what messages and media we use, by segment. We have to look at retention rates over lifetime value (LTV), so the message, content, and media can be A/B tested against app performance goals, cost, and ROI.

We need to define our process about what data we collect, how we collect it, and who is responsible for the optimization. Some say, “In the right time.” New roles, like chief data officer, will replace the old notion of CMO and champion new process.


Today, the identification of purpose is missing from many mobile applications, just like during the earliest days of the website deployment. I hear the excuse, “We’re doing it because our competition is doing it.” That’s not enough.

The understanding of purpose was key to building online business. And, like in the late ’90s, mobile is now in a very early stage of accelerating adoption, yet few organizations have much discipline around definition of goals. Analytics then and today is key.


And once you have your people on board, have identified your purpose, and have addressed the process, it’s time to think about the platform. Or, what tools and applications do you need to reach your goals? I’ve seen too many companies do this in reverse, usually falling prey to vendor hype compounded by not having the first three Ps set.

Then, when you have all of your Four Ps in place, start with a small and measureable project. If you don’t, your platform will likely become shelfware.

Rule No. 4: ABC – Always Be Clear!

We need to define our terms/words, as too many people are trying to measure everything, across every channel in real time, when few seem clear on the definition of much of anything. I’ve recently coauthored a report on convergence analytics, with Incisive Media, which included our survey about the definition of common terms like “real-time” and “multi-channel.” And it’s not surprising that there’s no clear definition of what the terms mean. Some think real-time is sub-second, while others think it is hours. Sometimes multi-channel means online and offline channels, while other times it means only digital channels or cross-enterprise silos – more marketing operations-like. Be careful and make sure you’re on the same page. Few are.


We need new hybrid skills to help drive mobile and online business – people who create process and apply numbers to words that convert, and who understand new engagement and conversion models. We need agile product developers schooled in both mobile-first design and the latest ways to take advantage of the underlying technology, both in hardware and software, and who are analytical. They will know about how augmented reality creates brand engagement; how the phone’s multiple signals can be tapped for conversion data; and where artificial intelligence works, and where it doesn’t. Next time I’ll write about the new marketing roles and how “big data” is making a big difference.



4 Key Facts From Convergence Analytics Showtime at SES NY

Written by Andrew Edwards. Posted in Convergence Analytics

Andrew Edwards | April 8, 2013

On Tuesday, March 26, 2013 we launched “The Dawn of Convergence Analytics” to a packed house. Thanks to ClickZ, Efectyv, my co-Author Rand Schulman, editor Melanie White, and our research associate Ron Labau, the 40-page report was released during our lively session at the SES New York show at the Marriott Marquis.

We were honored to have been joined by Google Analytics executives Adam Singer and Justin Cutroni on our panel. Additional notes of serendipity were piped by the announcement just days earlier of Google’s Universal Analytics tool, which, by all available evidence, is a convergence analytics tool extraordinaire.

The report is sponsored by Anametrix, Tealium, and Rio SEO. All three vendors offer powerful digital measurement tools applicable to a converged environment.

For those who didn’t seen the link at the bottom of every ClickZ article last week, you can download the free Convergence Analytics report here.

1. What is convergence analytics? Convergence analytics is both a class of vendor applications and holistic approach to digital measurement.

The tools combine cloud computing, big data, agile data connectors, sophisticated algorithms, and elegant display layers in order to help marketers gain new insights into the effectiveness of their digital content.

The approach comes from the marketer: wanting to know more about her customers, sooner, and with more dimensions than ever before.

Convergence analytics tools in the market today (many are listed in the report) allow the marketer to make use of this information in ways never before possible.

2. How does convergence analytics affect me? If you are a digital marketer or a vendor to digital marketers, then convergence analytics will change everything. No longer will a single silo of data suffice to say you’ve done the job of analytics. In the new convergence analytics paradigm, “everybody is measuring everything” (so says the report); and that means the inclusion of multiple streams of data formerly kept dark in rather useless silos deep inside the organization.

3. Attribution and lifetime value. During the session last Tuesday, Justin Cutroni said, “Attribution will get a huge lift because of convergence analytics”; and this is indeed the case. One of the most likely outcomes of convergence analytics may be the enhanced ability to trace the customer journey from campaign through conversion and beyond. The “beyond” is often referred to as “lifetime value” or “LTV” and is one of the important metrics tied to convergence.

4. Practices are as important as applications. One of the most important topics at the session was the ways in which convergence analytics applications will be best put to use for the customer. There was clear consensus that success would not be achieved just by signing up for a SaaS application. More than one panelist (myself included) stressed that having a method for deploying convergence analytics applications, and taking action on the data, is as important as having the tools themselves.

For instance, a dashboard is just a display layer. The marketer has to command content changes based on what the data in the dashboard is suggesting. In fact, process is so important that building a proper practice around these tools may be the next opportunity in analytics professional services.

Finally, it’s fair to ask what is the key element in convergence analytics. It’s you. It’s me. It’s us. The people who have to make decisions. Google is working on a self-driving car, but it’s still got some kinks. And analytics doesn’t drive itself either. At least not yet. So slide in behind the wheel and keep your eyes on the road (and the dashboard!).




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