Innovating in an Age of Personalization

The article also lays out six important decisions need to make based on what’s happening in this second digital wave:

Decision 1: Buy or sell businesses in your portfolio?
Companies that lack sufficient scale or expect a significant downside should consider divesting businesses.

Decision 2: Lead your customers or follow them?
Digital efforts risk cannibalizing products and services and could erode margins. Inaction, however, can be just as risky.

Decision 3: Cooperate or compete with new attackers?
Companies can neutralize attacks by rapidly building similar products or services, or even acquiring attackers. However, cooperation with some attackers can make more sense than competing given the number of competitors in many cases.

Decision 4: Diversify or double down on digital initiatives?
Diversification reduces risks but the many resulting small initiatives, however innovative, don’t get enough funding to endure or are easily replicated by competitors.

Decision 5: Keep digital businesses separate or integrate them with current non-digital ones?
Integrating digital operations directly into physical businesses can create additional value but it can be hard to attract and retain digital talent in a traditional culture, and turf wars can break out.

Decision 6: Delegate or own the digital agenda? 
Customer behavior and competitive situations are evolving quickly, and an effective digital strategy calls for extensive cross-functional orchestration that may require CEO involvement.

Let me explain why this imminent perfect storm will drive very different outcomes, and why I believe CEOs have such a rich opportunity to get on the right side of these changes—but only if they begin to take the initiative now.

1) The Demographics Revolution. In Europe, China, the United States, Japan, and other parts of the world, aging populations point to an unprecedented turnover in the workforces across all of those regions. Some studies indicate that in the U.S., at least 25% and possibly up to 40% of the workforce will retire in the next 5-10 years. That means one out of three workers will be gone in a relatively short period of time! On top of that, many of the new workers who’ll fill those tens of millions of vacancies will be millenials whose outlooks differ wildly from those retiring Baby Boomers in terms of technology, careers, compensation, collaboration, social media, mobile workstyles, and more. Unlike the Baby Boomers, these new workers have lived their entire lives immersed in technology, from smartphones to PCs and tablets to online shopping and banking to iTunes, Netflix, FitBit, and more. That tech-immersed lifestyle blends seamlessly into how they work and defines the workstyles many millenials will demand: always connected and able to use their own gadgets—and utterly intolerant of poor technology and unsatisfying tech experiences.

This imminent war for talent will extend well beyond this clash in professional perspectives and outlooks. It will begin with recruiting and the ability to use modern and social-driven tools and approaches to finding, attracting, hiring, training, retaining, and enriching the careers of these young people. World-class CEOs are leading the way in this war for talent, and in the process are leading the transformations of their HR organizations from back-office record-keepers to front-line leaders bringing high-value new talent into the company and ensuring those people are happy, productive, and fully aligned with the corporate strategy and objectives.

2) The Data Revolution. CEOs around the world have told me their company’s data volumes are expanding at a rate of about 40% a year. And with the cost of data storage now roughly $7,500 per terabyte, those CEOs are looking at huge increases in IT expenses just to keep up with that data growth, let alone being able to extract value from it. We’re talking tens of millions of dollars—in some cases hundreds of millions—just to keep pace.

It’s a pattern that clearly can’t continue, and businesses need to find new and better ways to keep up with the data explosion without spending themselves into oblivion. (We think we can help with that.) The right solutions will reduce data-storage costs dramatically, thereby providing the funding for innovative business-analytics and Big Data tools to turn all that data from cost centers into raw materials that companies can mine and manipulate to create new products, services, and revenue.

Again, the CEO has to be a front-line leader here for two reasons:

• The necessary changes go right to the heart of the economics of IT strategy and traditions and will require sweeping new approaches; and,
• This new type of approach will require fresh and decisive thinking about viewing data as a highly valuable raw material that can be shaped into products and services that customers want and need.

These changes are rooted in helping CEOs evolve their business strategy, their product-development strategy, and their corporate culture—the new data-storage technology and analytics become servants to those higher-value causes, not the end in itself.

3) The Devices Revolution. Another reason CEOs need to aggressively champion new approaches is because the third big factor in our perfect storm—the connection of tens of billions of devices to the Internet—will surely push today’s already-scary data volumes to unprecedented levels.

As big as today’s data-storage numbers are, just wait until this phenomenon called the Internet of Things starts to kick in, and we go from 8 billion or 9 billion devices connected to the Internet today, to 40 billion or 50 billion Internet-connected devices a few years from now. Everything from warehouse pallets to medical devices to pets and household appliances—not to mention clothing and tools and plants and swimming pools—will be tied into the Internet, streaming huge volumes of data about all sorts of things.

Here’s why all of this is so important: Companies that can deploy new data-storage technologies will be able to transform this data explosion and device explosion from runaway expenses to sources of enormously valuable insights and raw materials for new products and services, new and better ways of engaging with customers, and greatly enhanced abilities to anticipate what’s over the horizon.

Oil companies seeking new sources of energy miles below the surface of the Earth are enhancing their equipment with intelligent sensors and software to identify high-potential places to drill, or to warn of likely maintenance problems so they can be fixed before those problems happen, thereby saving millions and millions of dollars in downtime costs.

In a similar fashion, modern airliners are being outfitted with thousands of data-transmitting sensors to monitor and improve performance, evaluate new and enhanced procedures, and again detect and prevent costly maintenance problems and downtime.

So whatever industry you’re in—heavy manufacturing, retail, financial-services, healthcare, logistics, transportation, energy and utilities, and so on—the data volumes we’re talking about are simply staggering, and your CIO better be working very hard right now to help you find ways to get out in front of these trends. If not, that $7,500-per-terabyte cost of storage will not only continue to play havoc with your capital expenses, but also undercut your strategic ability to capitalize on the emerging Internet of Things phenomenon that’s sure to disrupt every type of company in every type of industry.

As always, top-performing companies will find ways to take full advantage of profound changes and will exploit these new worlds of demographics, data, and devices to their own advantage and to the benefit of their customers.

And best-in-class CEOs will understand that the time to begin turning these shifts into strategic assets is now.

To come up with our list of the cities with the fastest-growing information sectors, we zeroed in on the 55 metropolitan statistical areas that have at least 10,000 information jobs, which includes software, publishing, broadcasting and telecommunications services. We used the same methodology as for our overall ranking of the Best Cities for Jobs: we ranked the MSAs based on job growth in the sector over the long-term (2002-13), mid-term (2008-13) and the last two years, as well as recent momentum.

Our top 10 is dominated by large metro areas renowned as tech hubs – Madison, at No. 5,  is the smallest by far. In first place is Silicon Valley — San Jose-Sunnyvale-Santa Clara — followed by San Francisco-San Mateo-Redwood City, which together employ over 110,000 information workers. Both have been primary winners in the latest high-tech bubble. Since 2008 information employment is up 23% in San Jose and 27% in San Francisco.

They’re followed by Boston-Cambridge-Quincy in third place, and Austin-Round Rock-San Marcos, Texas in fourth. The foundation built in previous tech booms — including venture capital, educational institutions, corporate headquarters, and skilled workers — has helped many of the strongest tech regions become even more so this go around.

But there are some surprising places on our list, including a few Sun Belt metro areas that were hard hit in the housing bust. Take Atlanta-Sandy Springs-Marietta, Ga., which ranks sixth on our list, with a 7.7% expansion in information employment since 2010. Less expensive than the West Coast hotbeds or Boston, Atlanta could be emerging as a player in the sector. Last year General Motors opened a software facility in suburban Roswell, with plans to create over 1,000 new jobs.

Phoenix-Mesa-Glendale, Ariz., ranks ninth with 11% growth in information employment since 2008. In 2013, the metro area added as many information jobs, roughly 2,000, as the Bay Area, according to an Arizona State University study.

Starting with my generation as a “70er,” I grew up in the 70s with a fairly traditional education. During my middle school years, owning a TV at home was still much envied among my classmates. Communications were exclusive to the phone and writing physical letters. Most of us didn’t know what a personal computer looked like until college. Now almost 20 years into the work life, majority of us are more than sufficient when using digital technologies like WeChat, Google Hangouts or on-line shopping. But never the less, we didn’t grow up with them and this insinuates my generation’s ability adapt to new technology.

A 80er is an in-between generation. Computers had just made their way into high schools and colleges during this time, however use of cell phones and mobile technologies were still non-existent. While 80ers were early adopters of personal computers, many of them found it a bit challenging to transition to an almost all-encompassing online world.

A 90er is definitely the most “tech savvy” generation. Communicating via E-mails became ubiquitous in their time. They also witnessed in real-time, the transformation of the Internet from a simply a communication platform to a lucrative ecommerce platform. This was just the beginning, as the Internet branched into areas of powerful online gaming and self-promotion, all within a decade.

Currently we are living amongst a brand new generation, the digital. Comparable to what America refers to as the “Millennial,” or “Generation Y” group, the “00er” is anyone who was born after the year 2000. This generation understands and utilizes the power of Internet natively. These are the high-school kids who leisurely publish 10 Weibo (Weibo is the equivalent of Twitter in US) messages during the subway ride home from school, and have multiple WeChat windows open, while listening to the latest top singles on their digital phone. They have mastered digital multi-tasking. They are the generation who probably doesn’t know how to retrieve a voice mail from a traditional land line because their only point of reference derives from their mobile devices. It would be interesting to see what kind of social changes they bring to the work place when they graduate from college. What effect will their perspective have on companies like Alibaba, whose foundation relies on ecommerce and a digitally connected customer base?

"The reason why there's so many accelerators is because the venture capital industry is being disrupted. It's a classic innovators dilemma distruption, where the costs of starting a company today are, literally, one one-hundreth of what they were 10 years ago," said Belani. "So $50,000 today literally does what $5 million did 10 years ago. And, so suddenly, because the barriers of entry have gone down, there's all these accelerators popping up."

The disuption starts with the business model, in this case startups getting the money they need without having to go to VCs, he said, and then it sustainable thanks to the intangibles: it is a network effect, and the brains and products that emerge keep it going.

Ultimatly, founders will be served well, by having easier access to venture capital because he believes that accelerators will merge into something entirely different, and more effecient than the current VC model.

"The models that all these guys are developing, through all this hard work, which is going to serve many more entreprenuers by building these communication systems and communication platforms, will become better than the way that VCs are actually serving their high profile start ups," he said. "And so I think that this is just the beginning, I think, of disruption, ultimately, of the industry, over time."

According to Huang, the new accelerator models don't just point the way to a rethinking of how startups make money, but also how people are educated.

"For the last centuries we are going through an education system of cohort by age, where how old are we, and so we are assumed to have the same level of intelligence and interests because we believe that down the line, in 20 years, this is what;s good for humanity when, in fact, we don't know what's good for us in five years," she said,

"I think that the accelerator and incubator models today, and in the future, is going to shape what the education system is going to look like in the future." 

UNTIL 1890 China was the world’s largest economy, before America surpassed it. By the end of 2014 China is on track to reclaim its crown. Comparing economic output is tricky: exchange rates get in the way. Simply converting GDP from renminbi to dollars at market rates may not reflect the true cost of living. Bread and beer may be cheaper in one country than another, for example. To account for these differences, economists make adjustments based on a comparable basket of goods and services across the globe, so-called purchasing-power parity (PPP). New data released on April 30th from the International Comparison Programme, a part of the UN, calculated the cost of living in 199 countries in 2011. On this basis, China’s PPP exchange rate is now higher than economists had previously estimated using data from the previous survey in 2005: a whopping 20% higher. So China, which had been forecast to overtake America in 2019 by the IMF, will be crowned the world's pre-eminent country by the end of this year according to The Economist’s calculations. The American Century ends, and the Pacific Century begins.

Whatever the endgame, it could take decades to reach. In the meantime, this is a fight that rewards scale. Size means efficiency, efficiency means lower prices, and smaller providers of cloud services are going to have a hard time competing.

And there’s a third big player: Microsoft. The company launched its own cloud service, Azure, in 2008. Though Azure is an also-ran for now, the company is so deeply entrenched in corporate IT culture that at least some companies are willing to wait for it to bring its cloud services to parity with Amazon’s. And like both its main rivals, Microsoft has the money to spend on the engineers and infrastructure required to make its cloud truly big.

"I do think the market [for cloud services] will support three big players,” says Mickos. “Google and Microsoft will build big businesses but can’t take the lead away from Amazon anytime soon."

That still leaves room for a gaggle of smaller companies providing other services, such as private clouds for companies that are nervous about keeping their data on someone else’s servers in an age of hacking and NSA surveillance. Companies that offer such services, like Rackspace and VMWare, as well as Mikos’s Eucalyptus, can offer these clients more control over their data—though there is evidence to suggest that private clouds are no more secure than the ones administered by Google and Amazon.

Either way, the upshot of all this competition is that computing has never been cheaper, and it will only become cheaper still. And as the internet penetrates every part of our lives, down to the everyday objects like toasters and cars that will someday soon be “smart” and connected, humanity is only going to need more cloud.

In an age of personalization, the internet of everything, with elements of sensors for data collection, big data analytics, sophisticated mobile and web applications, integrated with operational elements of customized delivery services will reign supreme. Yack, yack, yack . . . so what does this really mean for the business opportunities ahead? Here are our projections.

Sensors: Sensor technology and adoption have evolved to the point of having too many sensors, not enough standardization. Sensors range from throw-away, single-use models to MEMs and RFID solutions. They can be apps on mobile phones to gadgets that are wearable or not to sensors attached to and even inside our bodies. So what needs to be done to ensure that the sensor technology remains relevant?

1. Integrate the sensor hardware and reports so that it is integrated with applications and analytics.

2. Create sensors that collect only the relevant data for specific purposes, short-term and long-term.

3. Manage the sensor development project so that each individual sensor solution is cost effective and also customized to the needs of the user.

Big Data Applications: Yes, it’s about the data, we have oodles and oodles of it, coming out of our ears, detailing everything from our web search habits to buying and texting patterns, from time spent in a room to preferred heating temperatures, from average speed on freeways to average expenditure for each trip to preferred stores, in preferred months, at preferred times of day. And sensors of every style and flavor will continue to add more and more data to be managed, overseen, and acted upon. The future must include this data though, so here are some thoughts on what you need to do with the data you have, when delivering personalized solutions for your customers:

4. Filter out relevant data – know what data is relevant, when and why. Create customized reports on that relevant data, so that various stakeholders can monitor and act on it.

5. Integrate all data sources into a common structure so that you can create inter-relations between the data.

6. Recommend actions based on data profiles. Allow stakeholders to update and manage which data profiles should elicit which actions.

7. Let the data tell the story about your customers and where they are trending.

Supply Chain Optimization: Thank you Dell for revolutionizing the supply chain process, making it on-demand. Thank you Google and Amazon for raising the bar beyond that, and aggregating the delivery of products to the door so efficiently and conveniently. The challenge and opportunity in delivering personalized products to the door is that the services must be customized to the needs of the user – not just combinations of off-the-shelf items! So how do you deliver this in a cost-effective way?

8. Integrate sensor, application/big data information into the manufacturing and delivery process.

9. Partner with stakeholders across the value chain, making each partner accountable for the customization before the delivery.

10. Target highest need classes of customers first, for although each will get customizations, it would be easier to deliver customized solutions if you had higher volumes of need for specific types of customizations.

The bottom line is that sensors, big data applications and supply chain solutions will be essential elements of successful personalized solutions, but integrating each element cost-effectively while wowing the customers is the ultimate challenge and reward.

E-mail us at info@fountainblue.biz with your thoughts.

It is now common knowledge that customer analytics will help retailers better understand and anticipate shopping behavior. Based on McKinsey’s Me Commerce and the Future of Retail findings, retailers can provide tailored product recommendations increase shopping volume by 5-10%, improve supplier negotiations, reducing costs by 1-2%, and schedule promotions for multiple locations increasing sales volumes by 1-2%. http://www.slideshare.net/McK_CMSOForum/me-commercefutureretail-r9

Based on that same report, the EBITDA growth rate for grocery retailers focusing on customer analytics is 11% vs 3% for those who don’t, and 10% vs 2% for big box retailers who do it. There’s a 10% increase in volume when ad campaigns are personalized, and 75% of NetFlix content is based on personal recommendations.

But if we could understand what happens *after* the product is brought home, we can better serve the customer, better anticipate her/his needs, and better connect them with the new types of products which may be of use for them.

What it would take is sensors to track and report on what’s happening, volumes of data and the capacity to integrate and manage it, applications that filter relevant information, actionable reports based on preferences, programs to ensure that various stakeholders receive relevant, meaningful information, as they define it, and the applications and processes to ensure that goods are cost-effectively transferred to the customer?

If we could bring it all together, we would better understand what’s in the ‘black box’, what’s behind the curtain, what happens after products are brought home. And if we know that, the world of retail would be forever transformed.

Description

Point of Purchase

Point of Use

1. Understand customer behaviors and preferences.

Understand the volumes (quantity, location) and types (sizes, colors) of merchandise purchased.

Know not just what was purchased but also whether and often it was used and when you are running out.

2. Use aggregated data to see and even predict buying trends.

Aggregated point of sale purchases show purchasing trends and help retailers make educated predictions on what will sell and how best to engage with the customer.

Supplement point of purchase data with usage patterns at home to more clearly identify trends and make educated predictions on future purchases.

3. Proactively manage supply.

Supply each store location on specific styles, colors, sizes and brands based on past purchase patterns.

Use both purchase and usage patterns and information to manage store supply.

4. Target new product introductions.

Experiment with new styles, colors, and products based on past preferences. Understand which experiments work, based on who’s buying and how many are buying.

Extend the experiment beyond the point of purchase to the point of use. Who’s buying and using something how often and with which other products?

5. Recommend other products based on current and past purchases.

Coupons for similar products from the same or different manufacturers presented at the point of purchase.

Coupons at the point of use would be more compelling as they are sent when a product is running low, not just provided at the point of sale when you have a fresh supply, and it’s not a given whether it would be used at home, or how long it would take to use it.

6. Tailor product recommendations and coupons.

Provide tailored product recommendations based on purchase patterns and know which categories of people and which specific individuals take advantage of these recommendations and coupons.

Provide tailored product recommendations and coupons based on usage patterns and also time them based on how much of the product is remaining.

7. Encourage feedback.

Invite customers at point of purchase to go online and report on shopping experience and reward them with coupons for doing so.

Invite customers who don’t use products purchased to give feedback on why not. Offer coupons for feedback and even replacement product if it makes sense.

8. Manage inventories.

Use analytics at point of sale to manage inventory proactively.

Couple POS data with POU data to augment your data set and better manage inventory.

9. Report purchasing trends to retailers and manufacturers.

Provide detailed analytics to retailers so that they can stock their shelves and manufacturers so that they can understand and predict the needs of the consumer.

Add point of use information to see which purchased products are actually used, which ones are used in conjunction with which products, etc.

10. Negotiate with suppliers on volume orders.

Better negotiate with suppliers on volume orders as you better understand purchase patterns.

Add point of use data to increase amount of data you have to anticipate product orders.

What are your thoughts for the next generation of retail? E-mail us at info@fountainblue.biz. 

 

How does a CEO cope with this unimaginable volume and velocity of data, much less harness it to excite and delight customers?

Here are three things CEOs must do to tackle this challenge:

1) Take care of your employees, take care of your customers.

Larry Ellison recently noted that the two most important priorities for any CEO today revolve around people: Taking care of your employees and taking care of your customers. Companies in today’s hypercompetitive business environment simply won’t be able to survive unless they’ve got world-class people at all levels of the organization.

CEOs must demonstrate a commitment to employees by becoming champions for HR systems that empower every employee to fully understand his or her job, how it ties into the corporate framework, what’s expected of them, what training is available, and how they can use an embedded social network to communicate, collaborate and excel.

Over the next several years, many of the world’s top industrialized economies will see a turnover in the workforce on an unprecedented scale. Across the United States, Europe, China and Japan, the “baby boomer” generation will be retiring and, by 2020, we’ll see turnovers in those regions ranging from 10 to 30 percent.

How will companies replace all that brainpower, experience and know-how? How will CEOs perpetuate the best elements of their corporate cultures in the midst of this profound turnover?

The challenge will be daunting, but it can be met with world-class HR technology. As companies begin replacing up to 30 percent of their workforce, they will need thousands of new types of data-native workers to exploit the Internet of Things in the service of the Internet of People. The shift in corporate mindset here can’t be overstated. The CEO has to be at the forefront of this new way of recruiting, training, motivating, aligning and developing truly 21-century talent.

2) Start thinking today about the Internet of People.

Some forward-looking companies have begun pursuing the “democratization of data.” This allows more people within a company greater access to data that can help them make better decisions, move more quickly and keep pace with the changing interests and demands of their customers. As a result, we’ve seen organizations flatten out, growing numbers of well-informed people authorized to make decisions without corporate approval and a movement of engagement away from headquarters to the point of contact with the customer.

These are profound changes, and I’m a huge proponent. As I think about what the next few years will bring as companies become deluged with unprecedented streams of data, I’m convinced that we’ll need dramatically different organizational structures, decision-making models, risk-management profiles and reward systems.

For example, if a car company’s marketing department mines incoming data to determine that customers are shifting rapidly toward neon-green models, how many layers of approval, review, analysis and sign-off will be needed before the factory starts cranking out more neon-green cars? Will we continue to have organizations where too many people are empowered to say “No” and too few are allowed to say “Yes”? If so, how will those companies be able to compete in a world in which customers have more choices, instant access to more information and less loyalty than ever before?

That’s why I think CEOs need to begin thinking about this problem right now, not in a year or two when competitors are already reshaping their organizations to match the marketplace’s new realities.

3) Partner with universities to help create a new type of highly skilled workers.

Several years ago, universities introduced new undergraduate as well as graduate-level programs in analytics and informatics as the business need for deeper insights into the booming world of data began to explode. Today, as the growth rate of data continues to soar, we know that the Internet of Things will only intensify that growth. Moreover, as Big Data fuels insights that can be shaped into products and services that generate revenue, the demand for data scientists and data specialists will go on unabated.

Beyond that top-level expertise, companies are going to need data-native thinkers at all levels of the organization. Where will this new type of worker come from? I think it’s incumbent on the business community to collaborate with universities to develop new curricula designed to turn out graduates who can capitalize on the data-driven world that the Internet of Things is surely going to create.

These new workers will create opportunities to help their companies in fields as diverse as product design, customer service, marketing, manufacturing and distribution. They will become innovative leaders in fashioning an entirely new type of workforce and organizational structure optimized to fully exploit the Internet of Things so that it becomes a high-value enabler of the Internet of People.

Oculus Rift has plenty of potential for changing human interaction, but what about other animals? One project from Iowa State University assistant professor Austin Stewart (via FastCo Exist) imagines how VR goggles could make chickens believe they’re free-range, even when they’re not. They can explore a virtual grassland, and with future iterations of Oculus, even peck at the ground and bob their heads around to take in the landscape at different angles.

It sounds absurd because it is, in part; Stewart’s so-called Second Livestock project is actually more of a social experiment than a genuine project aiming to bring virtual reality to farm flocks. He’s pitching it via a website with a deadpan seriousness that is fairly convincing, right down to the description of what are essentially high density livestock condominium complexes that purport to generate as little waste as possible by recycling waste and using animal body heat as the source for facility environment controls.

Stewart’s MO is to create tech-based projects that shed light on our relationship with gadgets and the world, however, and the way in which we can sometimes lean too heavily on tech in pursuit of relatively simple ends without stopping to consider how we might do it better without the bells and whistles. But in the end, the project isn’t designed to purely deride tech, its users or the people he claims to be selling to. Instead, Stewart hopes to spark discussion among even audiences that normally gloss over tech pitches about what we’re creating with digital environments.

Which isn’t to say Stewart isn’t open to the possibility of making VR for chickens a real thing – he says he’ll work with scientists who want to make it legit, should any offer their services.

The least popular, but perhaps most useful, advice I give every year to MBA graduates is to pick up sales experience as soon as possible – and the closer to the customer, the better. Jobs in sales-related positions will likely teach you how to do the following:

1) Conquer Rejection: Cold-calling, market surveying, and… rejection, can be tough. But as someone who got his start leasing warehouse space, I can attest to the value of overcoming rejection and developing a granular, customer-by-customer connection with the market. Jobs involving lead generation and lead qualification comprise corners of the sales funnel that may turn off some would-be sales reps, but can still be great ways to learn a market. Embrace them if that’s where you get your start.

2) Hone Your Networking Skills: People in sales learn to create and cultivate new relationships seamlessly, not only with customers but also with suppliers. Networking is a great way to meet customers, suppliers, potential joint venture partners and advisors in an industry – and it can be enjoyable.

3) Tackle and Solve Problems: The legendary head of sales for IBM, Buck Rodgers, used to say that his favorite call of the day was from an angry customer. He considered it an opportunity to prove to that person why choosing IBM had been a smart move. After-the-sale service jobs (often called account management) are vital to establishing and maintaining lifetime customers and can serve as a tutorial in what works and what doesn’t. Getting direct customer feedback will lead to product improvements and teach you how to respond to customers before you lose them.

4) Rise to the Top: As you master the art of sales, you’re honing your powers of persuasion, improving your listening abilities and developing the grittiness that makes salespeople such durable members of the workforce – all of which happen to be valuable leadership skills that can help you rise to the top and better manage your responsibilities once you’re there.

As motivational speaker and sales guru Harry “Zig” Ziglar used to say, “You will get all you want in life if you help enough other people get what they want.” If a job in sales can teach you that, you shouldn’t miss the opportunity. And, if you’re in finance, consulting, or supply chain management, there’s no reason not to borrow this salesman’s credo.

Venture capitalists invested more money in startup companies during the first quarter of 2014 than in any other since the dotcom boom went bust in 2001. They also spent more per deal than at any other time in the past 14 years, including a record nine rounds of more than $100 million each (for companies like Airbnb and Dropbox). And $1 billion-plus valuations for unprofitable private companies are now commonplace. This all comes courtesy of a voracious bull equity market that has welcomed most tech IPOs, similar to the last time around. Not wanting to be caught flatfooted again, many pundits are claiming we're near the top of a new tech bubble -- or perhaps just past the peak, in light of the Nasdaq's shedding 6.49% of its value in the six weeks beginning March 3.

There is no doubt that if the music hasn't already stopped, it will at some point. Perhaps tomorrow or a year from tomorrow. And when that time comes, what will happen to capital availability for startups? Will it be a repeat of 2001, when thousands of cash-starved companies collapsed under the collective weight of their foosball tables and hundreds of VC firms faded into the ether? Or is the "things are different this time" cliché actually true -- not in terms of the cycle's existence, but in the nature of its consequences? From my perspective, it's the latter. No replay of 2001 here, thanks to at least three major differences:

• VC lessons learned. During the dotcom boom, just about the only thing that grew faster than the number of startups was the size of the venture capital industry. Hundreds of new firms materialized, and existing shops raised more money than they could responsibly invest. Since the eventual reckoning, however, most of the VC survivors have stuck to their knitting -- raising smaller funds less frequently. For example, fewer than 200 U.S.-based VC firms raised just under $17 billion for new funds last year, compared with nearly 500 firms raising around $80 billion in 2000. In other words, it isn't usually venture capitalists taking the big-dollar risk this time around. Instead, it's hedge funds, mutual funds, and other VC industry tourists not integral to the startup ecosystem. Most of the real VCs will survive and continue to invest.

• Viable acquirers. Think back to 2001, when Amazon stock hadn't broken $100 a share, Google was privately held, and Mark Zuckerberg was still in high school. A large number of VC-funded startups at the time were Internet focused, but who was going to buy them once the IPO window slammed shut? Most of today's tech startups, however, do have potential acquirers. Not just consumer-facing Internet firms, but also all sorts of enterprise-software outfits as large incumbents scramble to keep up with irreversible macro trends toward cloud, mobile, and data analytics. The more portfolio companies a VC firm can salvage -- as opposed to scrap -- the more likely that firm will be in a position to make future investments.

• Fewer capital-intensive startups. Just because companies are raising more money doesn't mean they need to do so. The Q&A site Quora, for example, recently raised $80 million in Series C funding, despite having yet to spend most of the $50 million in Series B funding it raised two years ago. It referred to the new money as "insurance." Not only did the original dotcoms incur major infrastructure expenses (such as server real estate), but a lot of that era's largest VC losses came from capital-intensive telecom companies. Today's larger rounds are mostly about encouraging growth rather than just getting off the ground.

To be sure, a market downturn would be far from painless for startups in search of funding. For example, enterprises may slow down tech spending. Or institutional investors may reduce new VC fund commitments, particularly if the industry's median returns continue to lag most public indexes. But it won't be Armageddon, even if that's what the "tech bubble" stories seem to be preparing everybody for.

There are four ways to break into e-commerce:

1. Better service (Zappos)
2. Cheaper prices (flash sales)
3. Proprietary products (Bonobos, BetaBrand, Warby Parker, Revolve Clothing, etc.)
4. New experiences (ShoeDazzle, Rent the Runway)

Unless your company embodies at least one of these attributes, it’s nearly impossible to succeed as a viable e-commerce company. Your potential customers are already loyal to Amazon (after all, they pay for Prime), so you’ve got to offer an incentive to compete.

So, in an age where the most effective way to get distribution is to source sales to already-established retail channels, how can a brand connect directly with customers even if they don’t make the sale?

I’ve detailed three cases below, in order from most to fewest drop-off points. Check out these ways to connect with your customer even when you don’t make the sale.

1. Product Registration

Just before my son was born, I treated myself to a high-end dSLR camera. Being a retired, semi-professional photographer (I haven’t made a dime off my photography in over ten years), I let my ego get the better of me and settled on a camera that exceeds my current demands (Ireally do need to be able to take 10 frames per second at 1/64000 and f22 to properly capture my dog licking my one-year-old).

More expensive stuff always seems to come with a product registration form. It seems that these forms always come with products that aren’t sold by the manufacturers but rather by retail stores that are brand agnostic.

But, if a decent retailer offers a warranty or return policy consistent with the manufacturer (almost an expectation outside of bargain/discount stores), then why is registering a product necessary? In reality, the only real benefit to registering the product is to the manufacturer — you, the purchaser, opt into a list and subsequent promotional communications.

Tracking sucks on product registration because there are too many chances to miss key information about your customer… assuming the customer actually fills out the registration to begin with. If they provide an email address, you can put them on an email list and leverage Facebook custom audiences to enable remarketing and look-alike modeling if you can connect that email address to a Facebook profile.

The waterfall below helps to visualize the small percentage of users that can actually be marketed to based on product registration.

2. Social Media & Promotions

When you don’t have an expensive product and a significant percentage of sales occur offline, connecting with your customer base can be difficult. Social media outlets such as Facebook and Twitter present solid opportunities to connect with your customers by offering coupon codes and promotions for repeat purchases.

Consider the situation where someone purchases a Logitech BOOM Mini at one of the big box stores and pays in cash. The brand, Logitech, is two degrees away from the customer and will most likely never be able to connect with them – unless they can incentivize the customer enough to voluntarily opt into communication.

One possible incentive is through post-purchase giveaways and offers such as tweeting or posting on a specific hashtag to receive a discount on a subsequent purchase. Knowing this will be a secondary purchase, the brand, Logitech, can get relatively aggressive with the offer as margin was already made on the initial purchase.

Integrations with Facebook and Twitter (when you login with your FB or Twitter credentials) allow brands to link your purchase with an email address and put you on a list for future communications. Building off case 1, the goal is to mitigate the number of potential drop off points.

The waterfall below helps to visualize the trackable users:

3. Device Activation

I purchased a Roku 3 about a year ago. After researching various streaming devices, I was sold by Roku’s native integration with Plex so I could stream my library of movies from my local server to my TV.

It just so happens that my local Best Buy had a sale going on, and I was able to save a couple bucks by buying in store. So I took my new toy home, set it up, and the first thing that popped onto my TV was an activation code telling me to go to a roku.com link to “activate” the device. I created my account, customized the menus and started watching shows.

It was so subtle, yet it hit me like a Mack truck. The folks at Roku had created a system that ensured I would engage with the brand. It was a simple, non-invasive step allowing me to configure my device and customize features content. Genius.

Not surprisingly, other streaming devices manufacturers (Google , Apple, etc.) have followed suit, and Chromecast/Apple TV require a similar process to ensure the manufacturer does not give up customers engagement by allowing retailers to sell their products.

Keeping in line with the tracking waterfall, Roku ensures that 100% of costumers activate their device and engage with the brand:

Concluding Thoughts

As visualized in the waterfalls, it’s all about limited drop off points. Providing incentive for (orrequiring) customers to create an account will dramatically increase the likelihood of customers opting into engagement.

Not all products require activation, nor do I think that brands should modify their products to require activations. However, if you have the ability to offer something to your customers in exchange for their contact information, it’s likely that your customers will happily share their contact info. You don’t need to be creepy to get user data, you just need to provide value.

With more than 26 billion (or more) connected devices anticipated by 2020, there’s a big question about how those devices will talk to one another. But the scientists behind Neura, a startup that has offices in both California and Israel, are less worried about how devices will talk to each other and much more concerned with how humans will interact with them. It’s not like people want to spend hours tweaking their dozens of devices just to make them work.

Neura, which was founded in January of last year, thinks it has a solution to this problem in the form of a technology stack for the internet of things. The company has raised $2 million in seed funding led by venture capital firm Greenhouse Capital Partners, alongside SingTel Innov8 Ventures, Pitango Venture Capital, TriplePoint Ventures, and several angel investors. That funding is in addition to a $300,000 pre-seed round. While I might quibble with Neura CEO Gilad Meiri about his definition of a seed round, I like his thinking on the technology stack he’s promoting.

Neura’s goal is audacious: to make the internet of things all-inclusive and anticipatory. To do this, Neura has three layers of technology starting with data normalization. It calls this layer Harmony, and the idea is to essentially build device profiles and make the data each device gathers fit into a specific profile.

So while there are dozens of fitness tracking options on the market, the Harmony layer attempts to take each of them and figure out what information is relevant and then grab that data and turn it into a potential subscription. So it might be the number of footsteps from an activity monitor or the time spent asleep. For heart rate or glucose monitors, it will track down whatever the relevant metrics are, and then store it in a common format.

The next layer is a rules engine that will let the user or Neura partner set conditional rules (like if this, then that) today, but will eventually evolve into a pattern recognition engine that will then suggest rules to the end user based on their habits, devices and even connections. Neura calls this Trac.

On top of that is what Neura calls the physical graph, which is a pretty common terminology among folks developing products for the internet of things, but for Neura actually means a database of contextual elements that will influence and inform the rules engine. Meiri expects that your devices will share information about what they are connected to, who you’re connected to based on proximity (for example a Nike Fuelband that is constantly sleeping next to another person’s Jawbone every night implies that the people are married or at least in a close relationship) where someone is, and what services to offer based on all that information.

Neura’s core technology is set, but saying you want to be the connective tissue for the internet of things and actually getting there is another matters. Neura’s CEO has decided to focus first on building out the database and profiles for the health and wellness market, focusing on a few partners who will implement the Neura technology and include it as part of an app or service offering.

Currently the Neura team has added profiles for about 80 apps, which can take anywhere from an hour to three days to add, said Meiri. However, he expects that once Neura has profiles for more than 300 services, then the burden of integration will fall on the partner wishing to join the platform as opposed to the Neura team.

As ideas go, I like the way Neura is thinking about the problem and can’t wait to see what the end results look like. Meiri was very clear that for now the rules engine is conditional as opposed to anticipatory, but in discussing how the platform could publish notifications, such as my step count or my location and turn that data coming from a connected device into an insight worth taking action over, I got a hint of how we might tie the connected world together.

If Neura can make that reality — or anyone else for that matter — it would be a huge step forward.