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The emerging market for mobile-powered enterprise rainmakers July 31, 2014

Posted by Bernard Lunn in Enterprise Web 2.0, internet of things, Salestech.
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Mobile is clearly a big disruptive force in technology, but what markets will it disrupt and how?

Although most of us already have smartphones (in the West), a lot of what we do on those smartphones, such as surfing and email, is like talking heads on early TV. What are the mobile-native use cases that will disrupt major markets?

 

An early mobile-native use case made the headlines when Facebook acquired WhatsApp; this was mobile messaging replacing a lot of emails and browser based social networking. Facebook has spent $19bn to declare this “game over”. They may be right (I don’t think they are, but that’s another story), but entrepreneurs certainly want to go after markets where they don’t face a tough, agile behemoth like Facebook.

 

Fortunately there are still plenty of other mobile opportunities where you don’t need to deal with Facebook as a competitor. One of these “blue ocean” opportunities is “enabling enterprise rainmakers”. Outside Sales is one example of enterprise rainmakers; they are critical to making the transition from brilliant product to great company. These folks tend to not follow rigid processes; they innovate every day, using Big Data and Social Media to figure out what to do next. The good ones spend most of their time out of the office, so they live on their mobile devices.

 

One of the most interesting companies in this space is Clari. They were still in stealth mode when I was reviewing Salestech innovators here and here on ReadWrite. Since that time they raised a $20m Series B and are clearly on a roll and the market they are in is hot. Within days of Clari’s funding announcement was the news that Salesforce had snapped up RelateIQ and the CEO of Clari was writing a blog post entitled Did RelateIQ Sell to Salesforce Too Soon?

 

For RelateIQ, the answer was no, their timing was good. I am sure they could see Clari coming in their rearview mirror. In Enterprise-land, the second best technology with the best distribution often wins and in the CRM market, Salesforce has distribution nailed.

 

My assumption when I first saw Clari was that CRM was simply their market entry strategy to a much broader market of enterprise rainmakers who make a big difference mainly because they spend more time away from their desk than at their desk.

 

My work is teaching sales organizations the forgotten art of thought-leadership selling, which is another way of saying teaching how to be an enterprise rainmaker. This is an outside sales world. This world is not interesting to CRM vendors because the unit numbers are tiny. One rainmaker may transform the fortunes of a start-up but how many rainmakers are there and does it matter what CRM system they use?

 

The unit numbers today are at the intersection of Marketing Automation and Inside Sales, which is growing according to this expert on inside sales writing in Forbes:

 

“Over the past three years, inside sales grew at a fifteen times higher rate (7.5% versus .5% annually) over outside sales, to the tune of 800,000 new jobs.”

 

Inside Sales is all about big scalable processes, the world of CRM, Marketing Automation and Call Centers. If you price per seat (as most CRM vendors do), Inside Sales is much more interesting than Outside Sales.

 

Inside Sales is not really a mobile play; these folks work in the office at big screens.

 

However Outside Sales are only one example of Enterprise Rainmaker. Think of M&A bankers and VCs. Or think of the senior executives guiding the company; the best ones are out talking to employees, customers, partners and investors.

 

It might be better to call all these folks “difference-makers”. They are the ones who make a difference to your business. It is the rainmakers who do their work outside the office who will drive this. They can choose their own tools because they are rainmakers. They choose mobile tools because they do most of their work outside their office.

 

These rainmakers do not work alone. This is where Mobile intersects with Big Data/Data Science and becomes an enterprise story. The rainmakers are out there interacting with people in the market, but they are in touch with support teams “back at base”. In the case of outside sales people, they maybe working with a sales manager who can provide “just in time coaching” because the manager can see precisely where they are in a sales cycle and when they are available to talk after a meeting. Or they may work with sales operations folks, who rustle up the precise support they need at that point in time (such as collateral, data, demo, contact).

 

Clari has this nailed for sales teams. However I want to explore the broader market opportunity beyond sales teams.

 

The concept of a point-person with a back-up team is like a surgeon who is supported by nurses, anesthetists and others. The same is true for M&A bankers and VCs, who have analysts crunching data and assistants making contact requests happen.

 

These rainmakers and their backup teams are the key enterprise “resource”, so it is possible to think of these systems as the next generation of ERP.

 

The concept of enterprise rainmaker goes much further than today’s well-paid enterprise professionals. This is where the market intersects with other disruptions such as Internet of Things and Quantified Self.

 

This is more speculative. The actual implementations are not yet visible (I would love to hear from entrepreneurs working in this area).

 

In Healthcare, think of the market of personal trainers, nurses, caregivers, emergency response workers and physiotherapists who come to your home. Let’s call them health-makers. The market is strong due to the demographics of ageing populations.

 

The health-makers back-up team is critical. The health-makers can assess the patient using good old-fashioned analog tools known as the four senses (eyes, ears, smell, touch). This old-fashioned “data” can be augmented by data from devices attached to the patient (“quantified self”) and analyzed on the spot by experts across the globe; The back-up team has access to Big Data to compare this patient with millions of similar patients. This will be real time healthcare in action, not waiting weeks for results and another appointment. This will happen first in markets where the regulation allows skilled practitioners such as nurses to perform tasks that today can only be done by doctors (who are too important to come to you unless you are really rich).

 

The Health-Maker opportunity is much bigger on a user unit basis than Enterprise Rainmakers. It may also disrupt one of the biggest markets out there – Healthcare. However there may be an even bigger market. We all need help getting our bodies fixed (aka Healthcare) but what about our homes and all the stuff in our homes? As our homes become more wired and digitized with sensors sending data, the person who comes to fix something may come equipped with a smartphone linked back to Big Data systems – and may come before you have even noticed the problem. This will create a whole new generation of services and, now that service is the new marketing, create significant new revenues for many consumer products companies.

 

These front line people will become the new rainmakers. They are the brand experience as far as consumers are concerned. How well empowered they are by data will be key to enterprise competitiveness in future.

 

Enabling these new kinds of services will not need great mobile user experiences that are linked to cloud-based data systems and applications. This will need a new generation of application platforms that deliver context aware data just in time to the front line “rainmaker”.

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The Content Quality Dilemma in the Media Business July 28, 2014

Posted by Bernard Lunn in Uncategorized.
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Software is eating the world….one bite at the time. Are you Softzilla or are you Softzilla’s lunch?

The first bite was the media business. I was there when it happened. It hurt.

Softzilla (my shorthand for software, digitization, mobile, big data, etc etc) first bit into the print business. At the time I was running a startup that saw this coming and was helping traditional media firms to restructure, take out costs and become “online-first” firms.

In the print to online transformation, the mantra was that “$1 of print revenue becomes 10c of online revenue.” So, yes, you had to make the transformation, staying in print only was certain death, but you had to cut costs (translation: fire lots of people) to go online. Everybody had read Innovator’s Dilemma; it was obvious what had to be done. Online, with tose 10c of revenue, you could not afford lots of editors and people doing fact checking and research. So you cut into the muscle and fired the people who ensured that content was high quality, those well-paid journalists and editors, fact checkers etc. The content quality then, predictably, suffered and the audience clicked away.

Cut too slowly and you died fast. Cut too fast and you died slowly. This is what I call the Content Quality Dilemma.

The next startup was smaller but better known; it was ReadWriteWeb (now ReadWrite) where I was COO in 2009.

There was no Innovator’s Dilemma in ReadWrite. This was a pure-play online venture with low overheads (a global team all working remotely). However the dilemma was the same – how do you make enough money to pay for quality content?

In ReadWrite my COO job translated to a simple mission – sell enough advertising so that writers could get paid. That was where I saw the Content Quality Dilemma up close and personal.

The problem is very simple. It is that giant software only media firms like Google and Facebook set the rates for online advertising and with their scale and 100% automation (no messy journalists, editors and fact checkers who want to get paid) they can make huge profits on very low advertising rates. Those ad rates are too low to pay for lots of good journalists, editors and fact checkers.

In the tech blogging space it is easy to run this as an experiment. Take 15 days on a post with serious investigative journalism and analysis. Then take 15 minutes to dash off a post about a celebrity and use some pop-tech angle to make it tech relevant (the story is that the celebrity did something on Twitter or Facebook). The return on investment on that 15-minute post was stratospheric and the quality post was a financial disaster. Rupert Murdoch, when interviewed for this article, remarked, “what’s new buddy?”

This is now well understood. We are at the bottom of the Slough of Despond in the Media Business. Its not just the old pre web firms, its also the early web firms; look at the share price and derision hurled at AOL and Yahoo. They are both run by super-smart, driven CEOs who had big success at Google, but they are “rolling a rock up a hill”.

Most of the entrepreneurs who got early into the blogging game already exited, took the cash and left the owners figuring out how to climb up to the Plateau of Productivity – which some of them will do. There is a demand for Quality Content. The only job is figuring out how to get paid properly for Quality Content.

If you work as a journalist or editor, you have probably seen that Content Marketing is where the jobs are headed. In other words, you work directly for the advertisers, cutting out those intermediaries (aka Media firms) with their old fashioned rules about Church vs State (aka Editorial vs Advertising). However what about the folks who are running Media Firms? How do they create both quality content and quality profits?

I decided to look at who is making quality content as well as quality profits. In those stories might be clues to show how to climb up that tough slope to the Plateau of Productivity (to see which of these are replicable and scalable).

  • Wired. This is one for irony aficionados, a glossy and profitable print magazine for the folks helping Softzilla to eat the world. My takeaway, we all need a pixel break, but I don’t expect many media firms to be able to emulate this. It has to be really, really good (and that costs money) and consumers only want one in their chosen domain. Not easily replicable, could translate to a few other domains.
  • AVC. This is Fred Wilson’s blog (he is a top tier VC). The content is daily and it is great. The takeaway, first make sure you are a good host to your community and then find a way other than advertising to make money. Not easily replicable.
  • Techmeme. Gabe Rivera bootstrapped a profitable online media business by first using Softzilla to find content and then hiring some old fashioned humans to help filter out the junk and float the good stuff to the top. I assume he tweaks his code to learn from what the humans do. This 95% code and 5% human model might be a mainstream model. Possibly replicab
  • Bloggers Selling Expertise. Why do smart people blog/write for free? It is the same reason that smart developers contribute to open source – their fee rate and utilization goes up because customers can see how smart they are. The economics of blogging for attention are simple. This is powering lots of tiny micro-multinationals in lots of niche markets. Replicable but not scalable.
  • Financial Time and Wall Street Journal with Paywalls. It works for them because “time is money” for their readers. I don’t see this as a mainstream strategy, because only the best of the best can get away with a paywall. Not easily replicable.
  • Vice Media. They started as an underground low cost fanzine type of operation and have over time built a valuable business that had Rupert Murdoch swinging by with his checkbook. The model seems to be lots of stringers out where the news is being made plus a few editors back at base. It’s an old model re-enabled by mobile technology (the stringer is no longer waiting in line for the telex machine in the lobby of the hotel). Possibly replicable, but needs skill, style and technology.

There are a few experiments with peer rating rather than popular rating. Popular rating is simple Page Views, the currency of the web that is controlled by Google and Facebook, it’s a game you cannot win. The two experiments with peer rating are Reddit and Hacker News. It is too early to see how these experiments turn out because neither has yet tried seriously to monetize their audience. If they adopt a mass-market page view strategy, their audience will click away and we will be writing Myspace like epitaphs.

However if they can find a way to charge based on influence rather than views they will show the way to lots of other media firms. This could be the yellow brick road for media. Recall that tech blog experiment:

“Take 15 days on a post with serious investigative journalism and analysis. Then take 15 minutes to dash off a post about a celebrity and use some pop-tech angle to make it tech relevant (they did something on Twitter or Facebook). The return on investment on that 15 minute post was stratospheric and the quality post was a financial disaster.”

Let’s say the 15 minute post got 100,000 page views and the 15 day post got 100 views. Case closed? No, not if 10 of those 100 views were partners in VC funds controlling $10 billion in aggregate funds and another 10 were CXO level in enterprises controlling $10 billion in aggregate budgets. How on earth do you monetize that without seriously invading privacy? If you have that one figured out, please contact me so that we can become disgustingly rich.

 

When Did Big Data Become Data Science And Does Anybody Care? July 26, 2014

Posted by Bernard Lunn in Uncategorized.
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I promise to keep this brief, it’s just an out take from another post I am working on. I have stopped seeing pitches for Big Data. They are now pitches for Data Science. Ho, hum, what’s the game? I think it is simply the realization that the “Big Data” roller-coaster is careening down towards the Slough of Despond. So you want to re-name it. 

I think Big Data is an enabler for Mobile, which is a real disruptive wave of change. Unless Big Data is delivered within context to what consumers need right now, it is just another “digital land-fill”. This will need major innovation at the mobile UX layer and at the back end computer science layer.