Microsoft Licensing Some of GoPro's Patents

Tweet storm of mine this morning:

Lot of articles about Microsoft’s licensing of GoPro patents but not one actually looked at GoPro’s patents. #lazytechjournalists

1/5 Looking through @GoPro patents there are a number that could prove useful for @HoloLens . Here are a few to help #lazytechjournalists

2/5 8,737,803 covers A/V streaming; 8,786,680 for mo-cap using body-mounted cameras; 8,970,726 sensor-to-DSP compression/decompression

3/5 9,025,896 for efficient image compression; 9,113,068 coordinated media capture and aggregation; 9,159,371 forensic video recording (!)

4/5 9,171,577 low-processing-overhead encoding and decoding (probably most useful patent); 9,197,885 auto-alignment of overlapping sensors

5/5 9,253,421 on-chip image sensor data compression…super useful for @HoloLens because it adjusts compression factor based on power avail

WSJ Review of "What Stays in Vegas"

Nothing juicy in here except the profits the casino makes off you

Nothing juicy in here except the profits the casino makes off you

No, it's not a rat-pack tell-all memoir, nor a salacious modern exposé, but rather "What Stays in Vegas" is a book about how casinos are at the forefront of using data to optimize their profits. And by profits, I mean how much you lose without getting so discouraged that you never return.

There's a good review of the book in today's Wall Street Journal that in itself is an interesting read.

Salesforce Storage Pricing Stuck in the '90s

The reason for deleting activities as noted in the post below is because we are at 4.4x our allotted storage in Salesforce. "Wow," you might be thinking. "You guys must have a crazy amount of data." But no. We have only 4.4GB currently stored, which consists of little more than Hubspot email notification activity.

That's right, it's 2014 and Salesforce's default storage totals 1GB. So our account manager calls me today to sell me more space since it's their quarter end and they finally noticed our overage.

A measly 1GB is pathetic but I think, no biggie, buy 5GB or even 10GB to give us some headroom. Can't cost much.

What a naive fool.

"We sell storage in 500MB increments," he says. That's right, less than your average CD-ROM. "And the regular price is $1500 per year."

Every Salesforce user and admin, at least once a week

Every Salesforce user and admin, at least once a week

"But since it's our quarter end," he continues. "I can get you 40% off!" This is like the Porsche dealer throwing in a free car wash with every new 911.

This means Salesforce's standard pricing is $3K per GB, a price not seen since 1992. Even the smokin' hot, end-of-quarter deal of $1800 per GB takes us back to 1993. And don't forget that this is an annual rate, not one-time.

It drives me bananas that Salesforce continues to be trotted out as an example every time some journalist or analyst talks about cloud companies. Yes, it's technically a cloud-based company, but Salesforce was founded in 1999 and is as much of a lumbering monstrosity as Oracle and SAP. Use a service like WealthFront and then try to create a report in Salesforce and tell me they're equally "cloudy."

I continue to believe that one of the great disruption opportunities existing today is a rethinking of what CRM needs a modern, cloud-savvy enterprise has. Then build a platform on a modern stack, not a molasses-slow system that won't let you query both leads and contacts for a report.

Adventures in Salesforce Support

Salesforce: ”We received your request to delete activities from all leads/accounts”

Me: ”Yes”

Salesforce: ”We will need the CSV file with all the activities’ codes and then we can do that for you.”

Me: ”If I had the CSV I would do it myself.”

Salesforce: ”Well, it will take a lot of time to find those codes and create the CSV.”

Me: ”I know. That’s why I asked you to do it.”

Salesforce: ”…”

Salesforce: ”Okay, I will have to check on that and I will update you.”

UI and UX Done Right != Customer Satisfaction

Oscar is a health insurance company in New York that is essentially putting a beautiful front end on what turns out to be a fairly standard health care back end, leading to VC money and tech-press adulation. First, what do they do right?

The home page starts with a positioning statement that, within two sentences, tells you they're bringing something different (without being jargon-y). Continuing this friendly tone, each of their sections starts with "Your...," personalizing the healthcare for the user.

Impossible to make this look any friendlier

Impossible to make this look any friendlier

As you scroll down, their phone # is always at the top, obvious but unobtrusive. Very few sites do this well.

The product benefits are somewhat novel (e.g., free generics is uncommon, but it's not an innovative stretch considering the nominal copays most plans have). But again, how they're presented is friendly, non jargon-y and intuitively valuable.

If only they did the maps for every retailers' site

If only they did the maps for every retailers' site

Their map of providers is awesome because there are no inside-baseball terms that force the customer to figure out what preferred in-network means vs. non-preferred in-network. It's simple: is your doctor part of our plan or not?

I love the way they solicit information for a quote: it's a sentence that you modify with your high-level details (Beats Music also does this pretty effectively). No filling out a standard form and then waiting to be contacted, you can see plan pricing immediately. And the plans don't list every single term, just the high-level features that are consistent with the product page and you can click through for more details. This puts the first stage of the selection process on the potential customer, not one of their agents, likely yielding a better quality ratio for their leads. They also did some really nice UX work with the ability to side-scroll through the carousel of products that show your monthly premium without forcing you to reenter form information.

Just about every company with a service to sell could emulate this approach

Just about every company with a service to sell could emulate this approach

BUT!

Attractive UI, friendly UX, simple quoting system. This gets you $150 million in funding and guaranteed success! Apparently, yes, at least if the extent of your model is signing people up for health plans. But what was lost amidst all the design work and coding was...you have to do all the mundane, tedious work of actual healthcare once you have customers.

Stories are dribbling out of incorrect provider lists, nonsensical billing practices and inconsistent customer service. Their Yelp reviews are filled with 1-star horror stories that would be hilarious if there weren't people writing them whose lives are adversely affected. Nicely designed provider network maps are only as useful as the data underneath them.

The moral of this story is, by all means hire the designers and coders to help build a company that applies tech solutions to archaic services, but don't forget to also use some of your VC money on people who actually know how to succeed in that industry.

Build Charts that Illuminate, not Complicate

Creating accurate, honest and useful visualizations of data is one of the trickiest endeavors in business. Basic measures, such as revenue over time, are communicated nicely by the built-in charting capabilities of Excel, Numbers, Google Docs or any number of apps. But even then, temptation lurks in all the colors, styles and formatting options. It's all too easy to get carried away, adding superfluous labels, legends, bars, lines and even data itself.

As in marketing, product management, corporate strategy and even life, the best solution is to put yourself in the other person's shoes. Who is the audience, what's important to him and why does he need the information? For example, to an auto manufacturer, tracking monthly unit sales is critical, but arguably more important at a strategic level is their share of the total market. Increasing unit sales are great, but if the market is growing at a faster pace than sales, their market share is declining, which is information that must be communicated.

After establishing the who, what and why, then comes how you communicate the data, which is where charts come in. There are myriad options for presenting data to the team managing our example auto manufacturer, but the choice should be based on ensuring the audience receives exactly the data they need as simply and understandably as possible. Unit sales and market share, for example, are immediately grasped and understood when charted with two axes, much less so if just in a spreadsheet.

I recently ran into this in an analysis I was writing for my company. We conducted a survey of residential investors to better understand their recent experiences in the market, as well as their expectations for 2014. One question was, "In 2013, how many investment properties did you buy," followed by, "In 2014, how many investment properties do you plan to buy?"

A straightforward and standard Excel-type solution is a column chart that compares 2013 to 2014:

Simple, easy to read, but there's more information that could be conveyed...

The chart above accurately illustrates our survey respondents' optimism about their property acquisitions this year, with only 5% expecting to exit 2014 having not bought any investment houses. However, the amount of data contained in this chart is slight. If you're in the business of writing loans to these investors (as we are), it's encouraging but not actually helpful to know that people expect to buy more. More helpful would be to know exactly who expects to buy more, and how much more. For example, how many of the people who bought 1-3 last year expect to buy 4-6 this year, versus another 1-3?

To inject more meaning into the chart, I sought to show where members of each 2013 group migrated in 2014. My first attempt was a stacked column chart:

Answering the example question above, 18.75% of those who bought 1-3 properties last year expect to buy 4-6 in 2014, represented by the yellow section of the second column. So this chart has the desired information, but it's confusing. Charts are like jokes: If you have to explain it, it doesn't work.

The other problem with this chart is that I lost the 2013 and 2014 percentages for each group. What the reader of this chart would most appreciate is knowing those percentages, as well as generally understanding the migration between groups. The actual numbers behind the migration are overkill for the intended audience.

Therefore, I went old-school and sketched out a chart that would show everything I wanted:

Nothing fancy, just a quick visual check to ensure that what was in my head could conceivably result in what I wanted. I then worked out the tick marks I would need and cranked up Illustrator:

Now we have the percentages for each grouping, as well as a sense of the migration between those groups. We can quickly see that the bulk of investors expecting to buy 4-6 properties this year bought 1-3 last year, equipping us with knowledge to tweak our products and marketing accordingly.

Is the chart perfect? Nothing ever is and even looking at it now, a list is forming in my head of things I'd modify and enhance. But it capably visualizes and conveys the needed data for the intended audience, which is all we can ask of a chart.

How to Turn a Supercomputer into a Platform

I'd like you to meet Skynet's grandfather

I'd like you to meet Skynet's grandfather

Remember Watson, the IBM supercomputer that beat lowly humans on Jeopardy in 2011? Fast forward a couple years and IBM is trying to turn Watson into a business. In fact, they're putting $1 billion behind it and giving it its own headquarters. Not bad for a computer. But how does Watson work and what can it really do?

Watson is a cognitive system, which means it's a computer that's designed to think like a human, only much faster. The key to Watson's uniqueness is its ability to combine three capabilities: process natural language questions (think of a more powerful Siri), generate and evaluate multiple possible answers, and learn as it goes from its successes and failures. Essentially, to think and answer like a human.

Using Watson's Jeopardy performance as an example, Watson first interprets the question, looking for key words and even puns that could mislead it. It then formulates multiple hypothetical meanings, searches its database for answers and grades the probability for each that it has an accurate interpretation and answer. If a given answer meets a specific probability threshold, it answers the question. It's big data analysis made efficient and incredibly fast.

Big data is all the rage currently, but data is messy. It's stored in myriad formats, various databases and incompatible structures. There are a lot of companies that let you do clever things with your data (like Tableau), but they're limited in both what data can be read and what can be done with it. Taking more extensive advantage of the data available to you (like with a Hadoop cluster) typically involves extensive data cleaning and programming. 

If Watson is to live up to its promise, it needs to have more power than a Hadoop cluster but be as easy to query as a Google search. You could feed it a hodgepodge of data and then ask questions as you normally would, from simple to complex. Who are my top 20 customers this week? What else is someone buying when they put my product in their cart? Given these symptoms, what's the proper medical diagnosis? What soybean crop yields should we expect this year?

The problem is that Watson is so flexible and so powerful, IBM is obviously having difficulty communicating what it can do. They talk like enterprise-product engineers who want to play it safe and be as broad as possible in their description:

With Watson technology, we can move from a keyword-based search that provides a list of locations to an intuitive, conversational means of discovering a set of confidence-ranked responses.
— Watson website

In an attempt to rectify this and generate some concrete implementations, they're trying something very un-IBM-like: letting outside developers leverage Watson's capabilities via a challenge. Submit your idea, make the cut and get access to the Watson API to develop your app. Pretty cool. But insufficient.

Fostering the development of a couple dozen Watson-based apps is not going to capture the public's or developers' imaginations, nor is it likely to generate the revenue that justifies a $1 billion investment. They need to tap the creativity of more than a few dozen developers. They need to encourage use case experimentation. The greater the access to Watson's API, the sooner they can show real-world implementations.

IBM needs to create a WaaS platform: Watson as a Service. Open up the API to everybody, provide a free development tier and then offer metered production tiers. You cannot hand someone a black box and ask them to build a business on it, while paying for the privilege. If you're intent on keeping it a black box, let everyone experiment with the box, discover what it can do.

The Watson team can also make the technology much more approachable. Instead of talking so much about Watson, let people take it for a spin and see what it is. Create a "Stump Watson" page and let people ask natural-language questions. Show the answer, along with a graphic illustrating how Watson arrived at the answer, like they did on Jeopardy. The buzz alone will draw developers to experiment with the API.

The flaw in the Watson Challenge is that IBM is only going halfway with the crowdsourcing of implementations. IBM's developers and product managers will be vetting the mobile app proposals and picking winners. If they want to be surprised and delighted by how Watson can be used, they should let developers experiment and not presume they know the best ways to utilize it.

How to Explain Twitter to Your Mom. And Why She Still Won't Care.

If a tweet posts in a forest and no one's there to read it, did it post?

If a tweet posts in a forest and no one's there to read it, did it post?

"No, I'm not on Twitter. I don't even really know what it's for." If you enjoy Twitter as much as I do and have tried evangelizing it, odds are you've heard some variation of this, as I did from my mom. Twitter defies easy explanation, making it difficult for someone to get into, which is evidenced by Twitter's flatlining growth. Twitter themselves don't seem to have a good handle on what they do, considering how generic and malleable the definition is on their About Us page: Twitter helps you create and share ideas and information instantly, without barriers. Like Facebook? Like WhatsApp? Like PowerPoint or email or just about anything?

How can we explain Twitter to mainstream users so that it sounds intriguing enough that more people will climb the learning curve? And will they care enough to reach the summit?

The standard definition of Twitter is that it's a social media site, but it's not, really. Social media is networking and how many people actually use Twitter for communicating with their social network? Okay, how many people who aren't already famous or who live in Silicon Valley? Assuming you have any non-tech-industry friends on Twitter, try DM'ing them and see how long it takes for a response. QED. There are other services better suited for social networking.

How about a messaging app? For some, yes. But again, you need to already have some measure of fame or work in the tech world to have a sufficient number of friends and family on Twitter for it to act as a functional group messaging app. Easier to just keep adding names to your SMS text, or post a global status update on Facebook. And of course there's no shortage of messaging apps.

Is it a news site? Certainly, major news can break on Twitter, but it's not a passive source of news, which is what the average consumer wants. Here's another test. Pretend you're a Twitter neophyte who wants to get the latest news on Ukraine. Open your favorite Twitter client, type "Ukraine" in the search box and tell me how long it will take this potential new user to become a tried-that-and-gave-up user. It's like telling someone to search on Google but that the useful link they want is somewhere on the first 25 pages.

This is the problem with Twitter as a news site: Too much noise, not enough signal. To see the signal, you have to already be following the account that is breaking the news. Otherwise, Twitter "breaks" a big story when the subjects of the story announce it on Twitter, or when a major news outlet picks it up. It's easier to just search "Ukraine" on the site or app of your favorite news organization.

Where Twitter excels is in letting users conveniently and constantly keep current on their interests, given enough time and enough existing insight into the topic to know who/what to follow. They're then rewarded with ongoing news, tidbits, insight and links, curated by the people at the core of their interests. And this leads us to the best way to describe Twitter.

Twitter gives you global, unfiltered, real-time access to anyone or anything you're interested in.

Your favorite author is Stephen King? Follow @StephenKing to get his thoughts on writing, politics and life. Love Formula1 but it's not covered well in your country? Follow @f1, @InsideFerrari or @LewisHamilton. Into celebrity gossip or tech news? Follow...just about everything on Twitter. No matter what your interest, Twitter gets you more intimate, more behind-the-scenes than any other medium. Even your mom can appreciate the value in that.

Twitter taps into the interest graph and the unsurpassed depth and breadth of curated content for all your interests is the most unique thing about the service, as well as the reason why its growth is limited. The fact is, very few people are so passionate about their interests that they will actively pursue pertinent content (essentially a corollary to the 90/9/1 principle). Getting Twitter to the point where you're following exactly the right people takes work. Once you've found the right accounts to follow, it's impossible to keep up unless being on Twitter is part of your job or you don't have a job. Most people just don't care enough to do it.

Your Twitter feed.

Your Twitter feed.

Your best friend may dream about classic cars, watching every hour of every Barrett-Jackson car auction, but he's not going to follow and keep up with @jayleno, @classiccars_com, @ClassicCarMotor, etc., let alone the accounts covering all his other interests.

Reading a Twitter feed is like riding a bullet train: You have a sense that interesting things are going by and every once in a while you catch a glimpse, but eventually you tire of the blur and nod off.

The reality is, Twitter will never be mainstream. And that's a shame.