1/17/14

Time To Build 2014

Last year I wrote a new years resolution poem for 2013 that applied to a lot of things in life but each line was specific to lessons I learned the previous year and my professional goals for the next. I’m really bad at poetry but I’m going to take a shot at doing it again for my 2014 new years resolution post.


Once questions of “what if” turn into answers of “that’s it”;


Once research turns into discovery;


Once "a few" turns into team and artillery;


Once it is time to do what we do;


To put in the work;

To focus on the problem;


To create delight with what we’ve learned;


To surround ourselves with those who know;


To build onto a team that syncs as they row;

To put in the hard work;

To focus is what makes us grow;

11/5/13

The Future Of QuantifiedSelf

I have been working on passive and non-passive mobile tracking for the majority of my career. Up until this point, I have always felt that the majority of all tracking solutions have been nothing more than a stopgap before the hardware in smartphones could actually handle passive tracking in terms of battery life and data bandwidth. Navigation, local discovery, fitness tracking, retail, task crowdsourcing, and social networking are all going to be drastically changed by passive tracking capabilities being added to the core of smartphones.


Many of these industries have already been disrupted by non-passive tracking. I’m defining non-passive tracking as any solution that requires the user to take action and initiate tracking at the moment they need utility from the tracking app. The current fitness activity tracking apps are a great example of this. Before going for a run, you need to launch the app and click start to initiate the tracking.


What seems like a minor action by the user actually has much larger implications in creating additional user value. During the day you may quickly decides to take the stairs over the elevator, or walk a half mile to a new lunch spot. Those actions may not be recorded by the user and thus never tracked. This seemingly simple aspect of activity tracking has created a huge opportunity for independent passive tracking devices such as Fitbit, Jawbone Up, and others companies who focus purely on building separate passive fitness tracking devices that can handle the battery life that smartphones historically cannot. It is an important distinction as this industry battles to innovate and provide the most value to their users.


Chart provided by Google Trends. Innovation is the only way to stay ahead.

When smartphone’s can passively track, things are going to change. The launch of Google’s new Location APIs and Apple’s CoreMotion API allow these devices to passively track users’ location and activities without a lot of battery drain. You soon won’t need a separate passive tracking device to track your fitness activities as the smartphone you already own can now provide this feature.


The iPhone and Android platforms are extending their core capabilities. Each of the API’s documentation clearly use activity recognition and tracking as examples of their core capabilities.
The activity recognition service is a low power mechanism that allows application to receive periodic updates of detected user activities. For example, it can detect if the user is currently on foot, in a car, on a bicycle or still.


Being dependant on a platform, as all apps are, requires them to always be adding value on the fringe of these platforms. There is no value in duplicating the platform’s core functionality. But where does the Smartphone’s activity tracking capabilities end and where can apps innovate?


Big Data And Healthcare
If activity tracking is being done by the smartphone platforms, the current tracking apps can add value by extracting specific insight from the data collected. General insight from the data will surely be done by the platforms themselves but being able to take a deeper more specific dive for specific areas will be a great opportunity.


IBM recently just won a grant to use big data to predict heart disease long before it strikes. This type of innovation will need to be down for all types on health risks using all types of data. This research should provide the industry with greater insight into which patterns in health increase risks but consumers will need to have access to this information directly. It cannot be offloaded to the already overburdened healthcare system.


Startups like Ginger.io are doing a nice job combining health data-mining algorithms developed at research institutes and bring those capabilities directly to consumers. The app passively collects information on users and then uses that data combined with other collected health information to provide insight directly to consumer. It looks like they are also experimenting with partnerships with physicians and other medical professionals as well. As collecting health data becomes easier and easier to do, companies such as Ginger.io are on the cutting edge of innovation in this space. I just hope they can find the distribution they need to grow.



Health Coaching - CVS Minute Clinics
Another innovation in quantified self will be the use of health coaches. A combination between physical trainer, nurse, social worker, and pharmacist will become big business in the next 5 to 10 years. The world isn’t producing enough doctors to handle the world’s population and many of the tasks that a doctor performs on a day-to-day business include task that they are purely overqualified for. In fact, most manageable health conditions would be best treated on a low touch but more frequent and even day-to-day oversight by a low cost, non-doctor “health coaches” rather than by expensive monthly doctor office visits. These low touch health coach visits can be done virtually online or at local non-medical clinics. CVS minute clinics and other more retail-like clinics can also take on these day-to-day health coaching.



Summary

These industries are about to grow up a lot. The real value that will come from passive tracking will be world changing and disrupt many industries. Platforms are growing their core footprint and the ecosystem around them will be forced to innovate deeper into their perspective industries. Adapt or be acquired because new players will emerge and existing ones may quickly fade away.

9/16/13

Idea Vs Execution - What Is A Startup's Idea Vs Its Execution?


In the startup world, we hear the word “execution” mentioned a lot. “Lots of startups have great ideas, but the only ones that will be successful are the ones who can execute.”, “Can this job candidate execute?”, “Startups are all about execution!” But what does any of this really mean?


There are many articles on the web that go into great detail on how to A/B test landing pages, how to hire the best team, or how to acquire users, and each give great insight into these tasks. None of this actually explains what it means to execute because execution is not merely the collection of all these tasks. If a startup’s execution is viewed as such, there won’t be much focus and the team will easily become distracted.


The Big Risk - What Really Is The Startup’s Idea?
First we must understand that execution is separate from the startup’s “idea” - this is assuming the startup has figured out what it is actually doing. To get to the core of what a company’s idea really is, lets refer to what the investors at Sequoia Capital, refers to as the “Why now” question they ask each startup.
From PandoDaily:
YouTube’s “why now?”
bandwidth costs are plummeted, video cameras stated recording to digital files, and these new smartphones were coming online with – wait for it – built-in cameras AND an Internet connection.
Uber’s “Why now?”
smartphone ubiquity, GPS accuracy, and mobile app reliability. (The first generation of “apps” on platforms like Blackberry and Palm were just not stable and fast enough to do what Uber does).
Twitter’s “Why now?”
everyone had read a blog at MoveableType. WordPress, or Blogger, and they wanted to get involved in self publishing – but writing a blog post was too much of a commitment. Writing a headline to a blog (140 characters)?
Dropbox’s “Why now?”
cheap, on-demand storage and the faster, cheaper, and more reliable broadband in homes and offices.
The “why now” question for these companies all seem like very low risk assumption when you look at the world today, but at the time these companies were just getting started, these were really big risky assumptions. What if bandwidth costs didn’t plummet? YouTube surely wouldn’t have been a success. What if Uber’s apps weren’t reliable; the GPS was lousy or smartphones didn’t become all that popular? Uber would have failed. If people didn’t want a 140 character blogging platform, would anybody have used twitter? Or, if on-demand storage stayed expensive and slow, surely Dropbox wouldn’t have become popular. These companies needed their big risky assumption to come true in order to gain market share from existing players. There needs to be some giant change in the market that will allow the startup to gain an advantage.  This is why I argue that the core of every good startup idea is one big risky assumption or their one big risk

You Can’t Control Your One Big Risk
Large companies are also based on similar assumptions, but their assumptions, for the most part, are already proven to be true and the bet is that they will continue to be true. Established companies look to diversify against all risks and assumptions in order to continue their growth. Startups cannot do this. Startup must focus, as they don’t have the resources to diversify. If you do somehow diversify against your one big risk, then the startup’s upside will be drastically reduced and you won’t be large enough to compete with the incumbents. This means that your startup can’t do anything about its biggest risk. That one big risk to your startup cannot be controlled, managed, or reduced by the startup team. It set by the core “idea” behind the company and is controlled by market forces that are much larger than your small startup can handle. This means that once you identify your one big risk, execution must be everything else.

Execution And The Other Risks
Being able to identify your one big risk doesn’t mean your company only has that one risk. There are a lot of risks your company will face. For example, Uber faces legislation risk as existing taxi services work to ban Uber in each major city. Twitter faced risks from Facebook and other competing platforms that wished to beat Twitter to the punch. This is where execution comes into play. As the startup waits for their one big risky assumption to play out, the job of the company is to position itself to be the winner if the assumption turns out to be true. If it comes true and they are well positioned to take advantage of that outcome and the reward will be great. Thus, execution is simply the reduction of all of all other risks to the company that may prevent it from from gaining this positioning.

Execution And Focus
Now that we have defined execution, it should be clearer for a company to determine which tasks it should be focused on. Leadership at the startup should be focused on identifying and prioritizing each of these “other risks” to the company and building the proper team to tackle each effort to reduce these risks. Leadership can use Porters Five Forces and other strategy frameworks to help identify and prioritize these risk.

Any and all tasks being performed by the startup must ONLY be designed to reduce these risks. Everything else being done at a startup should be considered a distraction. Every project, every feature, every promotion, every sales call, every meeting needs to be focused on reducing these risks. If an effort cannot be directly measured to the reduction of one of these other risks, then that effort is utilizing resources and time that could be used to reduce those risks. If a decision is being made at the company, the only deciding factor should be if the outcome will reduce one or more of these risks.

Communicating These Risks To The Team
It is also very important to communicate these risks to the team. These risks are constantly changing, and a constant communication to everyone in the organization is required. It is easy in a fast moving startup to forget that your analysis and understanding of each of these risks are also understood by each player on the team. As the team focuses on their tasks, you must take time to recalibrate everyone on the risks the company faces and how well you are doing at reducing these risks. By defining execution this way and keeping everyone in the loop, employees will have a better understanding and direction for their own efforts. They will be less likely to become distracted with tasks and challenges that will not directly reduce these risks. They will also be able to measure how their tasks directly reduce these risks and thus get a great satisfaction from knowing how they are directly affecting the company’s success.
Separating a startups “idea” from its “execution” is critical to its success. If the one risky assumption behind the startup’s “idea” turns out not to be true, then the best executing team will never be successful. That is just how it is. Also, if the startup’s “idea” is a good one - the one risky assumption turns out to be true - but other risks are not dealt with in time, the startup will also never be successful as they couldn’t execute. That is why startups are so risky. However, if the idea is a good one and the team can execute, the startup will succeed.

9/11/13

Defining "Active User" And The DAU To MAU Ratio



Daily Active Users (DAU) to Monthly Active Users (MAU) ratio is a popular metric many consumer startups are being judged by. The ratio is used to find out how many of your active users are logging in on a daily basis. This metric is very important when determining how “sticky” your product is. In other words, it is a way to measure your product's retention. The first I heard of this metric being used was to determine which Facebook games were going to become the next Farmville. The question is, does this metric really work for non-gaming apps and websites?


Is DAU To MAU Ratio An Unfair Metric?

The issue I had when this metric first became popular was when it started to be used to measure the success of all consumer apps and websites. At first it seemed unfair to use a metric used for casual gaming on many apps that, by nature, can’t possibly be used on a daily basis. For example a travel website or an app used for car buyers certainly shouldn’t be judged by this metric, right? People don’t book hotel reservations or make car purchases everyday so how can this metric be used for these types of services? These products’ users naturally only use the product at rare events compared to a messaging app or a Facebook game. It surely isn’t fair, right? Not true! I argue that this ratio is actually still very relevant to these types of services. The only difference is how these types of businesses define their “active” users in reference to this ratio.


User’s Attention Span
The real core to the DAU to MAU ratio is based in the fact that people forget. People live busy lives and are bombarded with thousands and thousands of products and services. When that special time comes up to purchase a car or to book a travel reservation, will they think of your product? Will they remember that this is that special time when they need to search for your app, launch it, remember their login information, and fiddle with your UI? If you aren’t top of mind, they won’t. Instead they’ll use a competing solution and you are out of luck.

Staying Top Of Mind
By keeping users “active” you are keeping your product top of mind. The traditional definition of “active” is when a user logs into your product. But in reality, being top of mind doesn’t require a user to have to log into your app everyday. There are other ways to do this. In the car purchase or travel examples, you’ll notice that both are the type of services you would expect to see constantly advertising on TV and radio. In most metropolitan areas, the local car dealers are constantly fighting for TV and radio spots. You hear their ads multiple times a day.

Defining Active
Car dealers use these advertisements to stay top of mind for that one moment a person decides to make a car purchase. Their “active” users are those who view or listen to their daily ads.  They might not be logging in to an app or website everyday, but these people are still engaged with the service. They laugh at the salesy pitch lines or hum the commercial tunes. Whatever it takes, these people are actively keeping the service top of mind. If you could effectively measure the reach of these ads and define “active” as those people who are listening or viewing these ads, the DAU to MAU ratio would probably still hold up as an important metric.

Bringing This Back To Social Apps
My point in using the car dealership example is that your “Active” users might not just be those who log into your app. Your product should have a reach that keeps you top of mind on the days they aren’t logged into your product. At RunKeeper we were constantly aware of this. We initially defined our “active” user as someone who used our product to track a run, walk, or a cycling activity. The pure nature of health and fitness is one where people are sporadic with their fitness activities. While most apps worry about the number of clicks their users need to make, we were asking our users to get out and go for a run. Seriously! Think about that for a second. Suddenly the number of clicks on your app doesn’t seem like a point of user friction anymore does it? The challenge here was to get users to be more active but also to keep our product top of mind. We didn’t have the huge margins a car deal has to spend millions on ads so we needed to be creative.

Social Reminders And The Network Effects
A common solution to this problem is to highlight your friends usage on other social media platforms. If you aren’t running today, one of your friends might be. As your service grows, more and more of your user’s friends might be using the product on any given day. Use this as a means to stay top of mind. Posts to Facebook, push alerts, and other ways to remind your inactive users that your product can be used by their friends can help. Don’t be SPAMMY! These can’t be artificial, noisy posts, it needs to be a genuine share from your active users. This is tough but it can be done effectively and there are ways to measure this type of reach. I might not care about every run my friend goes on, but when he has a personal record, sets a new health goal, or finishes a race, I might actually enjoy those posts.

You can measure the effectiveness of these reminders too. Facebook Insights provides these types of stats and many email providers also give open rates and other types of ways to measure your marketing reach. If you can integrate this number into your definition of “active” for the DAU to MAU ratio will become more relivate.

Expanding The Scope Of Your Product
The other way to keep your users “active” is to expand the scope of your product. At RunKeeper we expanded the scope of our product to include more and more aspects of a user’s health that happened outside of the running activity. Researching training programs, monitoring their health trends with FitnessReports, FitnessAlerts, helping each other stay motivated with social encouragement via the FitnessFeed, and even an attempted means to allow users to share health and fitness content were used to keep users active. Long live the healthy button! I kid, it failed :) This can be a tricky area for a startup. You need to stay focused and not try to be too many things to your users, so tread carefully here. Each new feature you add may take away from your core offering, but if done right, you can create a much more robust and engaging experience around your core offering that keeps your users “active” each day.

Summary
The DAU to MAU ratio is a very powerful metric that every consumer company needs to track. Defining the “active” user is really the key to using it effectively. Logging in to your product is a great indicator of which users are engaged but it isn’t the only measure. Stay flexible with the definition of “active” and experiment with the scope of your product to really make the DAU to MAU ratio work for your product.


8/12/13

Solving Your Product's Retention Issues - How we did this in the early days of RunKeeper


Distribution and retention are two separate problems startups need to solve.  Scaling your distribution channels requires you to know why people are coming to your product. Growing your active user base requires you to know why users are coming back for more.  But do not confuse the two. Rarely do users stick around for the same reason they came in the first place.


Finding product distribution is always your number one problem but the retention problem can be even more challenging as you can’t simply use a canned Google analytics report to answer why users are sticking around.


Facebook & Twitter
During trips to Silicon Valley, I got to learn from Facebook and Twitter veterans who shared their stories on how they solved their respective retention problems. In the early days of Facebook, users signed up after receiving email after email from their friends who were already on the site.  But, according to the early Facebook employees I’ve spoke with, they discovered that users would stick around after seeing photos of their friends ..actually, off the record I was told it was photos of their attractive friends (although I don’t know how they figured that out).  Similarly at Twitter, users came to see why everyone was talking about this new thing called “Twitter”, but the average user would only return once they followed a celebrity who filled their feed with insight into the lives of the famous.  



RunKeeper

Adding to the lessons learned from Facebook and Twitter, I think it might also be helpful to know how we went about solving the same retention problem in the early days of RunKeeper. At RunKeeper, we knew people were signing up because our app was a low cost (free) alternative to expensive GPS watches ($0 < $200).  Users saw their friends posting individual running activities and a map of the route to Facebook and decided to download the app to give it a try.  We knew this very early on, but we didn’t know, for quite some time, why they stayed.


Finding out why they stayed was a long process that took years to figure out. You see, we never successfully built a large analytics platform at RunKeeper for the first 4 years I was there. We could track our incoming channels thanks to a tool built by an intern one summer, but not until around the time I left the company did they ever have the ability to truly dive into the analytics behind user behavior.


Instead, we built new features based on listening to user feedback and watching which features seemed to be popular on competing products. By doing so, we built a race platform, a training program platform, and a suite of social networking features. We then listened to user feedback and watched our database to see which of these features were being used the most.  The race platform was hugely successful but people only used it to declare which races they were training for. Other features of the race platform, such as spectators watching the races live, were barely touched.  The training programs (then called "FitnessClasses" at the time) were not very popular except for the losing weight program.


From this, it became our suspicion that people were continuing to use RunKeeper to achieve a goal such as running a race or to lose weight. They came to RunKeeper to track an individual fitness activity, but may have been sticking around because we were helping them progress towards their personal fitness goal. Seems obvious now, but not obvious at the time.


Taking Twitter’s lead of placing the “pick a celebrity to follow” walkthough at time of sign ups, we decided to investigate placing a “pick your goal” walkthough right after sign up as well.  This feature was launched after I left RunKeeper but is the main focus of the product today.


Retention is a hard nut to crack.  It takes time, patience, and the ability to really listen to why your active users are using the product. You can only try to solve this problem once you have started to solve your distribution problem, but once you do, you’ll really have a great product that will be used and loved by a large active user base.

8/5/13

The Market Pivot


There is a lot of talk about startups needing to find product/market fit lately. As defined by Marc Andreessen “Product/market fit means being in a good market with a product that can satisfy that market.” The problem is, you don’t know if you truly have product/market fit until you find distribution channels and start to scale and experience growth large enough to validate that you have both product and market fit.

Most of the startup advice these days seems to be on the the product side of the product/market fit equation. “Finding the wow factor”, the whole “is your product medicine or vitamins” arguments, and A/B testing strategies has been about product.  But there isn’t much talk about the “good market” side of the equation. Product isn’t enough, you still need to validate the “good market” side of things as well.  The challenge here is that for many truly disruptive innovations, this is the part that takes time to prove.

You might find product/small market fit in where you validate a product is useful for a small group of customers, but how do you know if the market is a “good market”. Many marketing people would interrupt me at this point and start talking about market research methods that can analyse the size of a market. I agree with many of these methods, but for truly disruptive products, there isn’t enough data to truly prove the market size. In fact, there might not be a market there at all yet.

For example, in the early days of RunKeeper, we were told many times that the market we were building our product for was too small.  “Who wants to run with their phone?” “the largest exist in health and fitness isn’t even over $30m.” are typical responses we got.  It wasn’t until the company started to scale toward 10 million users (now approaching 25 million users) that a market was validated.  Before this point, we were nailing product, but market was yet to be validated past our personal beliefs.

The time it takes to validate a "good" market is why you see medium size companies “pivot” even though they have already seen some level of success. Recent examples of these types of pivots are Fab’s recent pivot away from flash sales. They had 12 million users and $200,000 a day in sales and yet, the company has pivoted.

There was a sizable market for Fab before the pivot, but it was not a “good” market by their standards. Fab.com and the flash sale market was a product/almost-market fit. The interesting thing is, this pivot doesn’t change the product all that much.  If you have used their product recently, you’ll notice only slight variations with the product. The major shift is in their messaging that targets what they now believe is a “good market” for their product.

Foursquare is also in this camp. Foursquare is now focusing more on the local discovery aspects of their product over the famous “check in”. Discovery has been a part of their product since day one, but they are now focusing more on this part of the product. The check-in side of the market exists and even fuels their discovery functionality, but it seems they now feel that the “good” market is in venue discovery. Same basic product, but different market focus.

Startups take time to unfold and execution is key if you are to truly find product/market fit and experience true success for your company. The startup world is doing a great job at educating startups on how to quickly build a great product, but we can’t forget that finding the “good market” side of the equation takes time to validate.

7/31/13

Startup Catalysts & Distribution


As a startup, the number one challenge you have is getting distribution. You’ll need customers and a growing supply of them. The problem is that every other company in the world also has that same challenge.  There aren’t a whole lot of distribution channels out there, so the best channels are very crowded and expensive to use effectively.  If you have magic growth hacking powers, you can cast your marketing hacking spells on the usual existing channels and make it work for you.  But most likely, this won’t work.  Instead, I advise many founders to look for startup catalysts.

In 2009, there were full page New York Times and WSJ ads taken out that featured RunKeeper.  We didn’t pay for these.  We didn’t even know the ads were going to happen until they were printed. Apple’s app store was new and Apple needed to market their new platform by highlighting the apps that were on their platform. It didn’t stop there either. Icons on the doors to Apple stores, and countless press articles about these new shiny apps.  The same happened with Google’s App market, Twitter’s API launch, Foursquare’s API, Facebook Open Graph launch, etc, etc, etc.  We hit every single one of them.

These opportunities are startup catalysts.  You need them, you should always be looking for them, and you should be preparing for them ahead of time.  They don’t last long, so you need to be ready and jump when they occur.  Fight the urge that tells you that a new popular platform’s API will make you “just an app” on their platform because being called “just an app” that isn’t your number one challenge.  Getting distribution is your number one challenge.