Do More Faster

by Brad Feld

  At the same time, I spent time talking with Tom about what really drove him to start the company in the first place. He realized that he was motivated to help people find the right job direction and he thought temping was one way to do that. This was useful, but then I started to push him on why he was focused only on temping. Why not help people find the right direction in their career, however it takes shape? Tom got excited about this and began exploring changing the name of the company to GlideHire to expand its perspective beyond temping.

  At first this seemed exciting, but after a while, Tom came back and said, “Hey, it really is about temps—this is the thing I think will help the people I want as customers find the right direction. I’m going back to the TempMine name and the earlier plan.” For a little while, I felt bad that I had helped clarify things on the one hand while helping fuel a tangent on the other. Although it was only a detour of a week, that’s a lot in Techstars time.

  But then I realized that this is part of how Techstars works. The companies get connected with mentors who care and provide input. The input is diverse and will be conflicting. Even input from a trusted advisor will have elements that are not correct. The founders are quickly forced to realize that they cannot create a solution that incorporates all of the inputs they are getting. Their only hope is to listen to their head and their heart and follow a path that they believe in, keeping some of the feedback and discarding other thoughts and ideas.

  Is too much conflicting advice a bad thing? Nope. Having too much advice can teach you how to make better decisions, as long as you accept that conflicting information is a part of life. Remember that it’s just data.

  Saying “It’s just data” is one of the most common ways to end a mentor meeting at Techstars. We try hard to help mentors be as effective as possible, and one of the things that strong mentors, especially ones who are entrepreneurs, have to be careful of is not being too forceful with their advice. Experienced entrepreneurs usually believe they know the right answer and, while they often do, part of the magic of Techstars is helping the founders discover the right answer. As any successful entrepreneur knows, there are often multiple correct answers. As a mentor, being clear that you are only providing data and that it is ultimately up to the entrepreneur to make the decision is an important way to approach giving advice.

  Asking questions is a key method of getting “data.”

  Chapter 37

  Use Your Head, then Trust Your Gut

  Ryan McIntyre

  Ryan was a cofounder of Excite and is currently a partner at Foundry Group.

  You can’t manage what you don’t measure. I can’t overstate how important it is to have metrics on your business so that you can make intelligent decisions. Metrics are particularly important for companies that run their businesses on the Web and a mountain of otherwise unavailable data is there for the taking. Every single user interaction can be measured, categorized, and analyzed, providing tremendous value if you can properly interpret what you’re seeing.

  On the other hand, it’s incredibly difficult to start a company and create a product that never existed and try to sell it in a market segment that also never existed. And, unfortunately, there are often precious little data to go on in the earliest days of a company’s life. Even when data is available, it’s often confusing. To make matters worse, a company’s friends, mentors, advisors, and board members will give you conflicting advice. Market research and user focus groups can yield inconsistent data and lead to conclusions that are in opposition to one another.

  What is an early-stage founder to do? Let me offer two bits of conflicting advice (get used to that!). First, be suspicious of your data. Consider everything that you hear, measure, and learn to be anecdotal even if it is corroborated by several sources. Second, especially early on, remember to gather as much data as possible and measure every aspect of your business. If you don’t instill this discipline at the beginning, you’ll never catch up, and you’ll never have the right information to make the right decisions.

  Be prepared for the data to give you a head fake. Early success with a certain customer segment might lead to a decision to focus on a subgroup of customers that turns out to be really hard to sell to and that happens to represent only 4% of the overall customer base. Don’t be like the guy looking for his lost car keys late at night in the parking lot who is looking only underneath the lamppost because that is the only place he can see. Constantly revisit the data—measuring the wrong things can be worse than measuring nothing. For example, if you are running an ad-supported media site, a maniacal focus on increasing page views per user session might frustrate loyal users and could drastically reduce ad click-through rates, ultimately harming the business.

  Remember to think exponentially, especially in the world of technology. A few early data points on a geometric curve might lead you to conclude that you’re observing a linear phenomenon, which would lead to some seriously erroneous predictions about what points farther up the curve might look like. To paraphrase Ray Kurzweil, when presented with exponential growth, remember that people tend to drastically overestimate what will happen in the short term, but will profoundly underestimate what happens over longer time spans.

  It has been said that one measure of intelligence is the ability to hold contradictory thoughts in one’s mind simultaneously. Well, consider life as a founder of a startup to be one big intelligence test. In the end, you’ll need to get comfortable living with messy and incomplete data. Remember that living the startup life requires both art and science and is simultaneously qualitative and quantitative. Take all the inputs you can gather and then make the decisions that feel right to both your head and your gut.

  Isaac Saldana (right) of SendGrid chats with Natty Zola of Everlater (middle). Natty is now Managing Director of Techstars in Boulder and Isaac is a leader at Techstars Studio.

  Chapter 38

  Progress Equals Validated Learning

  Eric Ries

  Eric is the founder and CEO of Long-Term Stock Exchange. He previously was the cofounder and CTO of IMVU. Eric is also the creator of The Lean Startup methodology and the author of several books, including The Lean Startup and The Startup Way.

  I am an advocate of charging customers for your product from day one and I regularly counsel entrepreneurs to focus on revenue. Those who refuse to listen to my advice get themselves into trouble by running out of time—and money! But I now believe that revenue alone is not a sufficient goal for an early-stage startup and that focusing on it exclusively can lead to failure as surely as ignoring it altogether.

  The revenue problem brings up the following question. Would you rather have $30,000 or $1,000,000 in revenues for your startup? Sounds like a no-brainer, but I’d like to convince you that it’s not. To start convincing you, I want to share with you an example of two startups with vastly different revenues and different approaches to learning about customers.

  Consider Company A, with a million dollars of revenue and growth quarter after quarter. Despite those revenues and growth, their investors are frustrated because the metrics of success change at every board meeting. And the product definition fluctuates wildly—one month, it’s a dessert topping; the next, it’s a floor wax. Their product development team is hard at work on a next-generation product platform, designed to offer a new suite of products—but they’re way behind schedule. In fact, Company A hasn’t shipped any new products in months. Yet their numbers continue to grow, month after month. What’s going on?

  Company A has a product that is highly customized and, after great effort, one sale is made. The founders are exceptionally gifted—artists, even—at sales. They are able to hone in on the right key words, phrases, features, and benefits that will persuade another human being to give up their hard-earned money in exchange for even an early product. For a startup, having great sales DNA is a wonderful asset. But at the early stages, it can also devour the company’s future.

  There are problems in
selling each customer a customized one-time product. By learning about each customer in depth, the person who’s amazing at sales can convince each of them that this product would solve serious problems. That leads to cashing plenty of checks. The gifted salesperson can use his or her insight to understand what their customers really need to make the sale and then deliver something of even greater value. They’re closing orders. They’re gaining valuable customer data. They’re close to breakeven. What’s the problem with selling customized products that help customers solve a problem?

  The fundamental problem for Company A is that their business is nonscalable. Every sale requires handholding and personal attention from the founders. This process cannot be delegated because it’s impossible to explain to a normal person what’s involved in making the sale, as the customers prefer working with the founders. Although the founders have a lethal combination of insight about what potential customers want and in-depth knowledge about what their current product can really deliver, there’s only so much time in the day. As a result, potential customers are being turned away and the founders can only afford to engage with the customers who are best qualified and the current customers who they know well.

  Now, let’s look at Company B, with only $30,000 in revenue. Similar to Company A, Company B has a large, long-term vision, but their current product is only a fraction of what they hope to build. Despite the meager revenues, Company B is actually better positioned for future growth.

  Company B’s product is not sold in face-to-face intensive ways. Instead, each potential customer has to go through a self-serve process of signing up and paying money. Because Company B is unknown in the market, they have to find distribution channels to bring customers in. They can only afford channels, such as Google, that support buying in small volume.

  But because of the small volume, Company B is able to know each of their customers extremely well and they are able to experiment with new product features and product marketing to increase the yield on each new crop of customers they bring in. Company B has found a formula for acquiring, qualifying, and selling customers in the market segments they have targeted. Most importantly, they have lots of data about the unit economics of their business. They know how much it costs to bring in a customer and they know how much money they can expect to make on each new customer.

  In other words, Company B has learned how to acquire and keep customers, which allows them to scale; Company A knows its current customers. Given the data Company B has collected about early customers, they are also able to estimate, with modest precision, how big the market is for their product in its current form. They may be at microscale now, but because they know key metrics, they are in a very good position to raise venture money and engage in extremely rapid growth.

  Company A, our million-dollar startup, is limited by the founders themselves. Their future growth, despite the revenues, is not so bright.

  Examples like these have led me to this definition of progress for a startup: validated learning about customers. This unit of progress is valuable for every startup. First of all, it means that most aggregate measures of success, like total revenue, are not very useful. They don’t tell us the key things we need to know about the business: How profitable is it on a per-customer basis? What’s the total available market? What’s the return on investment on acquiring new customers? How do existing customers respond to our product over time?

  Validated learning about customers locates progress firmly in the heads of the people inside the company and not in any artifacts the company produces. That’s why none of the dollars, milestones, products, or code can count as progress. Given a choice between what a successful team has learned about key customer metrics and the source code they have produced, I would take validated learning every time.

  While the phrase “progress equals validated learning” might seem chewy and theoretical, it’s actually a brilliant combination of words. Fundamentally, all startups want to make progress. But as Eric points out, the measures of progress are often wrong and misleading, especially at the early stages. Using the filter of “validated learning” (namely— something that you’ve learned that you know is true) is a powerful frame of reference that forces more discipline into the discussion.

  We’ve gotten to know Eric well since the first edition of Do More Faster, and we think his work on the Lean Startup methodology is incredible. We’re also big supporters and super-excited about Long-Term Stock Exchange, as it has the potential to reward long-term investors and fix some of the more challenging aspects of the IPO market. We encourage all entrepreneurs to become disciples of Eric. .

  Eric Ries talks lean methodology with founders.

  Chapter 39

  The Plural of Anecdote Is Not Data

  Brad Feld

  Brad is a partner at Foundry Group and one of the cofounders of Techstars.

  A phrase that is often heard around Techstars is “the plural of anecdote is not data.” While the original attribution of this quote is murky, the meaning is powerful and applies to both mentors and entrepreneurs. Hearing anecdotes about your product or technology—even if you hear multiple anecdotes—is not as valuable as hard data.

  Anecdotes are tossed around Techstars by many of the mentors—and for good reason. The mentors are experienced entrepreneurs. They often have started multiple companies—some successful, some not—and they have a wide range of experiences. Through this experience, they’ve developed many stories and built anecdotes from them. These anecdotes are endearing, funny, clever, powerful, and repeated often, but if they are not put in their proper place in the information hierarchy, they can actually derail a young startup.

  While there is much for entrepreneurs to learn from storytelling and anecdotes, an inexperienced entrepreneur runs the risk of generalizing anecdotes into truths. During Techstars, entrepreneurs often get conflicting stories and advice from mentors. Mentor A believes that you should go after a specific vertical market as your market entry strategy and then explains how this worked for him in his first company. Mentor B, in a separate conversation, explains how a specific vertical market approach failed her in her first company and was a key contributor to its demise. She suggests starting out with a broadly horizontal platform approach instead, being careful to start picking off specific vertical markets as the customers start to emerge in bulk from them. In each case, they tell nice anecdotes that support their perspective.

  David’s mom, Ginger, gives him anecdotal advice.

  What should the entrepreneur do? We start by saying, “It’s only data,” meaning that the entrepreneur needs to synthesize the data—especially different perspectives—and form his own opinion about the correct course of action. If you take an additional step back from the problem, however, you realize that you can’t generate usable data from a single anecdote. An anecdote is just one point of data.

  One of our goals at Techstars is to surround first-time entrepreneurs with mentors who can flood them with stories, anecdotes, advice, and data. We view it as a huge advantage when there are enough of these pieces of information that they conflict with each other. This forces the entrepreneur to go deeper, think harder about what is going on, and apply it to his or her specific situation. If the entrepreneur relied on only one anecdote to form a point of view, she’d miss the variety of different circumstances that could affect her company.

  It’s often said that the information hierarchy starts with data, builds to information, and eventually peaks with knowledge. That’s true of the scientific method. Yet, in the entrepreneurial world, I’ve found that anecdotes come even before data. It is important to have a broad number of them before you start abstracting up to the data layer. Hence the phrase “The plural of anecdote is not data.”

  Chapter 40

  Don’t Suck at Email

  David Cohen

  David is a cofounder and the co-CEO of Techstars.

  During orientation each year, we implore the founders who are g
oing through Techstars not to suck at email. Sucking at email is a surefire way to get your mentors, potential investors, and customers to lose interest in you.

  There are many ways that new founders can suck at email, but there are a few common ones that can be corrected quickly. First, change your attitude. The most common excuse, “I get too much email,” is ridiculous. We all get a ton of email. I explain to the founders during orientation that it’s extremely unlikely that they get as many emails as I do. Reject and remove this excuse from your vocabulary, because email volume is no reason to suck at email. In fact, entrepreneurs should want even more email, especially from their customers.

  If you accept the notion that “you can’t get too much email,” you’ll then need a system for dealing with it. We recommend something similar to the Getting Things Done (GTD) system by David Allen, which includes tactics such as “inbox zero.” Your goal should be to touch every email only once and either respond to it immediately or put it on a to-do list with a due date to be dealt with later. Then, delete the item from your inbox. Do not use your inbox as your to-do list—this is a guaranteed path to email misery. This simple solution will keep most people from sucking at email. If your inbox has 2,000, or even 200, new messages in it right now, you probably suck at email.

  Second, nothing makes you look worse than a delayed response or no response at all. Taking weeks to respond to email or not responding at all are also terrific ways to suck at email. As a general rule, you should try to delete or respond to email within a day or two. If you are on vacation or out of pocket, set up an auto-responder so that people know what’s going on. If you don’t know how to answer an email, reply quickly and say that you’re going to think about it (and set up a to-do item).