Passing the Torch: The Most Important Video for Incoming MBAs (and Everyone Else, too)

When I began my MBA, I watched this 1998 talk given by Warren Buffett to the students of the University of Florida. It was a guiding light. Now, I’m passing the video onto my wife Hannah, who begins her MBA career the week after next at MIT Sloan.

The speech touches on a number of points, and I’ve done my best to annotate, but the highlights for an incoming MBA student are:

  • The MBA Game (Part 1, starting at 2:20)  – you are given the chance to invest 10% into one classmate. Which classmate are you going to pick, the one with highest IQ or best grades? No, you’re going to pick “the one you responded to best. The one that has the leadership qualities, the one that can get other people to carry out their interests. That is the person who is generous and honest and gives credit to other people for their own ideas.” Which classmate will you sell short?
  • Do what you love (Part 2, 9:00) Taking a job because it looks good on your resume is like “saving sex for old age.”
  • Remember how lucky you are (Part 10, 3:00) Let’s assume there are 6 billion people on earth. You are given the chance to exchange your life for the chance at 100 other lives. Would you do it?
PART 1 – Intro and the MBA Game
2:20 – The MBA Game – Which classmate will you invest in?
7:12 – Investing in Japan
8:25 – Cigar butt approach to investing, i.e. buying stocks valued below working capital
PART 2 – Wealth, leverage, and taking a job you love
0:10 – Long-Term Capital Management – Berkshire’s bid for the imploding hedge fund
4:30 – On the founder’s of LTM: “To make the money they did not have and did not need, they risked what they did have and did need. That is foolish.”
4:44 – “If you risk something that is important to you for something that is unimportant to you, it just does not make any sense.”
5:37 – On leverage – small upside, big downside
6:55 – “Betas don’t tell you a damn thing about the risk of stock”
9:18 – “Work in jobs you love. You’re out of you mind if you keep taking jobs you don’t like because you think they look good on your resume.”
9:50 – “Taking a job you don’t like is like saving sex for old age.”
PART 3 – The Moat
0:30 – Landing the job with Benjamin Graham; “I kept pestering him. I kept writing him and giving him ideas.”
2:00 – “I like businesses I understand.”
2:39 – “I want a business with a moat around. I want a very valuable castle in the middle. And I want the Duke in charge of the castle to be honest and hardworking and able.”
4:15 – Kodak and how they lost “share of mind” to Fuji
5:15 – “I’ve got one message to the managers: Widen the moat.”
7:00 – “I don’t want to buy any stock that if they close the NY Stock Exchange tomorrow for five years I won’t be happy owning it.”
7:25 – “You’re not buying a stock; you’re buying a part ownership in a business.”
7:56 – Buffett buys his first stock at 11 years old.
PART 4 – See’s, Disney and Coke: Building and Protecting The Moat
0:49 – See’s Candies purchase
3:45 – Disney
5:10 – Coca-Cola
PART 5 – Qualitative Analysis?
1:00 – “Almost every business we bought has taken 5 or 10 minutes, in terms of [quantitative] analysis…if you don’t know enough to know about the business instantly, you won’t know enough in a month or two months.”
2:10 – Circle of competence
3:10 – The Silver Bullet question – To find the best company in a market, ask all the players which competitor they would eliminate if they had the chance.
4:00 – HH Brown acquisition
4:45 – Asian Crisis & Coca-Cola
PART 6 – Mistakes: Warren is an “airoholic”
0:24 – Coca-Cola IPO; if you bought 1 share and reinvested the dividends, it would be worth about $5M now.
2:40 – Mistakes – “The biggest mistakes have not been mistakes of commission, they’ve been mistakes of omission: where we knew enough about the business to do something, but for one reason or another we sat there sucking our thumbs.”
3:20 – Fannie Mae
3:30 – Investing in airlines
4:20 – Solomon Brothers
4:35 – “One form of mistake is buying because you like the terms [of the security], when you don’t like the business that well.”
5:28 – “Never look back…you can only live life forward.”
6:55 – Macro factors – “Figure out what is important and knowable. Macro is important, but it is not knowable….We have never bought a business or not bought a business because of any macro feeling of any kind.”
PART 7- The value of NOT being on Wall Street
0:10 – Benefit of being an out-of-towner v. on Wall Street
1:00 – “Get one good idea a year, and then ride it to its full potential…and that is very hard to do in an environment where people are shouting prices back and forth every five minutes.”
1:30 – Stock brokers
3:00 – Berkshire dividend? No chance.
4:10 – Berkshire HQ: 12 people, 3500 sq. ft.
6:35 – “We never buy something with a price target in mind.”
8:08 – Arbitrage
PART 8 – Diversification
0:30 – Coco bean arbitrage
1:15 – Diversification: “If you are not a professional investor, than I believe in extreme diversification [and no trading].” In other words, buy and hold index funds. “Once you’re in the business of evaluating business, then diversification is a terrible mistake. If you really know businesses, than you probably should not own more than six of them.”
3:20 – Procter & Gamble
5:00 – McDonald’s
6:10 – Gillette
7:30 – Utilities
PART 9 – Large Caps and REITS
0:10 – Large caps
2:30 – Real Estate Investment Trusts – If you have a large amount of capital, REITs are not attractive.
4:30 – Texas Pacific Land Trust
PART 10 -You’re extremely lucky
0:00 – Down markets? “I prefer the market going down.”
0:55 – Net buyers should want the price of stocks to go down.
1:45 – Chapter 8 and Chapter 20 in Graham’s Intelligent Investor: “the two most important essays ever written on investing.”
3:00 – “The Ovarian Lottery.” Warren advocates for a John Rawls / Theory of Justice approach to social issues.
6:00 – If you could put your ball back (i.e. life), would you do it in exchange for 100 balls? You’re in the luckiest 1% of the world.
7:20 – Only work with people you like.

Thoughts from GigaOm’s Structure:Data Conference

The following article was first published in the MIT Entrepreneurship Review on April 1, 2012.

Economic expansion works like this: One trigger innovation spawns a number of supporting industries. The automobile, for example, brought us service stations, fast food chains, asphalt and suburban homes. Steel is another great example; the sturdy and affordable metal birthed the age of modern infrastructure.

Today, the world of web and mobile services has spawned a new and booming industry. The industry is called “Big Data,” and last week the key players got together in New York City at the GigaOM Structure:Data Conference.

Big Data is the result of the Internet and the decline in the cost of storage. To illustrate, just think about how much data you created and stored today. If you’re like me, you shot off a few emails, liked a Facebook comment, retweeted a Tweet and searched around for cheap plane tickets — then ate breakfast. And this is only a sliver of my day’s data history. Swiping my debit card, getting surveillance-video taped on the subway platform and key-carding into my office created additional data points.

In short, society is creating an exponential amount of data; 1,750 exabytes in 2011, according to the Economist. The most referenced fact at the conference was that more data was created in the last two years than in all of history. And it isn’t slowing down. The growth of the Internet and the increased adoption of sensors in everything from cars to microwaves will create ever-growing amounts of data. Data is “constant and relentless,” said Comscore CTO Mike Brown.

The Business of Big Data
Big Data is the business of making sense of these disparate data points. The first and most obvious use is commercial, more specifically marketing. Nirvana in the ad world is tying your likes, tweets, check-ins, credit card transactions, and even your eye patterns when you look at a billboard to deliver the most relevant advertisement or product recommendation.

Big data goes well beyond commercial use, though. Epidemiology and Big Data are a natural fit. Disease-chasers can identify pockets of illness by tying together Facebook comments, Google searches for doctors, phone calls to doctors offices, and retail store transactions for cough syrup. And of course security is big on Big Data. The conference hosted James Woolsey, the former CIA director, who spoke about using Big Data to identify security threats to the US electric grid.

Key Trends: Real-time analytics and democratization of Big Data
There were two main themes from the conference. The first is the quest for real-time analytics. For the most part, analysis of Big Data is done in batches. Take a large retailer, for example. It may update its  predictive models with end-of-day or maybe even end-of-month SKU data. Batch updating is adequate at best, since a lot can change in a week’s time. Thus, all of the vendors at the conference pitched existing or soon-to-be-released products that enabled real-time predictive analytics. That means that once you scan that carton of milk and pack of razor blades the store’s model is updated and refined.

The second trend is the democratization of Big Data. For the last several years, Big Data has been a luxury only the top technology firms could afford. If you weren’t Google or Facebook or Amazon you simply could not attract and retain the world’s top data scientists. That is changing, though, thanks to vendors offering out-of-the-box Big Data solutions. Skytree, for example, has brought to market a solution that enables companies that aren’t tech-centric to tap into their data. Skytree sits between the data, which can be stored in a relational database or a Hadoop cluster, and a front-end product like R or Matlab. Essentially, Skytree pulls in the data, looks for patterns and insight, and then pushes the data to front-end tool that most analysts are familiar with. In the coming months, the company will be releasing real-time capabilities.

What’s Next?
Big Data is slowly seeping into the mainstream conversation. Sometimes it creates outcries; for example,  The NY Times Magazine story about Target using customer data to identify pregnant woman in order to send them coupons when their “brand loyalties are up for grabs.” Other times, Big Data has been rejoiced. CellTel from Africa, for example, predicted the location of massacres in the Congo based on pre-paid phone card sales. And now the US government is fully supporting Big Data. On March 29th, theWhite House announced $200 million of funding to “greatly improve the tools and techniques needed to access, organize, and glean discoveries from huge volumes of digital data.”

In short, Big Data is a great opportunity. From a societal perspective, I’m reminded of the Saturday morning NBC public service announcement: The More You Know. We have all of this data. Now we just need to extract insights from it. From a business perspective, Big Data is booming. The culmination of ever expanding data points and practical analysis of that data equates to billions of dollars of value created for business, governments and people.

Nix the NDA. Ask for a PDA.

Over the last few months, I’ve met with dozens of people trying to get an idea off the ground. A few of them have asked me to sign a non-disclosure agreement (NDA). At first, I begrudgingly inked the boilerplate document. I felt it was easier to acquiesce than to kick-off a relationship with a conflict. But no more. NDA’s are bad for early-stage companies. In fact, founders should ask people to sign Please Disclose Agreements (PDA).

First, asking for an NDA to protect an idea signals that you think ideas matter. Ideas are the starting point.  But ideas, in the end, are worth little. Everybody has ideas. I have at least 10 one-pagers in my Google Doc account. To prove the value of ideas, I will disclose one of my favorites from my one-pager archive:

InteractiveBumper (IB) aims to deliver targeted ads to one of the last remaining captive audiences: the person(s) behind you in traffic. In short, IB will deliver geo-targeted ads onto a screen located on the rear bumper of cars. For example, a car equipped with an Interactive Bumper is idling in traffic one mile before the entrance to a Wal-Mart. Wal-Mart, a customer of IB, has bought this “spot” so delivers to the back bumper a promotion for the upcoming store. The cars behind the IB, as well as the cars to right and left, will have ample time to register the message and decide to stop in at Wal-mart or not.

Any takers? It’s all yours. Reach out if you want more thoughts on the idea.

In short, I’m disclosing InteractiveBumper because execution – not ideas – matters. Forming a team, building a prototype and convincing initial customers to test and then buy the product are what matters.

Of course, if you’re past the idea stage and have compelling IP, than by all means request an NDA.

Second, and most importantly, people in the start-up community want to help. There may be a few cheats, but the odds are several magnitudes greater that you’re sitting across from an ally. The people you meet will think about your idea and give you feedback. And even better, they’ll look into their network and connect you with relevant people like future employees or potential customers. If you silence these allies with an NDA, they can’t do what they do best: help you push your idea forward.

So nix the NDA and instead bind people to disclose your idea. The more you do this, the more allies you’ll gain, and the more feedback and connections you’ll make.

“Finance-ability” Frameworks for Venture Deals

Several years ago, I negotiated my first term sheet with an angel investor. At the time, I was raising money for a company I founded with Brent Ridge — yes, the same Brent from “The Fabulous Beekman Boys”. We were fresh-faced students and first-time entrepreneurs negotiating with a first-time angel. Neither of us knew what we were doing, so the negotiation devolved into who could swing the biggest one. No shocker here: the deal fell through and our company was not funded.

During the negotiation, I remember thinking, “Why isn’t there a framework to at least start the conversation about the deal terms?” Anything was better than just throwing outrageous numbers on the wall to see what stuck.

Well, after years of experience and studying, I have learned that there is a framework for evaluating early stage deals – in fact, there are two. I have built models for both frameworks and made them available as a Google Template; also available at the bottom of this post. If you’re an early stage investor, these models will help you evaluate deals. And if you’re an entrepreneur, they will help you understand how investors should be thinking about your opportunity.

As you use these tools, please remember they are not valuating your company. Rather, these frameworks evaluate the deal. In industry-speak, the tools test “finance-ability”

And one last thing: Please note, only change the YELLOW cells.

The VC Method
The first framework is called The VC Method, which is well documented by Andrew Metrick and Ayako Yasuda. The VC Method compares the present value (PV) of a future exit with the current investment. If the PV of an exit is greater than the current investment, than invest. If it is smaller, than walk away.

Let’s look at an example. The deal on the table is as follows: $250,000 for 33% of the company. Ok, that is pretty straightforward. Now, put on your thinking caps. To understand the PV of an exit we need to know (i) the potential size of an exit, (ii) the probability chance of the exit occurring, (iii) the number of years until said exit, (iv) how much dilution will occur between today and the exit and, finally, (v) the VC cost of capital. Ok, that is a lot. Where to begin?

Exit size is obviously the biggest “what-if.” Could you have called $23B for a search engine in 1998? Probably not. So pick a reasonable number based on the market you’re entering and then adjust with a probability chance of success. For this illustration, let’s assume a 50% chance of a $10M exit. Again, the exit size and the probability chance of the exit depends on the market opportunity, strength of the team, economic conditions — and the list goes on. Get familiar with these factors and populate the model as you like.

The next three factors are a bit easier. Time to exit refers to how long the investment will be locked away. It could be as little as one year or ten-plus years. Three to five years is a good middle ground. Retention is a measurement of dilution; more specifically, it is the stake in the company at the time of exit as a percent of the original stake. And lastly, the VC Cost of capital is the discount rate. This refers to the cost of capital on the entire VC portfolio and not this single investment. Why? Because risk was already factored in when we assigned a probability chance to the exit. Thus, the average VC is looking for a 15-20% return. This can change as market conditions change; for example, if interest rates climb, than VC cost of capital will, too.

Alright, that’s a lot of info, so let’s go back to the template. The template is pre-populated with assumptions that our $250,000 investment in exchange for 33% of the company has a 50% chance of exiting for $10M in 3 years. We also assumed significant dilution (50%) and a 15% cost of capital. Drum roll, please….Under those assumptions, it is a good investment because the expect return is $547k, which is greater than the initial $250,000 invested.

Play around with the numbers and see what you get. For example, if you lower the probability chance of a $10M exit to 20%, which is reasonable, the deal becomes unfavorable. Or, if everything is held constant constant except it takes 3-times as long to exit (9 years), then the deal becomes unfavorable.

What percent is the correct percent
In the above method, we assume that the deal is structured: $250k for 33% of the company, take it or leave it. Well, this is often not the case. What often happens is the company is looking for a certain amount of capital and the investor needs to decide what amount of equity they need in return.

The second model on the tab entitled “% of company required” calculates the minimum equity stake required for a particular deal. This model is taught by Alexander Ljungqvistof NYU Stern. If the investor gets less equity than model calculates, than they will not achieve the target rate of return — a bad thing. But if the investor gets more, than it is all gravy.

This is a much more straight forward model, so let’s dive in. The first variable is simple: How much is the company asking for? In this illustration, let’s assume $1M. In terms of dilution, it is an early stage deal so let’s assume 50%.

Now we get to the exit, which is more difficult indeed. Again, the size and timing of an exit depends on the market opportunity, the team, the company’s competitive advantage, plus hundreds of other factors. Take all these factors into consideration and come up with a reasonable best case scenario. For this example, I assume a $25M exit in 5 years.

Ok, last part: the investor’s target rate of return. In the previous model, we used the return on the portfolio and represented risk with the probability chance of an exit. In this model, we simply use the target rate of return for this one investment. Thus, the return is greater to reflect the risk of this investment and because of the need to supplement other investments that will be dogs. A rate as low as 25% to as high as 60% is acceptable. For this model, I assume 45%.

So without further adieu, a $1M investment in a company that gets diluted by 50% and exits in 5 years for $25M requires an equity stake 38.46%, assuming a 45% target return. Again, play around with the numbers. For example, by lowering the exit size to $20M but moving the exit up 1 year, the required stake falls to 33.15%.

Lastly, I have built another tool that allows you to see what the return will be for a given equity stake. For example, if instead of getting 38.46% of the company you get 10%, the investor’s return will be 10.76%. This is well below the target rate of return and thus unacceptable.

Passing on Homeruns: The Anti-Portfolio

Venture capitalists – or any investor, for that matter – make money by avoiding poor investments and loading up on homeruns. Of course, this is all hindsight. Dogs can easily look like bulls, and vice versa. As a result, investors often times invest in underperforming companies, all while passing on homeruns.

Bessemer Venture Partners, a top tier VC shop, calls out missed opportunities in what they dub the “Anti-Portfolio.” I’m highlighting the Anti-Portfolio for two reasons. First, it is refreshing to hear a professional firm say, “Hey, we ain’t perfect. This game is tough.” I would love to see consulting firms highlight “Anti-Recommendations” — you know,  recommendations that lead the client in back assward directions.

Second, the Anti-Portfolio proves how difficult it is to understand the future value of a market or a company. Just think of all the examples of companies that passed on revolutionary ideas because they could not envision the future potential. Western Union comes to mind. Alexander Graham Bell offered his telephone patent to Western Union. At the time, the telephone only worked at short distance, so Western Union saw it as a toy, not a next generation invention that would usurp the telegraph. And let’s not forget Hewlett-Packard. Before he started the personal computer revolution, Steve Wozniak felt morally compelled to offer the first Apple to his employer. HP passed; computers were for businesses not people, after all.

Bessemer’s Anti-Portfolio includes 13 companies. You can see the whole list here. My favorites are:

1. Google – “Cowan’s college friend rented her garage to Sergey and Larry for their first year. In 1999 and 2000 she tried to introduce Cowan to “these two really smart Stanford students writing a search engine”. Students? A new search engine? In the most important moment ever for Bessemer’s anti-portfolio, Cowan asked her, “How can I get out of this house without going anywhere near your garage?””

2. Apple –  “BVP had the opportunity to invest in pre-IPO secondary stock in Apple at a $60M valuation. BVP’s Neill Brownstein called it “outrageously expensive.””

3. eBay – “”Stamps? Coins? Comic books? You’ve GOT to be kidding,” thought Cowan. “No-brainer pass.””

Better to be a Porsche than a Jaguar: Performance v. Functionality

For the last five years, I have been immersed in technology. My journey began as a market analyst covering the technology needs and buying patterns of financial service companies. Currently, I help Teach For America budget and forecast its technology investments. Given the pace at which TFA invests in technology I have seen some amazing projects, most notably ERP and CRM implementations.

The amount I have learned in the last five years, however, does not sum to what I’ve learned in the last five weeks. Before Christmas, I began developing a mobile application with a team I met at NYU. I’ll spare you the details until we launch in mid-February, but let’s say we built and distributed a minimum viable product and the feedback has been overwhelmingly positive.

Having never worked on the product development side, the learning curve is steep. My biggest takeaway to date is deciding whether to invest in performance or functionality. Product novices take for granted that applications work reliably and securely. We log into Gmail and expect our emails to be there. We post a picture to Facebook and expect it to instantly appear in our feed. In other words, we take for granted what we cannot see. This is performance and it makes or breaks an application. Would you use Gmail if 1 out of every 100 emails got lost? Would Facebook be as popular if it took 15 seconds instead of 0.15 seconds to post a photo?

On the other hand, product novices are quick to identify — and long for — missing features. We are accustomed to using complete products built by teams of engineers. We expect every bell and whistle, and get flustered when we are unable to do a seemingly easy task. We cannot imagine a product that is not integrated with Twitter or designed to send alerts. Functionality is what you see, and it too can make or break a product. Instagram is a great example; would the up-start be as successful without filters?

Early-stage companies have limited resources and therefore must decide between better performance or more features. As I wrestle with this decision, I am reminded of my family friends. The husband drove a Jaguar and the wife drove a Porsche. When I got my license, they were kind enough to let me test their exotic vehicles. (My family had a Ford Taurus and a Mercury Grand Marquis so you could imagine my joy.) When I got into the Porsche, I was amazed at how sparse it was. It was basically an empty cockpit with a pathetic after-market stereo. Then I turned it on, put it in first gear, and slalomed through the back roads. Damn; it was the definition of performance. Then I got into the Jaguar. It had everything. Plush seats, a great stereo, beautiful wood paneling. It was comfortable and pretty but it didn’t drive much better than my dad’s Grand Marquis. And even worse, the Jaguar was always in the shop. In short, the Jag was all features and no performance.

So as I discuss the development roadmap with my team, I remind myself it is better to be a Porsche than a Jaguar. A sparse product that works is better than a fully-loaded flop.

#SocialMediaStrategy: @jonsteiman advises @FoodieKitchens

My father-in-law Sam designs and builds custom kitchens in Vermont.  Several years back, he established a website. The website did its job; it provided him a web presence that landed him a couple of jobs per year. In the past year or two, though, he has received fewer and fewer leads. “All I need to do is replace the jobs I use to get through the website and all will be well,” he told me over a scotch below the Vermont moon. Below is a follow-up email I sent him explaining how the web has changed and what he needs to do as a small business owner to evolve. For most of my readers, this is pretty obvious stuff. For others, I hope it is enlightening.

*     *
The internet has evolved since you built your website five years ago. At that time, the internet was “search-centric,” meaning people knew what they wanted and simply went to Google to search that topic. Obviously, this still exists; Google search is still extremely relevant. But the “search” era has evolved into the “discovery” era. In the discovery era, people start on a social network – namely Facebook and Twitter – and discover information posted by other people and companies.

Let’s use your business to illustrate the two eras. In the search era, a person seeking a new kitchen would go to Google and search for “custom kitchens in Vermont.” The result would be a laundry list of potential vendors and maybe a few bloggers talking about the topic. Depending on your search engine optimization (SEO) strategy, your company may be at or near the top. The person would peruse the top five or six websites and winnow the list down to two or three companies to call or email. Hopefully, you’re on that list.

Fast forward to today. You’re potential customers are definitely on Facebook and probably on Twitter. On Facebook, they are connected to friends, family members and maybe a few businesses. On Twitter, they are following people with similar interests. This may include high-profile chefs like Tom Colicchio (@tomcolicchio), local food businesses like Round Barn Farm (@roundbarnfarm) and the local news (@wcax). In this world, your potential customers are spending hours on their social network of choice and learning about new ideas and new products from people they trust. They may “discover” the benefits of a custom kitchen from a friend’s post or a chef’s tweet.

So how do you evolve your business for today’s internet? Simple: insert yourself and your company into the conversation.

Start a blog
A blog allows you to share your design philosophy and experiences with the world. A blog is not a sales tool, per se. Rather it is a tool that helps readers know you – and hopefully trust you. Once they do this they can be converted into customers.

Creating a successful blog is difficult. Here are some tips that I have found helpful:

  • Set a goal of x posts per month. When I started blogging, I set a goal of two posts per month. Doing so allows you to measure success with a metric you control. If you measure success on traffic or comments, you will be frustrated early-on.
  • Long, thoughtful posts are great but don’t be afraid to put something up quickly. When you invest time into a blog, it pays off. However, there is nothing worse than a stagnant blog. So in between opuses, take a few minutes to post a short blog.
  • Mix it up. Blogs are the ultimate in multi-media. Use pictures. Take videos. Record audio.

So you have a blog, now what? Promote it!

An active blog is of little value if no one is reading it. Thus, a key part of blogging is promotion. The first place to start is Twitter. Think of Twitter as the world’s largest user-generated headline service.

Here is what you do. After you write a blog, tweet it out. Be sure to include a shortened link (use Also, tweets in the form of a question usually get the best response. So instead of “Check out our tips for storing compost” try “Do you know the best way to reduce waste and increase your garden’s performance?”

Also, tweet at people and trends. Let’s say you write a blog about the local food movement and what it means for the home kitchen. This would obviously be of interest to people in the local food movement so you want to craft your tweet accordingly.  You do this two ways:

  • @ – A twitter name is called a handle. If you want to show up in someone’s feed, than simply include their handle in your tweet. In the local food example, you would want to identify people aligned with that issue, such as @FarmtoSchool and @SlowFoodVT. Thus you would want to craft a tweet that includes these handles. The ultimate goal is to have these people/organizations retweet you to their followers. Hopefully, you pick up some new followers and the viral loop takes hold.
  • # -The hashtag makes it easier to search a word or phrase. Thus, you would want to hashtag all relevant words, such as #LocalFood, #OrganicGardening, #CustomKitchens, #Vermont, etc.

As you read tweets you’ll pick up on the difference between @ and # and begin drafting tweets like it was your native language.

Use Twitter to insert yourself into the conversation

In addition to promoting blog posts, use Twitter to insert yourself into the conversations that matter to your business. The first step is following the same handles as your customers. These include people/organizations talking about your line of business (custom building), your local community (Vermont, Burlington, etc.) and parallel interests (local food, organic cooking, and ergonomic design). As you read these tweets you can simply retweet them to your followers; this is like a seal of approval. Or you can reply by including the persons @ handle.

Lastly, and perhaps most importantly, use Twitter to share brief thoughts and insights. Let’s say you try and love a new cabinet roller. Well, take two minutes to tweet out your findings.

Bringing it closer to home: Facebook

Think of Twitter as a macro tool. Ideally, you will attract tens of thousands of followers located all across the world. Facebook, on the other hand, is more of a micro tool.

On Facebook, you will set-up a page for your business. The primary purpose of this page is to connect with your customers. As you talk to customers, tell them you’re on Facebook and that they should “like” your page to stay updated. Use your page to post links to your blog, before and after photos of jobs, articles you find interesting, and other musings. In many ways, you are using the same content from Twitter but just in different format because you aren’t confined by 140 characters and you’re not using @ and #.

Lastly, Facebook is where you should consider running advertisements. Facebook, more than any other media, is highly targeted. Using Facebook’s self-service tools, you can chose to deliver adds to UVM Professors living in the Burlington area that are under 45, like cooking and have showed interest in home renovation. It is that precise. In fact, there is a wives’ tale of a Facebook employee knowing his wife so well that he was able to narrow down the parameters and deliver her (and only her) to-do list items as ads.

Obviously, a social media strategy is not an end-all-be-all. You still need to do what you do best, which is work referrals, partner with other builders in your area, etc. But it when it comes to the web, you definitely need to embrace these strategies so you can be “discovered.”