7 Marketing Secrets from 500 Startups Demo Days

Have Fun, Get Deals Done – The Future of Marketing is the Brand Experience

Pitching to top Silicon Valley investors like Tim Draper is nerve-racking. It helps when he’s dressed in a superhero costume.

From Valentine’s Day-Themed (Batch 19) to Summer of Love-Themed (Batch 20), 500 Startups Demo Day is more than a pitch day, it’s a festival where everyone has fun and gets deals done.

Here’s a look back at lessons we’ve learned from the last 7 Demo Days, and how 500 Startups stumbled upon creating the unique pitch day in Silicon Valley.

1. Listen to Your Audience

Back in the day, 500 Startups Demo Day was pretty basic (see Batch 8):


500 Startups Founding Partner, Dave McClure, speaking at 500 Batch 8 Demo Day (back when the most colorful thing at Demo Day was Dave’s language).

During Batch 13 Demo Day, things got a little bit more interesting.

It all started when I bought Dave a unicorn hoodie for his birthday, which happened to coincide with the Batch 13 Preview Day (an invite-only sneak peek to Demo Day). To our surprise, many investors and founders in the audience loved Dave’s unexpected fashion statement, talking and tweeting about it.

Dave noted the audience engagement and decided to wear the unicorn costume again on Demo Day. He also encouraged Founding Partner Christine Tsai, a former ballerina, to wear a rainbow tutu. Again, the response was extremely positive at Demo Day. Silicon Valley Business Journal even dedicated an article to Unicorn theme.

The lightbulb turned on, and we saw the potential marketing value in bringing creativity to our Demo Days. But it wasn’t a mere fluke — we listened to the audience feedback, saw the marketing value, and applied it.

 

2. Turn Challenges into Creative Advantage

When planning for Batch 14 Demo Day, we found out the only day the venue was available was the day before Halloween. We were not happy. Typically we tried to plan our events around major holidays, like Halloween, assuming people would be busy attending their own company parties. We were worried about not having enough investors attend our event, but we couldn’t change the date. So we decided to exploit the timing instead. Thus, Demo-Ween was born.

In our past Demo Days, we always focused on the pitches, not wanting to take away from the big day of our batch companies. However, the thematic timing forced us to look at the Demo Days from a different angle. We decided to make Demo Days more entertaining. We added the Halloween theme to our Demo Day, aka “Demo-ween” — presenting the content in a new form. The new form of Demo Day allowed startups and investors to dress up, have fun, and get deals done together.

As a result, the Demo-ween not only helped us maintain the previous demo day attendance, it also attracted more international investors than ever before (50% increase). By presenting the content in a more engaging format, we turned a challenge into our competitive advantage.

The first Demo-ween was so successful, we decided to make it an annual theme. 




3. Use Product-Launches to Rejuvenate Your Brand

In 2016, we started adding speciality tracks to our seed program, starting with a Fintech track in the Batch 16 program.

In order to highlight our new Fintech focus, we made the Batch 16 Demo Day poker themed. In order to create an authentic experience, the 500 events team hired a top poker player to give attendees poker lessons and play blackjack. Founding Partners Dave McClure and Christine Tsai also dressed up for the poker theme.

Partly in thanks to a successful Fintech-Themed Demo Day, we saw a 23% increase in Fintech applications to the following batch.

4. Embrace Company Culture

During the Batch 17 program in June 2016, the 500 team and batch companies attended the San Francisco Pride Parade. Pride inspired us to redefine the meaning of “unicorn” at 500. In tech, a unicorn company means a billion dollar company valuation. We decided that being a unicorn also brings about a sense of love and unity. We are not only about making profits and increasing portfolio company valuations but also about celebrating people and culture.

The momentum of the Pride Month continued into our Demo Day planning process. We wanted to use the upcoming Demo Day as a platform to promote 500’s company value of embracing diversity and inclusion. We chose the theme “Beauty & the Geek” based on our B17 tracks Fashion & B2B and decided to break down gender stereotypes by having Dave dress up as the “Beauty” and Christine the “Geek”.

After Demo Day, Microsoft offered to sponsor our efforts to advocate diversity in tech by supporting our Unity and Inclusion Summits. Our open and embracing culture has attracted a very diverse group of companies. In our latest batch, Batch 20, 36% of our batch companies were international (from 10 different countries), 20.5% of companies had at least one female founder, and 25% of companies had a black / Latinx founder.

 

5. Make It About Your People

At the end of the Batch 17 Demo Day, a flash mob of the 500 team appeared from the audience and started dancing on stage with Dave. The big screen started playing videos of venture capital investors and founders of successful 500 portfolio companies around the world wishing Dave a happy birthday. The B17 Demo Day happened to be Dave’s 50th birthday and our 500 family planned a surprise for Dave.

The Demo Day birthday surprise is just one example of the many things that we would do simply because we care about people. We build the 500 brand by connecting with people on a personal level.

6. Create Positive Emotion

From the previous Demo Days, we began to see that themes created a supportive environment for founders and investors to develop relationships. For Batch 19, we chose a Valentine’s Day theme because we wanted to bring more emotion into the experience.

We dressed up our founders as Cupid (Christine) and the Queen of Hearts (Dave) and decorated the stage with all shades of pink and hearts. Investors could give batch companies Valentine cards that said, “I have my eyes on you!”.



 

7. Leverage Culture & History

Our Batch 20 program was based in San Francisco around the same time as the city’s 50th anniversary of the “Summer of Love” – the 1967 summer event that drew nearly 100,000 young people to the city’s Haight-Ashbury neighborhood. Starting from early spring 2017, streets in San Francisco were decorated with the “Summer of Love” theme. We decided to do the same theme for our Demo Day to pay tribute to the city’s history.

With flowers, rainbow-colored lighting and our emcee in a Grateful Dead bear costume, this Demo Day brought a sense of nostalgia to the city many 500 Startups team members call home.



Conclusion

Our Demo Days are instrumental in building the 500 brand. We strive to create an organic ecosystem of investors, founders, and corporate partners by providing meaningful and engaging content to our audience.

If your goal is to stand out from the crowd and flaunt your unique brand to the world, don’t forget to incorporate these 7 Marketing Lessons from 500 Startups Demo Days:

  1. Listen to the Audience: Gather feedback from your audience, catch the opportunity, and act on it
  2. Reframe the Challenge: Look at the problem from another perspective and turn challenges into advantages
  3. Inspire with your products: Rejuvenate your brand with new products
  4. Embrace Company Culture: Integrate the company values and culture to create a powerful marketing message
  5. Focus on People: Build a people-centric ecosystem to organically grow your business
  6. Engage your audience with Emotions: Create Positive emotions to Drive Connection and Awareness
  7. Integrate Art into Business: Leverage the power of culture and history in your marketing

500 Batch 22 begins July 24th, 2017 in San Francisco.

Click Here to apply for our the Batch 22 Seed Program.

More from Yiying Lu: 


yiyinglu-profile-square

Yiying Lu is award-winning bilingual (English & Chinese) artist and designer. Born in Shanghai China, Educated in Sydney Australia & London UK, now based in San Francisco, Silicon Valley, she currently is a Design Lecturer at the NYU Shanghai Program on Creativity & Innovation. She is also an individual creative consultant who provides talks & workshops for global startups and corporate innovation teams on design thinking, entrepreneurship & creativity. Her projects have been featured in many publications, including The New York Times, Forbes, NBC News, TIME, CNN, BBC, San Francisco Chronicle, TechCrunch, Mashable, and The Huffington Post. She was named a “Top 10 Emerging Leader in Innovation” in the Microsoft Next 100 series. For more from Yiying, you can follow her on TwitterLinkedin and Medium.

 

A Tale of Two Squirrels: The Not So Simple Math on Venture Portfolio Size

By now most VCs are familiar with Dave McClure’s theory of venture portfolio size. In short, he believes that at seed stage, it doesn’t make sense to have a fund with fewer than 50-100 companies, because venture returns depend on outliers and you need a big enough portfolio to consistently capture them.

In the post, he outlines a range of typical outcomes for a large portfolio of seed-stage investments. You can see some variation of this trend in most published venture returns data such as Crunchbase or PitchBook.

Range of Potential Venture Outcomes from Dave McClure’s “99 Problems” blog post (May 2015)
Fig. 1: Range of Potential Venture Outcomes from Dave McClure’s “99 Problems” blog post (May 2015)

These are large ranges (because there’s a lot of randomness in startups), and depending on where you end up in these ranges, you could make or lose a lot of money. Most investors prefer a bit more certainty.

Thankfully, statisticians have invented something called a Monte Carlo analysis, popularized by Nate Silver of 538 fame, to simulate the impact of this randomness by simulating a large range of possible outcomes. And my friend Yannick Roux (@yanroux, blog), a London-based VC, kindly built a Monte Carlo simulation in Excel to help me model the range of possible outcomes for venture portfolios.

The “Blind Squirrel” Portfolio

We have an expression “Even a blind squirrel finds a nut every once in a while.” In other words, any VC with decent deal flow and a reasonable selection process, if they write enough checks, should eventually pick a winner. I’m not saying that’s a good way to invest, but let’s do the math.

“Eew, this one tastes like Ad-Tech.”

Working with Yannick’s model, I plugged in some assumptions from the middle of the ranges above. This represents the “average” venture investor, hence with outcomes that fall in the middle of these ranges.

Then the Monte Carlo engine quickly ran through 10,000 simulated portfolios and listed the outcomes. I repeated this five times, changing only the portfolio size each time, and leaving all other variables constant (such as fund size average investment per company per outcome). These are the results:

Distribution of portfolio return multiples (gross of fees) from a Monte Carlo simulation of 10,000 “Blind Squirrel” venture portfolios.
Fig. 2: Distribution of portfolio return multiples (gross of fees) from a Monte Carlo simulation of 10,000 “Blind Squirrel” venture portfolios.

As you can see, the results for the three largest portfolios are almost identical, but the results for the 20- and 50-company portfolio are worse. That’s because, in this model, we’re only expecting big (e.g. >50X returns) winners to occur 1% of the time. And in a portfolio of 20 companies, 1% of 20 is, more often than not, zero. But in a portfolio of 200+ companies, you could pretty reliably see a couple 50X outcomes in each iteration of the portfolio.

Here’s a frequency distribution showing the breakdown of return multiples 10,000 simulated portfolios of 20 companies vs. 200 companies. It’s a bit easier to visualise this way.

Frequency distribution histogram of portfolio return multiples (gross of fees) from a Monte Carlo simulation of 10,000 “Blind Squirrel” venture portfolios.
Fig. 3: Frequency distribution histogram of portfolio return multiples (gross of fees) from a Monte Carlo simulation of 10,000 “Blind Squirrel” venture portfolios.

But We’re Not Average! Enter the Super Squirrel.

The “blind squirrel” portfolio was designed to match the outcomes of the venture universe in-general. These are the middle of our ranges – and a median return of 3.18X before fees and after a 10-year lock-up isn’t terrible.

But we should hope that a well-known venture fund with a recognized brand and a large team of experienced partners would attract better than average quality companies, and be better than average at picking and supporting winners. So I re-ran the model with input assumptions towards the higher end of our ranges, a different picture emerged: 20 companies is still not a great portfolio. But in this model, 200 companies can get you better than 4X before fees.

Distribution of portfolio return multiples (gross of fees) from a Monte Carlo simulation of 10,000 “Super Squirrel” venture portfolios.
Fig. 4: Distribution of portfolio return multiples (gross of fees) from a Monte Carlo simulation of 10,000 “Super Squirrel” venture portfolios.

Now these are much better returns. And in this model, the impact of portfolio size becomes much more pronounced. That’s because payoffs in venture are asymmetrical, meaning the impact of the losers (e.g. you lose 1X your investment) remains the same regardless of how amazing you are, but the impact of the winners is exaggerated for Super Squirrel VCs, because there are more bigger winners in Super Squirrel’s portfolio.

Frequency distribution histogram of portfolio return multiples (gross of fees) from a Monte Carlo simulation of 10,000 “Super Squirrel” venture portfolios.
Fig. 5: Frequency distribution histogram of portfolio return multiples (gross of fees) from a Monte Carlo simulation of 10,000 “Super Squirrel” venture portfolios.

What about the 50 company portfolio?

As you saw above, the 50 company portfolio doesn’t do badly. The top quartile returns more than 6.34X, which is better than the 100 company portfolio. But it carries a lot more risk, and you can see that in the shape of the curves:

Frequency distribution histogram of portfolio return multiples (gross of fees) from a Monte Carlo simulation of 10,000 “Super Squirrel” venture portfolios with 50 or 200 companies
Fig. 6: Frequency distribution histogram of portfolio return multiples (gross of fees) from a Monte Carlo simulation of 10,000 “Super Squirrel” venture portfolios with 50 or 200 companies.

Notice that second gray hump on the right? That squirrel looks more like a camel! (a bi-modal, or Bactrian camel at that) That’s because your chance of hitting a “big winner” (50X – 100X) is about 1%. And in a 50 company portfolio, that will happen about half of the time. So the fund outcomes in the hump on the right have that one big winner in them, and the ones on the left don’t.

But in those great outcomes, it’s really down to that one big winner. If I re-run the Super Squirrel model and remove the top performing company in each scenario, then that whole second hump goes away. Notice below, the top quartile return for the 50 company fund drops by 49%, but the top quartile return for the 200 company fund only loses 20%.

Top Quartile returns for Super Squirrel funds with and without their single best performing company.
Fig. 7: Top Quartile returns for Super Squirrel funds with and without their single best performing company.

Now imagine you’re the manager of the 50 company fund. You’re six years in and you have that one company – late stage, growing fast, looking good. What if they “only” sell for $200M and you get crushed under a stack of liquidation preferences? What if Amazon goes after them? What if a similar company tries to IPO and it’s a disaster? What if the Wunderkind founder gets hit by a bus? Or suppose that company does well and you decide to raise another fund. Then you’ve got to convince your LPs that lightning will strike twice, and you’ll find another big winner again in your next fund. You explain that even though nearly half your returns from your last fund came from a single company, you’re sure you can pull that rabbit out of that hat again. These questions will haunt your dreams.

But We’re Not Squirrels!

It’s true, most VCs will tell you their investments are not random. They will claim they are able to access and carefully select the best companies in which to invest. So, as an LP in a 20 company fund, all you need to do is pick a fund manager who is consistently able to attract and consistently select the top 5% of seed stage startups.

But remember, if you have someone who can consistently select the top 5% of publicly-traded equities year after year, you have Charlie Munger of Berkshire Hathaway. That’s not a simple task!

And it’s theoretically easier to identify good companies in public markets, where you have decades of historical data, competitive data and armies of analysts poring over every available scrap of information. So the person who can consistently pick the top 5% of seed-stage startups is much smarter than Charlie Munger. (When you meet that person, please please please send her my way!)

But what about Sequoia Capital? Kleiner Perkins? Andreessen Horowitz?

Concentrated portfolios have been the venture game for the last few decades: Most institutional investors allocating into venture capital (representing at best a single digit percent of their asset allocation) have been fighting for allocations into a very small number of top-decile fund managers, typically based on Sand Hill Road.

How do we explain all those famous funds with concentrated portfolios that have done so well? It’s true, a few fund managers have done a great job of landing their outsized share of big winners fund after fund. So this must be possible.

We believe, the main difference is that these people are investing in later stages (Series A onwards). At later stages, a more concentrated portfolio might make more sense, as a higher proportion of your investments should be “winners” and fewer will go to zero. And in that case, your ability as a fund manager depends less on your ability to “select” winners and more on your ability to get into the best deals. That said, although companies in later stages may be 10X further along in traction and the likelihood of success may have improved somewhat vs. the prior stage, their pre-money valuations may have increased much more. (Our typical entry point on valuation for seed-stage is about $2.5M pre-money, whereas a Series A might start at $15-$20M pre-money and a Series B might be at $40M-$50M pre-money). Finally, entering at higher valuations means you need to exit at higher valuations to see a comparable multiple. For example, to get an Amazing (50X) outcome on an investment at $50M pre-money requires getting more than $2.5B exit valuation, whereas to get such an outcome on an investment at $2.5M pre-money requires getting only a $125M exit valuation (before dilution to simplify the math). The net of all of this is that, in our opinion, later-stage investing may have a worse risk-adjusted return profile than seed-stage investments, especially for fund managers who do not have the same kind of branding and deal access as the Legends of Sand Hill Road.

How Big Should My Portfolio Be?

We believe, if you’re 1) investing at seed stage, and 2) you are an average investor (in terms of deal flow & selection experience), and 3)  your main goal is maximizing financial returns, you’d want a minimum of 100 companies to get a decent shot at a 3X gross return. If you’re a really good investor, 50 companies might be enough. But if your one big winner doesn’t deliver hugely… that’s the risk. So, in our opinion, if you want consistent outperformance and unicorn failure insurance you should aim for 200 – 500 companies.

This is Not Revolutionary

I’m not the first person in the history of finance to suggest that diversification might be a good thing. And 500 Startups isn’t the first early-stage fund to favor a large portfolio. (That was Y Combinator, or Ron Conway before them). But we keep having this debate for some reason. So I wanted to unpack the math a bit.

Notes: I originally published this post on my Medium blogIf you’re seriously interested in learning more about early stage venture investing check out our investor education programs at education.500.co.


Acknowledgements

None of this math would have been possible without the portfolio Monte Carlo simulation engine developed by Yannick Roux, who also reviewed and improved drafts of the post. Plus great inspiration from @twentyminutevc in his great discussion with Josh Breinlinger and the ensuing tweetstorm. And many thanks to Dave McClure, Aman Verjee and Eddie Thai for all the feedback on drafts & constantly prodding the math. (And Yiying Liu for photoshopping the Patagonia vests on to the venture squirrels – priceless!) If you learned anything new from this post, it was truly from the shoulders of giants on which I stand.


About Matt Lerner

Matt Lerner, 500 Startups PartnerMatt Lerner (@matthlernerMedium blog) heads 500 Startups in the U.K. He has led over 30 early-stage  investments across Europe and the Middle East, and runs their “Series A” growth program for seed-stage startups. Prior to joining 500 Startups, Lerner worked as a Marketing Director and later Head of UK SME at PayPal. He built and managed growth teams that helped grow PayPal from an $800M business to an $8B business in 10 years. Lerner occasionally lectures on “growth hacking” at Stanford Business School and Imperial college.

 


LEGAL NOTICES

THE STATEMENTS HEREIN REPRESENT THE CURRENT OPINION AND BELIEFS OF THE AUTHOR.  UNDER NO CIRCUMSTANCES SHOULD ANYTHING IN THIS POST BE CONSTRUED AS INVESTMENT, LEGAL, TAX, REGULATORY, FINANCIAL, ACCOUNTING OR OTHER ADVICE BY 500 STARTUPS. THIS POST IS NOT INTENDED TO PROVIDE THE BASIS FOR ANY EVALUATION OF AN INVESTMENT IN A VENTURE CAPITAL FUND BY 500 STARTUPS OR ANY OF ITS REPRESENTATIVES OR AFFILIATES. THIS POST DOES NOT CONSTITUTE AN OFFER TO SELL OR A SOLICITATION OF INTEREST TO PURCHASE ANY SECURITIES BY 500 STARTUPS, OR ANY OF ITS REPRESENTATIVES OR AFFILIATES.

POTENTIAL RETURNS AND MODELS IN THIS POST ARE THEORETICAL AND PROVIDED FOR ILLUSTRATIVE PURPOSES ONLY.  THE PROJECTED RETURNS PRESENTED ARE NOT BASED ON PAST PERFORMANCE AND MAKE CERTAIN MATERIAL ASSUMPTIONS AND PROJECTIONS WHICH MAY OR MAY NOT PROVE ACCURATE. THE PROJECTED RETURNS HEREIN DO NOT PURPORT TO GUARANTEE FUTURE RETURNS, AND RETURNS FOR INVESTORS IN ANY 500 STARTUPS OR OTHER VENTURE FUND MAY BE LESS OR MORE THAN THE RETURNS REFLECTED IN THIS POST AND MAY DIFFER MATERIALLY FROM ANY PROJECTED RETURNS, PERFORMANCE EXPRESSED OR IMPLIED IN THIS POST.

THE VIEWS AND PROJECTED RETURN INFORMATION CONTAINED HEREIN HAVE NOT BEEN AUDITED OR VERIFIED BY ANY INDEPENDENT PARTY AND SHOULD NOT BE RELIED UPON IN MAKING ANY INVESTMENT DECISIONS.  NO REPRESENTATION OR WARRANTY, EXPRESS OR IMPLIED, IS MADE BY 500 STARTUPS AS TO THE REASONABLENESS OR ACCURACY OF THE PROJECTIONS OR ESTIMATES CONTAINED HEREIN, AS A RESULT, SUCH PROJECTIONS AND ESTIMATES SHOULD BE VIEWED SOLELY AS AN ORDERLY REPRESENTATION OF ESTIMATED RESULTS IF UNDERLYING ASSUMPTIONS ARE REALIZED.

VENTURE CAPITAL INVESTMENTS ARE CHARACTERIZED BY A HIGH DEGREE OF RISK, VOLATILITY AND ILLIQUIDITY. THE PROJECTED PERFORMANCE HEREIN IS NOT NECESSARILY INDICATIVE OF FUTURE RESULTS, AND THERE CAN BE NO ASSURANCE THAT ANY 500 STARTUPS FUND WILL ACHIEVE COMPARABLE RESULTS, ACTUAL RESULTS COULD DIFFER SIGNIFICANTLY

 

500 Startups Batch 1 — 5 Years Later. Where Are They Now?

At 500 Startups, each group of founders that is accepted into the accelerator’s four-month program is called a “Batch,” an apt description, since participants receive a series of commands they’ll later process and execute.

The founders who presented at 500 Startups Demo Day in August 2011 are considered Batch 1; today, Batch 17 is entering week six of a four-month program that will culminate in their own Demo Day, the product of intense study, practice and camaraderie.

Batch 1’s pitches were presented at 500 Startups’ Mountain View office, but today, Demo Days are held at Mountain View’s Computer History Museum, a venue that can accommodate hundreds of attendees, including investors, friends and the media.

High production values give these pitch sessions the same vibe as a high-energy stage show, but some things haven’t changed since Batch 1: participants continue to be “unified by a strong international and female founder thread and ‘attitude,'” a trait TechCrunch noted in its August 2011 Demo Day reporting.

Today, a look back at several companies that participated in Batch 1 Demo Day to see how far they’ve flown since leaving the nest.

Kudo

Based in Indonesia, Kudo describes itself as “an Online to Offline (O2O) company, bringing e-commerce to mass millions of Indonesians.”

In practice, this means creating sales kiosks in public areas that accept several forms of payment. By targeting consumers in physical spaces, Kudo’s founders hope to drive sales from people who might not be inclined to order online or visit a store.

Because approximately 81 percent of Indonesians don’t have bank accounts, Kudo’s payment and logistics platform bridges financial and technical gaps. Customers use Kudo kiosks to refill mobile phones, purchase tickets or buy physical goods.

Where are they now?

In November 2014, founders Albert Lucius and Agung Nugroho closed a seed round; six months later, their metrics were strong enough to land a seven-figure funding round.

Vidcaster

Vidcaster, a “video experience platform for marketing and training,” created custom workflows that let users easily promote, distribute and manage marketing and training content. Offering turnkey solutions that included hosting and SEO, co-founder and CEO Kieran Farr told TechCrunch that he followed Dave McClure’s advice to launch a freemium service that would augment his existing subscription services.

Three months after Demo Day, Vidcaster raised a $350K seed round, which gave the company enough runway to integrate with Salesforce, Hootsuite and Marketo, increasing its reach. After winning a grant from the City of New York to “hire and expand in Lower Manhattan,” Farr relocated the company from San Francisco.

Where are they now?

In December 2015, Vidcaster was acquired by Vidlet, a marketing research company based in Palo Alto. Farr remained aboard as CTO, where he helped the new company develop a service that uses smartphone cameras to conduct ethnographic research.

Snapette app, via Facebook

 

Snapette

Initially an app that connected shoppers with nearby shoes and apparel, Snapette quickly grew into an ecommerce discovery platform with more than 2 million users.

Where are they now?

In October 2011, co-founders Jinhee Ahn Kim and Sarah Paiji closed a $1.5M seed round; in August 2013, after partnering with more than 200 brands and stores, Snapette was acquired by PriceGrabber, a price-comparison shopping site, for an undisclosed amount.

Looksharp

InternMatch, a jobs marketplace for internships and grad students that launched in 2009, raised $400K in angel funding before securing its berth in Batch 1. While going through the accelerator, founders Andrew Maguire and Nathan Parcells redesigned their site to improve usability and search. A month after their demo, they raised an additional $500K.

Where are they now?

Initially focusing on west coast opportunities, InternMatch gained traction by building a large team of brand ambassadors who were also marketing interns. Employers pay to post listings, but students use it for free. In January 2013, the company raised $1.2M in a bridge round to expand its services to include internships and traditional paid positions for enrolled students and recent graduates.

Six months later, a $4M Series A round allowed the company to add more engineering and marketing roles and develop data products to match users with open positions. After changing its name to Looksharp, the company acquired competitor Readyforce in December 2014.

Today, Looksharp currently claims to serve 10 million users, or 70% of all new graduates and college students.

Elizabeth Yin, 500 Startups EIR, co-founder LaunchBit

LaunchBit

LaunchBit, a customer acquisition tool for SaaS companies, was created to help publishers send content to B2B audiences via niche ad inventory such as newsletters and blogs. The firm also helps publishers identify and manage ad units that can be inserted into email newsletter.

Where are they now?

A year after Batch 1, LaunchBit raised a $960K seed round and relocated from the Bay Area to Las Vegas in search of “cheaper operational costs and a better talent pool to tap,” co-founder and CEO Elizabeth Yin told tech.co. After BuySellAds, a LaunchBit partner, expressed interest in an acquisition, Yin realized that her “passion wasn’t in ads.”

After LaunchBit was absorbed into BuySellAds, Yin joined 500 Startups as a Entrepreneur-in-Residence, and now runs 500’s Mountain View Accelerator as a partner in the firm.

Batch 17 Demo Day is August 2, 2016

Batch 17’s Demo Day is already on the books for August 2, 2016.

Active, accredited investors and their representatives are invited to join our founders and our team at the Computer History Museum in Mountain View on August 2 from 12 – 6pm.

Demo Day requires pre-registration.

Sign up to join Batch 17 Demo Day here.