When Shark Tank first aired in 2009, the US economy was dealing with the backlash of the 2008 housing market crisis. During this difficult time, Shark Tank gave struggling entrepreneurs hope that the American dream was still alive and well.
In the wake of the COVID-19 crisis, the global economy is now similarly facing a downturn, sparking renewed interest in Shark Tank ahead of a possible recession. Season 11 viewership peaked at around 6 million on March 20, shortly after the WHO classified the coronavirus outbreak as a global pandemic on March 11.
This article analyzes 103 tech pitches from all 11 seasons of Shark Tank, searching for common threads that underlie successes and failures. The data set is publicly available here, so you can expand on these analyses and ask your own questions. The reader who submits the best interactive data visualization will win a $500 Amazon Gift Certificate (see details at the end of the article)!
Whether you’re a tech entrepreneur considering a Shark Tank appearance or simply someone who enjoys playing with data, this two-part series explores the question: what makes a successful Shark Tank tech pitch?
11 Insights from 11 Seasons of Shark Tank Tech Pitches
1. Greed doesn't pay.
The average amount sought by entrepreneurs who got a deal was just over $300,000, while that of their unsuccessful counterparts was over $500,000 (this difference was statistically significant at p = 0.014).
Furthermore, none of the companies that got offers from all five sharks asked for more than $500,000:
Entrepreneurs who valued their companies at more than $10,000,000 (based on the amount of money they asked for and the equity they offered) never enticed more than a few sharks:
2. Rethink Robert.
All sharks are not equal when it comes to tech investments—and the optimal strategy isn’t as simple as aiming for the two “tech sharks” (Mark and Robert).
Consider the current state of the tech companies each shark has invested in. Five of the 15 tech companies Robert made a deal with have since closed—a whopping 33.3%! For comparison, only one of the 21 tech companies Mark made deals with have closed (4.7%), and none of the four tech companies Barbara invested in are out of business.
While there are many reasons businesses close that are unrelated to investors, the differences among sharks here are a little shocking.
3. Male and female tech entrepreneurs are equally likely to get deals, but males typically land deals closer to their asking valuation—even though they ask for more money.
Tech pitches were overwhelmingly male. Only 11 pitches were delivered by female entrepreneurs, and nine pitches included both male and female entrepreneurs. The remaining 83 pitches came from male entrepreneurs.
The success rate was comparable across genders. If anything, businesses represented by both males and females (“Mixed Teams”) may have had a slight advantage; however, this was not statistically significant.
While the similar success rates of males and females indicates a surprisingly level playing field, a closer look at the numbers tells a different story. For one, males asked for more money on average than females.
Furthermore, when male entrepreneurs secured a deal, it was typically closer to their asking valuation than deals made with females. On average, female entrepreneurs got deals at a valuation $1,758,333 below asking, while their male counterparts got deals at a valuation $965,882 less than asking (and this is AFTER removing an outlier that skewed the male average to $200,000 OVER the asking valuation).
4. For long-term success, aim for a deal with multiple sharks.
Most tech entrepreneurs who got an offer on Shark Tank only got one offer. However, if you find yourself in the enviable position of receiving multiple offers, get as many sharks on board as possible! Most of the tech companies that went out of business since making a deal on Shark Tank made deals with only one shark, and none made deals with more than two sharks.
Importantly, this doesn’t indicate causation; it could simply indicate that companies that enticed more sharks were stronger to begin with. Nonetheless, it also makes sense that, with multiple sharks invested, more lifelines will be available if your company hits obstacles.
5. The amount of equity you offer isn’t as important as the amount of money you ask for.
The average equity offered by companies that did and didn’t get a deal was comparable—11.22% and 11.04%, respectively. The upshot of this? Don’t feel obligated to give up a large amount of equity unless it’s necessary to get the money you need and maintain a reasonable valuation.
6. Crying is okay. Talking over people? Not so much.
Tech entrepreneurs mostly kept their emotions in check, but during at least three pitches (BenjiLock, Circadian Optics, and VPCabs), folks got a little misty-eyed. Crying did not seem to sabotage their success, as all three companies secured a deal. In fact, two of the three companies got offers from four sharks, and every shark made at least one offer to a teary entrepreneur (interestingly, two of the three crying entrepreneurs were male).
Of course, an N of 3 isn’t enough data to extrapolate from and conclude that you SHOULD cry during your pitch (I definitely don’t recommend going full-on sociopath with fabricated sob stories or anything), but it’s at least comforting to know that you probably aren’t doomed if you do let a few tears trickle out.
Being super nervous and tripping over your own words also isn’t a deal-breaker; just ask the stammering entrepreneur from Bundil, who secured a deal from Kevin O’Leary after a less-than-stellar start to his pitch.
Some entrepreneurs, like the frontmen of Linka and Trobo, also shared immigration stories or tales of hardship, with mixed results. The take-home message? Again, I wouldn’t plan this as part of your pitch, but it probably doesn’t hurt anything if it comes up organically. Also, in the case of Trobo, this last-ditch effort actually seemed to reverse the entrepreneur’s fate in the tank.
Be careful that your humanity doesn’t manifest as constantly talking over the sharks, though; this happened during the pitch for Swimply, and the sharks were unimpressed and—in the end—uninvested.
7. Include puppies! I have no data to back this one up...
While I only noted one example of this ingenious entrepreneurial hack, the company that implemented it (Gallant) landed three offers from sharks!
8. It doesn’t matter if you pitch solo or present with a team.
The size of the entrepreneurial teams delivering tech pitches ranged from 1-3 entrepreneurs, with most entrepreneurs pitching solo. The number of entrepreneurs was not significantly related to success.
9. The type of tech company isn’t a huge factor.
Most of the tech pitches involved electronics, apps, or consumer services. The success rate (based on deal/no deal) was similar across categories, although the few cloud computing and VR pitches were not successful on the show:
10. Need lots of money? Consider Lori.
Some sharks had deeper pockets than others for tech companies. Mark gave the most to tech companies overall ($5,645,000), but Lori averaged a higher payout per deal ($321,667):
11. Southern charm might give you a leg up.
The Southeast had the highest success rate (77%), while the Northeast had the lowest (27%).
State was also significantly related to both the number of offers and deal/no deal (p = 0.03).
Where Are They Now?
About 18.5% of the tech companies that appeared on Shark Tank have since closed.
The good news is that a tech company’s status seems unrelated to whether or not they got a deal on Shark Tank:
In fact, many entrepreneurs have said that simply appearing on Shark Tank gave their business a huge boost—so don’t be discouraged if you make it on the show only to get rejected. Remember when Ring (formerly known as doorbot) showed up on Shark Tank asking for $7,000,000, got rejected, and then sold to Amazon for $1,000,000,000 five years later? Shark Tank can help your company, but it probably isn’t going to make or break it.
Coding Challenge: Win $500!
Thank you for reading! Stay tuned for Part II of this two-part Shark Tank series, which will analyze the questions asked on the carpet and the various reasons sharks go out—allowing you to more intelligently engineer your pitch.
Data Visualization Challenge: Play around with the data set and build interactive data visualizations to compare different variables (e.g., plotting the number of pitches from each state on a map) and uncover more insights! Send your github repositories, along with your Triplebyte profile, to email@example.com (deadline is June 30, 2020). We’ll award the best entry a $500 Amazon Gift Certificate!
Also, if you enjoy working with this data and discover novel insights, please share them with me! If you like, I can even feature your insights in the follow-up article.
Good luck, and happy entrepreneurship!
Methods and References
Data were aggregated from Sharkalyticsand Halle Tecco’s data set, and supplemented with additional information from ABC, allsharktankproducts.com, and Crunchbase. Data collected from these sources were manually verified (by watching the pitches themselves). During this verification process, additional tech pitches were identified and added to the data set. Variables not present in other data sets (e.g., number of offers and sharks making offers) were also added.
Data were plotted using SPSS and R, and select variables were analyzed using a multivariate general linear model analysis in SPSS. Dependent variables included
Number of Offers. Independent variables included
Amount Asked For,
Number of Entrepreneurs.
 Fun fact: I was incredibly tempted to make the terrible pun
sharking here, only to discover the term is actually slang for pulling down someone's pants. ↩