Entrepreneurs trying to build big companies turn to equity investors to raise capital. If a company is an established ongoing concern, investors can look at cash flows, growth rates, customer retention, capital assets, leverage, and other hard metrics to determine whether to invest and how to value the company. An early-stage company has few if any hard metrics, however. Startups are often just emerging from the idea stage into market trials, and the minimum viable products and services they offer are being tested by beta customers.
This presents a challenge for the entrepreneur. What will convince angel and early-stage venture investors that what she is building is not only a feasible company but one that has the potential to generate a large return on investment, and maybe even become one of those rare unicorn companies that will make its investors rich?
If she were to Google “what investors look for before funding a startup,” she would find myriad guides, many written by angel investors ad venture capitalists. Most of these guides include some variation of the four M’s outlined by entrepreneur and investor Mark Suster in his blog Both Sides of the Table.
Early-stage investors following this guide, or one like it, may believe they are objectively evaluating startups on factors such as management team credentials, sustainability of the business model, evidence of traction in the market, and large-company potential. However, new research indicates that regardless of what investors think they’re doing, the reality is subtly different. Investors, these findings suggest, are more influenced by an entrepreneur’s likability, positivity, and happiness than they are aware of. One implication of this for entrepreneurs is that your smile matters very much, which is a revelation that I find to be surprising—and somewhat disappointing.
Suster’s four-M framework is largely echoed in extensive research by Chicago Booth’s Steve Kaplan, Harvard’s Paul Gompers, University of British Columbia’s Will Gornall, and Stanford’s Ilya Strebulaev. In a study published in the Journal of Financial Economics, this team sought to answer the question: How do venture capitalists make decisions? They surveyed 885 institutional VCs at 681 companies worldwide from November 2015 through March 2016, asking them to rate their top three investment criteria. Nearly all the respondents said the target company’s leadership team was one of the top factors. The researchers narrowed in on the 241 venture capitalists who focused on seed and early-stage investment, and 96 percent in this group included leadership team in their top three criteria. The other popular criteria were the company’s business model (84 percent), product offering (81 percent), potential market opportunity (74 percent), and fit within the VC’s existing portfolio (48 percent). However, when asked to identify the single most important investment criterion, more than half the investors chose the founding team, demonstrating even more clearly their reliance on founder credentials in assessing early-stage companies. Asked to define the qualities they looked for in a startup team, the investors cited ability, followed by industry experience, passion, entrepreneurial experience, and teamwork.
Institutional venture capitalists who focused on seed and early-stage startups said the target company’s leadership team was the most important factor in their decision to invest.
Survey responses from seed and early-stage VCs
241 respondents, 2015–16 survey
A research experiment conducted in summer 2013 by Harvard’s Shai Bernstein, University of Southern California’s Arthur Korteweg, and AngelList’s Kevin Laws further validates this dependence by early-stage investors on the characteristics and experiences of the founding team, which serve as a quality signal. The researchers used AngelList, an online platform created to match startups with accredited investors, and randomly selected a cohort of companies seeking funding. At the time, when investors joined AngelList, they specified what kinds of startups they were interested in, and then AngelList periodically sent them an email of “featured” companies, with the intention of attracting them back to the website to learn more.
AngelList’s emails included information covering three areas: team credentials, current investors, and market traction. Bernstein, Korteweg, and Laws decided to mimic these emails to see which of the data categories most influenced an investor's decision to learn more about a particular company. Because AngelList often included information from just one or two of the categories rather than all three, the researchers were able to send out experimental emails that randomized the categories included, and they could see which ones made an investor more likely to click through to learn more about a company. They sent 16,981 emails about 21 startups to 4,494 active investors. Recipients opened 48 percent of the emails, and in 16.5 percent of these opened emails they clicked on the View button, an indication that the investor wanted more information about the featured company. The researchers also collected data on how often the investor then requested an introduction to the company, a further sign of interest.
Not surprisingly, as it supports the findings of Kaplan and his coresearchers, emails that included information about the team saw 13 percent higher-than-average click-through on the View button, with a click rate of 18.7 percent. This bump was even bigger when the investor’s area of interest and expertise coincided with the industry of the startup company—then there was a 20.4 percent click-through rate. The presence or absence of information in the other categories did not significantly alter the click rate.
Investors are smart in prioritizing team over other criteria in their investment decisions, research suggests. Numerous studies over the decades have found a correlation between human capital—education, experience, knowledge, and skills—and entrepreneurial success, and more recent research by University of La Verne’s Byungku Lee suggests that founders’ hard work is a significant predictor of new venture success. There is little doubt that a great team is critical to startup success. But how exactly are investors evaluating teams?
Research conducted in 2020 by Yale PhD candidate Allen Hu and Yale’s Song Ma reveals that investors may be sucked in by a smile. Hu and Ma created an experiment to use a new methodological framework to identify what features in human interactions matter in economic decision-making and to utilize cutting-edge technology to empirically represent, measure, and analyze those features across vocal clues, facial expressions, and language choices. They selected a random set of short startup video pitches created by 1,139 entrepreneurial teams as part of the process of applying to top accelerator programs including Y Combinator, MassChallenge, and Techstars, among others. Eight and a half percent of the teams were accepted into the accelerator program for which they applied.
Researchers created a set of metrics to measure a startup pitch’s persuasiveness.
| EMOTION MEASURES | |
 |
 |
| Visual positive | Visual negative |
| Facial expressions | |
 |
 |
| Vocal positive | Vocal negative |
| Tone and energy | |
 |
 |
| Vocal valance | Vocal arousal |
| Range of emotional quality | Excitement level and intensity |
| CONTENT MEASURES | |
 |
 |
| Verbal positive | Verbal negative |
| Use of language | |
 |
 |
| Verbal warmth | Verbal ability |
| Socially perceptive positivity (words such as “together” or “help”) | Industry and execution (words such as “intelligence” or “design”) |
Deutsch, 2021; Hu and Ma, 2020
Hu and Ma used voice and facial recognition software to deconstruct the videos—capturing facial expressions at 0.1-second intervals and tone of voice and inflection on a sentence-by-sentence basis, as well as word-by-word content. This created an enormous data set which they then analyzed via machine learning. Using well-established frameworks from psychology, finance, and linguistics, they were able to create 10 distinct metrics—six quantifying emotion in voice and facial expression and four analyzing the content. (See “How to turn voices and facial expressions into data” on the following page.) They examined how much time during each video a team displayed positivity or negativity according to the visual, vocal, and content metrics. Weighting each of these measurements, they created an overall pitch score that represented the “positivity” of the team’s presentation.
Not at all surprisingly, investors preferred teams that looked and sounded positive. In fact, a 1-standard-deviation increase in overall positivity improved a team’s chance of being selected into the accelerator by 35 percent, up from 8.5 percent to 11.5 percent.
But Hu and Ma also found that investors prioritized this positivity over all other factors in the pitch, to their detriment. A higher score on the verbal-ability dimension was actually negatively correlated with selection. When the researchers controlled for both the teams’ education and work experience—characteristics that in practice correlate with entrepreneurial success—they found that this did not change the results. Hu and Ma then tracked down the companies to see what happened to them. Looking at survival rates, jobs created, and the results of later funding rounds as a way to determine the success of the companies in their sample, they discovered that more-positive entrepreneurs, indicated by happier facial expressions and vocal emotions, built companies that raised less follow-on funding and hired fewer employees than the average of the cohort, while those who exhibited higher verbal ability were likely to employ more people at their ventures—even though they were less likely to have obtained funding. This suggests that entrepreneurs who use the kind of technical, content-rich language the algorithm picked up on are less likely to appear friendly and happy, and therefore to appeal to funders, even though their language correlates with more competent teams that build better businesses.
The study also suggests that first impressions disproportionately affect investor decisions. When Hu and Ma limited their analysis to the first five seconds of the pitch, an amount of time during which little of substance about the business could be communicated, the results were similar—the more positive the beginning of the pitch, the more likely the company was to be selected.
Many years ago, I was coaching an entrepreneur through Chicago Booth’s own accelerator program, the New Venture Challenge. The young man was an exceptionally talented and experienced engineer and presented a relevant technology concept in a patient, thorough, and thoughtful manner. It could not have been more boring. After his presentation, I asked him, “Ed, do you like your business?” He frowned, folded his arms, thought for a moment, and replied seriously, “I think it has a chance.” The room laughed nervously, and I said to him, “Ed, if that is how you feel about your own company, how are the investors supposed to get excited about it?” Needless to say, his startup did not receive funding. I have worked with hundreds of entrepreneurs, always encouraging them to show their passion for their companies and to smile and engage with their potential investors. Now there is scientific evidence to back me up.
Here’s some advice for early-stage entrepreneurs: research finds that the team you put together is the most important aspect of your business in investor decision-making and that being happy and positive about your startup is a huge subconscious signal to investors that your team includes people they want to invest in. In your presentation, immediately smile and express your enthusiasm for this opportunity, and work the backgrounds of your team members into the story early.
There are mixed messages for female entrepreneurs, however. When Hu and Ma looked at the gender composition of the teams in their study, they found that investor sensitivity to positivity affected female-only teams more intensely than male-only teams. When a female entrepreneur failed to appear positive and warm in her pitch, her chances of acceptance into the program decreased far more dramatically than her male counterpart’s. In mixed-gender teams, investors were affected by the positive visual signals from the male team members, and the facial expressions of the women didn’t seem to change the investment chances, implying that their smiles or frowns were being ignored. However, when the researchers analyzed the vocal signals, if a woman was pitching with a male colleague, the impact of her passion, enthusiasm, and energy switched and became negatively correlated with investment chances. Apparently, and sadly still, in 2021, investors prefer that women not upstage or dominate their male cofounders.
There’s advice here for early-stage investors, as well. Angel investors and venture capitalists should change their processes to gather information before meeting entrepreneurs. If investors are so quick to judge on a smile, and if this leads them to invest in underperforming companies, they should avoid face-to-face meetings until after they have done a little research. Request a one-page overview that focuses heavily on team background and company traction, and consciously overweight these criteria. To counter implicit bias, perhaps suggest that titles be used for the founders, rather than names, to avoid seeing names that give away the gender or ethnicity of the entrepreneurs. Investors, only after you assess team competency and determine whether a company fits with your portfolio should you allow yourself to fall for the founders’ dazzling smiles.
Waverly Deutsch is clinical professor at Chicago Booth and the Polsky Director of the UChicago Global Entrepreneurs Network.
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