Entrepreneurs, Remember the Power of a Smile

How to turn voices and facial expressions into data

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. 

Implications for entrepreneurs and investors

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.