Applying Behavioral Science In An Organization
I often joke that if a contest for the most mysterious job title in my company existed, I would be the clear frontrunner. It seems as if every time I’m introduced to someone, I’m asked the same question: “So, exactly what do you do?”
This week marked my two year anniversary of working as a behavioral scientist in a product-driven tech company, and I still don’t have an exact answer to that question. But, having worked my way through the company, I’m now in a comfortable position to think about the question more clearly at least.
My biggest realization about this role is a double-edged sword: Behavioral science actually overlaps with many roles in product-led tech companies. That’s good because that means behavioral science is becoming increasingly relevant to everyone, irrespective of what role one is in. That’s also bad because the onus of proving the importance of a stand-alone behavioral science role is entirely on us.
Based on my experience, I’ve put together some thoughts on where product organization and behavioral science overlap, and what differentiation a behavioral scientist can bring to an organization as a whole.
Is behavioral science the same as user research?
In a generic sense, yes. User research is, rather obviously, about understanding users. Behavioral scientists do the same; yet, the nuance is in the process.
User research teams conduct qualitative research through in-depth interviews, discussions, and usability tests. They also conduct quantitative research through surveys. This research is then condensed into a form that product and design teams can consume and use for the product development.
Behavioral science research is more focused on uncovering the reasons behind why people do what they do. While interviews and surveys are useful techniques, it is more important for behavioral scientists to understand the context under which decisions are being made. Doing so helps them use that context to map and diagnose the behavior of the user. In other words, putting into words what the user cannot say. This comes not just from interviews, but from experiments and observations and conducting literature reviews of existing theories.
Can user research benefit from behavioral science?
Absolutely. If you are a user researcher and you have a behavioral scientist in your organization, integrate them into your research to help you uncover biases and blindspots that are not necessarily visible in plain sight.
Is behavioral science the same as design?
As someone who loves all things design, I wish that this answer is a yes. A designer in a product organization focuses on putting the product into a visual form, taking into account the users’ and the business’ needs. This is a highly technical process that involves immense stakeholder management and a deep understanding of how various systems interact in the backend, with the goal of producing a front-end that is simple enough for the user.
Behavioral design is a subset of design that is concerned with using design elements to affect behavior change.1 Borrowing heavily from behavioral science, this stream helps designers design for the real user — the one who is busy, inattentive, biased and not perfect, as opposed to the perfect user (who may or may not exist).
Can design benefit from behavioral science?
Absolutely. Behavioral science helps designers understand the actual user, rather than the theoretical user. If you’re a designer and you want to involve a behavioral scientist, reach out to them in the initial phases of design. They can help you understand the ‘why’ behind what people really do. It is immensely beneficial to get a behavioral scientist to audit your design from a behavioral perspective so you can uncover fail points early on in the process.
Is behavioral science the same as data science?
No. Data science is a field that analyses structured and unstructured data using machine learning and algorithms to extract useful insights, as well as predictive models.2 Data Scientists typically use mathematics, statistics, analysis, and machine learning to investigate existing patterns in data. The models that they create feed directly into products, making them smarter. For instance, if you have used Spotify and love the recommendations the app gives you, that’s the output of a data science model at work, which takes into account your music preferences and a bunch of other variables to predict what songs you might like.
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Behavioral science, on the other hand, puts the predictions of data science models into the real world and helps drive the ‘last-mile’ behavioral change.3
Can data science benefit from behavioral science?
If examples are anything to go by, then yes. The 2012 Obama presidential campaign was a groundbreaking experiment that employed data scientists to predict voter behavior, which was then used to optimize marketing resources.3 The distinctive part about the campaign was the complementary use of behavioral nudges along with data science models. The data science models could accurately predict which way a voter was likely to vote. But the campaign’s main objective was to sway voters to vote for Obama, and that’s where behavioral science comes in. The campaign team was able to get more votes in their favour by using nudges in communications towards those who were undecided, or not likely to vote for Obama. In other words, behavioral science provided the “last mile” connect that the data science models needed to reach the voter.
If you are a data scientist and you want to see your models being used to drive real behavioral change, reach out to a behavioral scientist — they might just know exactly what to do.
Is behavioral science the same as product marketing?
Not quite. Product marketing is the connection between business and product, and is a critical part of the product life cycle. Before a product is launched, product marketers create the positioning and the go-to-market strategy based on user research. During the launch, they help business teams understand the product and drive its adoption through campaigns.4
Behavioral science plays a critical role in parts of this process, such as providing a deeper understanding of the consumers’ behavior, conducting a diagnosis of the users’ current behavior to identify biases, and identifying interventions in communications that can nudge the adoption of a product.
Can product marketing benefit from behavioral science?
I’m sure you’re seeing a pattern now, but the answer is yes. Product marketing relies heavily on understanding users and creating positioning based on that. However, marketing thrives on insights, and behavioral science can help unravel insights that allow a product to be positioned better.
A simple example of this is the difference between explicit and implicit goals.5 If you are marketing a food delivery app, the explicit goal is to make it easier to order food. This is what you would learn from talking to consumers. But, if you were to dig deeper to understand the implicit goal, you might uncover the goal of “excitement” — that is, when customers order food because they want every meal to be a surprise and different from what they’ve had previously. The product positioning then changes from convenience to a more nuanced “variety with convenience”. So, if you are a product marketing manager, talk to a behavioral scientist to uncover insights that might help position the product better.
Be all, end all?
My advice seems to be that everyone in the organization should talk to behavioral scientists. But, my intent is the opposite of that. I want behavioral scientists to proactively reach out to others in their organizations to offer insights. The simple truth that runs the world is “ask, and you shall get”. A stand-alone behavioral science role comes with the responsibility of proving its value, and this will happen only and only through collaboration. So, if you are a behavioral scientist in a product organization waiting for someone to give you a project, don’t waste your time. Instead, reach out and tell others how you can add value.
References
- Cash, P., Gram Hartlev, C., & Durazo, C. B. (2017). Behavioural Design: A Process for Integrating Behaviour Change and Design. Design Studies, 48(January), 96–128.
- Dhar, V. (2013). Data science and prediction. Communications of the ACM, 56(12), 64-73.
- Guszcza, J. (2015). The last-mile problem: How data science and behavioral science can work together. Deloitte Review, 16, 65-79.
- https://www.drift.com/blog/what-is-product-marketing/
- Barden, P. P. (2013). Decoded: the science behind why we buy. John Wiley & Sons.
About the Author
Preeti Kotamarthi
Preeti Kotamarthi is the Behavioral Science Lead at Grab, the leading ride-hailing and mobile payments app in South East Asia. She has set up the behavioral practice at the company, helping product and design teams understand customer behavior and build better products. She completed her Masters in Behavioral Science from the London School of Economics and her MBA in Marketing from FMS Delhi. With more than 6 years of experience in the consumer products space, she has worked in a range of functions, from strategy and marketing to consulting for startups, including co-founding a startup in the rural space in India. Her main interest lies in popularizing behavioral design and making it a part of the product conceptualization process.
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