And the result is a new beta framework: INCITE — Inspiring Narrative Change Innovation through Tracking and Evaluation. This new learning and evaluation framework has been developed to equip the pop culture narrative change field — comprised of artists, values-aligned entertainment leaders and companies, movement leaders, cultural strategists, narrative researchers, philanthropic partners, and more — with a shared methodology to unearth learnings and track short and long-term impact, at both the individual and collective levels. This launch of the beta INCITE framework is the first step in a road testing process set to take place over 2024 to make it useful and usable by field members and funders alike.

From a process perspective, our task then becomes figuring out the optimal behavioral flow that reduces the friction between intentions and desired behaviors and stimulates progression through the journey – assuming at least a moderate interest in what is being offered by the organization.

We constructed brand names for diverse products with consonantal stricture spots either from the front to the rear of the mouth, thus inwards (e.g., BODIKA), or from the rear to the front, thus outwards (e.g., KODIBA). These muscle dynamics resemble the oral kinematics during either ingestion (inwards), which feels positive, or expectoration (outwards), which feels negative. In 7 experiments (total N = 1261), participants liked products with inward names more than products with outward names (Experiment 1), reported higher purchase intentions (Experiment 2), and higher willingness-to-pay (Experiments 3a–3c, 4, 5), with the price gain amounting to 4–13% of the average estimated product value.

The fact of the matter is that each market/user group has its own particular set of situational and psychological differences that determine which behaviors will be adopted and which will never even be attempted. The job of every product team, whether they know it or not, is to make it as easy and delightful as possible for their target market/user group to perform a behavior that they find doable, useful, compelling, and enjoyable that also leads to an important business outcome for the company. If any of these things are missing, there is no Behavior Market Fit and the project and any associated products will be a failure.

FDA/Rescue

In one of my studies I showed that first-person internally focused narratives – that is, stories with a character in first person revealing their feelings, thoughts and motivations – heightened perceived dangers of prescription opioids, aroused anticipated guilt and promoted negative attitudes toward prescription opioids among the audience.

The motivation index was informed by the FBM, which characterizes motivation as three sets of opposing constructs—acceptance/rejection, hope/fear, and pleasure/pain [14]. Applying the FBM, we coded and analyzed responses from the key informant interviews conducted in Yopougon Est. The results of this analysis were used to develop 12 items that were aligned with each FBM motivation construct.

visual representations of things that can be described by various adjectives

Ikea researchers explore Kiwi homes before opening first NZ store Christine Gough, head of interior design at Ikea Australia, is one of 40 Ikea researchers visiting hundreds of Kiwi homes to gauge what products to stock in its Auckland mega store.

Resources to help you address frictions in your government services, improving customer experience.

“significant” p-value ≠ “significant” finding: The significance of statistical evidence for the true X (i.e., statistical significance of the p-value for the estimate of the true X) says absolutely nothing about the practical/scientific significance of the true X. That is, significance of evidence is not evidence of significance. Increasing your sample size in no way increases the practical/scientific significance of your practical/scientific hypothesis. “significant” p-value = “discernible” finding: The significance of statistical evidence for the true X does tell us how well the estimate can discern the true X. That is, significance of evidence is evidence of discernibility. Increasing your sample size does increase how well your finding can discern your practical/scientific hypothesis.

Opt-in samples are about half as accurate as probability-based panels

Mercier and Sperber prefer the term “myside bias.” Humans, they point out, aren’t randomly credulous. Presented with someone else’s argument, we’re quite adept at spotting the weaknesses. Almost invariably, the positions we’re blind about are our own.

Our results show that a decadeslong effort to educate the U.S. public about recycling has succeeded in some ways but failed in others. These efforts have made recycling an option that consumers see as important – but to the detriment of more sustainable options. And it has not made people more effective recyclers.

“We don’t have a hundred biases, we have the wrong model.” So said Jason Collins in a recent blog, perhaps somewhat provocatively likening the use of biases as akin to the activity of ancient astronomers who were required to compile an exhaustive number of deviations to retain the broken model of the universe revolving around the earth. Collins challenge is whether the model at the heart of behavioural science is similarly broken.

Causal layered analysis, a theory and practice of organisational, social and civilisational change, seeks to transform the present and the future, through deconstructing and reconstructing reality at four levels. The levels are: the litany or day to day unquestioned views of reality, the systemic, the worldview/stakeholder perspective and the deepest, often unconscious, myths and metaphors. Problems are considered at all four levels and multiple worldviews and stakeholders are brought into to consider alternatives. By moving up and down layers and considering alternative perspectives, transformative policy and strategic solutions are created.

Why do we believe misinformation more easily when it’s repeated many times?

Nudging provides a way to gently influence people to change behavior towards a desired goal, e.g., by moving towards a healthier or more environmentally friendly lifestyle. Personalized and context-aware digital nudging (named smart nudging) can be a powerful tool for efficient nudging by tailoring nudges to the current situation of each individual user. However, designing smart nudges is challenging, as different users may need different supports to improve their behavior. Determining the next nudge for a specific user must be done based on the user’s current situation, abilities, and potential for improvement. In this paper, we focus on the challenge of designing the next nudge by presenting a novel classification of nudges that distinguishes between (i) nudges that are impossible for the user to follow, (ii) nudges that are unlikely to be followed, and (iii) probable nudges that the user can follow. The classification is tailored to individual users based on user profiles, current situations, and knowledge of previous behaviors. This paper describes steps in the nudge design process and a novel set of principles for designing smart nudges.

If you have ever been tasked with influencing a behaviour, you will know that it is critical to understand that behaviour in context. You need to understand the issues faced by the people affected. At BIT, we refer to the process of understanding behaviour in context as Exploring. Exploring is about discovering what people do and crucially why.

If we are to use behavioural science as a lens to understand behaviour, we need to make sure that our lens is not always ‘zoomed in’ on the individual and their immediate situation but that we also ‘zoom out,’ so that we can see the wider social, cultural, economic and political environment. When we do this, we can see more clearly how our responses and behaviours are not only the result of our individual psychology but are also socially, economically and historically situated. There is a nuanced balancing act between the individual and these wider ways in which our behaviour is shaped that will inevitably be a source of debate and disagreement.

Below, I’ll break down the three key steps to creating a compelling pitch for behavioral science. A bonus: you can put it all together in one minute or less to make a short—and sweet—sell on our amazing field.

Draft your emotional Before/During/After for each moment. Challenge yourself to superforecast how you think people will feel at each moment. Design, adjust, re-adjust. Jobs to be Done

The JTBD Canvas 2.0 is a tool to help you scope out your JTBD landscape prior to conducting field research. It frames your field of inquiry and scopes of your innovation effort. Jobs to be done

In 2022, Nick Chater and George Loewenstein published a pre-print called ‘The i-frame and the s-frame: How focusing on individual-level solutions has led behavioral public policy astray’. The paper argues that “behavioral scientists“ have focused too much on policy ideas that aim to shape individual behavior (the “i-frame“), rather than the systems in which people behave (the “s-frame“) and therefore they “may have unwittingly promoted the interests of the opponents of systemic change”. I greatly respect the authors of this article and agree with their ultimate goal of applying behavioral science to public policy more effectively. However, I find this paper to be deeply flawed and ultimately self-defeating. My concerns come in three categories.

I hope this post gives some ideas to product leads on how to use the Decision Stack as a mental model in all sorts of conversations. The stack is a really powerful coaching tool. It is a framework that helps you to discuss things like: How to achieve alignment and directional clarity across the board. Use the Stack to connect the dots. Ask why things are the way they are and how the organization is planning to reach their goals. Use it to discuss goals and where shared goals would be possible. Use it to discuss team topologies, team empowerment, and mandate.

Linguistic accessibility is important because people in a group often speak more than one language with various degrees of confidence. People also use different varieties of the same language or create their own variety. The way a language develops in a multilingual group reflects what people need and want to communicate.