Beginning last October, Brooks Bell and Irrational Labs teamed up to tackle the topic of Behavioral Economics through a six-part blog series exploring the basics of behavioral economics and providing tips to help you apply it in your experimentation program. In this final blog, we’re going to revisit some of the big takeaways from each post.
Read more. Test more. The first step to understanding social science is to appreciate the complexities of humans. There is no ‘one size fits all’ solution to any problem.
In this post, we introduced you to Kristen Berman, co-founder of Irrational Labs. Irrational Labs uses the power of behavioral economics for good: helping companies improve the world by saving people money, encouraging healthy living, among other things. They often publish their findings in academic journals.
Here at Brooks Bell, we encourage the use of behavioral economics to understand customers, applying these principles to guide digital experimentation strategies.
Despite these two distinct applications of behavioral economics, our processes for implementing them are incredibly similar.
Expert intuition is not always correct. It’s important to use data and behavioral economics to better understand your users and their motivations – and experiment from there.
Although both Kristen and I have run thousands of experiments between us, even we get caught off guard by test results from time to time. In this post, we shared examples of experiments that kept us guessing–highlighting one of Irrational Labs’ Google Adwords promotions and a test we ran on behalf of one of our clients, the Jimmy V Foundation.
Behavioral economics enables you to better understand the intricacies of human decision making–even when people’s actions surprise you. Applying this to testing gives you the best chance at creating a successful experience for your customers.
And while there’s no universal template for designing a customer experience, there’s a huge opportunity to test into the experience that works best for your customers. These examples highlighted the importance of having an experimental mindset rather than relying on your intuition.
Post 3: Create a Powerhouse Methodology Using Quantitative and Qualitative Data Alongside Behavioral Economics
The only way to know if something affects another thing is to do a controlled trial.
This post detailed two different approaches to bringing quantitative data, qualitative data and behavioral economics together to create a powerhouse ideation methodology.
Brooks Bell and Irrational Labs’ approaches to ideation are very similar, differing only in structure and terminology.
At Brooks Bell, we use an iterative, five-part structure that begins with pre-strategy data, dives into user needs, problem/opportunity identification and experiment brainstorming, and finally ends with a prioritization process. Behavioral Economics is engrained throughout the process but takes center stage during the problem/opportunity identification as well as the experiment brainstorm.
Irrational Labs’ process begins with a literature review, followed by a quantitative data study and qualitative feedback. Then they run their controlled trial (a.k.a. an A/B test).
Of course, applying these processes into your organization depends on your resources, timeline and many other factors.
If you’re unsure where to start, let’s talk! Brooks Bell has years of experience building world-class testing programs and can help you build and implement an ideation methodology that’s specific to your team and your business goals.
When we understand the power that companies have over our decisions, it becomes unethical when they do NOT experiment on their users.
In this post, we examined the topic of ethical experimentation: is it always right to experiment on your users? And how do you ensure you’re testing in the customer’s best interests?
Central to this debate is the imbalance of power between a company and its customers. Companies need to drive profit, and while driving profit may drive customer value, there are some situations where it could drive high prices and/or negative customer value. The most famous example of this? The tobacco industry.
But not experimenting is not an option. If a company doesn’t test a feature, it means they think the engineer who first designed the feature got it 100% right. This means the power to influence our decisions lies with the engineer who designed the feature and did so without any data on how the feature is influencing the end user.
So, how do you design a system to ensure noble intent with your experiments? First, focus on building tests with short-term and long-term value. Be transparent about your experiments. Online dating service, OK Cupid, for example, openly uses its customer data for research and publishes summaries of the insights.
Finally, give customers a means of public recourse if they feel they’ve been wronged. This not only empowers the user but also shows that your company prioritizes customer relationships over reputation or profit.
If you get familiar with [behavioral] principles…your digital experiments are going to be more inspired, and better-informed than ever.
There are decades of behavioral science experiments at your fingertips that can be leveraged to better inform your digital experiments. This post highlighted a few of them, including social proof, choice overload, goal gradient hypothesis and the sunk cost fallacy (among others).
We also provided a few tips and tricks to help you and your team become more familiar with these principles, with additional links to various resources (including one of my personal favorites, Dan Ariely’s Irrational Game).
We had a lot of fun creating this series and hope you found it valuable. If you have additional thoughts or questions about behavioral economics and how to apply the principles to experimentation, let us know! We’d love to help!
Suzi Tripp, Sr. Director of Experimentation Strategy
At Brooks Bell, Suzi sets the course of action for impact-driving programs while working to ensure the team is utilizing and advancing our test ideation methodology to incorporate quantitative data, qualitative data, and behavioral economics principles. She has over 14 years of experience in the industry and areas of expertise include strategy, digital, communications, and client service. Suzi has a BS in Business Management with a concentration in marketing from North Carolina State.
Kristen Berman, Co-founder of Irrational Labs, Author, Advisor & Public Speaker
Kristen helps companies and nonprofits understand and leverage behavioral economics to increase the health, wealth and happiness of their users. She also led the behavioral economics group at Google, a group that touches over 26 teams across Google, and hosts ones of the top behavioral change conferences globally, StartupOnomics. She co-authored a series of workbooks called Hacking Human Nature for Good: A practical guide to changing behavior, with Dan Ariely. These workbooks are being used at companies like Google, Intuit, Neflix, Fidelity, Lending Club for business strategy and design work. Before designing, testing and scaling products that use behavioral economics, Kristen was a Sr. product manager at Intuit and camera startup, Lytro. Kristen is an advisor for Loop Commerce, Code For America Accelerator and the Genr8tor Incubator and has spoke at Google, Facebook, Fidelity, Equifax, Stanford, Bay Area Computer Human Interaction seminar and more.