Short-sighted about investing? Step back to take a long view

Short-sighted about investing? Step back to take a long view

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This article originally appeared on ING’s eZonomics.com

Data is everywhere – flowing through your phone, across your desktop, and even streamed beneath your favourite TV show. Thanks to mobile apps, anyone from an amateur investor to a seasoned pro can tap into data to monitor their investment portfolio in real time.

You may think that having data at your fingertips is a good thing. In some cases, however, it can harm your financial outlook. This is because frequently checking the status of your investments reduces your desire to seek risk – a necessary component of investing.

Often equated to gambling, investing involves taking a certain amount of risk in hopes of receiving a larger future gain.

Many investment portfolios and retirement funds automatically balance “safer” risks, such as bonds, with riskier investments like stocks for you to achieve the perfect balance. Convenient, right? These combinations are, in fact, a great place to start out because they reduce the risk of your whole portfolio tanking because one company performs poorly.

People often say that investing is a “long play”. Investing has earned this description since returns on market investments have a higher chance of rising over an extended period of time. While a single stock may not change much value-wise day to day, portfolios that take calculated risks over time generally provide higher rates of return.

Don’t fear the market
Reporters often talk about the movement of the markets – up or down depending on when you tune in. Don’t fear the small dips in daily performance. Being overly cautious about your financial choices because you fear a small drop in your investment is not healthy for your financial future.

Focusing heavily on these changes – for example, obsessively checking your performance, even when the markets are closed – if the market is down can instill a terrible fear of the calculated risks necessary to grow your portfolio.

This avoidance of risk when exposed to an excess of data has been dubbed “myopic loss aversion“, by famous behavioural economist Richard Thaler.

In an experiment by Thaler’s team, one group of investors were shown more market performance data than another that saw very little.

Those with access to the most data took the least risk in growing their investment portfolio for the future. And as a result their profits shrank: they made less money than everyone else in the experiment.

You might think having more data available on your finances has to be a good thing. However, Thaler and his colleagues proved that too much data can actually be harmful.

Here’s how to avoid trouble
If you want to step away from the distraction presented by large amounts of financial data, mark a date on your calendar about once every three to six months to revisit investment plans.

Checking in less often, instead of daily or weekly, will help you assess how your portfolio does over time.

Data can be totally addictive, especially when it’s readily available via your mobile phone or on social media. So try removing apps from your phone or moving investing-related apps behind others. This should make your performance data harder to reach as often. They’ll still be available when you really need them.

Another tip: read articles that focus on the broader state of the economy – not specific investing-focused ones. Taking a broader view can reduce the chance of myopic loss aversion. Separating yourself from share market performance data can improve your ability to think clearly and make better decisions.

Checking how much money is left in your wallet before payday is no fun. Neither is reviewing your investment portfolio every day.

Instead, take a break from the data and focus on the life around you. Markets can be scary enough.

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How to Effectively Leverage Behavioral Science in Market Research

How to Effectively Leverage Behavioral Science in Market Research

 

This blog originally appeared on greenbookblog.org

There is a lot of discussion in the market research community surrounding the application of behavioral science to survey research. This dialogue has challenged the insights community to address several methodological shortcomings that have long plagued the field. Such weaknesses include a general lack of predictive validity, and the inability to isolate and replicate insights outside of the survey context.

To researchers, these pitfalls often reflect the status quo. To a client, these caveats determine whether a decision based on consumer insights will become a success, or fail with spectacular fashion. The interjection of behavioral science has challenged both parties to think critically about the insight collection process and the application of valuable learnings to solve business challenges.

This change in vantage point is spurring innovation in areas that have traditionally gone unchallenged since their inception. The namesake field of behavioral science has lent the most impact to market research, more so in the rigorous approach than any specific methodologies used. At its core, behavioral science utilizes the scientific method to understand the drivers of behavior and introduce theories to guide an observed behavior towards a targeted alternative.

On a broad scale, behavioral insights are applied to reduce the consumption of unhealthy food, increase the amount of those who sign up for organ donation, and ensure that retirement funds are endowed well for the future. In the consumer context, behavioral science is used to increase the adoption or uptake of new products, and strengthen the relationship that consumers have with brands.

As the discourse on applying behavioral science to enhance the understanding of consumer behavior continues, there are three things that market researchers can do to implement a more scientific approach to their work:

1. Identify a testable hypothesis

Designing quantitative questionnaires with a pre-defined, testable hypothesis in mind ensures that the insights uncovered in the study are in line with the stated business objectives. Just as scientists develop hypotheses before testing theories in a lab setting, market researchers should work cooperatively with their clients to identify the underlying factors that answer the fundamental business question. Defining the business problem upfront and ideating solutions supports the creation of clear and concise deliverables that are actionable. Reframing research briefs from “what would we like to uncover” to “what sort of behavior do we think we can change” brings traditional market research one step closer to its social science brethren.

2. Measure actions, not an intent

Consumers struggle with predicting their behavior thirty, sixty, or ninety days into the future. This fact challenges the convention of traditional survey logic where researchers use their one touch point with consumers as a be-all, end-all data capturing moment. One way to circumvent this future prediction inability is to ask survey respondents questions that they can answer at the moment. Asking consumers to choose one product over the other in a forced choice fashion, or to “invest” game-like currency into one concept or another starts to replicate how consumer choices are made in the real world, rather than evaluating them in a speculative bubble.

3. Utilize control groups

Common reactions to this recommendation are often immediately followed by questions of: Use a control group? For what? How will that enhance my current concept testing study design? When testing concepts of any sort, utilizing control groups isolates the potential effects that a new concept may have on the parent brands’ perception. Without an unexposed control group, it is nearly impossible to identify the extent to which the concept alters brand perceptions. Control groups are a valuable addition that can help explain how well one concept iteration performs over another and the impact that it has on the brand.

There are countless crossover applications to market research one can borrow from behavioral science. The underlying scientific method-based approach ensures that there are accountability and confirmatory powers in consumer research; two components that researchers have struggled achieving in recent years when utilizing the present approach.

The first step in uncovering actionable insights is ensuring that the data patterns discovered are representative of human behavior in the marketplace. Additionally, insights should be easily replicated across large populations to ensure that the responses observed reflect how a majority of consumers will act in a given situation. Methods used in traditional online surveys should not be asked in an isolated research bubble either; instead, successful researchers must employ tools that bring the insights uncovered closer to the reality of how consumers make decisions.

Applying the three takeaways listed above is not the final chapter to this story; instead, it is where the challenge to expand the horizon of market research begins.