adilkhan-mit

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Placebos: Fair and Lovely vs Airborne

The Fair and Lovely product brought to market by Hindustan Unilever taps into a widespread social phenomenon in India - fairer skin is more desirable. Despite a lack of scientific evidence that the product actually makes a person’s skin lighter, the product has been wildly successful. The skin cream is benefitting from a placebo effect: a belief that a change or outcome is the result of some behavior, which in reality has little or no impact. Like with Fair and Lovely, a placebo effect is particularly strong when the change or outcome is a desirable one. Outcomes that prey on physical insecurities or that suggest they will better enable individuals to conform with social norms are unsurprisingly most effective.

Another product that comes to mind when thinking of the placebo effect is Airborne. Airborne is a dietary supplement typically mixed with water that contains amino acids, electrolytes, and vitamins (amongst other things) and has long been sold as a way to prevent the common cold. However, there is no scientific evidence supporting Airborne’s claim that it is effective at preventing the cold. In fact, Airborne was successfully sued for $23 million in 2008 in a class action law suit over this very claim. Like Fair and Lovely, Airborne sought to prey on a physical insecurity, getting sick, and offer an easy solution to avoid that outcome. In the case of both Fair and Lovely and Airborne, it is interesting to see that perceived value rather than actual effectiveness is enough to generate millions of dollars in revenues. Another reminder of the adage, perception is reality.

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As we continue to live in quarantine as a result of the COVID pandemic, I recently read about a “test and trace” project being co-developed by Google, Apple and the US government to curb the spread of the disease. In short, the solution would leverage geo-location data on smartphones in combination with an app for inputting COVID test results to alert individuals if they had come in close proximity with an infected individual at any point in the last 14 days. Per Apple and Google, the solution would anonymize personally identifiable information and be disabled once the pandemic has passed.

Thinking about this solution in the context of Roger’s five factors for diffusion, I see relative advantage and compatibility having opposing effects. In terms of relative advantage, the technology enabled tracking and alert system is no doubt superior to the manual tracking and relative oblivion to exposure that people face today. Individuals are likely to want to adopt the solution because of these clear advantages. The product diffusion should benefit. Where issues arise, however, are in compatibility. Societal concerns around data privacy and doubts about the ethics of big tech companies like Google permeate the population. Such concerns could lead to poor diffusion as there are strong attitudes of distrust and skepticism around treatment of such sensitive information. Should we risk our privacy for our health? How easily will it be for Google and Apple to turn back on these tracking solutions after the pandemic has passed?

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“A practitioner’s guide to nudging” defines a nudge as any aspect of the ‘choice architecture’ that alters people’s behaviour in a predictable way, without removing any options or changing economic consequences. It proceeds to breakdown nudges on four primary criteria: one, to boost self-control or activate a desired behavior: two, externally imposed or self-imposed: three, mindful or mindless use: four, encouraging or discouraging of behavior. Upon reviewing this breakdown, I was immediately reminded of the MyFitnessPal application that I recently downloaded to help me manage my diet and caloric intake to gain weight.

In the context of the above mentioned article, MyFitnessPal is leveraging nudges to activate a desired behavior through a self-imposed, encouraging and mindful approach. The way the (free version of) MyFitnessPal works is you input some basic information about your height, weight, and activity level. You then specify your goal regarding weight gain or loss with the app ultimately spitting out a target number of calories you need to consume each day to achieve that goal by a recommended date. Where nudging comes in ties to notifications sent from the app, which are only sent when you fail to input records of your meals. For example, around 4 pm I will receive the notification showcased as the cover photo of this post. Granted, I have opted in to receiving such notifications (hence self-imposed) but so far I have found them to be an effective way of nudging me to follow my health plan.

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One of the three main points that the “Consumer Behaviour Online” article presents as distinguishing consumption behavior online from that of behavior offline is “The Choice Engine Effect”. This effect is defined as the paralysis that  consumers feel in making decisions due to the overwhelming amount of information or choices available to them. To address this issue, technology solutions have been built to do customized recommendations based on past consumer activity (e.g. other songs/movies/products you might like) or what product may best fit your needs based on response data (e.g. financial plans via robo-advisors). Another solution discussed is preference-feedback engines, which leverage digital access to peer input for driving decisions (e.g. positive or negative user feedback). These two solutions mentioned by the article are concentrated on aligning the next or pending consumer choice with past behavior. They are optimizing for “fit”.

I believe there is another form of recommendation that fits under this “Choice Engine Effect”. To give it a label, I would call it the “convenience-preference engine”. The idea is simply a recommendation solution that focuses on maximizing convenience in the next or pending consumer choice rather than fit with past behavior, choice, or peer feedback. I believe we are starting to see this solution emerge with a nice example being UberEats’ offerings of waived delivery fees for orders from restaurants already delivering in your area or get your meal in under X minutes filters. These solutions tap into convenience as the ultimate driver in consumer choice while simultaneously reducing the burden of decision making by reducing the number of options. 

Another application of this concept that comes to mind is in the retail space. Often times when shopping people are interested in clothes that will match their existing wardrobe. An idea to maximize convenience and reduce the burden of choice is visual avatars showcasing a few recommendations for clothing or accessories on previously purchased clothes, photos of uploaded clothes, or clothes in a user’s shopping cart. Such a solution could speed up the time to decision/purchase for a convenience oriented shopper.

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Adil Khan - Black and Decker

The primary issue that Black and Decker is facing in the tradesmen segment for power tools is brand perception. The company is a market leader in the industrial segment (tied with Milwaukee Electric at 20% market share) and far and away the leader in the consumer segment (market share of 45%). This success in the consumer segment, however, is having an adverse impact on Black and Decker’s success in the tradesmen segment. It is leading to a perception that B&D’s tools non-industrial tools are meant for DIY household consumers rather than more serious professionals such as carpenters, electricians, or plumbers. This sentiment is best captured in a quote from a tradesmen who was interviewed; “Black & Decker makes a good popcorn popper, and my wife just loves her Dustbuster, but I’m out here trying to make a living.” Diving deeper into the data, the attitude expressed in this quotation suggests the tradesmen’s dislike for Black and Decker tools is driven by perception rather than quality. Looking at the blinded Power Tool Product Assessment in Figure E, we see that Black and Decker ranks as having leadership quality in corded drills, cordless drivers, circular saws, chop saws, and finishing sanders, while only ranking as weak/undeveloped in belt sanders and miter saws. Despite having leadership quality in these different product types, Black and Decker’s market share in the tradesmen segment lags significantly behind that of Makita - for example, B&D has <10% share in cordless drivers compared to Akita’s 80%. This incongruity in tradesmen opinion and actual quality lead me to conclude that the fundamental issue that Black and Decker is dealing with in this segment is one of perception. My recommendation for the brand is to drop the Black and Decker name from the tradesmen product offering and rebrand under another name (e.g. DeWalt). Changing the color of the tools alone will not overcome the fact that the Black and Decker name is synonymous with consumer grade products.