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Bias case study for investment analysis...

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Introduction The rise in popularity of online shopping has led to the emergence of a highly competitive economic environment. To succeed as an e-commerce business, it is vital to understand consumer behaviours, motives, and intentions. The online shopping company Wish.com, has implemented features based on customer behaviour to increase purchases made through their site and app. Wish was founded in 2010 by former google developer Peter Szulczewski and former Yahoo developer Danny Zhang. Last year, the company had upwards of $1 billion in annual revenue and was the number 1 shopping app in 42 countries. It is an e-commerce site and app where users can browse and purchase products directly from their manufacturers. This allows Wish to sell their products very cheaply. Wish’s strategy is to use behavioural finance to draw in customers who make impulse spending decisions. Research shows shoppers on Wish open the app with the intention of browsing, not searching with the intention of buying. From their data, 9 out of 10 purchases on Wish.com do not begin with a search query. This is unlike competitors such as Amazon where consumers have a product in mind 67% of the time. Wish have used spending biases to their advantage and have tailored the online browsing experience for snap decisions. Wish has an incentive to increase impulse purchases and have considered the spending biases of its users. This includes the present biased preference, the consumers tendency to overestimate self-control, price anchoring and the purchasing behaviour of its users.

Screenshot taken from Wish.com

Present bias Users of the Wish app like browsing through the fun and different products on sale. They are drawn to the high discounts on display and will buy products despite not having a need for them. The products arrive weeks to months after the purchase date, at which point the product may not serve a useful purpose. The experience of browsing through Wish is entertaining due to the often weird nature of the products and buying products on sale has been shown to trigger a sensation of instant gratification. This is due to the neurotransmitter dopamine being released when consumers see sale items when shopping. Dopamine helps control the reward and pleasure centres of the brain. Therefore, this can be seen as a present bias, as consumers prefer to have the instant gratification of browsing and buying items on sale with little regard to their future need of the products. Wish collects complex analytic data based on users browsing history, social media use, and the ads that consumers click to provide personalised feeds and product recommendations, targeting users desire to buy items at discount, which justifies their purchase and satisfaction resulting from the purchase. Wish also has a feature where a user can spin a daily wheel to win discounts. This can result in more dopamine surges. The feeling of wellbeing is associated with browsing and thinking about buying instead of the buying itself. When users first sign up, they are encouraged to log in every day to receive a stamp. If they receive 7 stamps, they can receive an additional 50% off. This encourages a habit of logging in daily and getting satisfaction from the online platform.

Screenshots taken from Wish.com

Restraint Bias As discussed previously, most people go to Wish with no intention of purchasing something. Wish has positioned their app as a browsing experience as opposed to a shopping experience. Browsers have the illusion of control. They enjoy scrolling though the apps continuous feed, and if they are to purchase something, it is most likely on a whim. Amazon based its business around ease of purchasing and receiving a product a client needs, whereas Wish focuses its efforts on its browsing experience and impulse purchases. People have a tendency to overestimate their control over impulsive behaviour. This inflated self-control leads users to expose themselves to more temptation in the form of using the app, which leads to greater impulsiveness. Wish’s app is designed to increase impulse buying, targeting behaviours such as the bandwagon effect, and the scarcity effect.

Bandwagon Effect – People have been found to adopt behaviours, styles, and attitudes which align to those of a group. The perception that other people are doing something has a significant effect on a person’s choices. Studies have found that people are more likely to trust a product with many mediocre reviews, then a product with only a few good reviews. Wish plays into this by displaying the number of people who have bought a product on high turnover listings. See example, ‘20000+ have bought this’. Wish also rewards buyers with ‘points’ if they make reviews and upload photos. These points can be applied as discounts on further products. They do this so people are more likely to trust a product, as they can see that many people have bought the product also.

Scarcity Effect – Wish uses strategies on their site and app with creates a false sense of urgency. People tend to place

higher value on products which are perceived to be scarce. This plays into a person’s cognitive fear of missing out and regret bias. Users do not want to miss the deal and regret not buying the product when they had the chance. This can lead users to impulsively purchase an item. Tactics used by Wish include: ‘Almost Gone!’, ‘Limited Quantity Deal’, ‘Buy now for cheaper price’ and having discounts which can be unlocked and are only available for a certain amount of time.

Price Anchoring - An arbitrary number can influence a person’s ideal price by “anchoring” them to that number. Anchoring is a cognitive bias where someone bases their judgements and decisions based on an initial number, in this case price. Wish uses this in two ways; by displaying related products, and by using heavily discounted products.

Related products – when a user click on a product they could potentially be interested in, the Wish site/app allows the user to see all the related products. In the example below, the laptop case is listed as $11. The related items page displays additional products, including the same laptop case for $6 and $7. To the user, the $6 and $7 laptop case, seem like a much better price compared to the $11 product, which was the first one users will find. This comparison to the original $11 is what makes the $6 listing more desirable. Numbers shape what we are willing to pay for product and related products. Clicking though Wish and finding cheaper related products increases chances of the customer to impulse buy.

Discounting – Wish also heavily discounts most of their products. The original prices on many of their products seem to be arbitrary numbers. The ‘regular’ higher price is contrasted with the lower sale price. Shoppers are seeing products with 50-99% off tags even though the original price listed might seem far higher than what that product is worth. The original high price however can subconsciously increase the consumers internal reference price. In the example above, we can see that the price $34 is crossed out, and by comparison, the discount price $6 seems much lower in comparison.

Purchasing behaviour – using credit card and purchasing items one at a time In order to purchase products from online shopping sites such as Wish, buyers need to use purchasing methods such as credit/debit cards, pay pal, or after pay. These methods of purchase mean that buyers do not see the exchange of money and therefore are less concerned with spending money. It has been found that overspending is more likely when shopping online versus in a brick and mortar store. Unlike many other online shopping platforms, Wish has a set delivery price per product. This means that once a customer decides to purchase a product, they can do so straight away. They don’t need to add it to their carts while they browse for other products, as there is no delivery savings of having multiple items together. This lowers the chance of consumers placing items in their carts and not purchasing the product. It also means they are more likely to buy more products as they don’t see the total price of each purchase. (5 items of $6 seems cheaper than $30.) Wish also incentivises this ‘buy now’ purchasing behaviour, by making the product cheaper if a user buys it in the next few minutes. See screenshot.

Conclusion These decision making behaviours outlined are critical for the success of the company Wish. Wish relies on the unplanned purchases of its users and use the mentioned strategies to increase impulsive buying. It is through these behaviours Wish has managed to be such a successful business today....