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Navigating Waves: How Exogenous Factors like the COVID-19 Pandemic Shape Product Adoption

There are many things that impact product adoption and diffusion, as mentioned in this week's reading. Those include but are not limited to:

1. the product itself (is it designed well? is it significantly better than other alternatives? does it address a new or existing customer need?)

2. the market fit (is the company targeting the right audience with this product? is the price of the product appropriate for that audience? is the product being offered in the right stores to reach those consumers? are they talking about the product in the right way?)

3. the competitive landscape (are there competing products and services that may impact adoption rates? is this product competitively priced? how does our marketing compare to competitors?)

A fourth factor that did not come up in the reading but can impact product adoption rates just as much, if not more, than the aforementioned factors are what I will call "exogenous factors". These include things like geopolitical events or natural disasters/crises, which can in turn impact both customer sentiment and also customer needs/priorities. One prime example of this is the COVID-19 pandemic.

Peloton is one brand that was well positioned for a global pandemic. Its product was able to offer a home workout solution for millions of people who were now no longer able to go to gyms or workout classes. What followed was a huge increase in adoption rates for the fitness app. This is an example of how exogenous factors (such as a global pandemic) can impact adoption of a product or service -- either for the positive or for the negative. While Peloton road the pandemic wave, they have been hit hard by a "return to normalcy", as subscribers have dropped off.

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Nudges: Influencing Customer Behavior Online

As described in the reading, a nudge is something "that alters people's behaviour in a predictable way, without removing any options or significantly changing economic consequences".

Having worked in e-commerce before, this is a very familiar concept. I have included a series of examples of where e-commerce companies tend to use nudges to influence customers.

Surfacing Own-Brand Products in Preferential Locations: You will notice that this is common on Amazon. Usually throughout the homepage, department pages, or when you navigate to a particular product, you will find an option to select from Amazon's collection

Defaulting into a Preferred Shipping Method: This is another one that you will find on Amazon. Oftentimes retailers will default you into a more expensive/faster shipping method. While they do not restrict your choices, you will have to take an action to change to the free/slower shipping option.

Nudging You To Log In Rather than use Guest Checkout: E-commerce sites like to encourage you to log in in order to build loyalty. You will notice that Amazon does this through copy like "See personalized recommendations - sign in", "Enjoy fast, free delivery, exclusive deals, and award-winning movies & TV shows with Prime", and "Try Prime and start saving today with fast, free delivery".

Encouraging Repeat Purchases: Amazon's "Subscribe & Save" feature is a lot like the gym membership example that we read about. Rather than having people make a one-time purchase of something like toilet paper, Amazon defaults them into the "Subscribe & Save" method, where customers choose how often the product should be delivered. While the customer gets a slight discount from using this method, they will be automatically making future purchased and have to actively remember to cancel in the event that it is not needed.

There are many more examples of nudges in the e-commerce space. The above list is just an example of how minor visual adjustments, copy edits, and customer features can completely shift customer behavior.

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Customer Journey Maps to Optimize the e-Commerce Experience

In my time before Sloan, I worked on the A/B Testing team at an e-commerce company. It was our role to run controlled experiments on anything that was being proposed as a change on the website (product or shipping prices, sort algorithms, new customer features, content, promotions, etc.). While some of the items for testing came to us from other parts of the business, another part of our job was to ideate on changes and new features to test. In order to come up with ideas, it was very important to understand the different user journey. If our goal was to optimize for the customer, reduce friction, make it easier to find products and check out, we had to understand more about what the many user journeys to get to the website looked like, as well as the different motivations of customers once there.

The two below scenarios show how two different customers can be at very different stages of the user journey when they arrive at an e-commerce platform. Our team worked on testing different features and content based on what we knew about the different entry pages and types of customers using them.

Customers arriving to a product page from search - these customers, unlike the other options below, might not know much about the company. They were probably searching for a specific product on Google and got linked to something that fit the bill on our website. We should make sure that in addition to surfacing that product and plenty of information about it, that we surface relevant information about our brand and its reliability (reviews, return policy, testimonials from others who have shopped there, etc)

2. Customers arriving from the email channel - these customers are already signed up through our email list, and are probably some of our most loyal. They are familiar with the company and brand and have likely placed an order in the past (given that is the most common way to sign up for the email distro). When they arrive on site, rather than making them familiar with the brand, we should try to surface new product offerings to encourage a repeat purchase! We also know the types of gear they have purchased in the past, so we can use that to offer up products of interest.

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Modelo: Becoming a Market Leader in Imported Beer

Modelo had become the market leader in the beer industry in its native Mexico already by 1956; however, extending this success to other foreign markets posed a new challenge for the company. The below sections indicate how Modelo achieved success in being one of the top importers of beers in each of the markets that it entered.

Strategic Choice of Countries and Cities to Target: When deciding which countries to export to, Modelo looked to three measures: 1. total beer consumption in that country, 2. share of beer imports, and 3. existence of a Mexican food retail market. This ensured that the country would be a good fit for the Modelo brand before even entering the market.

Selecting Good Importers: The next strategic advantage that Modelo had was choosing the right importers of their beer. As the case mentioned, "selecting a good importer is like choosing a good host family to send your children overseas". These importers bought the beer from Modelo at the point of origin, handling shipping and import of the beer and managing distribution within the country. The importers also handled their own advertising, which Modelo financed half of and received approval over. This guaranteed consistency in advertising message.

Brand Positioning: The next step that set Modelo apart was its brand positioning in its advertising. The company emphasized that its beers were of foreign origin, and 100% made in Mexico, foreign origin. This was at a time when the consumption of experimental and foreign beers was increasing, and a potential sign of status. As a result, Modelo's beers were priced at a premium in the U.S. and other markets. Their advertisements focused on the theme of pleasant times spent in Mexico to reinforce this positioning.

Identifying their Target Audience: Finally, Modelo did a good job of identifying and catering to its target audience. When they started to import to the United States, they began with cities bordering Mexico and specifically honed in on those that had high university populations (San Diego, Austin, etc). This aligns with market research indicating that imported beer drinkers were more often younger, more affluent, and having a higher level of education. Starting with these cities then made it easier to branch out to other cities of the United States once they had established a presence. Research had indicated that these foreign beers were more often consumed on-premise rather than off, so promotions focused on on-premise consumption in restaurants, bars, and discos.

The combination of the above factors, as well as operational execution, allowed Modelo to become a top contender in beer imports in each of the markets that it entered.