Our Algorithmic World
We live in a world dominated by algorithms. Algorithms are basically instructions, you provide input, things occur, you get something out. An extremely simple example would be a recipe. Add flour, eggs, sugar, water, etc., bake for 30 minutes, get a cake. Algorithms are also the basis for all computing. Our computers don’t think, they execute algorithms. Google doesn’t answer our questions because it’s smart enough to ponder the answer, it runs through a complex algorithm of past inputs and outputs, language matching, and feedback in various forms to produce a (usually correct) answer.
The Changing Face of Algorithms
Algorithms have gotten significantly more complex in recent years. Netflix, YouTube, Amazon are all big names in this space. In each case, the algorithms are taking what it knows about you, running an algorithm based on its training set (what people like you have watched or purchased in the past), then recommending relevant products and entertainment. If it’s wrong what happens? You don’t make the purchase or finish the movie. This is then factored into future calculations for both you and other users. Algorithms are, therefore “trained” by accruing more and more data.
How Algorithms Help Us
This all sounds pretty good, right? For the most part, it is. It’s been estimated that the average adult makes between 30 to 35 thousand decisions a day. Decision fatigue is a real and well-studied area of psychology. Algorithms allow us to take some of that decision-making load off us. We don’t want to search through all of Netflix’s libraries to select a movie, we’d rather have a choice of 10 movies that we are likely to enjoy. This sums nicely a not-so-well-known axiom in marketing, ‘people don’t want more choice, they want greater confidence in the choices they are making’. We at CreatorDB go to great lengths to give marketing agencies and brands greater confidence via our platform’s algorithms.
Can Algorithms Hurt Us?
Giving algorithms this much control over our lives may have its downsides. It’s a given that Facebook & Twitter (among MANY others) train their algorithms to maximize time spent using their services. They don’t try and maximize happiness, connectedness, or wellbeing. They only care for hours of eyeballs. What was the result of these platforms having this goal then? Well, it turns out what catches people’s attention more than anything is an outrage. Content that caused negative emotions were more likely to be commented on, shared, and viewed leading to it being presented more often in a vicious cycle. The result of this “optimization” is being felt in a real way with the widespread political divisiveness we see today. And we haven’t touched on the correlation between social media use and mental health.
Algorithms in Commerce
E-commerce was a giant leap forward compared with its bricks-and-mortar predecessor. Removing the need to stagger around the brightly lit corporate hellscapes of most major retail chains was a huge boon, people quickly grew to love online shopping. Off the back of this, we saw the introduction of one-click ordering, further removing the barriers to purchase. The convenience was staggering, we became addicted to spending, and Amazon (the clear winner here) started gobbling up market share like crazy. Can we go further though? Can we get to an even less frictionless purchasing experience?
We’ve covered TikTok and will continue to do so for a good reason, it’s got the best algorithm in the game. TikTok more than any other social media platform is able to serve up content bites fit for any palette. The fast-paced short-length nature of the content means that it very quickly is able to build a profile on your tastes through the feedback you provide in the form of likes, follows, and time watched. Scott “Prof G” Galloway coined the term ‘Signal Liquidity’ to describe the speed at which algorithms learn. In this case, TikTok has far higher signal liquidity than say Netflix. If you haven’t already played with TikTok give it a try, it’s really quite remarkable. TikTok has dabbled with e-commerce via live events with direct links to Walmart products being shown off. This is an interesting concept and one likely to see success in the near future. More interesting however is the partnership between Walmart and TikTok.
The Future of E-commerce & A-commerce
It’s exciting to consider the further possibilities of a long-term partnership between Walmart and TikTok. What if we apply TikTok’s algorithms to Walmart’s products and fulfillment networks, zero-click commerce becomes possible. What would this look like though? Let’s begin with food. Get customers to like and swipe on food products that they enjoy cooking and eating using TikTok’s usual user-friendly interface. After around 30 minutes Walmart will have a solid profile of what it takes to feed you. The next step is for customers to subscribe to a thrice-weekly box of goods, they’ll get everything they need to feed the family for the week with this. Finally, any unused items are returned to Walmart in the same boxes, providing further training for the selection algorithm. Very quickly your weekly shopping will be purchasing itself without a single required click. You’ve freed up thousands of decisions across your week to be better served elsewhere in your life.
The Real Kicker
If you’re not already convinced, let me hammer home the point by saying that purchasing your groceries in this way will give you incredible savings. The reason here is three-fold. First, Walmart will be able to much more accurately purchase the required amount of goods from suppliers, cutting waste (yay environment), and therefore reducing the price. Secondly, market investors go beserk recurring revenue. Most retail chains are valued at 2-3 times their revenue, companies with recurring revenue in the form of subscriptions (Netflix for example) achieve significantly higher valuations, often more than 10x. What does this mean for Walmart, it means doubling or tripling their market valuation – making them flush with cheap capital (aka cash) to further innovate, negotiate, and pass on further savings. This is why you see every product from toiletries to underwear moving to recurring revenue models. Finally, time is money. It takes time to drive to the grocery store, shamble around, decide what to buy, check out, then drive home. At the US median wage of $19 an hour, this amounts to over a thousand dollars a year of saved time. This frees you up to make more money elsewhere, or increase your leisure time.
There really is no fighting against the tides of change. Once this hits markets and the user base reaches a critical mass for the savings and algorithmic predictions to be fully realized, you won’t want to say no.
*Be sure to check out the Prof G remarkably insightful podcast. This post was inspired in large part by Episode 28 – Algorithmic Commerce