Algorithmic purchasers: Balancing efficiency, ethics, and consumer trust

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  Quantumrun Foresight
• July 24, 2023

Insight highlights

In a world dominated by algorithmic purchasers, traditional sales and marketing strategies may lose effectiveness as algorithms prioritize rational factors like price and delivery speed. This shift could lead to a more competitive market where companies focus on improving products and services instead of appealing to emotions. Algorithmic purchasers may streamline the shopping process for consumers, but challenges include transparency, consumer distrust, and potential anticompetitive practices. 

Algorithmic purchasers context

The process of selling goods and the selling points that appeal to purchasers transform when the buyers are no longer human. In the media industry, programmatic buying utilizes different potential platforms to perfect ad placements. Meanwhile, retail uses algorithmic commerce to foresee shopping patterns based on historical consumer behavior. Giants like Amazon and Alibaba are currently employing predictive analytics to fill up customers' shopping carts before placing an order and then forward those items to distribution hubs to reduce delivery time.

Now, algorithms have taken over purchasing decisions. Although this has significant implications for sectors like high-frequency trading on Wall Street, non-human entities are managing more intricate market tasks. As customers become more trusting of these non-human buyers, they are likely to delegate even more purchasing authority, which could extend beyond merely replenishing their household necessities. They might begin to rely on algorithms to make significant decisions like when to retire or the optimal time to sell a property.

Businesses that offer goods and services must adjust their sales techniques to appeal to these sophisticated algorithms. These algorithms will likely prioritize factors like price, speed, precision, impact, and even sustainability. In a world dominated by algorithmic purchasing, buying choices will be less affected by emotional factors, such as traditional advertising strategies.

Disruptive impact

The prevalence of algorithmic purchasers may require a comprehensive overhaul of sales and marketing strategies. Traditional advertising techniques, which often rely on emotional appeal or brand loyalty, may lose effectiveness as algorithms prioritize rational factors such as price, delivery speed, and product reviews. This shift could lead to a more competitive and transparent market where companies are motivated to improve their products and services in tangible ways. It might also reduce the power of established brands and level the playing field for newer or smaller businesses, as algorithms are indifferent to brand names and more focused on objective metrics.

On the consumer side, algorithmic purchasers could streamline the shopping process, reducing the time and effort required to make purchasing decisions. Additionally, sophisticated algorithms might lead to more personalized shopping experiences as these algorithms become better at predicting individual preferences. However, there could be downsides as well. 

A significant challenge is the current lack of transparency in how these algorithms make decisions, which could lead to consumer distrust or manipulation. Large retailers are already being called out for anticompetitive strategies, such as putting their own brands first on search results. There might also be privacy concerns, as predictive algorithms often require collecting and analyzing large amounts of personal data. Governments would need to update consumer protection laws to consider how their data is being used to influence their purchases.

Implications of algorithmic purchasers

Wider implications of algorithmic purchasers may include: 

• Increased market efficiency by automating purchasing decisions, optimizing prices, and reducing transaction costs, resulting in improved business profit margins, increased competition, and potentially lower consumer prices.
• Job displacement in roles that involve manual or repetitive purchasing tasks. However, it also opens opportunities for managing and developing algorithms, data analysis, and strategic decision-making.
• Governments establishing regulations and oversight to ensure transparency, fairness, and accountability in algorithmic decision-making.
• Optimized supply chains and logistics leading to reduced waste, lower energy consumption, and minimized carbon footprints. However, increased online purchasing facilitated by algorithms may increase packaging waste and transportation emissions.
• Specific populations benefiting from personalized product recommendations based on their preferences, while others may face exclusion or limited choices due to algorithms perpetuating existing biases or discriminating against particular demographics.
• The consolidation of market power in the hands of a few dominant players. Smaller businesses may struggle to compete with larger entities with more advanced algorithms and data resources.
• Increased impulse buying because of personalized recommendations and reduced brand loyalty among consumers.

Questions to consider

• Would you prefer an algorithm to decide what you want or need to buy?
• How can businesses be regulated to ensure they don't manipulate these algorithms?