Growth of online trade in South Africa leaves millions of consumers behind during Black Friday

Black Friday is one of the largest shopping periods of the year, but for retailers, ensuring sales is only half the battle. Behind every successful online order is a team of warehouse workers who operate under tight deadlines to accurately and promptly pick, pack, and ship purchases.

As South Africans prepare for Black Friday sales and the holiday shopping season, sellers face a familiar problem: the need to ensure a sufficient number of employees ready to handle a sharp increase in demand.

Simply increasing staff numbers may not be enough. Without proper preparation, planning, and training, even a larger staff may not cope with the pressure of the peak trading season.

Seasonal hiring is often postponed until demand begins to rise, but this approach forces businesses to rush to fill vacancies as orders come in. Recruitment, candidate vetting, training, and assessment processes take time, making early planning critical for retailers who wish to avoid unnecessary delays and customer disappointment.

Black Friday creates intense competition for temporary workers, especially in warehouses and e-commerce fulfillment centers, where companies often need people for picking, packing, inventory processing, and shipping.

When multiple employers hire simultaneously, suitable candidates can be quickly taken. This narrows the pool of available talent, increases salary expectations, and makes it difficult to find workers who meet the operational needs of retailers.

Starting the hiring process well in advance gives companies more time to identify suitable candidates, confirm their availability, complete necessary documentation, and align expectations regarding shifts and duties.

It also provides an opportunity to verify whether new employees are truly ready for the demands of the job before the busiest trading days arrive.

For buyers, a delayed parcel, incorrect order, or out-of-stock item can quickly turn the excitement of a Black Friday bargain into frustration.

Behind these problems may be a warehouse team struggling to meet demand due to insufficient training of temporary workers or their lack of knowledge of the systems and processes they should follow.

Warehouse staff must understand all aspects—from using scanners and inventory management systems to adhering to picking and packing procedures, proper handling of goods, and compliance with occupational health and safety requirements.

Practical assessments also play an important role, helping employers determine if workers can accurately and at the required pace apply the knowledge they have gained.

When workers are hired before they are ready, managers and experienced staff are forced to spend valuable time correcting mistakes, providing additional instruction, and covering unfinished work. Consequences can include incorrect orders, missed shipping deadlines, damaged inventory, product returns, and customer complaints—all against a backdrop of increasing pressure to meet obligations.

The takeaway for retailers is clear: having an available employee does not guarantee that they are ready to do the job.

Retailers can also consider partnering with Temporary Employment Service (TES) providers to prepare for seasonal demand.

Instead of waiting for vacancies to arise, a recruitment partner can work with the retailer to transform forecasted order volumes into a workforce plan. This includes identifying priority roles, planning hiring and training, and ensuring workers are ready to join operational teams when needed.

A recruitment partner can also monitor workforce readiness, identify potential issues before they impact operations, and maintain a reserve pool of workers to manage absences or unexpected surges in demand.

This approach shifts the focus from simply filling vacancies to ensuring the availability of trained and reliable personnel capable of sustaining company operations.

Nevertheless, retailers must still evaluate whether their staffing decisions deliver the required results during the peak trading period, including reliable attendance, accuracy, and consistent performance.

One of the most useful ways to prepare for the holiday rush is by analyzing previous peak trading periods. Retailers can assess where delays occurred, which items were hard to fill, how long it took new employees to become productive, and whether staffing levels matched actual demand.

These insights help businesses develop a more realistic hiring and training schedule, working backward from the date their operations must run at full capacity.

It is crucial that the hiring process allows enough time for onboarding, practical evaluations, and any additional training required before temporary staff are deployed.

As Black Friday approaches, and holiday shopping creates additional pressure on order fulfillment operations, preparation cannot wait until orders start piling up.

For retailers, success is not just about having more people on staff. It is about having the right people, with the appropriate training and support, ready to accurately and consistently fulfill orders during peak demand moments.

For buyers, such preparation can be the deciding factor between a seamless online shopping experience and the frustrating wait for a long-awaited purchase.

Artificial intelligence is fundamentally changing how consumers find information online. Consequently, brands from South Africa face a critical question: how to remain or become the most visible when search engines stop providing lists of web links and start generating direct, conversational answers to user queries?

The application of AI is deeply integrated into people's lives, and among South Africans, who are the primary target audience for brands, the adoption rate is quite high. According to a recent study, 70% of adults have used an AI chatbot (Google and Ipsos data), which is significantly higher than the 45% recorded in 2023. This figure is even higher among the consumer class and white-collar workers—nearly 80% (BrandMapp 2025; BCG AI at Work 2026).

What people search for, remember, and discuss is increasingly shaped by these tools. This means that the digital footprint created by AI systems is already being formed, regardless of whether a brand intentionally contributes to it.

Global media scientist Karen Nelson-Field, founder of Amplified, is in South Africa under the auspices of The Up&Up Group to help companies navigate these changes. Last year, Nelson-Field collaborated with the media agency Connect from The Up&Up Group to conduct the country's first survey on human attention and the implementation of attention-based benchmarks in the local digital media market.

Nelson-Field's upcoming visit focuses on a provocative idea: what if the most effective way to ensure discoverability in an AI-driven search ecosystem is not just optimizing for algorithms, but also shaping human attention and memory?

Since Large Language Models (LLMs) and AI modes in search engines have changed the rules of the game, it is unsurprising that many marketers worldwide view visibility in AI purely as a technical optimization task. According to Scott Ryder, Chief Operating Officer at Connect, the problem with this approach is that it ignores the fuller picture of how generative AI models collect and synthesize information from the internet.

Digital Footprint

Ryder explains: 'AI search tools draw information from the broad environment of digital information. They index online discourse and brand presence, as well as active conversations generated by humans. We know that media experiences with a high level of attention help shape mental availability and brand memory in the human audience. What people remember, search for, and discuss online creates a digital footprint that AI systems can rely on.'

Ryder emphasizes that he does not present this viewpoint as a proven causal formula, but rather as an evolving perspective for marketers navigating the automated media landscape. He adds that the upcoming meetings will explore what this could mean for modern brand strategy, creative development, and effectiveness measurement, given the constant control over media budgets and the need to balance machine discoverability with human relevance.

Robert Grace, Chief Strategy Officer at The Up&Up Group, believes that the takeaway for brands is obvious: 'As brands appear in more and more places, they need to represent something cohesive and absolutely clear to both the algorithm and the consumer. When brands fragment their digital media across numerous niche campaigns with small budgets, weak creative, and short campaign durations, they are effectively turning their brand into a digital shard. That strategy will no longer work.'

Some topics that Nelson-Field and Connect may explore include rethinking viewability, as standard metrics do not guarantee real impact, and how measuring attention provides clearer signals about brand memory; balancing search and brand equity in an AI-mediated environment; and navigating AI discovery so that campaigns resonate with human audiences while maintaining visibility on automated platforms.

Ryder notes that contextual knowledge from empirical measurement systems, including Amplified's Attention AI technology, will enrich discussions on how attention data can help media planners assess channel quality and effectiveness. He concludes: 'It is clear there is a drive to optimize for the machine. However, we believe it is critically important to study how human attention builds the fundamental brand equity that AI systems ultimately encounter and reflect.'

When making online purchases, it often happens that the item that seemed appealing during ordering turns out to be different from what is shown in the photos upon receipt. There may be discrepancies in color, fitting issues, or simply a feeling of unnecessary possession. Some buyers return goods after almost every second online purchase, whether it's clothing, shoes, or bags. This raises the question of what underlies this behavior: a tendency toward impulsive decisions, quick decision-making, or a change in mood after the purchase?

Research in psychology and consumer behavior indicates that there can be many factors contributing to this behavior. These factors range from a habit of spontaneous buying to the product not meeting expectations. Nevertheless, one cannot conclude a person's character based solely on the habit of returning items.

Some shoppers are not inclined to think deeply while browsing. They might like an item—a dress, gadget, or pair of shoes—and immediately place an order. Often, the purchase decision is influenced by discounts, sales, or an attractive image. This type of purchasing is called impulsive, meaning it is made suddenly and without prior planning. At the moment of purchase, the delight in the item is so strong that the person does not consider the actual necessity of the item.

However, when the item arrives home, the initial enthusiasm fades, and the person may realize their mistake. They might feel they spent too much money or that the item will not be useful. As a result, they decide to return it.

Does it happen that an item was very appealing at the time of purchase, but later the thought arises that it shouldn't have been bought? In psychology, this phenomenon is called post-purchase regret. It can occur if a person feels they made a hasty decision or that the money could have been better spent elsewhere. For example, if someone buys a dress for 2000 rubles online and then finds a similar model on another site for a lower price, they might decide they overpaid. Similarly, after the purchase, a feeling of not needing the item may arise. In such cases, returning the item might seem like a simple way to change one's mind. However, the return is not always motivated by regret.

In online shopping, the customer cannot touch, try on, or use the item. The decision is made based on photos, videos, product descriptions, and reviews from other buyers. Often, the color of the item in reality differs from what is presented in the pictures. The size of the clothing may not fit, the fabric quality may be lower than expected, or the electronic device may not work as anticipated. In such circumstances, returning the item is a natural step for the customer. A study published in the Journal of Retailing and Consumer Services in 2024 identified reasons for returns such as incorrect fit, delivery problems, misleading advertising, and post-purchase disappointment. Therefore, one cannot automatically assume that a person who frequently returns items is spoiled; often, the problem lies not with the customer's decision, but with the quality of the product or the provided information.

Some people tend to look at many alternatives when choosing an item. They might choose one dress and then look at another that seems more suitable, and so on. Sometimes they order two or three identical items to compare them at home and decide which one to keep. This is especially common when buying clothes, given the potential discrepancy between the online image and the actual fit. It is important to understand why a person compares options. Perhaps they are trying to make the right choice. But if they constantly order many things and return most of them, this approach to shopping can take up a lot of time and effort.

Many buyers like the item, but after payment, they start to doubt the expediency of the expense. Consider this example: a person buys shoes worth 3000 rubles. During the order, they felt the shoes were good and the price was acceptable. However, after receiving the item, they begin to ponder whether they could have purchased a higher-quality pair for that money. In this situation, two thoughts may conflict in the person's mind: on one hand, they like the item itself, and on the other, they are trying to justify their spending.