AI is a foundational technology in the retail sector. Deployed to enhance personalisation, operational efficiency and optimise workflows and planning, AI solutions are rapidly becoming practical, enterprise-scale deployments that allow for deeper human-machine collaboration and customer satisfaction.

They’re also proving critical to ensuring retailers remain ahead of evolving customer expectations and accelerating ecommerce growth – global ecommerce retail sales are expected to reach $3.52 trillion this year, accounting for nearly a quarter of all retail sales.

Behind the sleek storefront apps and loyalty platforms, however, lies a fragile reality. Many retailers are weighed down by brittle code, outdated processes and development cycles that can’t keep up with demand.

This knocks into reliability and resilience. When core systems are held back by inefficiencies or poor code quality, the impact is immediate.

Outages at point of sale, delays in stock updates or sluggish online checkouts translate into frustrated customers and lost revenue.

The high cost of poor code

It’s easy to underestimate the amount of time and budget consumed by preventable errors in code. Manual requirement gathering, repetitive documentation and lengthy review processes slow projects down before a single line of value-adding functionality is even deployed.

However, retailers want their projects delivered in months at a high quality so they don’t risk falling behind competitors that can launch their new loyalty features, adapt their pricing models and respond swiftly to operational disruptions.

It’s a balancing act. Retailers need the speed of service delivery, but they can’t risk that this comes at the cost of reliability.

They’re running in a race they didn’t choose with horses they didn’t buy against competitors who want to win the whole track.

Projects that stretched over 18 months are expected in three to six, and they have to deliver new features, stabilise old systems and do it without adding costs or risks. And without compromising on quality of delivery.

In retail, mistakes, poor quality and bottlenecks cost more than time. They erode customer loyalty and trust and result in lost sales. The irony isn’t lost on most – at the very moment retailers need to be fast, their systems make them slow.

A new layer in the development chain

The good news is that AI is changing the narrative. Chatbots can distil hours of discussion into structured requirement documents which provide product teams with a head start.

In design, AI can generate architecture diagrams and build estimation tools in days compared to the usual weeks. And, in development, automated code reviewing tools are capable of inspecting every line, flagging risks and suggesting fixes, while MCP (model code protocol) is changing how different AI tools work together to achieve specific results.

The best part is that they don’t tire and they maintain the momentum needed by retailers to compete effectively in the current market.

These tools don’t replace development teams, they instead remove friction, reduce repetition and help companies build stronger code foundations.

Human-machine collaboration

For retailers, these developments mean that projects land faster and features reach customers sooner. The systems that run stores and ecommerce platforms are more resilient, and code quality becomes inherent.

The AI in tandem with developers and decision-makers smooths over the rocky complexity that comes with most development cycles by reducing effort and errors.

Staying up to date with the AI trends as they evolve and grow is essential, ensuring that tools add value to clients beyond simplifying manual efforts.

The goal is to embed AI carefully throughout the product development lifecycle and to validate outputs with human oversight, ensuring that security and ethics remain non-negotiable.

In practice, this means fewer defects in production and more predictable delivery with systems capable of scaling reliably across every store node.

AI’s role in software delivery in retail is still maturing with different tools serving different functions. Today, the smartest approach is to combine them. Tomorrow, emerging standards will allow AI agents to chain tasks seamlessly from requirement to deployment.

As AI evolves, retailers need to rely on trusted partners capable of strengthening their systems, so they are in a position to innovate and adapt quickly.

AI is already changing how retail systems are built and maintained. The tools will evolve, but the direction is clearly towards software that adapts quickly, scales reliably and is delivered at pace.

For leaders, the decision is whether to tackle that future now or be forced to catch up later. Retail resilience, and retail growth, will depend on the strength of the code beneath the surface.

According to the group, these charges have gone beyond hurting business margins to also suppressing innovation and weakening Europe’s competitive edge in global trade.

The retailers, including Amazon, Carrefour, Ikea, Marks & Spencer and others, sent a joint letter to the European Commission on 13 May, with a message that Visa and Mastercard’s pricing model is out of control, and regulators have been too slow to act.

“International Card Schemes (ICS) have been able to increase their fees without competitive challenge or regulatory scrutiny. They have also rendered their system of fees and rules so complex and opaque that players are unable to understand, let alone challenge, what they are paying for and why,” the letter stated.

Visa and Mastercard, both U.S.-based, control around two-thirds of all card payments within the eurozone. For years, European businesses have spoken up about how these firms calculate and increase their transaction fees.

However, the issue has taken on new urgency, with many accusing the companies of using their market position to avoid transparency and sidestep competition.

A study published this year by The Brattle Group revealed that fees charged by ICSs increased by 33.9% between 2018 and 2022, averaging 7.6% annually. This sharp rise, they say, has not been matched by any improvement in services offered to merchants or consumers.

In response, a Visa spokesperson, who spoke to Reuters, defended the company’s fee structure, saying, “This includes extremely high levels of security and fraud prevention, near-perfect operational resilience and reliability, and a wide range of consumer protections and high-quality, innovative products and services that serve consumer and merchant needs.” Mastercard, on the other hand, has not provided any response.

The retailers want immediate regulatory moves under EU antitrust laws, stronger enforcement around interchange fee rules, clear disclosure requirements, and an independent regulatory tool that can oversee actions taken by card payment networks.

This also highlights deeper structural concerns. As the EU drags its feet on implementing a digital euro, a move aimed at reducing reliance on U.S. payment networks, businesses are left absorbing higher costs without alternatives.

The European Commission’s slow progress on this front has angered both policymakers and the private sector, who say Europe’s digital sovereignty is being compromised.

Meanwhile, the concerns raised reiterate regulatory moves in other markets. In Nigeria, the Central Bank is rolling out the Payment System Vision 2025 to enhance digital payment security, promote financial inclusion, and ensure fairness in transaction fees.

Nigerian regulators are already reviewing switching platforms to make sure pricing is transparent and competitive.

Europe’s situation, by contrast, shows how slow regulatory inertia can allow monopolies to tighten their grip. 

Black Friday is not just about immediate sales, it lays the groundwork for long-term customer relationships.

It’s an opportunity to showcase a brand, test new products, and gather invaluable data on consumer behaviour. However, in the mad rush things can, and do go wrong, which means a solid data strategy is non-negotiable.

Black Friday 2024 is a good time to reflect on how retailers can shift from being on the back foot to using the period as a successful launching pad.

Those that enjoy the promise and potential of Black Friday promotions have one thing in common, they work with reputable data partners and implement a well-governed, secure data platform.

They learn the right lessons and make correct, data-driven decisions to improve performance during the Black Friday period.

A few retailers, who have successfully implemented robust data platforms and processes with data specialist partner Insight Consulting, have shared their experiences on how to effectively manage Black Friday campaigns. Key themes emerge, each with the effective management of data front and centre.

Data-driven forecasting

First, there needs to be accurate data-driven forecasting. Here, retailers rely on historical data to predict future demand, and this is crucial for extraordinary periods like Black Friday.

Shaun Michaels, head of Data at Bash, says:

“Data is the cornerstone of our planning, monitoring, management, and decision-making processes. It empowers us to scale our business, roll out valuable features, and ultimately keep delighting our customers, even during the busiest times.”

He adds that the business’s app and web traffic, along with order volumes, soar to new highs over the Black Friday period.

Steve Pearson, head of Supply Chain at Retailability believes data is fundamental to accurate forecasting.

“How can you do any forecasting without data?” he asks, adding that the data they analyse includes: “Previous sales, transaction attributes such as promotions and markdowns, top-line budgets to be met, and more. We check previous Black Friday trends, and then factor in pay days, as well as the nature of the promotions used previously which determine the uplift”

Muhammad Omar, director at Toys R Us says their business uses historic item trend analysis and Black Friday item sales history to forecast accurately, and Jennalee Callister, Merchandise Manager at Toys R Us adds that they “Assess current stock levels and compare it with historical sales data to determine optimal stock levels.”

Inventory optimisation

As all retailers would know, the Black Friday promotion period is crammed into a short space of time, making effective inventory management crucial. Here, successful retailers use data to determine optimal stock levels, allocate stock to different channels based on demand, and monitor real-time inventory levels.

“By reviewing turnover rates and current stock levels, data should be able to allow us to identify slow-moving items and determine to mark down or find replacements on lines that are moving above predicted sales rate,” says Toys R Us’s Callister.

Pearson says Retailability uses data for longer-term stock management, which effectively manages the Black Friday rush. “Inventory has a longer term view so it can’t be controlled on the day. It may determine what promotions we load if we want to get rid of certain stock, but we typically take a punt on certain stock for the season rather than  build extra for Black Friday specifically”.

Real-time performance tracking

Real-time monitoring of key metrics, such as sales, revenue and conversion rates allows retailers to make timely adjustments on the day, while also optimising their strategies with an eye on the future.

Michaels from Bash says real-time data is essential for smooth running on the day. “Engineering, operations and marketing teams are glued to real-time dashboards during Black Friday. They’re actively monitoring our infrastructure and services, sessions, number of orders, sales values, margin and more,” he says.

This speaks to real-time decision making and how a strong platform, working off clean data, enables cross-functional collaboration. This intelligence informs strategies that are based on accurate, actionable insights.

Omar says that real-time data analysis is important in Toys R Us’s management of Black Friday. “We closely monitor our data to measure unit sales against forecast, value sales against forecast, sales by hour versus the prior year and Black Friday promotion items as a percentage of total sales for the day.” It is clear how these types of insights inform planning and decision-making for future successful Black Friday campaigns.

Customer feedback and analysis

If we appreciate that Black Friday is about more than just higher sales volumes for a specific campaign and crucial to attracting and retaining customers, then listening to them is non-negotiable.

By analysing customer feedback, retailers can identify areas for improvement to enhance the overall customer experience.

“Customer feedback is a very important data source that we actively utilise to identify pain points and improve our customer experience,” says Bash’s Michaels.

Omar says Toys R Us continuously analyses what its customers are saying via various channels to ensure a good customer experience, including “feedback from our operations team, internal audits, marketing channels, and CRM.”

South Africa’s interest in Black Friday has been higher this year than during any of the three prior editions, according to research from the Bureau of Market Research.

Over and above this, a recent news article said the annual discount bonanza would boost the economy to the tune of R88bn, comprising what its source says includes R22-billion from direct retailer revenue, R28-billion in indirect economic impact, R32,1-billion from the wholesale sector and an another R6,2-billion in fuel sales.

That’s a lot of payments in a fairly short period. Black Friday is no doubt a highlight of the retail calendar. However, it is no longer a day.

In many cases it has expanded to Black November. Beyond this, looking at trends in the sector, there’s a spillover now between November and the classic festive season.

This means that the last quarter – especially for retailers selling bigger ticket items such as appliances – is a peak period where under-pressure consumers are waiting for the end of the year to look for bargains, either in the form of Black Friday deals or Christmas specials.

This bottleneck puts pressure on retailers to carefully manage an array of moving parts, all while trying to uphold a positive customer experience.

In a dynamic retail environment, with so many considerations from supply chains to fulfillment, an omnichannel payment platform managed by a specialist partner shouldn’t be one of the things stressing retailers.

It should already be fully under control, freeing the business to work on its business: delighting customers so it sells more inventory.

Imagine the following scenario, which is a real-world example: Someone goes online and sees a good deal for a dishwasher. It falls within a set budget and so the customer makes an online purchase.

The customer, who doesn’t live in one of the major hubs, accepts that delivery will take a week or more. If the payment doesn’t work, the customer can, and will, go elsewhere. Game over.

However, in our scenario, payment goes smoothly. Then, just before the item is meant to be delivered, the customer is contacted and told the business cannot fulfill the order as there is no stock.

The customer is offered a credit or a refund, which is extra admin. If refunded, when will he get his money? And what if he does not want credit on his account because he is irritated with the retailer? In this scenario, which did in fact happen, the customer was so disappointed he vowed never to support the retailer again.

It is clear that payments are fundamental to customer experience, and why that aspect needs to run efficiently, because retailers have far more to consider.

Stock issues happen, we all know this. The customer in our scenario, who is a reasonable person, knows this too.

However, he was angry because the communication was not timeous, and he was not given other options. It is entirely conceivable that had the retailer made other options available in lieu of being unable to fulfill the order, the customer may well have decided to top up the payment with a few hundred rand and choose another brand.

He would have remained a customer with a good experience, feeling that the retailer was both transparent and making an effort to attend to his needs.

During peak periods such as Black Friday or the festive season, customer experience is, arguably, even more important than during normal periods.

Besides the increased volumes, the actual discounts are a great opportunity to bring new people into the store or onto the ecommerce site.

This means that beyond margin pressures for retailers, they face the risk of customer blowback because of increased demand on the value chain.

And so, all through the year and especially during peaks like Black Friday, retailers need to be able to pre-empt stock demand, manage the supply chain accordingly, monitor real-time data to make adjustments as needed, and – importantly – provide alternative options for customers. If there’s no stock, the retailer must know this in real-time and give the customer a plan B.

There needs to be a strategy to retain the sale, and even possibly upsell. This is especially true with big ticket items because they’re not impulse buys but a conscious purchase decision resulting from a need and the means to afford one.

This concept is taken further – a conscious and planned decision to buy a TV may well be followed by an impulsive decision to add a sound bar because it is presented as a good special, and is related to the primary purchase.

The customer journey is crucial. Businesses already know this, and the ones that fare better have invested in good technology platforms to continually improve the customer experience. However, underpinning an improved customer experience strategy is a seamless, reliable, omnichannel payments ecosystem.

Payments are one of the key areas of friction and potential breakdown in the customer experience or value chain.

If a customer cannot pay because his card does not work, the bank is not available or the website is down… that sale is lost. This is a basic housekeeping, hygiene factor.

Businesses have so many other things to consider, such as delivery times, stock availability, consumer choice patterns, various fulfillment options and different pricing and promotion strategies, that payments really should be taken care of as a fundamental pillar so they can focus on attracting and retaining customers along every step until a purchase is made, with full confidence the payment will work.

The route to achieving this peace of mind – and the space to innovate elsewhere – is to seek out a trusted payments advisor that has been around the block, has a robust product and services stack, has scale, and can deliver near 100% uptime.

• Salesforce data and insights based on the activity of global shoppers reveal strong consumer interest in Cyber Week and the power of AI agents to maximise conversion
• AI contributed to 17% of global purchases in the last seven weeks

Salesforce reports that Cyber Week is expected to drive $311 billion in global sales as consumers eagerly await holiday deals, with the use of AI and agents set to influence up to 19% of those orders.

The Salesforce Shopping Index — which analyses data from 1.5 billion global shoppers, more than 1.5 trillion page views, and hundreds of millions of unique SKUs on the Salesforce Customer 360 platform — showed that since the start of October, digital retailers using generative AI and agents increased their average order value by 7% compared to those without the technology ($117 vs. $109).

AI and agents were also responsible for driving 17% of global orders through personalised recommendations, targeted promotions, and smarter customer service.

Retailers using AI-powered agents during this time frame also doubled customer service engagement, addressing complex cases faster as 30% of consumers prefer agents for speedier service.

“Agents have the potential to transform the holiday season by helping retailers provide personalised, timely, and efficient service to shoppers when they need it most,” said Zuko Mdwaba, Salesforce area vice president/Africa executive and South Africa. “There is a wide open opportunity for digital retailers to use AI for personal shopper agents that help consumers find exactly what they’re looking for and continue to make the path to purchase an easy one.”

Salesforce’s Cyber Week 2024 predictions: Reviewing real-time aggregate data stemming from Agentforce, Commerce Cloud, Service Cloud, and Marketing Cloud, Salesforce expects to see four major trends during this year’s most critical shopping week:

• AI steers the shopping cart: AI and agents will likely influence 19% of Cyber Week orders, accounting for $61 billion in global sales.
• Cyber sales surge: Cyber Week sales are expected to reach $311 billion worldwide, accounting for 23% of all holiday purchases in 2024, and $75 billion in the United States.
• Discount rates are expected to be attractive: Average discounts will likely peak at 28% globally and 30% for the U.S., fueling 5% YoY sales growth.
  • Top discounts rates globally are expected in:
    • Beauty & Makeup – 38%
    • Skincare –  33%
    • General Apparel – 33%
  • Mobile rules digital checkouts: Mobile orders will make up 70% of sales, driven by better on-the-go experiences in recent years, and presenting a new conversion opportunity with AI agents on mobile messaging apps.

Separately, a recent Salesforce survey found that 45% of global consumers are waiting to make purchases until Cyber Week, beginning November 26, to take advantage of the best deals of the season.

This points to an opportunity for retailers to capitalise on shoppers’ excitement and drive more conversions with discounts and agentic customer service experiences.

In addition, the Salesforce Shopping Index’s early holiday findings, captured between Oct. 1 and Nov. 14, showed:

• Global sales are growing: Global online sales dipped 1% year-over-year (YoY) during the last seven weeks, but rose 8% YoY in the first week of November, suggesting that consumer interest in holiday shopping is picking up pace.
• Highest-growing sales categories:
  • Makeup (+10% YoY)
  • Active Footwear (+9% YoY)
  • General Handbags and Luggage (+8% YoY)
• Consumers are interested in AI agents for faster customer service: Since early October, retailers who have invested in AI-powered service agents have seen double the rate of customer service engagement compared to those who have not invested in AI-powered agents.
• This growth is an early indicator that agents can take on a higher and more complex case load and adequately serve customer needs.
• Customers, meantime, seem open to engaging with agents. A full 30% of consumers said they would work with an AI agent if it meant faster service.

• AI and agents augment the shopping experience: While a relatively new technology, major retailers are already employing AI agents to help improve shopping experiences, including:

• Brands like Saks are using Agentforce to streamline routine tasks such as order tracking, enabling customer service teams to focus on delivering a highly customized shopping experience that drives conversion.
• Nearly one-fifth (24%) of consumers also said they’re already comfortable with AI agents shopping for them.

• Discounts and consumer demand are ramping up: Discounts peaked at an average rate of 20% in the first week of November – a 17% YoY increase, indicating that retailers are gearing up for a competitive holiday season.
  • Online orders have also seen a 4% YoY increase, signaling a positive shift following a year of reduced consumer spending.

• Chinese shopping marketplaces entice consumers with low prices: Sixty-seven percent of buyers who use apps like Shein, Temu, and TikTok Shop reported that they are planning to make holiday purchases on them this season.

• The top marketplace option for shoppers is Temu, with 40% of global consumers saying they’ve made between two and five purchases on this marketplace in the last year.

• Returns present a challenge and opportunity for retailers: Returns in October and November were 33% higher than the same time frame last year, forcing retailers to take a closer look at their retention strategies and return policies to avoid losses.

As retailers strive to create memorable and engaging experiences for their customers, understanding the core elements that contribute to effective personalisation has become increasingly crucial.

This is especially critical as retailers now enter into peak shopping season globally, with the likes of Black Friday and the festive season approaching.

Core elements of successful personalisation

Personalisation within CX begins with a deep understanding of the customer. It’s essential for retailers to identify who the customer is, their preferences, and their behaviours.

This foundational knowledge allows them to tailor their services and offerings to meet individual needs effectively.

However, personalisation is not just about knowing the customer; it’s also about ensuring consistency across all channels.

This omnichannel approach means that whether a customer interacts with a website, a social media page, or a mobile app, the experience remains seamless and uniform.

The digital and physical CX should mirror each other, reinforcing the brand persona and values at every touchpoint.

Another critical aspect is customer support. Personalisation extends beyond product sales or brand engagement; it encompasses how customers are supported throughout their journey. Effective customer support ensures that the personalisation process is complete, providing a holistic and satisfying experience for the customer.

To determine the effectiveness of a personalised CX strategy, retailers need to track a variety of metrics. Engagement metrics are a primary indicator of success.

By measuring how customers interact with the brand, companies can gain insights into loyalty and the effectiveness of their personalisation efforts. For example, an increase in customer interactions through mobile apps or social media platforms can indicate heightened engagement.

Revenue growth is another crucial metric. A well-implemented personalised CX strategy often leads to higher sales and faster customer acquisition rates.

In addition to revenue, tracking customer churn and lifetime value provides insights into customer loyalty and the long-term benefits of personalisation.

Lower churn rates and higher lifetime value indicate a successful strategy that fosters lasting relationships with customers.

Best practices for an effective CX strategy

A successful CX strategy that delivers on these metrics is underpinned by robust data management and governance.

As customer data grows, it is important for retailers to ensure its protection and proper handling, giving customers confidence that their information is secure.

Consistency across all touchpoints is essential. Personalisation efforts must ensure that every interaction a customer has with the brand is uniform, reinforcing a coherent and positive image.

Customer segmentation is also critical; understanding that customer preferences and behaviours evolve over time allows retailers to continuously adapt their personalisation strategies.

Additionally, testing and measuring the impact of personalisation strategies are essential for continuous improvement.

By analysing data and customer feedback, retailers can refine their approaches to ensure they meet customer expectations effectively.

Avoiding Pitfalls in Personalisation

Despite its benefits, personalisation can fail if not correctly understood or implemented. A common pitfall is the lack of a clear understanding of the definitions and goals of CX and personalisation.

Retailers should start with a clear identification of who their customers are, how they will serve them, and through which channels.

Inconsistency across different channels can also undermine personalisation efforts, making it crucial to ensure identical experiences across all platforms.

Another significant challenge is the effective use of data. Retailers must leverage data insights to inform their strategies and act on customer feedback promptly.

Without the right tools and processes, it becomes challenging to develop an effective personalised CX strategy.

A winning CX strategy is one that deeply understands the customer, ensures consistency across all channels, and uses data effectively to drive continuous improvement.

By focusing on these core elements and avoiding common pitfalls during the looming peak shopping season, retailers can create a personalised and humanised CX that not only meets but exceeds customer expectations, fostering loyalty and driving business growth.

As the market evolves, staying attuned to customer needs and preferences will be the key to sustained success in CX personalisation.

Today, 60% of consumers believe that advances in AI make trust even more important, and with AI agents on the rise, the findings point to real opportunities for companies to win back consumers with trustworthy AI agents this holiday season.

This opportunity is greatest with Gen Zers, with almost a third of Gen Z consumers saying they’d be comfortable having an agent shop for them.

Faced with a challenging holiday shopping season and sinking consumer trust, brands can’t afford to get AI wrong—especially as more than $200 billion in global online sales will be influenced by AI this holiday season.

AI agents, or intelligent software that understands and responds to customer inquiries without human intervention, can help companies drive higher margins and keep consumers buying by delivering incredible customer service.

From alleviating clunky purchase experiences to difficult return processes, there’s an agent for that. But to build trusted customer relationships, brands need trusted AI agents that are grounded in transparency and the right data.

Consumers trust less, expect more

Consumer trust is at its lowest point in eight years, and advances in AI make earning that trust more critical than ever.

• Nearly three-quarters (72%) of consumers trust companies less than they did a year ago

• 65% feel companies are reckless with customer data

It’s not just about trust; consumers also expect best-in-class experiences.

• 69% of consumers expect consistent interactions across departments

• Nearly 60% of consumers prefer using fewer touchpoints to get information or complete a task

While better deals are a top driver for consumers to switch to a new brand, customer service experience, convenience, and consistent product or service quality drive more long-term brand loyalty.

• 43% of consumers say poor customer service experience will stop them from making a repeat purchase from a company or brand

• More than a third of consumers say that inconvenience, such as a difficult return process or clunky purchase experience, will cause brands to lose them

Younger consumers are most open to AI agents

The research shows Gen Zers and millennials are more willing than older generations to use AI agents to improve their customer experience by creating more personalised, or useful content.

Younger generations, in particular, hold companies to a higher standard when it comes to adapting to and anticipating their needs—43% of Gen Zers and millennials say AI raises the bar for customer experiences compared to just 32% of baby boomers.

Gen Z and millennial consumers are more likely than older generations to consider the benefits provided by agents.

Transparency is key to building consumer confidence in the AI agent era

Despite the promise of young shoppers, many consumers haven’t made up their minds on AI yet. Nearly half of consumers are neutral about AI’s impact on their lives, whether personal or professional.

In fact, many consumers feel a mix of suspicion (44%) and curiosity (41%) about the future of AI —revealing a ripe opportunity for companies to help consumers see and understand the benefits of AI agents.

• Over a third of consumers would work with an AI agent instead of a person to avoid repeating themselves

• 30% of consumers—even more among Gen Z and millennials (37%)—would work with an AI agent instead of a person for faster service

• A quarter of consumers — even more among Gen Z and millennials (roughly one-third)—would share their personal information with an AI agent so it can better anticipate their needs

To build confidence in the agent experience, businesses need to bridge the trust gap through more transparency.

• Nearly 75% of consumers want to know if they’re communicating with an AI agent

• 45% are more likely to use an AI agent if there’s a clear escalation path

• 44% are more likely to use an AI agent if its logic is clearly explained

“Retailers face a much more competitive shopping season this year, as they look to deliver higher margins in the midst of increasing customer demands. AI agents can help brands deliver consistent, personalised experiences for shoppers across every channel – deepening customer loyalty and ultimately driving more sales,” says Linda Saunders, Salesforce director Solutions Engineering Africa.

Yet, despite this, they need to give customers (and their employees) the kind of payment experience they demand.

Beyond this, defining and implementing a seamless customer experience, while managing payments efficiently, becomes a differentiator – meaning customers want to return.

In the multichannel world we have all become accustomed to over the years, customers have various means of paying for goods.

They can pay online, instore, on different devices and through different platforms.

While being able to offer this convenience to the customer, retailers are increasingly finding the management of this is becoming cumbersome and expensive. Because of this, more and more retailers are seeking one vendor for everything payment related, leading to more synergy across in-person retail and ecommerce platforms.

It’s obvious why: Different vendors mean different SLAs and technology stacks, yet somehow all these things need to talk to each other in a way that not only enhances customer and employee experience, but that supports the business’s objective of driving growth and profitability. Retailers want simplicity.

How do we know this? With the experience of managing 20% of all South Africa’s card transactions and being the payment provider to 65% of the country’s JSE-listed retailers, we have come to understand that despite each context being unique, there most definitely are shared pain points, with multiple vendors adding complexity to the multichannel often being front and centre.

How can retailers change this?

The answer lies in appreciating the difference between a multichannel environment and a true omnichannel ecosystem.

Picture this scenario: A customer walks into a brick and mortar store and asks for two pens, a blue one and a red one. There is only a blue pen in the store.

The customer pays once, at a single POS, and the red pen is automatically scheduled to be delivered to them the next day.

The subtlety in this scenario lies in the fact that the customer wasn’t instructed to go onto another channel, online, nor was the customer expected to make a second purchase.

This type of scenario, more often than not, requires a terminal agnostic, interoperable solution architecture, which is why, certainly from our perspective, it is achieved with home-grown, in-house technology that can speak to the array of devices and platforms being used in the country.

Achieving a true omnichannel payments environment requires removing the complexity between point of sale (POS) and payments – not only from a technical perspective but also from a compliance point of view. Every retailer in this country will understand the regulatory obstacles, which is one of the major contributors to them seeking a single point of contact that removes complexity.

Retailers would do well to seek out, and test, the integration capabilities of their preferred vendor. An entire article, possibly a series of articles, could be dedicated to the sheer volume of solutions and products in the market. Interoperability is crucial.

When integrating, each cog needs to shake hands – or, be friendly – with the next or the machine won’t turn efficiently.

Finally, retailers should seek out partners that can enable the experience they are after. Setting up a flagship store is very different from doing pop-up stores, yet the experience and efficacy of payments should be consistent in order to maintain the same customer experience and brand promise.

Simplifying the customer and employee experience, and reducing retailer headaches by prioritising the removal of complexity in the payments landscape, should be a priority – and if it isn’t yet, it will be soon. The technology and expertise to achieve this state effectively already exists.

It is entirely possible to run online payment accepting and processing, in-store accepting and processing, the software and recon for both, and backend switching with a single vendor.

Battling in the old complex paradigm is well and truly a thing of the past for retailers of the future.

However, nearly half of the 1,300 retailers surveyed are struggling to make their data accessible, and just 42% are connecting their various data silos, which can lead to ineffective or inaccurate AI outputs.

Generative AI is expected to have a $9.2 trillion impact on the retail sector by 2029 as retailers see the benefit of implementing this technology to streamline operations, increase productivity, and deliver more personalised experiences for shoppers and associates.

However, just 13% of customers completely trust companies to use AI ethically, and 63% are concerned about bias in AI outputs.

Salesforce perspective

“The AI revolution is about data, trust, and customer experience. Looking at artificial intelligence in isolation, without understanding these elements as a package, will hurt a retailer’s ability to build loyalty and improve customer relationships. This research we’re announcing today aims to help retailers better understand the need for a unified data strategy, the practical applications of generative AI and how that can be used to enhance the experience for both shoppers and associates,” says Linda Saunders, salesforce director solutions engineering Africa.

Retailers are eyeing generative AI for personalisation and customer service use cases

The retail industry isn’t shying away from AI adoption.

• Retail executives surveyed estimate that 36% of their employees are already using generative AI today, with that number expected to grow to 45% by the end of 2025.
• 93% of these retailers state they are already using generative AI for some sort of personalisation, such as personalised email copy and product recommendations.
• 81% of respondents also report having a dedicated AI budget, with an average of 50% of that assigned to generative AI.
• The top three areas where these retailers plan to use generative AI are customer service, marketing, and store operations.
  • Retailers are prioritising customer service use cases, with a desire to augment agents with highly personalised, automated messages and content to send to customers quickly.
  • After customer service, the second most important use case for retailers is creating conversational digital shopping assistants to help shoppers find the right product or service.

Retailers struggle with data strategies to support effective generative AI

Retailers understand the importance of data, according to the survey, but many are still working through how to unify all of their data and build a single view of their customers to unlock more effective generative AI outputs.

• Only 17% of respondents reported having a complete, single view of their customers and harnessing their data effectively. Forty-nine percent are still in the preliminary stages of building or even considering the creation of a complete customer data profile.
• The inability to harmonise and manage data means that a retailer’s generative AI model could deliver ineffective or inaccurate results, or responses laced with toxicity and biases. Even though 67% of retailers say they are fully able to capture customer data, only 39% say they are fully able to clean that data, and just 42% say they are fully able to harmonise it.
• Many retailers are also struggling with using their data for making decisions (40%) and making their data accessible (47%), indicating many retailers have a significant amount of siloed data not being leveraged for effective generative AI outputs.

Trust, ethics increasingly critical to generative AI adoption

Retailers are aware of the security and trust risks surrounding generative AI. Fortunately, they’re ready to address them and are already taking steps to do so.

• Fifty percent of retailers surveyed say they have the ability to fully comply with data security standards and data privacy regulations.
• Retailers cite bias, when AI algorithms produce prejudiced results or responses, as the top risk in using generative AI — with half of respondents noting this was a concern for them. In addition to bias, retailers see hallucinations (38%) and toxicity (35%) as large risks.
• 62% report having guidelines to address transparency, data security, and privacy, when it comes to the ethical use of generative AI in technology, as well as commitments around trustworthy and unbiased outputs.

The Retail AI Council perspective:  

“In today’s retail landscape, AI isn’t just changing the game; it’s reshaping the entire playbook. It isn’t only a backstage assistant to merchants; it’s also the emerging co-star in the customer’s shopping journey. AI is now the imperative for anticipating needs, tailoring experiences, and transforming shopping from a transactional chore into a personalized and evolving adventure,” Jenna Posner, CDO of Solo Brands and Vice Chair of Retail AI Council.

Summary:

• Retailers are eyeing generative AI for personalisation and customer service use cases: 93% of retailers surveyed state they are already using generative AI for personalization, prioritising customer service use cases as a top area for implementation.
• Retailers struggle with data strategies to support effective generative AI: Only 17% of respondents reported having a complete, single view of their customers and harnessing their data effectively. 49% are still in the preliminary stages of building or even considering the creation of a complete customer data profile.
• Trust, ethics increasingly critical to generative AI adoption: 50% of retailers surveyed say they have the ability to fully comply with data security standards and data privacy regulations. but cite bias as the top risk in using generative AI.

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Most retailers in this segment reconcile their payments with spreadsheets and many can’t expect a view of the previous month until a few weeks into the following month. Even then, what is an acceptable deviation for them and how confident are they in the data?

It’s not just the sheer volume of transactions that puts tremendous pressure on large teams of people trying to reconcile payments; it’s also the rapidly increasing types of transactions.

Many retailers have up to 100 value-added services (VAS) plugins in their systems, and each of these comes with additional layers of complexity in the fees and commissions payable.

Human error in an environment like this can become costly. Automation is the only plausible way for merchants to solve the problem of reconciling at scale and ensuring accuracy.

Automated payments reconciliation can radically transform a retailer with a number of positive knock-on effects for the business.

The best way to illustrate this is to look at the benefits of automation in this unglamorous but fundamental part of every retailer’s business.

Cost savings

What was previously performed by large teams of people can now be performed by far fewer, freeing the business to redeploy its staff into areas that benefit the business.

We engaged a business that had a team of more than 100 people working on payment reconciliation. After automating, this number dropped to 12, with 88 people being repurposed in positions that added more value for the business.

Immediacy and speed

This is a recurring theme when speaking about technology – it’s ability to take processes that have traditionally taken a long time and make it almost instant.

No more waiting weeks, with automated reconciliation in place, businesses have a single version of the truth the next morning. Being this much closer to the coalface empowers businesses to make the right decisions quicker.

In addition to reconciling, automation identifies exceptions on a transactional basis. Doing this at speed enables the business to investigate the cause of the exception quickly.

An exception might be a recorded sale without an accompanying settlement from the bank.

A further piece of the automation value is being able to configure business rules that automate the action the retailer takes around those exceptions.

Accuracy

Human error is removed from the equation. If one considers that a typical medium-sized retailer will wait two to three weeks to gain a view of its position at the previous month end, it becomes clear how many opportunities there are for mistakes to creep in. Monotonous tasks are the breeding ground of human error.

Automation gives peace of mind that what you see is the truth, removing the typical 1 to 3% error factor.

Automating fees and commissions

There are many different types of transactions and tender types that retailers need to enable, in order to meet their customers’ expectations.

This all increases the complexity of the environment. For example, if a customer buys a bottle of cooking oil, he or she could pay with cash, card, wallet or even a voucher pin linked to a loyalty programme.

Beyond this, VAS has added immense complexity to a retailer’s environment. Consider a R10 airtime voucher.

Either the airtime is bought on consignment or it is bought in real time. Obviously, a certain fee must go to the telecoms provider. Now, imagine that the store is a franchise branch, meaning that within that transaction, a part must go to the telecoms provider, another to the franchisor, and the remaining amount to the bank account.

The best automation software not only builds in automated reconciliation for these complex transactions that result in varying fees and commissions payable, it also extends to settlement instructions that communicate with the bank for the payment of the fees.

The automated future

There’s little doubt that the days of spreadsheets are over. Automated reconciliation helps businesses investigate and solve upstream problems much easier and quicker in a congested ecosystem.

In addition to this, underpinned by strong data governance and compliance, retailers know that the integrity of the data is sound.

In a hyper competitive world where speed, safety and accuracy of data is paramount for the right decisions to be made, retailers need to calculate the cost of not automating and weigh it against the very real and measurable benefits of investing in good automation software, implemented by partners who have a proven track record.