Forrester predicts one in five US and EMEA retailers will launch customer-facing GenAI applications in 2025. Enhanced product search, personalized recommendations, and improved category navigation are top use cases. So why did automated interactions cause the US’s customer experience rating to decline by 5% in 2023—the bottom since 2015—and what can retailers learn from this before making their GenAI investments?
The 2023 KPMG report highlights failure to fulfill customers’ expectations because the explanation for decline, with overuse of technology that lacked strategic profit to shoppers. Of 50 CIOs and CTOs in Fortune 500 enterprises questioned on their GenAI projects, most found their pilot technology addressed the unsuitable business need.
As we enter 2025, retailers must prioritize customer-centric GenAI strategies. Relatively than adopting the most recent technology as a nice-to-have, take a look at the business needs. Retailers should review their customer journeys, discover the room for improvement, and construct or adopt solutions that fit their use case, not the opposite way around. Listed here are 4 lessons for retailers to think about on their journey to raise the user experience (UX) with GenAI.
Ensure Business-Data-AI Synergy
RAND researchers present in 2024 that 80% of AI projects fail on account of five key areas: misaligned goals, data deficiency, tech-first approach, infrastructure gaps, and overambitious AI.
Retailers require a solid data foundation and expertise to construct the required algorithms and succeed with their GenAI investments. They need to ask themselves, “How can we ensure sufficient data availability to fulfill the answer’s requirements? And the way much of this data is proprietary?” Successful GenAI projects hinge on high-quality, relevant information. The more unique data formats the organization has, the more customizable the answer must be.
A 3rd query to ask is, “What specific talent pool and operational structure changes are needed to leverage GenAI effectively?” Understanding the extent of upskilling, together with the motivation, costs, and time, will help retailers resolve the return on investment (ROI) for constructing, customizing, or managing solutions in-house.
Today, non-technical experts can work with no-code tools or hire a long-term AI partner to leverage the advantages. When choosing third-party GenAI solutions, e-commerce executives should prioritize aspects beyond pricing and ROI, comparable to scalability, performance, data security, vendor expertise, and tech stack compatibility. A transparent business case and expected outcomes are crucial before committing to any latest integration.
Take an Incremental Approach
In 2024, BCG Group evaluated the adoption rate of the top e-commerce GenAI use cases; namely, content creation comparable to blogs, product descriptions, and product image supplementation. More advanced use cases include personalized product recommendations, dynamic pricing, and competitor analytics. Familiarize team members with systematic services before trying your hand at more complex tasks to regulate to latest processes seamlessly.
Retailers should encourage their e-commerce teams to leverage out-of-the-box GenAI tools to acquaint themselves with the tool’s capabilities. Easy use cases and no-to-low-code solutions comparable to product descriptions and image creation are excellent starting points as they show team members the possible time savings, in addition to help them adjust their operations to incorporate frequent validation checks. Introduce weekly or biweekly reviews within the early stages to measure the tool’s progress and adjust approaches along the way in which. Team feedback and participation shall be key to success.
As team members turn into more familiar, retailers can introduce latest use cases. Engineers can streamline development with AI code completion assistance. Marketers can introduce AI-driven personalized upselling and cross-selling recommendations, and loyalty managers can construct adaptive loyalty campaigns based on customer engagement level.
Create a Security-First Culture
Disconnected systems are weak links that may result in security vulnerabilities, and GenAI has the potential to lower the entry barrier for low-skilled threats. Cybercriminals can use GenAI to construct scripts that could possibly be functionally malicious if used accurately, automating attacks and targeting specific vulnerabilities. Retailers should aim for a solid data foundation, streamlined workflows, and a well-connected network of applications to maintain their systems secure and straightforward to watch.
Cybercriminals can also use GenAI to control consumers through highly convincing fake content (i.e. social engineering and phishing). Due to this fact, identity verification shall be much more critical in 2025. Multifactor authentication, comparable to sending time-sensitive codes to user devices via SMS, email, or a dedicated authentication app, will help secure customer loyalty programs and shopping platforms—especially where financial information is saved.
As well as, retailers must ensure developers frequently update software, software libraries, and systems to handle vulnerabilities and minimize attack surfaces. This safety-conscious, verify-first mindset needs to be filtered through the whole organization. By conducting regular security awareness training and simulations and inspiring employees to report suspicious activities promptly, retailers can construct a security-focused culture.
AI-powered monitoring and alerting systems, comparable to advanced endpoint detection and response (EDR) solutions, may help retailers detect and mitigate threats in real time. Even so, it’s vital that each one employees are within the habit of verifying that systems, especially cybersecurity software, are working as they need to.
Be Empathetic by Design
The most important explanation for AI distrust is its use in customer support channels. Some 53% of consumers would consider switching to a competitor in the event that they came upon an organization was going to make use of AI for customer support.
Customers fear that GenAI will construct a wider gap between them and support agents. They need peace of mind that their issues shall be understood and resolved in the easiest way possible, ideally with managers who’ve the authority to supply complimentary gifts for his or her troubles. Nevertheless, retailers can construct these steps into their automated services. But it surely’s still vital to begin with easy tasks first. Making FAQs and online information more accessible via conversational chatbots are helpful use cases.
At first, more hands on deck to answer customer feedback, confusion, or queries shall be a proactive and welcomed buffer as retailers adapt to GenAI’s capabilities. Real-time feedback from support teams will help retailers imagine all scenarios where tasks are too complex for GenAI tools. In these scenarios, chatbots must direct customers to an agent with a holding message, comparable to: “Offer not helpful? Contact an agent” button. Analyze this feedback day by day until all possible common queries are answered simply and robotically.
It’s essential that each one tasks GenAI tools undertake seamlessly transform into an agent chat that picks up where the chatbot left off if needed. It is also critical that customer support agents remain a key a part of the user journey, saving them for high-value tasks comparable to watching the information and identifying underlying causes of recurring customer issues. This manner, retailers have a basis to propose solutions and stop future problems with automated response channels.
Whether retailers decide to adopt GenAI or not, competitors, customers, and malicious actors will. Preparing team members with easy use cases will help them adjust to latest ways of working and higher understand the brand new potential threatscape. Retailers can leverage out-of-the-box tools and trial GenAI projects in a phased approach, constructing on their teams’ knowledge and expertise with more advanced algorithms every time a project is fulfilled successfully. By automating the transactional tasks and keeping an authority team of human agents, customers can enjoy quicker access to desired products and feel reassured there’s an agent a call away in the event that they need them.
