While AI advancements have been extraordinary, the path to game-changing ROI doesn’t have to be disruptive. By starting small with strategic and contained use cases, retailers can achieve major operational wins and enhanced customer service in extremely short time frames.
While AI may seem intimidating with so much hype and pressure surrounding it, you don’t need to reinvent your customer experience strategy to get started. Beginning with a small, targeted use case, you can reap massive operational gains and improved customer experiences — all with minimal risk and investment.
By taking an iterative approach, you can rapidly achieve ROI from AI while validating your long-term strategy and building the internal experience required for further use cases. Let’s look at how other businesses have started out and the results they achieved from their AI projects.
Start small and focused
Begin with bite-sized projects that solve specific pain points rather than trying to reinvent everything at once. When selecting your first AI use cases, here are a few steps and best practices:
- Automate existing channels before creating new ones.
- Look for high-volume, low-complexity issues.
- Narrow the issues to those that are solely or mostly manual, repetitive and costly.
- Map the process and identify the stakeholders and systems involved (e.g., inventory management, online shop software, etc.).
- Once you have a list of possible candidates, compare complexity and estimated ROI.
Remember, the biggest quick wins often come from low-complexity tasks, not cutting-edge “art of the possible” stuff. Here are the three most common use cases that companies have started with the last few years.
1. Automate identity verification and simple order inquiries
One of the easiest places for retailers to start is by automating the initial identity verification (ID&V) process and basic order status inquiries like “Where is my order?” (WISMO). These are extremely high-volume yet straightforward interactions that consumers can and do frequently self-serve.
A major insurance company implemented an AI virtual agent just to handle caller ID verification. Within months, this simple use case achieved a 95% automation rate while reducing handling times by an average of 1.5 minutes per call – a 27% improvement. Deploying AI for a contained process like ID&V allows you to maximize impact while minimizing risk.
For retailers specifically, automating WISMO inquiries can drive huge operational improvements. One European e-commerce eyewear company fully automated over 50% of these calls within just three months by implementing an AI virtual agent. This saved 30 seconds per automated call while massively reducing live agent workloads.
2. Implement AI agent assistance
For a low-risk project with major productivity benefits, consider deploying an AI agent assist or copilot that works behind the scenes with your existing agents. This virtual support agent runs in the background, monitoring conversations in real time to provide suggestions, retrieve relevant information, and automate after-call work.
By integrating with your CRM, knowledge base, and other systems, the AI copilot can instantly bring to the surface customer details, order status, and recommended responses as the conversation happens.
This saves agents from constantly searching different applications, switching tabs and putting customers on hold to manually check other systems. Even more powerfully, the AI agent copilot can then draft call summaries, auto-generate case notes or tickets, and pre-fill forms and case data based on the conversation context.
For retailers, an AI agent copilot could reduce tedious after-call responsibilities like documentation from several minutes per call down to just seconds with a quick review. It essentially gives your agents a real-time personal assistant to boost productivity. Finally, this technology is entirely agent facing, meaning it will never be exposed directly to customers, thereby eliminating any risk. At the same time, the gains in agent confidence, productivity and accuracy directly impact and improve the customer experience.
3. Optimize IVR call routing with conversational AI
While AI virtual agents can directly handle many inquiries, conversational AI can also improve CX by streamlining self-service processes. One major use case is enhancing your existing IVR phone by retiring the legacy tree-based IVR systems that anger customers in favor AI. A conversational IVR or AI voicebot understands the caller’s intent using natural language processing so the customer can speak freely.
With conversational IVR, you can skip menus entirely and simply jump straight to the right issue as if speaking with a human. It will dynamically route callers to the appropriate self-service flow or live agent based on their clearly stated need. This bypasses the frustrating experience of having to listen to multiple menus. By getting customers to the right destination more quickly, you can massively improve containment rates for self-service while boosting first-call resolution when a live agent is required.
For retailers with high call volumes, even small improvements to routing and containment can translate to huge operational savings and better customer satisfaction.
Getting started: Best practices
To minimize risk and accelerate time-to-value when first getting started with AI, retailers should consider:
1. Running initial proof-of-concept projects to validate solutions before full investment. AI vendors or partners can often provide pre-built POCs for common use cases.
2. Leveraging cloud-based AI solutions for easier deployment versus complex on-premises installations and management. Cloud-based AI solutions can still be integrated with existing on-prem systems.
3. Focusing on change management by upskilling agent teams, addressing resistance through clear communication of AI benefits, and updating processes to accommodate the AI-augmented workflows.
While recent AI advancements have been extraordinary, the path to game-changing ROI doesn’t have to be disruptive for retailers. By starting small with strategic and contained use cases, you can achieve major operational wins and enhanced customer service in extremely short time frames. These quick successes build internal momentum for your long-term vision of AI-powered retail experiences.