As retail and consumer-goods leaders know, the seemingly simple act of delivering a product into the hands of a customer requires a complex orchestration of processes, including inventory management, store planning, sales forecasting, enterprise resource planning (ERP) management, and customer support. As customer expectations evolve, supply chains grow more agile, and omnichannel experiences become the norm, retail organizations find themselves navigating an increasingly complicated business landscape.
Capgemini estimates the retail industry could save as much as $340 billion a year by automating key processes like customer returns, supply chain management, updating customer databases, maintaining inventory records, and more. One of the most effective ways to achieve this level of automation in retail is through robotic process automation (RPA), a form of automation that uses software bots to carry out structured and repetitive tasks typically handled by humans.
What is robotic process automation (RPA) in retail?
When implementing RPA, you create bots that follow set scripts to replicate the steps a human worker would take to complete a task in a software environment. RPA has enjoyed widespread adoption throughout the retail and e-commerce industries because it offers a way to automate and streamline many of the interactions between people, processes, and applications that underpin successful retail strategies today.
Because RPA bots mimic human actions, they can serve as universal points of integration, allowing even apps and software systems that lack APIs to integrate. If a team member needed to transfer data from a spreadsheet to a customer relationship management (CRM) system, a bot could simply be scripted to transfer that data between systems the way a human would. No additional programming expertise would be required.
In the retail business, RPA is typically applied to rote tasks like data collection, tracking inventory status, and processing simple customer returns.
The value of RPA in retail
The key benefit of RPA in retail is that it allows human workers to hand repetitive tasks over to robot coworkers so that employees can focus on more creative, strategic, and value-added tasks. For example, RPA can reduce errors in tasks like data transcription, ordering, and customer support. Unattended bots can be scheduled to handle repeatable work, like database updates, around the clock — resulting in faster completion times. RPA can also be used in combination with AI-powered chatbots to assist both customers and customer service agents with basic tasks like product inquiry or the return process. When a customer or team member makes a request (e.g., checking the status of an order), the chatbot can relay the request to an RPA bot to carry out the task.
On its own, RPA automates straightforward, time-consuming, rule-based tasks. But RPA can also be a valuable gateway to more far-reaching automation efforts because of its low cost, relative ease of setup, and potential to integrate multiple disparate systems. Leading RPA solutions often leverage low-code or no-code platforms that allow users with little technical knowledge to create effective scripts for bots — making RPA an accessible starting point for hyperautomation and broader process optimization.
Once RPA is in place, retailers can build upon this foundation to automate increasingly complex tasks by augmenting RPA’s basic capabilities with advanced artificial intelligence (AI) and machine learning tools. For example, a business rules management system (BRMS) can help RPA bots mimic human activities and make smarter decisions about which tasks to carry out when.
Operational Research Systems (ORS) reports seeing 8-15% improvement in fulfillment rates — and between 8-12% margin and revenue increases — from deploying AI engines in retail applications. Chandra Subramanian, Head of Retail and Manufacturing at ORS says, “Strategically placed data bots could feed AI-based forecasting and inventory pooling systems in real time to allow for better fulfillment, reduced stockouts, better allocation reshuffling, and inventory decisions.”
Workflow automation software can create fully autonomous RPA processes overseen by AI. With process mining algorithms, retailers can even dig into the data on RPA performance and identify more ways to optimize RPA deployment. And according to Subramanian, “RPA bots can feed data into advanced AI-based simulation tools, aka digital twins. Simulation tools have been difficult to use in the past because of the availability of relevant streaming operational data, limited computational and analytical capabilities, and complex coding requirements to make them run. RPA bots, combined with digital twin simulators, allow decision makers to run what/if analysis rapidly and improve business outcomes.”
How RPA works in retail
In a retail context, RPA can be deployed to perform both back-office and customer-facing functions. It can carry out any task that requires defined, repeatable steps or the manipulation of structured data. Typical applications of RPA in retail include the following:
- Collecting employee information for back-office uses like onboarding, payroll, and scheduling
- Generating and processing standard invoices
- Answering common customer questions via chatbots
- Gathering and aggregating register reports
- Sending automated messages to customers and suppliers
The benefits of RPA in retail
RPA automates repetitive tasks to the benefit of both customers and employees. Employees can focus on more fulfilling, engaging and organizationally significant tasks — resulting in higher job satisfaction and productivity. Similarly, customers appreciate the ease and speed of RPA-delivered services, which drive customer satisfaction and directly influence revenue. According to PwC, customers are willing to spend 16% more in exchange for great customer experiences.
Some of the specific benefits of RPA in retail include the following:
- Improved customer engagement. With RPA, customer-facing tasks like returns processing, order updates, and chat-based support can be conducted in real time and on demand, allowing the organization to deliver a world-class customer experience. When customers have more complex needs, human employees can spend more time delivering effective solutions as rote tasks no longer bog them down.
- More efficient inventory management. RPA can track inventory data, alert teams when inventory levels are low, and facilitate inventory management to avoid both overstock and undersupply.
- Reduction of errors. RPA tends to be less prone to error than human workers in data entry and form preparation, resulting in more accurate invoice processing, order management, and general recordkeeping.
- Access to more strategic data. RPA can make it easier to collect and analyze data on customer sentiment, purchases, and store transactions, which can inform strategic decisions about store planning, promotions, new product introductions, and pricing.
- Cost savings. RPA can carry out the same tasks as human workers in less time, eliminating human errors and dramatically reducing operational costs.
- Increased revenue. Considered altogether, the benefits of RPA can drive increased revenue by allowing companies to plan smarter, make more strategic decisions, and offer an improved customer experience that keeps customers coming back.
Use cases of RPA in retail
RPA is most effective in automating tasks that are manual, repetitive, prone to errors, and based on structured data, with little-to-no opportunity for human workers to add value. It’s also an efficient way of making disparate systems talk to one another. These are some of the most common RPA use cases in retail:
- Automated supply chain management. The procure-to-pay cycle depends heavily on accurate data and the preparation and exchange of numerous documents. To streamline the process, retailers can author bots capable of copying data from supply chain management systems, like Oracle and SAP Ariba, into standardized order forms. RPA bots can even submit orders through online portals. Bots can also help process invoices by entering invoice data into accounting systems, like FreshBooks and Xero.
- Automated inventory management. RPA bots can ensure inventory databases are continuously updated. An unattended bot could be scheduled to run at the end of every day, using sales data from each store to update records in inventory management systems, like Zoho Inventory or Square. If equipped with AI-processing functionality, the bot could even determine when two slightly different names refer to the same product, thereby eliminating transcription errors.
- Supply and demand planning. RPA bots can help retailers prepare the reports necessary for broader, more strategic levels of supply and demand planning. Teams can automatically compile data from multiple documents and sources in a single spreadsheet using attended bots for easy analysis. If the RPA solution can run multiple bots at once, such comprehensive reports can be generated at a moment’s notice.
- Automated order management. RPA can optimize key components of the order-to-cash process. Unattended bots can be scripted to transfer information from e-commerce platforms, like Shopify, to warehouse management systems, like Fishbowl, so orders can be filled faster. Intelligent virtual agent (IVA) chatbots can also answer customers’ questions about the status of their orders using RPA bots to fetch the required details from the company’s order management system.
- Facilitating sales analytics. RPA can help retailers gain more precise insights into consumer behaviors, store performance, and other critical data points. Unattended bots could be scheduled to regularly pull data from the company’s Point of Sale (POS) system, like NetSuite, and create reports for company leaders to review sales numbers, store performance, and other trends.
- Returns processing. RPA can facilitate returns around the clock with minimal human intervention. Intelligent chatbots and interactive voice response (IVR) technology can guide the customer through the returns process. As this is happening, RPA bots can run in the background to update inventory systems, customer records, accounting records, and any other systems involved in processing the return.
- Automated virtual agents. The omnichannel expectations of today’s consumers mean customers want to receive service via whatever channels are most convenient to them at the moment. Chatbots can be available 24/7 for customer queries, and they can use RPA bots to carry out basic tasks for customers, like surfacing answers to frequently asked questions. Chatbots can also act as utilities for customer service agents. If customer service agents frequently deal with the same kinds of requests — like resetting a customer’s login credentials — they can ask chatbots for help instead of doing the process manually. The chatbot, in turn, relays the request to an RPA, which executes it.
- Fraud detection. When fraud prevention teams come across suspicious orders, they can use RPA bots to help investigate. Multiple bots can run at once to check a current order against customer databases and other records, leveraging AI processing to identify any discrepancies that could point to fraud.
- Tailored promotions. An RPA bot can transfer data about customers’ previous purchases from a CRM, like Salesforce, to a marketing system, like HubSpot, where that data can be used to segment customers for tailored offers and advertisements. RPA can also communicate with customers about personalized offers through IVA chatbots and IVR to encourage repeat business.
- Employee scheduling. With many retailers relying on just-in-time scheduling for brick-and-mortar stores and fulfillment centers, RPA can simplify the process. An RPA bot can transfer data about employee availability from documents, like Excel spreadsheets and Google Forms, to an employee scheduling software, like Sling, where managers can use the data to create schedules.
To learn more about the cost savings and other business benefits of RPA, read the IBM RPA Total Economic Impact™ study from Forrester Research.