Intelligent Automation for Retail: 9 Use Cases
As the retail landscape shifts, we can help retailers use intelligent automation in a number of ways. Those include: anticipating trends, building better prediction models, accurately forecasting inventory, and staying a step ahead of customer wants and needs.
This rundown of use cases will show you how we use automation and artificial intelligence to help with:
- Data merge between channels, whether that’s mobile sales, ecommerce operations, or brick-and-mortar stores. Follow the customer journey and compare information from different data sources to analyze the overlaps instantly.
- Building a recommendation engine that takes into account factors like past purchase history, demographic data, click behavior, ratings, and other characteristics. Your site (or sales staff) can then instantly identify more products the customer might like.
- Personalizing loyalty programs. Our AI models can learn from patterns in data over time to help you personalize an offer for each customer segment, so that each group receives more meaningful rewards.
- Speeding up product returns. Our platform helps you simplify returns from start to finish. Let’s say customers routinely email a company service desk to ask how to return products. We can help you build an AI model that analyzes incoming emails to detect intent, and then it automatically selects which are about returns.