Machine Learning in Retail
Disruptive factors for retail’s future. Machine learning is proving to be a valuable tool
retailers can use to maximize results and touch-points on multiple levels.
Overview
- Demand forecasting
- Segmentation
- Analysis of prices and competitors
- Detection and prevention of customer outflow
- Additional sales
- Inventory management
- Customer service
- Recommendation service
- Chatbots, virtual personal assistant
- Personalized digital content
Features
Powerful Capabilities to Increase Retail Efficiency:
- Forecasting of demand for goods at a discount
- Identifying and using customer behavior patterns to predict their future action
- Personalized offer for certain groups of buyers (segments) of certain products at the time of greatest need
- Replacement of sales consultants by an automated system to select goods based on the experience of previous customers and individual preferences of a particular client
- Optimal number of personnel for high-quality customer service for a particular location and time (during seasonal sales, marketing campaigns, etc.)
- Optimized product placement (taking into account the behavior patterns of customers, seasonal changes, trends, etc.) – buyers will not leave your store without buying
- Optimization of warehouse storage – the storage space will be utilized for the benefit
- Virtual personal assistant checks the shopping schedule and reminds the buyer of the need to make a new order, or selects the best product based on his or her preferences
- Targeted digital content (depending on sex, age) at points of sale to stimulate demand and increase sales
Benefits
Driving Results with Artificial Intelligence Tools:
- Increasing sales and revenues
- Winning customers from your competitors
- Improving conversion rate and increasing average check
- Optimization of pricing
- Improving effectiveness of marketing campaigns
- Manage customer behavior
- Improve customer experience
- Create the future of your business