AI in Retail
The retail landscape is literally in turmoil. Informed shoppers are more demanding and price sensitive than ever before. Technology, products and fashions are changing rapidly and keeping pace with consumer preferences is increasingly difficult. With the global shift to online buying, traditional retail has to embrace the best that artificial intelligence (AI) can bring to the playing field, in order to stay relevant.
Well-tested algorithms can address retail business specific use cases such as Product Mix Optimization, Price Optimization, Replenishment Optimization, Propensity Modelling, Marketing Spend Optimization, Churn, Demand Forecasting and Customer Segmentation.
What is your goal?
Optimizing supply chain – analyzing hero products and customer demographics across stores to optimize product assortment and distribution
Improving conversions – knowing the customer buying patterns
Customizing shopping experiences – based on customer profiling and spend patterns
Micro-targeting - Automated micro-targeting of campaigns
Demand forecasting leading to better planning - apply patterns and parameters of similar previous products to the forecasting of new products for both initial and later stage adoption rates
Campaign management – Optimizing marketing, advertising and campaign spends
Pricing optimization – using machine learning to arrive at the right discounting and store selection for markdowns and price offers
Store locator - Find the right location to open a new store that generates good sales
Whatever your goal, Aarleo can help.
We can, through Machine Learning, improve inventory management decision-making – through contextual, actionable information
Through AI, we can help you implement dynamic pricing using any number of desired criteria
Through AI, we can create customer experiences that are targeted and timely
Deploy market basket analysis in order to increase revenue, increase the efficiency of marketing. You know what are the products that your customers are going to buy in future and you can maintain your inventory accordingly. Place your products in order. Run a bundled promotions to clear dead stock. create relationships between specific items and accurately predict which items will be purchased next by assigning a certain level of probability.
Our algorithms discover unproductive inventory early in the season, simulates the inventory performance of each product and recommends price off for each product. It also identify various variables influencing demand like consumer behavior, pricing, market trends, purchase history etc. are analyzed and processed to prescribe the price that can stimulate demand and at the same time ensure maximum possible profitability.
Forecasting is not just based on historical sales, there are much more causal variables that play a vital role. With accurate forecasting, you can optimize buying & merchandising. Manage your cash flow, right staffing and avoid out of stock situations. Improve customer satisfaction and maximize the revenue.
Provide provisions to understand the impact of increasing or reducing or deleting certain product categories from the merchandise mix. Use the information for future product launches. Effectively balance shelf breadth and depth in your store clusters or stores based on how people shop.
Simulate before promotion execution. Understand which marketing channel is yielding results and which is saturated. Optimize your spending to increase the revenue and reduce spending on marketing
Group your stores based on common store and demographic characteristics. It also provides grouping stores based on both performance (e.g. sales volume) and non-performance (e.g. store size) parameters. It supports assortment planning and allocation as well as maintaining a customer-centric merchandise approach. Helps to derive common marketing strategies across clusters.
Are you opening a new store? Make a decision scientifically. Our AI backed model will pin the exact location and predict the sales as well! Save time, cost and avoid human bias to decide the exact location.
The logic inbuilt to discover items which are going to be out-of-stock, identify which stores are having excess stock, when is the expected receiving date and order from stores with excess stock and warehouse. To optimize the inventory even the store with excess inventory is pushed to the stores where the stock is fast moving. It’s a complete automated process to manage the inventory effectively.
Wish to know more about how Aarleo can partner with you to build AI enabled solutions for running more profitable retail stores?