The Models are the HERO of the PredictRetail Solutions
The variety of pre-built models in PredictRetail allows for a staggered AI adoption process aligned to your business goals, essentially giving you the right solution at the right time. These predictive and statistical models will then customise themselves to your environment enabling real-time, actionable insights into corporate performance.
Price Elasticity
What is price elasticity?
This model analyses the effect of past price changes on volume sold by category (regular, promo, combined, covid).
Why use a price elasticity model?
Understand the impact of price changes on volume
Understand the impact of price changes on complementary and substitute products
Determine regular and promo price elasticity by product and store
Price Optimisation
What is price optimisation?
This model recommends the most effective price points and pricing strategy per product to help maximise margins or market share.
Why use a price optimisation model?
Determine optimal price points per product to maximise margins or market share
Easily evaluate the performance of historical price points for every product
Perform “What-If” analysis to predict the impact of different pricing strategies on demand and GP, before they happen
Promo Analytics
What is promo analytics?
This model analyses the impact of past promotions on products plus the impact on Halo and Cannibal products.
Why use a promo analytics model?
Improve promo decision making and return on investment (ROI) on promo spend
Determine optimal promotional strategies by product, category and brand
Improve promotion strategy outcomes on margins and market share
Sales and Demand Forecasting
What is sales and demand forecasting?
This model predicts the supply and demand of inventory more accurately.
Why use a sales and demand forecasting model model?
Reduce cash-flow tied up in underperforming inventory and overstocks
Reduce understock and out-of-stocks by improving on-time deliveries
Proactively address changes in demand patterns
Market Basket Analysis (MBA)
What is market basket analysis?
This model identifies the customer purchasing patterns and groups commonly sold products to help target and predict customer demand.
Why use a market basket analysis model?
Increase sales by identifying related products for cross-selling and up-selling
Improve cross-selling by creating personalised, targeted marketing campaigns and promotions for products related to items a customer has recently purchased
Improve up-selling by grouping products that commonly sell together in-store layouts or on e-commerce sites
SKU supersession
What is SKU supersession?
This model predicts sales and demand for new and/or similar products which may not have a sales history.
Why use a SKU supersession model?
Enhance your sales forecasting and demand planning accuracy for new products
Utilise history of similar products nearing end-of-life to define sales, pricing and stock strategies
Maximise sales opportunity by recommending new/improved/seasonal products
Personalised recommendations
What are personalised recommendations?
This model allows you to determine what products or services are most likely to trigger intent for a particular customer.
Why use a personalised recommendations model?
Improve customer experience (CX) by personalising marketing offers and promotions
Reduce churn and improve customer retention
Increase basket sizes and repeat sales
Customer Segmentation and Clustering
What is segmentation and clustering?
This model groups customer personas into various segments, i.e., Champions, Loyalists and Potential Loyalists, New, About to Sleep, etc.
Why use a customer segmentation model?
Improve your marketing focus
Build tailored, effective marketing engagements for each segment thereby improving your marketing spend and ROI
Personalise your customer engagements, ensure your customers feel understood
Payment Profile Segmentation
What is payment profile segmentation?
This model forecasts the number of months that a customer will take to settle their account, continuously incorporating new behaviours and giving you the insight of knowing when to engage.
Why use a payment profile segmentation model?
Proactively maximise financial returns based on the behaviour of credit customers
Improve sales and profitability by engaging at the right time
Optimise marketing spend and focus on the most suitable audience for retargeting
Customer Lifetime Value Analysis (CLV)
What is customer lifetime value analysis?
This model helps you measure how valuable a customer is to your business. Recognise and retain your most valuable customers by providing a view of the customer spending to date, and projecting future spending.
Why use a lifetime value analysis model?
Identify your most valuable customers to maximise long-term profits
Improve customer loyalty and engagement
Improve sales lead generation with enhanced marketing ROI
Image and Video Recognition
What is image and video recognition?
This model identifies information (such as objects, places, people, writing, and actions) from an image or video to process this for further use/analysis.
Why use an image and video recognition model?
Improve visual searching, tagging and labelling
Enhance data relating to documents, images or videos
Speedily automate the extraction of information from non-text items and build data points
Product Life-cycle Analysis
What is a product life-cycle analysis?
This model determines what stage of its life-cycle a product is in: introduction, growth, maturity, decline or obsolete.
Why use a product life-cycle analysis model?
Develop effective marketing and targeting strategies to support the cycle that a product is in
Enhance demand and sales forecasting to support the life stage of products
Manage product profitability
With PredictRetail you can determine optimal pricing strategies plus improve your customer & product strategies. We predict many great things in that kind of future.
