Clienteling Metrics
The ability to measure your clienteling effectiveness provides important insight into the type of customer experience you are attempting to create.
Read MoreCategory: Analysis
Detecting Retail Sales Trends with Machine Learning
How machine learning can detect sales trends and enhance your retail sales forecasting.
Read MoreAssortment Planning: Why Technology Can’t Replace the Merchant
Technology plays a crucial role in assortment planning, but the process still requires a buyer’s insight.
Read MoreDigital Transformation for Retail: Build a Successful Roadmap
Critical factors for a successful retail digital transformation roadmap.
Read MoreFour Forecasting Methods You Have to Know: Variable Response Smoothing
Use variable response smoothing, or VRS, as a machine learning method for demand forecasting.
Read MoreFour Forecasting Methods You Have to Know: Sales Profiles
Use sales profiles for forward-looking demand forecasts.
Read MoreFour Forecasting Methods You Have to Know: Exponential Smoothing
Use exponential smoothing as a quick way to detect trend in your demand forecasts.
Read MoreFour Forecasting Methods You Have to Know: Moving Averages
Use moving averages as a quick way to obtain a forecast.
Read MoreAffinity Analysis: How To Supersize Your Customer’s Cart
A quick retail analytic to improve the probability of selling more product per sales transaction.
Read MoreInventory Management: How to Double Your Turnover
Interestingly enough, small changes in the timing of your receipts can have a tremendous impact on your inventory turnover.
Read MoreFour Forecasting Methods You Have to Know: Overview
This Retailitix post is a four part series that steps through basic forecasting methods, moving averages and exponential smoothing, and leads to one of the most popular seasonal forecasting methods used today, variable response smoothing, or VRS.
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