Clienteling Metrics
The ability to measure your clienteling effectiveness provides important insight into the type of customer experience you are attempting to create.
Read Moreby Jared Dolich | Feb 8, 2019 | Analysis, Business Intelligence | 0
The ability to measure your clienteling effectiveness provides important insight into the type of customer experience you are attempting to create.
Read Moreby Jared Dolich | Jun 18, 2018 | Analysis | 0
How machine learning can detect sales trends and enhance your retail sales forecasting.
Read Moreby Jared Dolich | Jun 10, 2018 | Analysis, Strategy | 0
Technology plays a crucial role in assortment planning, but the process still requires a buyer’s insight.
Read Moreby Jared Dolich | Jun 4, 2018 | Analysis, Strategy | 0
Critical factors for a successful retail digital transformation roadmap.
Read Moreby Jared Dolich | May 20, 2018 | Analysis | 0
Use variable response smoothing, or VRS, as a machine learning method for demand forecasting.
Read Moreby Jared Dolich | May 20, 2018 | Analysis | 0
Use sales profiles for forward-looking demand forecasts.
Read Moreby Jared Dolich | May 20, 2018 | Analysis | 0
Use exponential smoothing as a quick way to detect trend in your demand forecasts.
Read Moreby Jared Dolich | May 20, 2018 | Analysis | 0
Use moving averages as a quick way to obtain a forecast.
Read Moreby Jared Dolich | May 10, 2018 | Analysis | 0
A quick retail analytic to improve the probability of selling more product per sales transaction.
Read Moreby Jared Dolich | May 6, 2018 | Analysis | 0
Interestingly enough, small changes in the timing of your receipts can have a tremendous impact on your inventory turnover.
Read Moreby Jared Dolich | May 1, 2018 | Analysis | 0
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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