RETAIL

The Problem

The retail client is a 6th generation jeweler, specializing in classic jewelry, wedding bands, engagement rings, and many more.

The client had multiple data points from separate systems for Point of Sale (POS), employee time logging, foot traffic count, weather type, advertising campaign, inventory, etc.

They had difficult time keeping track of all information. Specifically, they had been looking at each piece of data/information in isolation. In doing so, they had to look at separate places/systems for each information they wanted to gather. For example, for daily sales report, they had to look at a report from POS system. For ad campaign, they relied on a separate report from campaign manager/provider. For employee time sheet information, they had to resort to another report, and so on.

This myriad of many systems and information consumption in isolated fashion did not provide key insights in a timely manner to the decision makers.

The Solution

Aver Analytics listened to the client’s problem and frustration. We gathered all the existing data available and developed Key Performance Indicators (KPI) for the client.

Microsoft’s Power BI provided a one-stop place where the client is able to gather all the necessary information. This eliminated the need to use different reports from various systems and tools.

The Value

The client now has power. They have all the information they need, in a timely manner, to make sound decisions.

Everything they want to monitor is at their fingertips, so they now can easily identify any problems or issues arising early.

The following metrics have proved to be invaluable:

  • Close Rate - how many people that walk in to the store end up buying something

  • Sales $ per Hour - average number of $ per employee hour

  • Average discount - Discount given by sales representative, by product, by customer base, by price point, etc.

  • Correlation between Discount Rate and Close Rate - “Does more discount given lead to higher Sales?”

Also, the client now has a key insight where most of their customers coming into the store on partly cloudy days or rainy days. They now know the number of potential customers walking into their store is not on sunny, clear sky days. With this, they are launching advertising campaigns when the upcoming days are cloudy or rainy. Now that having best bang for the buck! It is quite an intelligence in good use.

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