Analytics Dashboard & Logistics System

Written by PLATMA

Updated 6 months ago

Case:

The owner of an online store had long wanted to start keeping records to know who buys, how profits grow, and where losses occur. All this was to properly plan and make decisions based on data. He hired a specialist who recommended connecting Google Analytics to the store. As a result, there was a misunderstanding, and the owner was very disappointed because it turned out that it only provided data on website visits. Now he needs to figure out how to collect data from other sources, some of which are simple spreadsheets manually maintained by the shipping manager. The budget for digitalization was spent, and the desired result was not achieved. Where to find the budget for a whole team that can implement this solution? And how can he now trust specialists? The owner was recommended to use Platma, where you can go, dictate your request to the AI, it will clarify a few questions, and provide a ready-made solution. For an absolutely acceptable budget, he gets a tool that he will use every day, spending now just 1 minute a day analyzing the business situation.

Functionality:

Collecting data from various sources and displaying them on a single dashboard.

Updating all data automatically.

Adaptability (phone, tablet).

Possible data sources:

Google Analytics;
Excel spreadsheets;
Google Sheets;
Databases;

At the initial stage, we are considering a case without CRM integration. Since there are many similar services on the market and at this stage, we cannot predict which CRM the user will have.

As a result, the user will be able to access a ready-made dashboard where, in just 1 minute, they can see all the processes occurring in the business and the key metrics.

UI components:

1. Main metrics board: Total Sales, Orders Quantity, Revenue, Average order value, Returning customer rate (data from Excel/Google Sheets)

2. Sessions (data from website - Google Analytics)

3. Conversions (events in Google Analytics should be set)

4. Audience Analysis: Country, Gender, Age (if data available)

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