Data Management or how to improve the efficiency of your online business

Data Management or how to improve the efficiency of your online business

03/30/2022 - Artificial Intelligence

Automated data management is one of the data trends for digital business growth in 2022. How can data management help increase your online store’s profits? We’ll tell you the 3 ways you can use data management to drive the improvements your business needs. These are competitor analysis, dynamic pricing and stock management.

Competitor analysis

The extensive range of online sales makes the competition more numerous, diverse, and dispersed than ever before. Competitors are no longer just stores that look like or are of the same model as your business. The competition has opened to include other business models that can also grab a significant sales percentage of products you include in your catalogue.

Tracking and analysing the competition requires a much more significant amount of data to be collected than before. Studying competitors’ behaviour is key to making your business competitive. Therefore, having tools to help you collect and manage this data is essential.

Data warehouses allow you to collect, accumulate, and organise this mass of data, then analyse and draw market conclusions. How many competitors do you have? How many products do they include in their catalogue? When do their sales peaks occur? What types of promotions do they offer?

 

Big data and dynamic pricing

The behaviour of online users and the variety in sales platforms make price fluctuations constant and very numerous. Price management tools allow you to compile all your competitors’ price changes to elicit trends and change and seasonality triggers.

It is also possible to link this information to the product’s market positioning in terms of sales volume, online searches, etc.

The key lies in reading data en masse. It would be impossible to carry out this task manually, so it is essential to have the necessary technology to manage data collection and resultant actions.

Stock management using AI

Stock management using AI

The context of intense post-pandemic online sales has boosted the number of digital transactions per year. To be precise, more than 500 million users bought online in Europe in 2021. This new reality directly affects the warehouses of all online businesses. Restocking formulae need to be prepared to cover demand peaks and avoid stock breaks.

Artificial Intelligence appears as the ultimate remaining bastion for data management that allows your business to have a healthy and efficient warehouse. Data management of this information is essential to avoid structural or maintenance overspends, or even worse, the accumulation of expired products in your warehouse.

A practical example: Analysing historical sales and available stock data will help you efficiently predict how to restock your warehouse to meet user demand.

As you can see, data management spans different tasks and departments within your organisation. Data management allows you to plot the path to efficiency within the market. Trends in data use promise that data management will be accessible for all. Hence, making use of data collection and analysis will be possible for everyone. Sales and management profiles, human resources management and warehouse profiles allow you to make better decisions to improve the efficiency of your online business.

Category: Artificial Intelligence

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Maria Jose Guerrero
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