Automated price monitoring: Maintain margins
Thousands of companies compete with each other. Unlike traditional retail, dropshippers do not have exclusive products: often dozens of sellers offer the same goods. In such an environment, it is the price that determines who will keep the customer, according to experts at Betonlogos company. Even a 2–3% error can eat up all the profit, as the margin in dropshipping rarely exceeds 10–20%. But tracking prices manually is not only difficult, it is practically impossible on the scale of modern e-commerce. How can manual price monitoring be avoided?
At Betonlogos s.r.o., we have long been convinced that old methods of analysis — Excel spreadsheets, selective checks, manual filters — can no longer keep up with the speed at which the market is changing. Parser-based software solutions allow you to quickly and accurately track prices, analyse changes and generate reports. Automation not only speeds up the monitoring process, but also reduces the likelihood of errors that occur when processing data manually.
Parsers and machine learning-based systems allow you to:
- scan competitors' websites in real time
- collect data in different formats (HTML, XML, JSON)
- generate reports and dashboards for analysts
- adjust prices
- predict price changes
According to eMarketer research, companies that have implemented dynamic pricing maintain margins that are 10–15% higher than their competitors on average. And in highly competitive segments, the response time to price changes is reduced from several hours to minutes.
Let's try to calculate. If an online store has 1,000 products and at least 10 active competitors, then 10,000 prices need to be tracked daily. Even an experienced analyst is physically incapable of processing such a volume: by the time they check some of the items, the rest will have already changed.
The situation is complicated by the dynamics of marketplaces. On Amazon, price adjustments occur dozens of times a day. On AliExpress, promotions can last only a few hours, and the price of popular items changes several times a day. Shopify is structured differently: the seller builds the sales system themselves, and the platform does not bring in buyers. You need to advertise yourself, attract and interest potential buyers. And that is difficult, costly and time-consuming.
Why does manual monitoring no longer work?
Technology instead of manual labour
Artificial intelligence in pricing
Today, it is no longer just about collecting data. Machine learning algorithms recognise website structures, automatically find prices and product cards, analyse seasonal fluctuations and predict dynamics. According to Gartner's forecast, by 2027, more than 70% of online stores will use such systems.
Whereas companies used to ‘catch up’ with their competitors by adjusting prices after they changed, algorithms now offer a ‘get ahead’ strategy. The system can take several factors into account at once: demand on a specific day of the week, buyer activity from different regions, the history of previous promotions, and even exchange rates or inflation. The algorithm not only records a competitor's price change, but also ‘understands’ whether it is worth responding to it, according to managers at Betonlogos s.r.o. If the reduction is due to a one-off sale, the system can ‘pause’ and maintain the margin or react instantly if there are signs of dumping.
Betonlogos: when price works for you
The Betonlogos dropshipping automation platform allows you to process and track data from a database of thousands of products from hundreds of system-verified suppliers in near real time. When connected to the platform, dropshippers can use the automatic order processing option and enable the information update feature.
Betonlogos works with dropshippers, manufacturers, and retailers. We help businesses automate their routines, reducing costs and building new supply and sales chains.
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