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Case Studies
29.11.2024
140

Case Study: Dynamic Pricing for Scaling Home Appliance Sales

Content:

Client

Tasks

Solutions

Results

Client feedback

Client

Our client is the Ukrainian branch of a globally recognized manufacturer of small household appliances.

The manufacturer’s portfolio includes several brands. In 2021, the Ukrainian branch launched three mono-brand online stores as part of a global initiative by the manufacturer to establish their own channels for distribution to and communication with end consumers.

To drive sales growth through these online stores, the client needed to continuously monitor price dynamics in the market and respond to changes in real time while minimizing human error.

Expanding online was the logical next step for scaling our business. However, we knew that the Ukrainian e-commerce landscape was already highly competitive, so we had to remain price-competitive. Previously, we could gather competitor pricing data in Excel sheets and upload it into 1C, but that was no longer sufficient. Competitors’ prices now fluctuate multiple times a day. To achieve the sales targets we set for the online channel, we needed a solution that provided real-time, accurate data and automated product repricing.
Manager, Client’s Ukrainian Branch

Tasks

Task 1: Ensure competitive market pricing while avoiding price dumping

In Ukraine, online shoppers primarily use search engines to find products, making paid search ads a key driver of sales in the household electronics and kitchen equipment segments. Customers typically begin by searching on Google, then visit multiple websites to compare prices and select the best deal.

If our online stores offer products at prices higher than the market average, this may result in the loss of potential customers. At the same time, as the official representative of brands, we cannot afford dumping because our competitors are also our wholesale customers. It would be unfair and unacceptable on our part. We do not want to initiate price wars. Therefore, we need to maintain average market prices.
Manager, Client’s Ukrainian Branch

Context:

Many online stores sell products from the client’s brands. To demonstrate responsibility towards their partners, the client does not lower their prices just because a single competitor’s price has dropped below the recommended retail price. For example, if a small retailer buys products of one of the client’s brands from an unknown source and sells them for UAH 5,000 while the recommended price is UAH 8,000, the client will not respond. Doing so, in fact, would cause them to violate their own recommended price and could end up damaging the brand’s pricing integrity.

We understand that small shops are not our true competitors when it comes to pricing. We have different business objectives than they do. Therefore, we focus on market dynamics shaped by key competitors, who are our strategic distribution partners.
Manager, Client’s Ukrainian Branch

The core principle behind pricing adjustments was clear: Only react to pricing actions of online stores that are leaders in sales of the client’s products (referred to as key competitors).

However, situations can arise where a small retailer lowers their price first, prompting Key Competitor A to adjust their price accordingly. Key Competitor B, monitoring competitor prices, then notices Key Competitor A’s lower price and follows suit. This triggers a chain reaction, with all key retailers engaging in price cuts. If our client continues to adhere to the recommended price during this process, they risk losing sales.

Thus, the second key condition was to react when the majority of key competitors have already lowered their prices.

We adopted a balanced approach: If one competitor sets a low price, we observe. But when most key competitors have lowered their prices, that’s when we take action. First, others will inevitably follow, and second, with a history of price changes as evidence, we can be confident that we are acting fairly and transparently.
Manager, Client’s Ukrainian Branch

Task 2. Ensure the marginality of goods

The second important task was to automate the process of returning prices to the original level in order to avoid margin losses when other online stores start to raise the market.

Previously, we reacted to price changes situationally, in manual mode, focusing only on key positions that provide the company’s main revenue. Managers were tasked with performing timely monitoring of price increases for these positions in the market and promptly adjusting prices in our online shops accordingly. However, due to limited resources, we were unable to promptly address all price changes across the entire assortment.
Manager, Client’s Ukrainian Branch

Therefore, we set the following goals for this project:

  • Automate data collection from competitors’ sites
  • Enable comparison and analysis of prices for the client’s goods relative to prices on key competitors’ sites
  • Develop and implement a dynamic pricing system that would provide for automatic repricing of goods in accordance with the established rules and transfer updated prices to the client’s websites

Given the specifics of the client’s CMS and accounting systems, all of these requirements necessitated an individual approach. This was an interesting challenge, and our team readily accepted it.

Solutions

Internal client data

The client’s mono-brand online stores are built on the same platform and use the same accounting system, while the front end and sites are spread across several domains.

In the accounting system, managers store and update data on:

  • Availability of goods
  • Recommended prices
  • Minimum allowable prices below which sales of goods become unprofitable

Each of the client’s online stores has a separate feed for transmitting information to the Pricer24 platform.

External data (prices of competitors)

Competitors’ price data is collected by Pricer24 parsers several times a day. Our system analyzes collected prices, compares them with recommended prices, and identifies possible deviations.

To ensure data accuracy, the client keeps up-to-date information on availability along with recommended and minimum prices in their accounting system, and Pricer24 daily checks and updates data on new products that appear on competitors’ websites or in the client’s catalog.

Product repricing script

Repricing of products on the client’s mono-brand online stores is carried out according to an algorithm that provides for a prompt response to changes in market prices in both directions: price decreases and returns to the initial price level.

A scheme for calculating the optimal price using dynamic pricing. Here's how to maximize profit with tools like Pricer24.
Scheme for calculating the optimal price

Transferring data to the client

Prices calculated by the repricing script are transferred to the client’s accounting system. If more than two instances are found where a product’s price in the market differs from the price submitted by the client in the feed (e.g., the recommended or MAP price), the client receives information about these pricing violations and the violating sellers in the form of a JSON feed.

If a calculated price is higher than the minimum allowable, the accounting system allows it to be displayed on the client’s online store. Otherwise, it sets the minimum allowable price.

Thanks to parsing, which is carried out several times a day, the client promptly receives updated competitors’ prices in the feed. This makes it possible to avoid margin losses, ensuring timely price corrections when competitors return the price to the recommended level.

Results

  • The process of repricing goods is automated, which significantly reduces the need for manual intervention and reduces the possibility of errors.
  • The role of operations manager on the client’s side is now reduced to periodic monitoring to identify anomalies and adjust prices if necessary.
  • A solid foundation has been created for scaling sales in the client’s online channels.

Client feedback

“Initially, we planned to receive feed files and process them manually. However, thanks to Pricer24’s flexible approach, we implemented a custom API, allowing for near real-time data processing.

During the implementation phase, the team was always open to communication, and all technical issues were addressed promptly.

The tool has become essential for our scaling efforts. We received even more than we expected: a high-quality product tailored to our specific needs and business goals. This is what we value most about Pricer24.”

Take a consultation
  • Market analytics
  • Price parsing
  • Product visibility
Take a consultation
  • Market analytics
  • Price parsing
  • Product visibility
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