Case Study: Increasing Profit in the Graphics Card Category on the TELEMART.UA Online Store

Client

TELEMART.UA is an online store specializing in computer components and peripherals for gamers. It is among the top 50 online stores in Ukraine according to Retailers.ua.

The TELEMART.UA website features a PC configurator as the main sales tool, allowing visitors to build their own customized computer according to their needs. Every day, website visitors use this tool to make over 8,000 virtual configurations.

In this case study, the TELEMART.UA team shares how they increased their market share in the graphics card and personal computer categories.

Disclaimer: This case study was originally written several years ago and includes screenshots of the Pricer24 interface in 2020.

Task

In September 2020, Ukraine experienced a surge in the cryptocurrency market, accompanied by a significant increase in the Bitcoin exchange rate. Mining activity intensified, leading to rapid growth in demand for graphics cards while market availability was limited.

Considering the market shortage and sharp rise in the price of graphics cards, our objective was to conduct rapid market analysis by segment (chipset, memory capacity, brand, and product line) to achieve the following goals:

• Identify segments with supply shortages for procurement and gain extra profit
• Create product availability reports for distributors and competitors to facilitate early reservations and procurement
• Determine pricing in particular segment based on market offerings to increase sales dynamics during the high season
• Analyze new niches within the category and identify growth opportunities

Solution

Data parsing

Time spent by the Pricer24 team: 4 hours

To analyze the graphics card market, we needed to perform product segmentation.

Since our customer chooses products based on technical specifications, we created a custom report in Pricer24 that included key parameters.

The platform began gathering the following data:

• Graphics card series (NVIDIA, AMD)
• Chipset (RTX 3070, GTX 1660 Super, etc.)
• Memory capacity (4 GB, 8 GB, etc.)
• Number of coolers (1, 2, or 3)

The next step was matching products within the custom report to competitors’ and distributors’ SKUs, allowing us to track the following characteristics on a daily basis:

• Minimum, average, and maximum prices
• Number of market offerings by competitors
• Number of market offerings by distributors

Thanks to the custom report, we were able to analyze the product’s SKU and technical characteristics (segments) dynamically.

Following the comparison, we finalized the preparation and tasked ourselves with generating reports for market analysis.

Reports

Report on market shortage analysis

To determine shortages, we generated a report analyzing the number of unique market offerings by competitors within a specific period.

The report clearly showed a decrease in the number of offerings in competitors’ stores for NVIDIA 1650 and NVIDIA 1660 Super chipsets, which were the main drivers of graphics card and PC sales in the sub-$1000 segment.

This analysis, combined with internal sales data and the store’s product profit report, allowed us to generate a list of SKUs to procure for the warehouse.

Report on product segments for distributor procurement

After analyzing competitors, a similar report was generated for distributor offerings.

The analysis resulted in a list of segments and SKUs that the distributor subsequently imported to Ukraine for sale in the online store.

These shipments and data on the availability of limited and/or exclusive products allowed us to form:

• A graphics card sales plan for the marketing department
• A plan for preparation of a prebuilt PC
• A warehouse operations plan (including renting additional storage space for liquid products)

Availability notification report by segment

Most distributors provide information about product availability through emails or messengers, which do not allow for real-time updates on incoming goods.

Parsing product availability by both SKU and segment helped reduce the time required for analysis by the category manager.

The daily routine of reviewing the market offerings report, which takes less than 30 minutes in the morning, enabled early reservations in segments with limited availability.

Hypothesis testing

Case Study: Analyzing Factors Behind Sales Stagnation and Achieving 100% Growth in New Segments

In early December 2020, TELEMART.UA purchased a significant stock of 1050 Ti graphics cards (in the entry-level gaming segment), which had not been previously available in the store.

During their first three weeks on TELEMART.UA there were no sales of 1050 Ti cards even though Telemart had the lowest SKU price in the market.

This SKU was initially also available at two competitors, but by mid-December, it had completely disappeared from competitors’ stores. However, there was no emergence of sales dynamics for this product on TELEMART.UA.

Then at the end of December 2020 and the beginning of January 2021, there was a sudden surge in sales of the 1050 Ti with consistent daily demand, while the price remained stable throughout the entire month of December.

After conducting in-depth market analysis of graphics cards in this segment, we found that at the end of December, similar items were brought into the market at a price 15% less than the selling price of our client’s products.

After these items disappeared from competitors’ assortments, the 1050 Ti became the most affordable offering on the market and gained popularity among customers. This was reflected in the sales report.

Report on the 1050 Ti segment:

• Average price of products in the segment
• Minimum price of products in the segment

According to the report, the product price was higher relative to other products in the segment at the beginning of the month but became average (or even below average) towards the end of the month, which helped drive demand in the low-end sales segment where price is a key purchasing factor.

Results

With the help of a flexible reporting system, we established management algorithms for:

• Procuring limited items, which improved profit and revenue indicators
• Promptly procuring products from distributors
• Differentiating sales based on market demand and supplier offerings, which was lacking among competitors