The large majority of shops grow profitably after pricing is implemented, and the price of the license is paid only by the growth in profit. At the same time, the load on product managers is reduced, and they optimize individual pricing areas such as sales, unsaleable products, pricing promotions, and PPC optimization. All this leads to gradual business growth.

Yes, the service is available in all EU countries

Pricing can be done almost automatically after the initial setup and the time required for administration is in the range of hours per month. If the customer wants to get the most out of the product, they use analytics, test new strategies, and the time commitment increases.

The balancing strategy looks for the profit peak in the product. Inputs to the calculation are product price, traffic, margin, long-term historical data, short-term data, time, day of the week, competitor price if available, and other parameters. The strategy is combined with lower and upper limits that limit the possible range of "float" price settings. This ensures that the price is not set outside the range that the user does not want, but constantly reflects market events and product sales. The strategy is more powerful than the standard following of competitors' prices.

Simply drag the mouse to place the pricing strategy on a specific directory/category. Products can then be manually or automatically placed into the category.

Yes, you can directly set specific shops that the pricing strategy then evaluates.

The exact order can be set. For example, a product can be first on the market, or 1-6 on the market. It can be combined with a list of selected VIP competitors to define the ranking within this group. At the same time, it is possible to move within the selected ranking range using a balancing strategy. A frequently used option is to use the median/average of the market calculated from e.g. the 10 cheapest competitors.

There is a list of ignored shops. Most often these are some smaller shops, or a clone of a shop from the same customer.

The price deviation can be set from the median, average, market or even specific shops. It is possible to set either a percentage deviation or a nominal deviation. All of these settings can be combined with lower and upper price limits.

Competitors' prices are repriced using a balancing strategy that seeks the profit peak of the product. At the same time, the initial price of the product can be derived from price levels or from other products. The price of products is therefore responsive to sales and not static.

The minimum product margin can be set individually for each product or globally for a pricing strategy. The minimum margin can be set directly in the admin environment or in the import XML from the customer's system. Analyses are then available that show the relationship between the set minimum margin and the actual sales margin. This information indicates whether a product "bumps" the minimum margin if, for example, the price level in the market has changed. This often leads to a drop in sales.

A temporary minimum margin is most often used for new products, where for example the minimum margin is higher for the first 14 days and then the market price is accepted.

The minimum product price is most often used for low nominal value products, where for example the product must cost at least EUR 2. The minimum price can also be used as an additional lower limit that the product price can reach.

The recommended end price can be applied as the final price, or a maximum percentage deviation from this price can be set. For example, a strategy that reacts to the price of selected competitors and follows the price. This does not result in a price spiral and the price is limited to X% of the recommended end price. Subsequently, the net profit and success rate of products in PLA campaigns is also evaluated, possibly automatically placing them in another PLA campaign.

There is a pricing strategy that calculates the minimum price for the last 30 days and sets the desired discount from the current price. It is also possible to automatically return products to the previous pricing strategy after X days. The standard use is for discount promotions, where it is easy to select products that have, for example, a 20% margin even after the discount. This discounted price can be automatically sent to Google and displayed as a "crossed out" price.

The set strategy is applied after the previous pricing strategies, which are layered. The final price of the products included in the set is then reduced by X% according to the settings. The individual products in the set can thus be dynamically repriced, but the resulting set of products always has a better price.

The manual price of a product can be set directly in the admin or in the import XML. For manual price you can also set the validity period of the manual price. After this time the product is automatically moved to the previous pricing strategy.

It is possible and this information is transferred via XML and Karsa sets the corresponding values specified in the XML.

Yes, you can set the number of places to round for each strategy. For example, it is possible to have two decimal places for the euro.

Ruleflow is used for this purpose, which places products according to conditions into individual pricing strategies.

If we do not have such a strategy already created, or the desired price behavior cannot be achieved by a combination of settings, it is possible to create a new strategy that is only available for your store.

To successfully reprice products, it is necessary to rely on analytical data. Without analytics, prices are set according to "impressions" and this is less powerful than making decisions over data. After repricing/changing strategy, it is also good to evaluate the impact on profitability. This process makes the store more efficient. "What can be measured can be optimized".

The basis is our developed analytical pricing cube, which offers analytical and pricing APIs. This API is executed using Karsa script, thanks to which we are able to flexibly extend reporting and pricing strategies.

A customer information system that sends information about completed orders, at the same time the XML feed with products is regularly loaded. The individual columns in this can be used in analysis, reporting and pricing strategies. At the same time, information from Google Adwords, GMC, GA4 is downloaded several times a day. Therefore, information about actual visits and costs are available.

The data in a cube is updated every 15 minutes. It is therefore possible to monitor the profitability of a store during the day. For each project, however, it also depends on the frequency of repricing and sending orders.

The analyses are split into two main groups. Analysis in the product listing, where individual products are displayed on a line. Parametric and full-text searches can be used to filter products, and the aggregation row provides information about the filtered group of products. Segmentation analysis combines data from individual products. A store or any generated product group can be evaluated and various attributes can be used for segmentation, such as manufacturer, price, margin, profitability, strategy, eshop category, fixed products, products with and without competition, and more. A segmentation report is a very important tool that helps with evaluating business results.

Yes, you can create custom tabs in the product listing and edit the content of the contained columns.

It is a column that is created by calculation, similar to Excel. You type in an expression or condition and the result is displayed in a column named by you. Calculated columns are often used to show success over a selected time period, or to calculate a trend of when a product will sell out.

Competitor prices are available in several reports. In the product detail, in the product listing and in the segmentation analysis. You can see how many times a competitor has been below your price, whether they are increasing their price variance, how many times they were first with their price and other useful columns.

Each order contains expense information such as free shipping, discount coupon and other free defined costs. These costs can be added to each order and, according to the attribution model, allocated among the products included in the order. It is then immediately apparent that products that are frequently sold solo have a lower netprofit than products sold with other products.

Yes, this information is then displayed for coupons, traffic, profit, margin and other metrics. For example, you can see who is taking advantage of coupon promotions and whether, for example, a product discount has been attracting new users so that the store is taking market share.

Yes, there is a configuration in the segmentation report for this purpose. Individual pricing strategies are analysed in this way.

Yes, it is possible to analyze the whole eshop structure or just the selected level of category. More than 100+ metrics are available.

If only the nominal profit is evaluated, it is difficult to assess what impact the price increase before Christmas had on a group of products, for example. Naturally, profit and conversion increase as Christmas is approaching. By using the profit weight you are able to see what profit share this group of phones had before and after the change in pricing strategy, for example. This weight can be applied to the entire store as well as to the category.

Yes, and the difference columns for each metric are also displayed.

It is an exchange of 3 XML files and inserting JS code into the eshop. The whole connection can be done in 8 hours. It all depends on the customer's possibilities. Standard time including communication and data verification takes approximately 14 days. A documented API is available. We support OpenAPI, REST, Web service and FTP file exchange.

It is possible to use the extended XML feed for Google GMC or Karsa XML format.

The XML file with the products should be available at the url where the Karsa service has access. The file is loaded before each repricing, i.e. several times a day. During the day the purchase prices of products are updated, new products are added or the minimum margin is updated.

After the Karsa prices are calculated, your system is notified and the prices are distributed to Google. Therefore, it is ideal to display the newly proposed price in the e-shop as soon as possible. Karsa optimizes prices during the day and a price that is not displayed does not have the desired effect.

Yes, our administrators will mark the newly added attribute as to be archived and then it will be available in reports or pricing rules. Examples could be availability, stock levels, expiration dates.

Karsa primarily optimizes profit, so it is important to regularly export new orders to Karsa at short intervals of about 15 minutes. The strategies evaluate, in combination with other factors, how optimal the current product price is and whether it should be changed if necessary.

We support the exchange of XML files using FTP