Dynamic Pricing Examples in eCommerce


You are an online retailer and you have more than 10.000 products on your offer. Some of them you have in stock, some you don’t.

How many category managers do you need for all products to be marketed at the right price, at the right time, for the right customer? A lot!

Imagine being able to set up an algorithm that tracks default parameters for you and sets prices for all 10000 products? Well, you can. It's called 𝐝𝐲𝐧𝐚𝐦𝐒𝐜 𝐩𝐫𝐒𝐜𝐒𝐧𝐠.

Dynamic pricing is a software solution that calculates the optimal sales price of a product based on the input data.

If the system is fully automated, prices are automatically applied to your eCommerce website. If you choose not to apply it automatically, an approval process can be implemented that allows your administrators to double-check the pricing suggestions and apply it manually.

Dynamic pricing examples

We have gathered a few concrete examples of how dynamic pricing in eCommerce works, divided into two groups:

GROUP 1 – Basic Dynamic pricing, first-party data-based

In this group, the dynamic pricing algorithm is based on a number of visits to the website and/or a specific product page, and own sales data. Calculation frequency can be set at the customer’s request, as well as rules per product type or category.

(numerical values in the examples are fictional and need to be adjusted according to business specifics)

EXAMPLE 1 πŸ‘‰ you regularly sell the product at a price of 9,99€, with average sales of 10 pieces per day - you can set the algorithm so that the price drops by 5% if the 3-day average sales fall below 7 pieces.

EXAMPLE 2 πŸ‘‰ a product in stock is not sold for 3 weeks - set the algorithm so that it lowers the price by 3% every 2 days until sales are achieved

  • create separate rules for slow-moving goods or fast-moving goods (e.g. for some products the time frame can be two months if it’s usual to sell 1 or 2 pieces monthly, while for some products time frame will be 1 week)

EXAMPLE 3 πŸ‘‰ you sell a product that is seasonal and scarce (it is rarely found on the market) - set the algorithm so that by increasing the number of visitors to the page of that product (Analytics) the price increases by 2% after every 2.000 visitors

  • you might decide to choose another direction and decrease the price by 2% after a visitor threshold is achieved – it’s up to you, you need to choose the best logic for your business

EXAMPLE 4 πŸ‘‰ a unique website visitor visited the same product page 4 times in two days - the algorithm can lower or raise the price by 3%, depending on the industry and consumer habits, with the aim to motivate the customer to make a purchase

  • Extra tip: An additional step can be made in this case by displaying a unique discount code for frequently visiting customers. This is not a part of dynamic pricing, but it can create the same effect – encourage the customer to react faster.

GROUP 2 – Advanced Dynamic pricing, competition-based

Do you always want to be cheaper than the main competitor in a certain part of the product portfolio? Or do you want to keep your position in the middle, to use your brand recognition and customer trust to compensate for the lack of the lowest price?

The second group of Dynamic pricing rules relies on market data, so it is competition-based. The system tracks competitors’ moves and price changes and uses them as input for dynamic pricing calculations.

When you implement this type of dynamic pricing, you need a source of external (market) data, and this is the point where KLIKER market jumps in. KLIKER market is a competition monitoring and price comparison software, which delivers accurate and structured market data in real-time.

EXAMPLE 5 πŸ‘‰ You want to have the best price on the market (3% or 10€ lower than the competition) - based on Kliker data the dynamic pricing calculation will offer the price which will make you the seller with the lowest price on the market

  • What is ‘the market’?
    KLIKER market covers the most visible and relevant merchants on the market, as the customer sees it. But in terms of dynamic pricing input data this can be adjusted in two ways:

- we can remove merchants you don’t consider as direct competitors from the data set that is feeding dynamic pricing algorithm

- we can add new merchants that are currently not in the scope but have a significant impact on your business

EXAMPLE 6 πŸ‘‰ You want to hold the second-best position (e.g. 3% higher than the lowest price on the market) - based on Kliker data

EXAMPLE 7 πŸ‘‰ You want to have a 5% lower or higher price from a selected competitor

Every rule can be adjusted for a product category, attribute (like brand, color, size, and similar), and exceptions can be made for specific products.


What is the value-added from KLIKER market?

Besides the obvious, real-time price comparison throughout the competitive landscape, there is one more thing that is kind of crucial for this process to work.

It is product matching.

Product matching is a process where KLIKER algorithms connect the same products from different websites, to be able to compare their prices. It seems simple, but it can be challenging since retailers and eCommerce websites tend to write product’s names different, and on the other side there are many products that differ only in one of two characteristics (ex. RAM memory of a smartphone) that might seem a minor thing, but it affects the price a lot.

Our product matching algorithm is enhanced daily, using several information sources to ensure accuracy.

Product matching is a key precondition to compare prices among retailers. For example, if you sell sporting goods, let’s say football balls, the ball should have a specific brand and model so KLIKER can find the same product on the market and match it. If the ball is no-name, it cannot be compared and matched.

To use dynamic pricing or not?

When talking about dynamic pricing, the question that often arises is how 'fair' it is, whether it is OK towards customers and whether the term 'price discrimination' can be applied here.

Generally, this process happens all the time in the offline world, we just don’t perceive it because as customers we cannot be in as many stores several times a day as we can online.

Dynamic pricing increases stock turnover, competitiveness on the market, and response time to competitor moves.

In the online world, everything scales, goes faster and on a larger sample. And the fastest and most agile win!