Dynamic pricing in eCommerce

Dynamic pricing adjusts prices to market demand

Dynamic pricing is a strategy in which a business adjusts the selling price of a product or service according to current market demand and other internal or external factors.

It can mean that the same product is offered at different prices at different times or to different customer segments. Pricing algorithms may consider competitors' prices, availability, current demand, customer behaviour and purchase history.

Dynamic pricing and revenue

Dynamic pricing is familiar in B2B business, where suppliers often prepare individual offers and negotiate prices with each customer. In B2C markets, it has long been used in travel, accommodation bookings, airline tickets and taxi services.

Retailers have increasingly adopted the approach, particularly online, where price calculations and updates can be automated. Prices may be reviewed weekly, daily, hourly or even every few minutes.

Examples of dynamic pricing

Uber and similar services

Ride-hailing services provide a familiar example. Apps such as Uber adjust fares according to demand, represented by people requesting rides, and supply, represented by available drivers.

Uber surge pricing: increased fares during periods of higher demand. Source: Uber.

Airlines

When searching for flights, travellers often notice that the same route costs more than it did the day before or a few hours earlier. Demand may also change after the announcement of a major concert or an international sporting event.

The original article discusses repeated searches alongside changing fares. Observing a price increase after searching, however, does not by itself establish that an individual search caused it.

The airline industry has used revenue-management and dynamic-pricing approaches since the 1980s, with American Airlines highlighted as an early example. The article also names Etihad, Lufthansa, Air China and Emirates as major airlines associated with these practices.

The subject has generated extensive research and many pricing strategies. Airlines dedicate specialist teams to managing demand, available seats and revenue.

Dynamic pricing in the airline industry.

Retail and online stores

The article highlights Amazon, Walmart and Target as retailers that brought dynamic pricing into everyday shopping, including groceries and household products. Amazon is presented as an example of a retailer capable of recalculating prices very frequently.

Fashion platforms such as Zalando are also discussed in the context of pricing strategies designed to improve sales performance and profitability.

The sectors highlighted for growing adoption are fashion, beauty and health, home and garden, and food retail.

Benefits of dynamic pricing in eCommerce

Improved profitability

Dynamic pricing responds to changes in product availability and demand. It can combine market-price movements, competitor activity and product-level supply and demand to calculate a suitable price for the current situation.

How can this improve profitability?

• When demand rises, a somewhat higher price may increase the difference between the purchase cost and the selling price.
• When demand falls and stock remains unsold, a lower price may accelerate sales and release money tied up in inventory. Across many products over time, this can make a substantial difference.
• Automated calculations and updates reduce manual pricing and administrative work, saving staff time.
• A relevant price at the moment a customer decides to buy can improve conversion and increase the number of completed orders.

These potential benefits explain why many online retailers adopt dynamic pricing or consider it seriously. Actual results depend on the quality of the strategy, data and safeguards.

Greater control over pricing

Automation does not necessarily mean losing control. A well-configured system can give retailers a clearer view of their pricing because they:

1. Continuously monitor price trends in their sector.
2. Follow competitors' positioning more closely.
3. Develop a better understanding of supply and demand for individual products.

That information supports more informed pricing decisions and the pursuit of revenue and profit targets.

Flexibility while protecting the brand

A common concern is that changing prices could damage the brand or the customer experience. Customers unfamiliar with the practice may interpret different prices for the same product as manipulation.

This deserves attention, but a considered approach can reduce the risk. Pricing rules should support the brand promise, whether that promise is premium quality, value, speed, personalisation or something else.

Set minimum and maximum prices that reflect the intended positioning. A premium product may need a minimum price even if a lower price would technically be possible. A budget or best-value range may need an upper limit.

Within those boundaries, dynamic pricing can support seasonal and promotional offers while protecting profitability and brand consistency.

Partial or full automation

Managing hundreds or thousands of products efficiently usually requires automation. Dynamic pricing can be fully automated, covering both calculation and publication, or partially automated, with an administrator approving suggested prices before customers see them.

Different businesses and sectors have different requirements, so the ability to tailor the workflow is important.

Learning from errors

Like any human-designed algorithm, a pricing algorithm can make mistakes. Those mistakes can reveal where the model or its safeguards need improvement.

The original article discusses large retailers such as Amazon, Best Buy and Walmart to illustrate how frequent recalculation may limit the period during which an incorrect price is available. This should not be taken as a guarantee that errors are harmless.

It also notes that specialist websites look for unusually low or erroneous airfares. Such attention may bring new visitors, but reliable controls, monitoring and prompt correction remain important.

Challenges of dynamic pricing

Customer understanding

Customers accept that prices change, but they want to understand how and why. A seasonal or weekend promotion feels familiar. If a shirt costs 20% more on Monday because a weekend offer has ended, the reason is relatively clear.

Price changes within the same day, or differences between an online store and a physical branch, may be harder to understand. Although dynamic pricing can save customers money, it is also used to improve retailers' margins. Someone who discovers that another customer paid less may feel disappointed, abandon a purchase or lose trust in the brand.

Communication and transparency

Explain the pricing approach clearly in the relevant sales information and customer communications. Promotional language should be truthful, whether it highlights a changing offer or a genuinely personalised price.

Customer-service teams should be able to give a clear, informative answer when asked why a price changed. Consistent explanations help people understand the offer and make their purchasing decisions confidently.

Lost sales across channels

ROBO stands for “research online, buy offline”. Customers may compare prices online even while standing in a physical shop.

If they discover that the same retailer offers a lower online price, they may postpone the purchase or look elsewhere. Clear in-store communication about online offers and convenient ways to buy through the retailer's own channels can help retain the sale.

Immediate need also matters. A customer who needs a product straight away may still choose the physical store despite a lower online price.

Customers adapting to the system

Some shoppers believe that repeated browsing can influence personalised prices and use private browsing to limit the information available to a retailer. The original article discusses this as an example of customers changing their behaviour in response to perceived pricing rules.

Another example involves comparing several ride-hailing apps. The article describes scenarios in which a returning user is shown a different offer after checking alternatives within 30 seconds or a minute. Such behaviour depends on the service and its actual algorithm, so it should not be assumed to apply universally.

Price wars

If two competitors both configure their systems to undercut one another, repeated reductions can continue until one reaches an unprofitable price.

This is a scenario to avoid. A strategy based solely on being cheaper than the next retailer can undermine the business and does not create sustainable value.

Four pricing approaches used in eCommerce

1. Segmented pricing

The perceived value of a product may differ between customer segments or geographic markets. A warm jacket has a different practical value in a polar region than in the tropics. Fishing equipment is more relevant near the coast than in a desert.

A segmented pricing model can take those differences into account. The original article compares this with familiar offline examples: coffee on a central city square may cost more than in a neighbourhood café, and groceries on a tourist island may be 10% to 20% more expensive than on the mainland, even within the same chain.

These examples explain the commercial reasoning behind segmentation. Any actual implementation must be appropriate for the market and the customers concerned.

2. Time-based pricing

Time-based pricing uses periods of the day or other time windows to determine higher or lower prices. Transport services such as Uber and Bolt are familiar examples.

Food retail offers another illustration: prepared food such as sushi may be discounted in the evening to sell the remaining stock.

3. Peak pricing

Peak pricing raises prices during periods of particularly strong demand. Examples include accommodation during holidays, Christmas lights before the festive season and swimwear before summer.

A dynamic model may use search or visitor activity as one of its demand signals, adjusting prices within defined limits as interest increases.

4. Penetration pricing

When entering a new market, a retailer may temporarily offer lower prices to build awareness and encourage customers to try the brand.

A rule could give a customer a 30% discount on their first purchase, or first few purchases, before returning to normal prices. This makes the introductory offer conditional and automatable.

What is needed to implement dynamic pricing?

Three components are required:

1. A strategy: define the overall approach and the rules for each relevant category or brand.
2. Pricing software: use a dedicated external application or functionality within the eCommerce platform to calculate prices.
3. Input data: provide the necessary internal information, analytics, market observations and competitor-price comparisons.

How prices normally reach an online store

An eCommerce platform is often integrated with the company's ERP. The ERP holds product names, technical specifications, purchase costs, selling prices, inventory and sales information.

In a typical setup, selling prices are transferred from the ERP to the online store. When a price changes in the ERP, the integration updates the store accordingly.

Where dynamic pricing can be implemented

Within that architecture, price calculations can be introduced in three places:

1. Inside the ERP, using an appropriate pricing component.
2. In an external pricing application connected to both the ERP and the eCommerce platform.
3. Inside the eCommerce platform itself, as with the Shape Core approach described here.

In every case, the pricing software needs input data that the configured algorithm can use to calculate the selling price.

Input data and example rules

1. Internal sales data: reduce the price by X% if daily unit sales fall below ten.
2. Supplier availability: increase the price by X% if supplier stock falls below Y units.
3. Customer information: where appropriate, use geographic, demographic or behavioural signals. The original example changes a price by X% when a customer has visited more than five times in the past week.
4. Market comparisons: adjust the price to place the offer among the three lowest-priced sellers, while respecting the retailer's limits.

Dynamic pricing in Shape Core stores

Shape Core supports a dynamic-pricing algorithm for calculating product selling prices. Because the module is developed within the same platform as the online store, integration can be more straightforward than connecting an unrelated pricing system.

The model is tailored to the sector and the client's requirements. We examine the module's capabilities alongside business needs, define the rules together and then refine the algorithm as results become available.

Calculated prices can be published automatically or submitted for administrator approval. The retailer also determines how frequently prices are calculated and updated, retaining control over the process.

KLIKER market data for eCommerce pricing

What is KLIKER?

KLIKER is a web-based application for market analysis, competitor monitoring and price comparison. It brings information about a market together in one interface.

The My Market screen in KLIKER market. The example shown is from July 2021.

The application described in the article collects online-offer data several times a day for a particular market and product category, such as laptops in Croatia. It processes that information and presents it in several ways:

1. My Market: an advanced search view with category-specific filters and sorting, potentially covering more than 30 characteristics.
2. Dashboard: graphical views of key indicators and market trends.
3. Alerts: recent changes such as newly listed products, price changes and stock movements, searchable by retailer or brand.
4. API: access to the data for further calculations and analysis in connected systems.

The API and demand for pricing tools led to the KLIKER dynamic-pricing module described in this article, which supplies market information as input for price calculations.

After integration, information can be transferred directly into the pricing system. Users can also browse and analyse it in KLIKER or export it to Excel. The described update schedule varies by category, with several refreshes per day and the possibility of an on-demand refresh.

Data available for an individual product

For a product identified by a unique SKU or EAN, the dataset can include:

1. The number of retailers currently offering the product.
2. The lowest selling price in the market.
3. The retailer offering that lowest price.
4. The average selling price.
5. The retailer's own current market position.
6. Promotional information.
7. Stock availability at individual retailers.

Combining market and internal data

Combining KLIKER market information with the retailer's weekly unit-sales data provides a useful foundation for a dynamic-pricing model.

KLIKER is presented here as a browser-based SaaS application, accessed by signing in without a local installation. The subscription described depends on the number of product categories and markets monitored.

For more information, contact us and we can introduce you to the KLIKER team.

Conclusion

Dynamic pricing is an important tool in a competitive online market. It uses software to calculate prices from inputs that may come from the ERP, first-party and zero-party customer information, or external market-data services such as KLIKER.

Shipshape offers dynamic pricing as an option for retailers using Shape Core. The algorithm and pricing rules are agreed with the retailer, who can choose full automation or a workflow in which an administrator approves calculated prices.

The objective is not simply to change prices more often. It is to use reliable information and clear boundaries to improve commercial performance while retaining control and customer trust.