Dynamic pricing is not a new theory or practice. Rather, the concept of updating prices based on supply and demand has been an integral piece of commerce strategy for centuries.

Today, however, in the technology-driven world of ecommerce, a new angle is emerging.

By pairing dynamic pricing concepts with advanced ecommerce strategies, brands are now able to tap into powerful methods for maximizing profit margins. And much of it can happen automatically.

With this being said, let’s look at how dynamic pricing works and ideas around how best to implement dynamic pricing into your ecommerce strategy.

What is Dynamic Pricing?

Dynamic pricing incorporates scalable and continual repricing strategies, that involves constantly changing the price of products based on key critical factors, including:

  • Supply and demand
  • Market trends
  • Competition and industry standards
  • Consumer expectations
  • Website and consumer behavior
  • Inventory level

A prime example of this is Amazon’s pricing model. Amazon constantly adjusts its pricing on a minute-by-minute basis. Their algorithm filters through large amounts of data, including market trends, competitor pricing, consumer habits, and more. The result is that they can sell more products at the highest profit possible.  Have you ever put something in your Amazon cart or wish list only to get a message later that the price of the item has changed?

Now Amazon is a MASSIVE MARKETPLACE, but the same ideas hold for all ecommerce sites.  They are an ideal setting for dynamic pricing strategies by leveraging new technology platforms (many utilizing AI), where prices can constantly adapt intelligently – benefiting both you and your customers in finding the optimal price points for your products and services.

Dynamic Pricing vs. Personalized Pricing

Dynamic pricing is not to be confused with personalized pricing – these are different based on the following factors:

Dynamic pricing looks at the relative value of products in relation to the rest of the market. This pricing strategy allows you to adjust to changing market conditions without the need for personal information or invading consumer privacy.

Personalized pricing changes a product’s value based on individual behaviors and past shopping experiences. This pricing strategy can be considered controversial as it may factor in data that is private and personal.

Dynamic Pricing Benefits:

  1. Responds quickly to consumer demand
  2. Takes into account price perception
  3. Allows for greater pricing strategy controls
  4. Is a revenue driver
  5. Allows for more precise SKU pricing
  6. Enables optimization of profit per product

How Dynamic Pricing Works

Dynamic prices are algorithmically figured by self-improving machine learning equations. These algorithms take into account a multitude of pricing optimization variables, some of which are below:

  1. Price management automation
  2. Profitability analysis
  3. Price/trend forecasting
  4. Price competition marketing analysis
  5. Customer analysis for personalized pricing
  6. Sufficiency to adapt to different situations and change

For Dynamic Pricing to work, two main actions must be taken: 1. Information gathering, and 2. Information organization.

Information Gathering could entail the following:

  • Pricing Information – for each product, configurations, and discounts
  • Availability – for each product, and configurations
  • Product Information – for each product that can include SKU’s, titles, dimensions, weight, color – all for price & product matching
  • Final Price – shipping and any other costs associated with the order

Information Organization could entail the following:

  • Price Calculations – based on interval settings (contribution margins, inventories, and competitive prices)
  • Price Forecasting – for price management to manage future categories
  • Psychological pricing – price associated with perceived quality
  • Product Matching – external and internal product matching

How Dynamic Pricing Algorithms Work

Pricing algorithms enable companies to manage pricing through artificial intelligence and machine learning techniques – which allows them to make informed decisions to scale and grow more efficiently.

This brings flexibility in pricing operations – which in turn, allows you to set prices dynamically, as the market changes. Factors such as market trends, customer behaviors, buying patterns, and demand change all factor into setting an optimal price, and the perfect time.

Dynamic pricing algorithms work by understanding the difference between price and demand – and consider many of the following factors to formulaically adjust pricing. These factors include:

  • Demand cannibalization
  • Competitor prices
  • Inventory Costs
  • Procurement Expenses

Dynamic Pricing Workflow Examples

By developing automated pricing strategies that can dynamically adjust to the market, companies are now able to understand their target markets and audiences more than at any time previously.  To understand a typical workflow, a typical dynamic pricing algorithm can follow these four steps:

  • Step 1: The dynamic pricing algorithm crunches competitive price points,  historical sales data, and market demand.
  • Step 2: The dynamic pricing algorithm identifies interdependence in demand points
  • Step 3: The dynamic pricing algorithm processes mathematical models across a wide range of pricing and non-pricing factors to yield correct estimations and optimal prices.
  • Stage 4: The dynamic pricing algorithm deploys the prices and continually reruns the equation for the latest repricing results.

Understand that this is a basic framework, and more specific/complex cases are certainly used. Neural networks and other sophisticated techniques are now being used to process hundreds of millions (and even billions) of data points to generate pricing details, depending on the size of the business, and the sophistication of the strategy.

Creating and executing this kind of strategy is complicated, which makes choosing the right dynamic pricing software/platform that much more important in order to maximize this strategy.

What is Dynamic Pricing in Ecommerce?

Dynamic price optimization is the process of offering products at various prices that adjust according to market conditions. Pricing on products and services are dynamically changed based on competitive pricing, supply & demand, sales requirements, and conversion rates.

Currently, by leveraging machine learning algorithms, pricing can be efficiently automated to find and maximize price points by using sophisticated formulas, leveraging all of the available proprietary and public data of a market.

Related Reading: The Essential Guide to Ecommerce Pricing Strategies

Want more advice on this topic?

Learn More >

Dynamic Pricing of Tomorrow

The evolution of Dynamic Pricing now also includes the aspect of behavioral-based pricing. Not only is pricing based on item-specific elements, but also based on product performance, customer behavior on the website, and inventory level on the warehouse. An idea of combining what we know about our own products, with the knowledge of the market plus the insights we have from our product performance.

This will shift the focus from a spiral to the bottom in terms of pricing to a maximization of your product profit, and securing the prices which the consumer wants to pay, and not what the market dictates.

Imagine, that you automatically would be able to group your products based on last time of sale, amount of visitors on the product page, percentage of your conversion rates, the level of products in stock. All combined could be described as your “slow movers”, which could be placed in a more aggressive strategy to push out more goods and increase your turnover rate, completely automated.

Seeking a dynamic pricing tool, features such as these should be an essential part of your need.

Price Optimization Based on Market Trends

Perhaps the most fundamental application of dynamic pricing is optimizing prices based on market trends.

This analysis begins by identifying the competitive landscape for both current and new markets. Based on this analysis, pricing can be adjusted to tap into previously untouched markets. Overall market-based pricing is a great way to begin the optimization process and deliver on a growth objective in your digital commerce strategy.

And, while market trends have generally / always played a critical role in pricing — standing alone, this data set does not tell a holistic picture.

Getting to Know Your Competitors and Retailers

Married to market trends is the adaptation of pricing based on your competitors and their current, as well as historical, pricing strategies. This is particularly relevant in the B2C sector, where pricing plays a critical role in decision making given that a small price difference in an item can add up to a huge impact.

Factoring this into your dynamic pricing strategy involves carefully monitoring and tracking your competitors’ prices constantly.

This is another area where ecommerce sites are ideal for this technology – with dynamic pricing platforms, you can automate the tracking down to the item or SKU level.

For B2B commerce, tied closely to tracking competition’s pricing is monitoring retailers and resellers to gain an understanding of who is selling your products, where, and at what price.  This will help you determine the right wholesale pricing strategy.

This is especially helpful for verticals adhering to MAP (minimum advertised pricing). There is also an application for retailers, gathering this data can be an arduous task if it’s not automated by a dynamic pricing platform and monitoring competitors for MAP violations can give you leverage (information) to go back to your suppliers.

Creating an Aligned Ecommerce and Marketing Strategy

If your business already has a dynamic pricing strategy in place, then the key to optimizing this tactic further requires that your pricing strategy and ecommerce strategy are aligned.

For omnichannel retailers, this is critical. For example, take a look at profit margins across channels for apparel retailers.

On average:

  • In-store sales had a profit margin of 32%
  • Online sales had a profit margin of 30%
  • Buy online pick up in-store (BOPIS) had a profit margin of 23%
  • And online ship from the store had a profit margin of 12%

It is also important to factor in that BOPIS returns may have a higher contribution due to upselling opportunities while in-store and minimizing returns.

In the same vein, it is critical to align your marketing budget to the most profitable products based on dynamic pricing. This is one of the most important insights to bring back to your marketing team and is one of the top pricing strategy mistakes.

Putting marketing dollars in support of the most profitable products is an essential best practice that helps align all strategies. In doing so, marketing teams can adjust their spending in real-time as product pricing is also dynamically shifting.

The Key to Implementation

While the fundamentals of dynamic pricing are well established, the difficulty lies in how you gather large data sets on an ongoing basis and feed this back into your ecommerce strategy.

The manual methods that businesses have relied on historically can only get you so far. For this reason, the first step to implementation is picking the right platform.

Shifting to a Dynamic Platform

Today, AI-based pricing applications, such as PriceShape, eliminate manual competitive analysis from the ever-increasing market (often more than 100+ competitors) and calculations, providing an automated process that combines internal and competitive pricing with inventory data.

These inputs eliminate guesswork and can be weighted on a custom basis. This allows for data-based, intuitive pricing decisions that can be enacted in real-time.

Additionally, because many of these tools track stock levels, you can use this as an upsell opportunity to move more products. In times of high seasonal demand, you can monitor stock levels and increase prices relative to competitive inventory. Not only does this create a competitive advantage, but it can also create more loyal customers via a better customer experience.

Constantly Re-Evaluating Your Strategy

Regardless of the process or platform you use to implement your dynamic pricing strategies, you must re-evaluate the overall strategy continuously. This is not a one-and-done scenario, as your competitive landscape is constantly changing. Simultaneously, your overall ecommerce customer experience and the expectations that follow never remain in one place for long.

This can all have an impact on the potential for increasing revenue and maximizing profit. Through daily, weekly, and quarterly evaluations, you can ensure that your pricing structure paired with your ecommerce strategy is still delivering the expected value.

Rely on Expertise

In most ecommerce businesses, there is a lack of bandwidth for implementing new platforms and pricing models – placing a heavy burden on IT, marketing, or merchandising teams.

At Vaimo, we can help you optimize your pricing strategy so that it aligns with your business goals and delivers the best value to your customers.

We begin with an analysis, benchmarking you against your competitive set, then help you develop a strategy around the best paths forward that have the most business impact. If you are not currently employing some form of dynamic pricing strategy and would like to learn more—reach out, we’d be glad to chat.

Learn More >