Dynamic Pricing: A Comprehensive Guide for Retail and eCom in 2023

With the Price Segmentation Strategy (also referred to as Segmented Pricing), a retail chain or eCommerce organization can offer varied prices to each distinct customer segment.

A majority of the "dynamic pricing scandals" emerged as a consequence of flawed or inaccurate implementation of Segmented Pricing.
For instance, there are stories online about how a regular customer of an online store inadvertently discovered that their "exclusive personal low price" was substantially higher than the standard price accessible to other customers. Another narrative involves two friends booking flights, only to realize that an Android user was presented with a lower price than an iOS user. Similar cases have surfaced regarding taxi passengers.

Such practices are typically labeled as "price discrimination"; we will delve into this issue in greater detail toward the end of the article.

How Dynamic Competitive Pricing works in eCommerce / retail companies:

✓ You pinpoint key competitors within each market and establish a pricing strategy tailored to that market.
✓ You launch an automated process for collecting competitors' pricing data.
✓ You input pricing rules into the dynamic pricing system.
✓ As your competitors modify their prices, the system automatically adjusts yours in alignment with your target market price positioning.

For instance, in a specific city and for certain SKUs, your target price position is to be the second-lowest among your competitors. When your competitors alter their prices, you aim to maintain your price at the intended position. State-of-the-art dynamic pricing systems can effortlessly accomplish this task.

On the internet, one can find instances of unsuccessful implementations of dynamic competitive pricing.

"Two booksellers using Amazon's algorithmic pricing to ensure they were generating marginally more revenue than their main competitor ended up pushing the price of a book on evolutionary biology -- Peter Lawrence's The Making of a Fly -- to $23,698,655.93"
(a sourse: wired.com/2011/04/amazon-flies-24-million/)
One bookseller employed a strategy where the price of the book should be calculated according to the rule "competitor's price + 27%."
The second retailer established a different pricing rule. When the competitor's offer changed, the price was automatically recalculated and set at 1% more than the competitor's one. As a result, the book's price escalated until it reached $23.6 million.

There are warnings about price wars, where several ecommerce shops engage in an automated battle to offer the lowest price. Consequently, the profit margins for the entire market plummet to zero.

Nonetheless, quality pricing solutions can effortlessly prevent such adverse effects.

✓ Leading dynamic pricing platforms offer highly flexible pricing rule settings. With such software, to prevent losses and erroneously high prices, one simply needs to establish upper and lower limits for the permissible margin.

✓ The lowest price strategy is seldom necessary. Even for KVIs, the second-lowest price is often adequate; more information can be found here: The optimal price position for KVIs. Therefore, the root cause of price wars is the incorrect strategy and improper configuration of automated rules, rather than dynamic competitive pricing itself.

Zone Pricing is a pricing strategy that treats each location as a distinct market, with a tailored pricing approach. Typically, Zone Pricing is vital for:

● Retail chains, including multichannel ones and those situated in multiple cities.
● E-commerce stores that deliver goods across various geographic areas, including those with warehouses solely in their headquarters city.

Without zone pricing and with the same SKU's price for each location, a retail or e-commerce company risks losing customers and profits. For most SKUs, or even the entire assortment, the market environment in two different cities tends to differ significantly:

With Dynamic Zone Pricing, a retailer or e-commerce shop can significantly boost sales and profits by taking into account the unique characteristics of local demand, supply, competition, and logistics for each SKU in every specific location.

For more information on how to implement Dynamic Zone Pricing and how it functions, refer to: ZONE PRICING.

In today's market, offering an appealing price is a crucial factor in motivating consumers to make purchases in a specific store. However, employing a strategy of having the lowest price for every SKU is evidently hazardous, as it can lead retailers to financial ruin.

To address this issue, retailers and e-commerce shops establish their "good deal prices" reputation and manage profitable growth by utilizing a KVI Pricing Strategy.

KVIs (Key Value Items) comprise a selection of goods that simultaneously fulfill several vital functions for a store:

Where can a retailer (or e-commerce shop) recover its margin elsewhere in the assortment, and on which SKUs can it charge higher prices? Such SKUs exhibit the following traits:

Complementary goods and impulse items often hold the potential for increased margins.

Today, the list of KVIs is no longer static, as it was a decade ago, and tends to change significantly within a week or even a day. Owing to the growing complexity of KVI Pricing, e-commerce companies and retailers have started investing in dynamic pricing solutions.
A dynamic pricing platform can assist in pricing KVIs efficiently through:

You can find more information about how to launch Dynamic KVI Pricing and how it works here: KVI PRICING.

Dynamic demand-based pricing takes into account current customer demand and its fluctuations, adjusting prices accordingly.

There are two approaches to optimizing retail prices for foreground and background items.

Approach 1 — Rule-based dynamic pricing.
If a retail / eCommerce company optimizes its pricing from a low base — for example, price calculations are based on a system of fixed markups and scheduled promotions — then, with an agile rule-based dynamic pricing system, pricing experiments can provide impressive growth.

How it works:
● A pricing specialist identifies segments and groups of items with profit growth potential, relying on their experience and intuition.
● They develop specialized dynamic pricing rules for these segments and input them into a dynamic pricing platform.
● They monitor the results, searching for the optimal price.

Note that high agility of the rules settings and powerful analytics tools are crucial for pricing efficiency in this case.

Advantage of the method: The pricing specialist maintains complete control over the pricing process and manages any changes.
Disadvantage of the method: With the rule-based approach, it becomes challenging to consider all the critical factors that influence pricing efficiency, particularly the relationship of SKUs within a category, such as product cannibalization, substitutes, complementary goods, traffic drivers, and profit drivers.

Approach 2 — Machine learning algorithms for fully automated assortment-level dynamic pricing. Price optimization, based on demand sensing.

Assortment-level automatic price optimization maximizes a chosen criterion — gross profit, revenue, or sales volume in pieces. AI-driven algorithms identify the optimal set of prices under prevailing conditions. The resulting optimal price set enables retail or eCommerce companies to achieve maximum gross profit, revenue, or sales volume at the assortment level.

Machine learning algorithms assess cross-impacts among products and then segment items based on their roles in consumer baskets: basket drivers, traffic drivers, profit drivers, complementary goods, substitutes, and more. Each segment receives an optimal pricing strategy aligned with the retailer's business goals. Such solutions also enable retailers to optimize prices for specific product categories and swiftly determine optimal prices for new items.

Advantage 1 of the method: The approach helps avoid product cannibalization within categories and consider the cross elasticity of items.

Advantage 2 of the method: AI-driven algorithms help identify situations where competitive pricing falls short. This occurs when all competitors err by setting prices too high from a consumer perspective, resulting in diminished willingness to pay and disappearing demand.
Algorithms assist retailers in finding a new optimal price and reigniting retail demand.

Advantage 3 of the method: readily detect short-term demand surges due to temporary product shortages or unforeseen spikes in demand. In such cases, the pricing solution promptly raises the price of relevant SKUs and maintains it until demand normalizes.
This approach significantly enhances retailers' gross profit.
You can explore an example of such a success story here: CASE STUDY

Advantage 4 of the method: Assortment-level automatic price optimization substantially boosts profits for both brick-and-mortar stores and eCommerce shops. Generally, eCommerce stores experience faster gross profit growth compared to offline stores, as they can adjust prices more easily and rapidly.
For more information on implementing AI-powered Demand-based Dynamic Pricing and how it works, visit: AI-DRIVEN PRICE OPTIMIZATION.

In a relatively short time, dynamic pricing helps reduce excess stock, eliminating unpopular items from the assortment, free up the capital for new items, while preserving marginality as much as possible.

Moreover, dynamic pricing solutions enable retailers to minimize the risk of overstocking. Analytical tools facilitate inventory tracking and the identification of SKUs that should not be reordered in the future.

You can find an example of dynamic pricing solution with Inventory Turnover Module here: DYNAMIC PRICING PLATFORM.

Some online retailers and retail chains deliver goods directly to consumers from suppliers' warehouses. In certain cases, multiple suppliers offer the same item at identical or varying prices.

How Stock-Based Dynamic Pricing works:

You can find an example of dynamic pricing solution with Stock-Based Module here: DYNAMIC PRICING PLATFORM.

What is Time Pricing:
A retail or eCommerce company identifies periods when short-term price adjustments can significantly boost sales or profits, effectively capitalizing on such opportunities.

The most prevalent types of time pricing include:

For more information on how to implement Time-Based Dynamic Pricing and how it enables retailers to enhance their profits, visit: DYNAMIC TIME PRICING.

The most debated aspect of "dynamic pricing challenges" is psychological, stemming from negative reactions by consumers who encounter what is known as "price discrimination."

Price discrimination is a pricing strategy that aims to sell the same product to different consumers at varying prices, based on individual customer characteristics, such as income and willingness to pay more.

As mentioned earlier, people can become upset when they realize they are being charged more for tickets, hotels, or taxis simply because they own an iPhone.

However, various forms of price discrimination and dynamic pricing exist that do not lead to scandals or negative outcomes. Examples include social benefits and discounts for less affluent segments of the population or practices that have become commonplace.

If your pricing strategy involves offering different prices based on specific customer characteristics, the following tips can help avoid most conflicts:

✓ Label the highest price of an item as the "Regular price."
✓ Lower personal prices should result from individual discounts provided to customers.
✓ A higher personal price might not cause resentment if it includes special benefits or additional services.

Regardless, it's clear that the dynamic pricing methods discussed in this practical guide for retail and eCommerce companies are not associated with price discrimination. Be sure to bookmark this article for reference when studying and implementing effective pricing strategies!