Price Segmentation Strategy (also called Segmented Pricing) may charge different prices for each segment of clients.
Note that non-experts commonly link dynamic pricing exactly with the Price Segmentation strategy.

Most of the "dynamic pricing scandals" were a result of the imperfect or incorrect implementation of Segmented Pricing.
For example, on the Internet you can find some stories about how a regular customer of an online shop accidentally discovered that his "special personal low price" was much higher than the common price available to other customers.
Another story: two friends were booking flights and found out an Android user saw a lower price than an iOS user. There are similar stories about taxi customers.

Such practices are commonly called "price discrimination"; we will discuss the issue in more detail at the end of the article.

However, in reality Price Segmentation is usually not related to "discrimination". Segmented Pricing is profitable to almost any retail or eCommerce company: the better the price offer meets the personal needs of the client, the more this client buys, and the higher the probability becomes this client will return for repeat purchases.

Special prices for each customer segment are highly relevant for:

How Dynamic Competitive Pricing works:

✓ You identify key competitors in each market and determine the pricing strategy for this market.
✓ You set up an automated gathering of competitors'prices.
✓ You enter pricing rules into the dynamic pricing system.
✓ When your competitors change their prices, the system automatically adjusts your prices, according to your price positioning in the market.

For example, in a certain city, for certain SKUs, your target price position is the second-lowest among your competitors. When your competitors change prices, you want to maintain your price at the target position. Modern advanced dynamic pricing systems perform this task easily.

On the Internet, there are examples 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 used a rule "the price of the book should be calculated according to the rule "competitor's price + 27%".
The second retailer set a different pricing rule: when the competitor's offer changed, the price was automatically recalculated and became 1% less than its current price. As a result, the price of the book rose until it reached $23.6 million.

There are warnings about price wars, as well, when several ecommerce shops start an automated fight for offering the lowest price. As a result, the profit margins of the entire market fall to zero.

However, good pricing solutions helps avoid described negative effects easily.

✓ Leading dynamic pricing services provide very agile pricing rules settings. With such service, to ensure against losses and erroneously high prices, you just need to set the upper and lower limits of the allowable margin.

✓ The lowest price strategy is rarely necessary. Even for KVIs, the second minimum price is often sufficient; you can read more about it here: The optimal price position for KVIs. Therefore, the wrong strategy and incorrect setting of automated rules lead to price wars, but not dynamic competitive pricing itself.

Zone Pricing is a pricing strategy that takes every location as a different market with a tailored pricing strategy.
Generally, Zone Pricing is essential for:

● store chains, including multichannel ones and located in a few cities,
● e-commerce stores, delivering goods within a few geographic areas, including those who have warehouses only in a headquarters city.

Without zone pricing, with the same SKU's price for each location, a retail or ecommerce company loses customers and profits. For most SKUs or even for the entire assortment, the market environment in two different cities generally differs considerably:

With Dynamic Zone Pricing, a retailer / an ecommerce shop can significantly increase sales and profits, considering in pricing rules the unique characteristics of local demand, supply, competition, logistics of each SKU in each particular location.

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

Today the attractive price is a key consumer motivation for buying in a specific store.
However, a strategy of the lowest price for each SKU is obviously dangerous, as it leads retailers to a crash.

To solve this problem, retailers and ecommerce shops build their low-price reputation and manage profitable growth with KVI Pricing Strategy.

KVIs (Key Value Indicators / Items) is a group of goods, which can perform several essential functions for a store at once:

Where can a retailer (or ecommerce shop) recover its margin elsewhere in the assortment; on what SKUs can it charge higher prices? Such SKUs have the following characteristics:

Сomplementary goods and impulse goods often have the potential to raise the margin.

Today the list of KVIs is no more static, like it was 10 years before, and has a tendency to change significantly in one week or even in one day. Due to the increased complexity of KVI Pricing, ecommerce companies and retailers have begun to invest in dynamic-pricing solutions.
How can dynamic pricing platform help in price efficiently KVIs:

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

Dynamic demand-based pricing considers current customer demand and its fluctuations, and adjusts prices according to that data.

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

Approach 1 — Rule-based dynamic pricing.
If a 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 the profit growth potential, based on his experience and intuition.
● He creates special dynamic pricing rules for those segments and puts the rules into a dynamic pricing platform.
● He monitors the results, seeking for the optimum 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 keeps the pricing process entirely under control and manages any changes.
Disadvantage of the method: with the rule-based approach, it is difficult to consider all the important factors that affect pricing efficiency, in particular, the relationship of SKUs within a category — product cannibalization, substitutes, complementary goods, traffic drivers, 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 selected criterion — gross profit, revenue, or sales volume in pieces.
AI-driven algorithms find the optimal set of prices under current conditions. "Optimal" means, implementing that price configuration, the retail company achieves the maximum gross profit margin, revenue, or sales volume at the assortment level.

Machine learning algorithms evaluate goods' cross-impact and segment items by their roles in the consumers' basket: basket drivers, traffic drivers, profit drivers, complementary goods, substitutes, and others. Then each segment gets its optimal pricing strategy according to retailer's business goals.
Such solutions also allow retailers to optimize the prices of a specific category of goods and rapidly find optimal prices for new items.

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

Advantage 2 of the method: AI-driven algorithms help identify situations in which dynamic competitive pricing does not work. It's when all competitors make a mistake and charge prices which are too high from the point of view of consumers, so both the willingness to pay and demand disappear.
Algorithms help retailers find the new optimal price and reignite retail demand.

Advantage 3 of the method: Advanced pricing tools easily recognize short-term raises in demand caused by short-time shortages of goods or unforeseen rush demand. In such a case, the pricing solution quickly raises the price of the relevant SKUs, and keeps it before the moment when the demand normalise again.
This approach empowers retailers to significantly accelerate their gross profit.
You can study an example of such a success story here: CASE STUDY

Advantage 4 of the method: Assortment-level automatic price optimization increases profits significantly both in brick-and-mortar stores and in eCommerce shops.
Generally, eCommerce stores gain speedier growth in gross margins compared to offline stores, since an eCommerce company can change prices easier and faster than an offline store.

You can find more information about how to launch AI-powered Demand-based Dynamic Pricing and how it works here: AI-DRIVEN PRICE OPTIMIZATION.

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

Also, dynamic pricing solutions allow retailers to reduce the risk of overstocking. Analytics tools help to track inventory and identify the list of SKUs not recommended for reordering in the future.

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

Some internet stores and retail chains ship goods to consumers straight from suppliers' warehouses. Sometimes a few suppliers offer the same item, at the same or at a different price.

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 company identifies periods when short-term price adjustment sufficiently increases the company's sales or profits and efficiently exploits such opportunities.

The most common types of time pricing as follow:

You can find more information about how to launch Time-Based Dynamic Pricing and how it empowers retailers to increase their profits here: DYNAMIC TIME PRICING.

The most discussed type of "dynamic pricing issues" is psychological. It relates with negative reactions of consumers who faced so-called "price discrimination".

Price discrimination is a pricing approach that aims to sell the same product to different consumers at a different price, depending on the particular customer's characteristics, especially on their incomes and willingness to pay more.

As was mentioned above, people are not happy realizing they offered to pay more for tickets/ hotel/ taxi just because they are owners of an iPhone.

However, all people face various types of price discrimination and dynamic pricing, not leading to scandals or other negative effects. This is about social benefits and discounts for the less wealthy part of the population or about things that have become habitual.

If your pricing strategy includes offering different prices depending on some characteristics of the customer, the hints below will prevent most conflicts.

✓ The highest price of an item needs to call "A regular price".
✓ Other, lower personal prices, need to be a result of discounts given to customers individually.
✓ A higher personal price may also exist and not cause resentment if it comes with special positive conditions or a set of services.

Anyway, obviously, dynamic pricing methods, mentioned in that practical guide, are not related to price discrimination.
Bookmark the article for studying and implementing efficient pricing strategies!