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Sunday, 25 April 2021 07:46

Post Covid - Leading an effective salesforce / 3. Dynamic Pricing Featured

Pricing is at the very heart of digital transformation. As businesses become faster and more virtual, prices more transparent and costs more volatile, the best way to reverse eroding margins is through more intelligent and more focused Pricing. Read how Data and AI will fuel dynamic pricing, a must to comprehend.

Most know of Dynamic Pricing when they book airline tickets or hotels; that is why they search incognito to find the best deal. Everyone knows that Supermarkets adjust their prices constantly, gas stations too, not to mention Amazon which practically has no fixed prices.

What we now see is how Dynamic Pricing moves from B2C to B2B where there is an even bigger potential. All big consultancies agree that Dynamic Pricing could improve profitability by 2-5 pp, sometimes within 3 to 6 months.

What is Dynamic Pricing
Businesses which adjust their prices, according to season or through promotional offering, already implement it. However, the game changers are the explosive extend of application, speed, and sophistication.

It is what transforms a boat with oars to a speed boat. It is the engine that will make a difference, how it is build in, as well as the adjusted capabilities of the people on it.
Static pricing considers geographic dimensions, seasons, quantity, product type and channel. Dynamic can be simplistic or sophisticated, rule or algorithm based.

It is based on the willingness of different customers to pay different prices. Think of segmentations of types of customers in terms of: Bargain hunters, Brand hunters, High end buyers, Risk avoiders and Occasional buyers and the need for a differentiated pricing will be immediately clear.

It considers competition prices, web traffic, weather, demand evolution, reviews and ratings and the general strength of the brand.

In rule-based dynamic pricing, prices are constantly and mechanically reviewed and adjusted, combining different rules, although the competitive price is often the most decisive factor. In such cases, a gap between a company’s product and that of the competitor can be established, and price is changed accordingly to maintain the difference.

These rules can be predictable, unpredictable or apply the principle of Hit & Run, which means that there is an unexpected drop or increase of prices, for a short time and then, return to the old. Market leaders can exercise effectively that rule.

Algorithmic dynamic pricing can use machine learning algorithms to determine optimal prices. These measure customers' willingness to pay, using price elasticity for any given product.

A self-learning algorithm identifies data patterns and can calculate the ideal price for each item based on the collected data and pricing factors, such as inventory or competitor prices. In doing so, it considers all previously defined targets and frameworks.

As pricing reacts dynamically and automatically to a change in customer behavior, also discounts can be applied in a more differentiated and intelligent way.
This is the foundation for a savvy market segmentation that allows a business to properly optimize its strategy, marketing, and sales activities.

Prices are continuously modified and optimized automatically and in real-time. The rules are checked and upgraded resulting in automated changes. That allows seamlessly varying within the continuum or spectrum of possible prices, even at the level of cents, and practice the flexibility that maximizes profits and value.

The algorithm can also simulate different pricing scenarios and forecast revenue, sales, and profit results for specific targets.

How to implement
When moving to dynamic pricing, there are different strategies at play. What will help you decide what model to choose are the number of market inputs to consider, the frequency of shifts, the frequency of product changes, the difficulty to construct the right price and the data needed to support the decision.

Key is the involvement of Sales. They will implement the prices and that will influence their relations with their customers, and their target achievement. They need to trust that the engine works well and the recommendations are applicable.

They also need to add their experience in building the customer segments and the factors shaping their behavior and preferences. Finally they will be the ones to provide continuous feedback to improve the system and reap the maximum benefit.

It is strongly recommended to establish a central dedicated team to implement and evolve the model applied.
A team which will produce the KPIs to follow and will track the benefit. Which will maintain the engine and will train the team of how to use it best.

What tools are available.
There are several software suits to support you, depending on the size of the company, the industry characteristics and the company needs. For competitor monitoring, see Prisync (, for complete, easy to apply tool look into Priceedge ( and if you are in the retail business look at Netrivals ( )

Just beware: making such a decisive step successfully is not as easy as it seems. It involves a complete transformation of the way of thinking of your Revenue department and a thorough deployment.
But, again, it is the only way to survive in the post covid era!

Last modified on Sunday, 25 April 2021 08:11