We want to point out that price sensitivity differs from price elasticity. Price elasticity analyses a product's demand change as a result of its price change. But, in price sensitivity, there are more drivers than the price that you need to consider.

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When customers set out to buy a price-sensitive product, they check various factors. Those factors can be the brand value, competition, the product's lifecycle stage, etc.

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But how do you know which factors drive your customers to buy your product? To do this, you must discuss with your stakeholders and use machine learning to confirm. You can learn how to optimise profits through price sensitivity. But for this, you must combine human judgement and machine learning.

Sensitivity pricing strategy uses more drivers than price elasticity.

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Watch full webinar on Price Sensitivity Analysis here.

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What Factors Affect the Price Sensitivity of a Product?

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We can see the factors influencing price sensitivity from 2 levels. A product level and a customer level. You must consider both to find the optimal price.

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Product-Level Factors Influencing Price Sensitivity with Examples

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Product-level price drivers are all those that have a direct relation to the product.

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• Product Type: How the nature of a product influences its sensitivity

This driver assesses if Type A products are more price-sensitive than Type B products. Product types can vary, such as high-margin items or often-purchased goods. Here's an example. Basic groceries (daily necessities) are more price-sensitive than luxury watches (occasional purchases). A small price increase in bread might trigger an immediate backlash. But, luxury watches may face less impact due to infrequent buying.

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• Buyer Frequency: A key indicator of price sensitivity

How often customers buy a product indicates its price sensitivity. Often-purchased items face more price scrutiny. Symson's price sensitivity model compares typical buying habits to recent trends. This helps us suggest optimal prices for adjustments. Example: People buy products like toothpaste often. This makes customers more price-sensitive to regular items like toothpaste. A significant price increase in a popular toothpaste brand may lead customers to switch to a cheaper option.

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• Price Change Frequency:

How often a product's price changes affect consumer's perception of its value. Symson's sensitivity algorithm identifies the products with frequent price adjustments. Our tool also considers this factor in pricing strategies. Example: In the airline industry, frequent price fluctuations are common. Customers who are aware of this, often wait for price drops. They also use price comparison tools before booking flights, showcasing heightened price sensitivity.

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• Brand Value: The power of perception

The strength of a brand influences how sensitive consumers are to price changes. Renowned brands often enjoy lower price sensitivity. This gives them more leeway in pricing decisions. Symson's model evaluates the impact of a brand’s value on each product's price sensitivity. Example: Apple products often exhibit lower price sensitivity due to strong brand loyalty. Customers are willing to pay a premium for new Apple products. This is not the case with lesser-known tech brands.

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• The Product Lifecycle Stages

A product’s lifecycle stage affects its price sensitivity. The lifecycle stages include the introductory stage, maturity stage, growth stage, etc. Our algorithm categorizes products by lifecycle stage to support better pricing decisions. Example: New-launched electric cars may be less price-sensitive than established gasoline vehicles. As a new and innovative option, customers may accept higher prices for electric cars.

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• Competitor Intensity

In markets with many competitors, price sensitivity tends to be higher. Our model studies the relationship between a product's competition and its price sensitivity. Competition among platforms like Netflix and Amazon Prime leads to higher price sensitivity. A slight increase in subscription costs could lead to customers switching to another.

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• Price Level: Balancing Perception and Reality

Understanding a product’s price compared to its perceived value is crucial. Our model evaluates how price levels affect sensitivity to price changes. Example: Luxury hotels are less price-sensitive than budget hotels. A significant price increase in luxury hotels may not deter their customers as much. But, it would change for budget hotels.

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• Inventory Type

A product’s inventory status affects price sensitivity. Whether they are regular stock items or non-stock items ordered as needed. Example: Special-order luxury cars (non-stock) are less price-sensitive than mass-produced models (stock). Their exclusivity and made-to-order nature justify higher prices, reducing sensitivity.

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• Favourite List and Product Ranking

A product’s popularity indicates higher perceived value. You can see popularity through ratings, and presence on favourite lists or wishlists. In the online world, these show a higher perceived value. Our model also analyzes how a product’s order ranking affects price sensitivity. Example: A popular novel that people often add to their online bookstore wishlists. This shows it may have a lower price sensitivity. Its high demand supports a stronger pricing strategy.

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• Basket Size

This factor considers whether a product sale was individual or in bulk. The way people buy the product affects its price sensitivity. Products often purchased in bulk may have different price sensitivities than single-item purchases.

Example: Staples like rice or toilet paper are often bought in bulk. That's why they may have lower price sensitivity. Bulk buyers are less deterred by small price increases. In contrast, luxury items like expensive chocolates. People usually buy such luxury items in smaller quantities. That's why they are more price-sensitive. Even a slight price increase might lead customers to switch or rethink the sale.

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• Customer Type

This driver examines how sales concentration among certain customer types affects price sensitivity. You already group customers based on their similarities. Hence, different customer groups have different price sensitivity levels.

For example, a professional photographer buys a high-end camera. The photographer may be less price-sensitive as he/she values quality. But, for a regular person buying the same camera, the price sensitivity would be high.

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• B2C Channel Differences and Price Comparison Sites

The perception of a product's value changes across different channels. This has a direct effect on price sensitivity. During our experimentation with price sensitivity, we saw that a product has a different sensitivity in Otto than Amazon.

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Watch Full Webinar Now: Price Sensitivity Analysis Webinar

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Here, you'll understand how to approach price sensitivity through clear steps.

Symson considers how a product’s presence on different channels influences this sensitivity. For example, a smartphone is often more price-sensitive on e-commerce platforms than in physical stores. That's because people can compare prices with other phones on the same platform.

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What are Customer-Level Factors that Influence Price Sensitivity?

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‍The customer-level price sensitivity drivers are those that relate to buyer behaviour. It means all their interactions related to buying. For example, the frequency of buying, return frequency, etc.

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Here, we'll break the customer-level factors down into 2 parts for clarity. One is customer loyalty factors. The other is customer segmentation drivers.

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Customer loyalty factors affecting price sensitivity

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‍In pricing, you can take customer satisfaction to another level. But first, you must know who are your loyal customers. There's a customer loyalty score that determines it. But, how do you calculate customer loyalty?

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You can analyse customer loyalty through various behavioural patterns that pricing tools capture. Below are some metrics that help you find customer loyalty.

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• Buying Behavior (Product Types)

Once you know the types of products a customer buys, you will get a sense of their loyalty. Let's say a customer buys a premium product from an electronics store. According to data, the customer is more likely to return for more purchases.

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• Buyer Frequency

Buyer frequency measures loyalty by how often purchases occur. It compares this to typical behaviour or set KPIs to determine loyalty. Example: A streaming service views subscribers who renew monthly as loyal customers. They value them more than irregular users.

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• Shipment Delivery Performance

Shipment Delivery Performance measures loyalty based on delivery consistency and reliability. Customers who receive deliveries on time are more likely to make repeat purchases. This is how an online retailer sees the connection. It shows that there's a link between on-time delivery and loyalty.

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• Support or Complaints Tickets

This measures loyalty through customer interactions with support and complaint resolutions. A telecom company finds that resolving support tickets well leads to higher retention. This is how you can link support quality to loyalty.

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• Returns

Returns analysis shows how product returns affect loyalty. A fashion brand reduces returns by addressing sizing issues and increasing customer loyalty.

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• Customer Engagement

You can track loyalty through customer interactions online. Their engagements on campaigns show the level of their engagement with your brand. Customers who take part in the brand’s loyalty programs or use discount coupons are more likely to make repeat purchases. This may lead to more frequent buying.

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• Customer Satisfaction / NPS Score

This is another factor affecting your product's price sensitivity. It measures how logistics and delivery speed affect satisfaction. In food delivery services, faster deliveries boost satisfaction scores. This allows an opportunity for premium pricing in time-sensitive markets.

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Customer segmentation factors affecting price sensitivity

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• Revenue, Location, Buying Habits

A SaaS company sees tech clients with high revenue buy more premium services. This helps them with targeted marketing.

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• Buying Groups, Segments or Industries:

A B2B medical supplies company segments customers by healthcare sectors. Each customer group has different buying patterns and preferences. The idea is to capitalise on those preferences and increase sales.

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• Markets, Behavior Classification

A beverage brand segments health-conscious customers, finding unique buying behaviours and price sensitivities.

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How Does Symson's Price Sensitivity Model Help Your Pricing?

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Symson’s Price Sensitivity Model recommends optimal prices through a scientific approach. This is so even if you have limited price elasticity data.

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With Symson, you can:

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• Identify and leverage key price drivers.
• Predict optimal willingness-to-pay (WTP) prices.
• Gain clear insights into customer behaviour without a black-box approach.

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Sensitivity scores let you set precise pricing. Its boundaries help control price predictions. Symson’s advanced algorithm helps you understand your customers better.

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