Define your specific price sensitivity levers.
Map price drivers to product / customer clusters
Develop regression model for price sensitivity drivers.
Test model for computation accuracy and consistency.
Use sensitivity scores to generate optimal price
Take advantage of the innovative Pricing Sensitivity Algorithm of SYMSON. Gain insight into your customers' behaviour and set the best prices.
Predict optimal prices via business-specific price levers
Combine with Price Elasticity Algorithm
Use lower/upper boundaries to control your price prediction
Competitor intensity refers to the level of competition within a market which can significantly influence optimal pricing decisions.
Competitor Intensity measures:
Market Competition Density: number of active competitors and their relative sizes within a market.
Price Positioning: how your product's price stands in comparison to competitors' pricing.
Competitive Response Rate: how quickly and frequently competitors adjust their pricing in response to market changes.
Market Share Shifts: fluctuations in competitors' market shares as a result of pricing strategies.
Our Price Sensitivity Algorithm measures price levers to understand customer behaviour to detect their willingness to pay. Organisations use this understanding (sensitivity score) to set the optimal price per customer / product cluster.
Price sensitivity and price elasticity are different when it comes to pricing optimisation. Let's uncover their differences so you can implement them at the right time.
Let’s start with expressing that we are big fans of Price Elasticity, thanks of its ability to accurately predict the optimal price, but we also need to mention that Price Elasticity rather cannot always be used. Price Elasticity does a great job at finding the optimal price, however it does need a high volume of specific data. Organisations don’t always have such a high of volume of very specific data. However, they may have different types of data that can be leveraged to find the best prices. This is where Sensitivity really shines.
All relevant data for each price driver is gathered on product level and therefore includes information on product segment, country, specific customer or customer group, etc. This algorithm can be applied to each dimension (combination of country, customer group and segment), as long as each chosen dimension has enough data of good quality.Examples of price drivers: Buyer Frequency of a Product, Price Change Frequency of a product, Brand Value, Competitor Intensity, The Product Lifecycle, Basket Size, Price Level of a product, Product ranking, Customer type, Inventory run rate, Favourite List, etc.
The outcome of the Price Sensitivity Algorithm, focussed on customer price drivers, can be used to:
1. Optimise your prices or/and price lists
2. Raise or lower the 'current given suggested price' with a %.
3. As a Sensitivity score for each price driver, useful in other use cases, models, systems (API connection)
4. To get a better understanding of the customer behaviour.
This model is designed to discover the optimal price of a product. The model consists of several price drivers relevant to your organization and sector, and discovers via a scientifically proven method if and how the price drivers influence the price. The model outputs a number for each price driver, which represents its impact on the price: a sensitivity score related to the driver. In other words it calculates how much the price driver influences the price and gives the price driver a score. The model uses the correlation between all the different driver scores to suggest raising or lowering the 'current given suggested price' with a %.
Symson’s data quality report engine gives the suggested price a data quality score, that indicates whether the outcome of the algorithm could be trusted (i.e. if it has enough data points), or if more data is needed for an optimal outcome.
Engaging in market research and customer surveys helps companies gain accurate insights into customer preferences, perceptions, and purchasing decisions. At SYMSON, we have extensive conversations with our clients to understand their specific price drivers for their product assortment
We’ve curated the the best of our content resources around pricing to empower you with the knowledge you need to get started on your price optimisation journey!
We are big believers in bringing the human and machine perspective together to improve the rate of learning. Empowering people with the knowledge and technology to solve problems and improve is our mantra. This is Hyperlearning™.
Unlike blackbox AI. we made sure this model is explainable and transparent to all who use our platform. Every recommendation from the AI provides the logic and the rules applied to arrive at that price. It’s crucial for the users to understand the algorithm and provide their own input to make it better. This way, we can harness the best of man and machine.
Provide your own input
Spot errors and recognise shortcomings
Improve accuracy
Continue to learn and upgrade the process
Check out this Case Study to see how we define your Use Cas: Goal Setting, Identifying Product Catalog, Price Drivers and Strategy and more.
Here, we discussed a case study that emphasizes how SYMSON helped a company in:
Increasing gross margin
Data driven decisions
Interpretable insights
Fine-tuning brand value
Our collection of expertly curated guides is here to empower you with the knowledge you need! Explore innovative pricing strategies that will help you boost revenue, retain customers, and outsmart the competition.
Got a question? We're here to answer! If you don't see your question here, drop us a line on our Contact Page.
Price Sensitivity measures consumer response to changes in a product's price. Businesses use this understanding to optimise pricing strategies, ensuring stability in demand even when prices fluctuate.
To calculate the price sensitivity of a particular product we follow a simple process. First, we identify price drivers - market and consumer factors that may influence prices. Then, we build a model that uses the price drivers info as well as multiple external sources to generate a sensitivity score which then can be interpreted.
In the context of price sensitivity, 'sensitive' refers to consumers' high responsiveness to changes in price; a small change in price leads to a significant change in demand. 'Insensitive' means consumers' demand is relatively stable despite changes in price; they are less likely to alter their buying behavior because of price fluctuations.
Understanding price sensitivity is crucial for businesses to set prices optimally. It informs how price changes affect sales volume, revenue, and profitability. By knowing how sensitive customers are to price fluctuations, businesses can tailor pricing strategies to maximize profits, remain competitive, and meet market demand effectively.
Competition affects price sensitivity by offering consumers alternatives. In a market with many competitors, consumers are more likely to be sensitive to price changes, as they can easily switch to a competitor if prices rise. Conversely, in markets with few competitors, price sensitivity may be lower as consumers have fewer alternatives and may be less responsive to price changes.
Yes, price sensitivity can change over time due to factors like shifts in consumer preferences, economic conditions, brand loyalty development, introduction of new products, or changes in the competitive landscape. For instance, during an economic downturn, consumers may become more price-sensitive, seeking better value for money.