In the intricate space of consumer behaviour, the concept of price sensitive customers stands as a crucial facet that deeply influences purchasing decisions. These customers exhibit a heightened awareness of price fluctuations and are highly responsive to even minor changes.

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Understanding their motivations and behaviours is not just insightful; it's a strategic imperative for businesses aiming to thrive in competitive markets. In this blog, we delve into the nuances of price sensitive customers, the methodology of customer price sensitivity analysis, and the transformative benefits it offers.

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Decoding Price Sensitivity: The Customer Perspective

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Price sensitivity is the manifestation of how customers react to variations in product prices. While some consumers place a higher premium on quality or brand loyalty, price sensitive customers prioritize cost-efficiency. They carefully evaluate the price of a product relative to its perceived value, seeking the best possible deal. This behaviour is particularly pronounced in markets where alternatives are readily available and easily comparable.

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However, to navigate this, it’s vital to understand the level of sensitivity for any pricing strategy to work. Traditionally, businesses used the Van Westendorp pricing model to find the optimal range of pricing. They asked their customers a few questions regarding the pricing of a particular product/product category and plotted their responses in a graph. However, the method is not ideal for modern pricing where advanced algorithms do the work with precision.

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Also Read: The Price Elasticity Guide to get an in-depth understanding of how it works.

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Implications for Businesses to Manage the Price Sensitive Customer

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Research by Boston Consulting Group highlights that companies can determine price sensitivity by not just understanding who the customers are but also delving into the context of their purchasing decisions. Consumer behaviour depends on the product/product category, the market and the situation. Having said that, let’s look at some crucial methods you can implement:

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• Customising pricing strategies according to the policies of different countries is vital as the policies of global uniform pricing aren’t optimal.
• Brands must identify ways to bring consumers to spend. For instance, charging differently for the same coffee at different times of the day isn’t ethical. In this case, offering coffee with the main dish at a slightly higher price can be one of the ways.
• As mentioned by BCG, companies must “gain a nuanced understanding of the motivations that drive price-sensitive purchases in specific markets, categories, and circumstances. Such knowledge can be the key to winning in a market—by being both price competitive and profitable.”

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Now, let’s look at how to identify new drivers to be able to calculate their accurate price sensitivity scores.

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Also Read: Price Sensitivity Examples and Identifying New Driver to Calculate Sensitivity Level

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Customer Price Sensitivity Analysis: 5 Steps to Assess Product Price Sensitivity

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Customer price sensitivity analysis helps unveil the complex interplay between price and consumer behaviour. In modern pricing, you can calculate the price sensitivity of your products using an advanced pricing system that relies on real-time datasets and, human expertise and intervention to find accurate optimal price recommendations.

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However, the process includes discussing with customers and using data to identify new drivers and then computing them into the pricing system to automatically calculate sensitivity. Let’s briefly have a look at the 5-step method for customer price sensitivity analysis.

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• Identify new drivers for price sensitivity

The first step involves discussing with a few customers to find current parameters that they consider. Together with the responses and datasets, you will be able to find critical drivers to calculate price sensitivity with precision.

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• Build a regression model including price, quantity and the identified drivers

Considering a time period, you can calculate the quantity, average price, and other numerical or categorical factors for each product to construct a data frame for the customer. Using this dataset, we at SYMSON built a regression model.

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Studying these datasets allows businesses to quantify the influence of each driver on price sensitivity and sales volume. Leveraging a regression analysis helped SYMSON gain a more nuanced view of how customers respond to changes in price.

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• Aggregate relevant coefficients from the regression model to predict price sensitivity

This step uses the regression output to calculate the price sensitivity scores of each product. The equation returns a price sensitivity prediction, which represents how a 1% change in price impacts the % change in quantity sold or demanded. For instance, price sensitivity of -4% means that a 1% rise in price results in a 4% drop in the quantity sold.

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• Interpret price sensitivity scores

The price sensitivity score reveals the volume of customer responses to price changes. Based on the coefficient computation from the regression model, we assign weightage differently to different coefficients to calculate the sensitivity score.

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A higher sensitivity indicates that customers are more responsive to price changes, while a lower score indicates a less significant response.

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• Act upon price sensitivity to increase margins or sales

After testing the price sensitivity scores, you can implement strategies for the product group in order to balance profit margin expansion and sales growth.

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How Customer Price Sensitivity Analysis Improves Business Outcomes

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As indicated in the previous section, businesses using AI pricing solutions must intervene with human expertise to identify new parameters that drive customers today to make a purchase. This procedure of synthesising expert human judgement and the power of Machine Learning is the Hyperlearning^TM approach. Now, let’s look at how analysing customer price sensitivity helps companies enhance business outcomes.

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• Allow Forecasting Demand-Level with Precision

With the above-mentioned 5-step approach, businesses can not only set optimal prices in real-time but also accurately sense the demand level in the future. This helps to prepare pricing strategies ahead to avoid decreasing sales volume or leaving money on the table.

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• Find Optimal Pricing Strategies to grow Sales and Margin

As you equip your AI-driven pricing system with new and relevant drivers to determine sensitivity, you can automatically find optimal pricing strategies. Over a period of time, those strategies would help accelerate revenue generation and increase profit margins.

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• Cash in on Price-Insensitive Products to Enhance Margins

Once companies get clarity on their price-insensitive products, they can experiment with setting higher-yet-optimal prices to increase margins. AI-pricing tools like SYMSON help find the correct price recommendations that are not only profitable but also within the range of the customer’s willingness to buy.

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• Strengthen Customer Loyalty with Personalised Pricing

Segmenting customers according to their buying behaviours and personalising prices accordingly can influence them to engage more with your brand. This further can lead to increasing brand loyalty as well as inducing brand advocacy.

Navigating the business landscape with price sensitive customers requires a multi-dimensional approach that encompasses analytics, psychology, and strategic thinking. By embracing the 5-step methodology of customer price sensitivity analysis, businesses can harness data-driven insights to make informed decisions that resonate with consumers' value perceptions. In a market defined by dynamic pricing and evolving preferences, the ability to decipher and cater to price sensitivity is the cornerstone of a successful business strategy.

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