In an ever-increasingly competitive world, the majority of companies have been experiencing shrinking margins like never before; yet these same organizations firmly believe the solution to enhancing profits directly lies in the implementation of strategies either related to cost-cutting or volume growth. By shifting all their efforts, resources, and capabilities towards visioning these strategies, organizations tend to underestimate a key untapped profit lever, known as “PRICE”, resulting in a considerable amount of money left on the table.

Based on a recent study, only 12% of companies believe the growth of profit revolves around price. Well, this is certainly only a wrong perception and according to multiple studies, optimizing prices, in particular, can boost your bottom-line profits by 30% to 50%. 

Unfortunately, the majority of businesses possess insufficient price management capabilities to significantly minimize their losses in these events and mainly resort to basic short-term solutions such as quantity-based discounts, bundling of products, and multiple-part pricing. These strategies are too traditional and as we know, most organizations adopt these same tactics during a pricing war therefore these options play out to be quite ineffective.


When organizations want to derive an optimal price for a specific product, they are heavily reliant on utilizing the traditional pricing methodologies, namely, cost-based, value-based, and competition-based; thus experiencing internal struggles usually inflicted by sales managers, brand or marketing managers, and finance managers; these individuals believe that the optimal price should be based on what suits their internal departmental targets, therefore ignoring the bigger picture.

In the below chart, we cross-compare the 3 most common practices when setting the price. For instance, the finance department would want to price the SKU at a rate that can guarantee maximum profits; however, both the sales and marketing would usually follow different pricing approaches as highlighted in the below table resulting in a pricing disagreement amongst all three departments.

These methodologies might have been efficient at some point in time and maybe to some extent today, but market dynamics have significantly changed in the past few years thus companies require some sort of model which can capture a 360° view of all direct & indirect key price influencers, such as competition, internal advertising expenditure, internal profitability, income per capita, changes in consumer preferences, policy changes, and many other optional variables.


As a general recap of the above, the key issue nowadays is upon deciding an optimal selling price, multiple variables can significantly play a role in determining the final pricing outcome. The complex behavior of these variables (e.g. pricing of competitors, customer demand, price sensitivity, changes in consumer preferences, and policy changes) creates the need for businesses to quickly react to live changes in these variables

The predictive pricing model allows businesses to deepen their understanding of these variables, their interrelationships, and future motions. This is something traditional pricing models do not factor in as they tend to focus on a singular characteristic, as emphasized in the above table. The predictive pricing model complements statistical and mathematical techniques with your sales data in explaining the behavior of variables and forecasting future trends. This methodology takes into consideration multiple variables thus addressing the issues which other models tend to ignore.


Below is an extensive guideline that illustrates the key steps a company should undertake to successfully optimize their price-point through implementing the predictive pricing model technique.


Identify your Target Customer

 Understand clearly who the target customer is by characterizing them based on a differentiating factor such as demographic, need, and behavioral aspects. Such segmentation will draw the customer profile willing to purchase your product/service.

Weigh the Decision Factors

By determining who the target customer is, organizations can further evaluate the key decision factors influencing the way these customers perceive value in their products. In general cases, perceived value can be pinpointed towards product attributes/features or even, the organization itself in the form of brand image, customer service, customer experiences, and after-sales services. The weight of every criterion changes based on who is your target audience.

The Value Equivalence Line

The above two steps are imperative in the process of creating the value-equivalence line (VEL) which highlights the grouping of your brand vs what is available in the market; thus enabling companies to understand their relative positioning in the market and whether their respective product/brand is a market share gainer or loser. By weighting each key-value factor obtained from step 2, we can calculate the overall perceived value score and couple it with the perceived pricing of the product to establish a player’s market position. In addition, the way VEL categorizes competitors enables an organization to map out who its “KEY” competitors are, as shown through the different segments in the graph below.

Collect Required Data

Gather your Sell-out data (i.e. price and quantity) of a particular SKU that can be utilized and applied alongside price data variation of the same time period of the identified key competitors in step 3 and other optional variables such as your marketing actual spent during this period.

Apply the Regression Analysis

We apply a regression analysis on these data points with the independent variable being the quantity demanded of an SKU and the dependent variables being the remaining variables. We can then formulate an econometric demand equation as a function of the dependent variables thus allowing us to forecast sell-out data. Based on the assembled data points, the sensitivity of customers towards price and the relationship of this particular SKU versus other market players will also be inferred.

Set the Price

The unit price can be optimized while adhering to the conditions of maximizing profits and maintaining the unit price within the desired boundaries. A sensitivity analysis based on profitability and a range of unit prices can be carried out and a subsequent illustration can be visualized as shown below.

How We Could Help

Digital transformation of businesses is rapidly becoming a norm in our era and the integration of digital technology to an organization can significantly facilitate the collection of big data, achieve proper data governance and ensure a smooth path for the creation of a predictive pricing management system. Digital-enabled initiatives such as a retail data-sharing platform between an organization and a retailer can allow organizations to receive an updated daily sell-out data for a particular SKU, obtain live prices of competitors and subsequently optimize the price on the spot. This seamless process was something organizations never dreamt of given the limitation of digital technology in the previous decades.

As a management consulting firm with strong expertise in customer digital transformation, we specialize in driving revenue growth and help you successfully implement the 6-step approach to the predictive pricing model. With our understanding of customer behaviors and advanced analytics, we take full ownership to embark you on a digital transformation journey of the key parts of an organization’s workflow and by assembling the necessary components to set optimized prices and maximize profitability accordingly.

Take the 1st Step Towards A Successful Digital Transformation

Contact us for a fruitful discussion on how this can aid your sales revenue growth. Learn more about our approach to Digital Transformation.