In every business, pricing of products & services remains the most crucial decision that directly impacts the bottom line of any organization. Therefore it is very critical to price the products & services within an optimal range that justifies value for money to consumers. However, when it comes to pricing decisions, most companies tend to price products based on experience-based intuition, which causes potential opportunity loss.

Apart from operational/manufacturing cost, pricing of products depends upon myriads of other factors such as target customers, competition, selling for cash or credit, appeal of various product/service features etc. All this play a vital role to assess best possible price that could be charged for your product/services.

Some marketers believe that they can offer the lowest prices possible to acquire more & more customers. But to do so you will probably have to give up amenities that your competitors are offering e.g. personal attention, better after sales service, prompt replacement of defective merchandise, and/or easier credit terms. If you don't offer such service, then there is every chance that you are going to lose customers who are seeking such services and are willing to pay for it. Therefore it is very critical to price the product after understanding the pulse of consumer needs & wants. 

At AbsolutData, we offer “Pricing Analytics” to address all these perplexities & help companies better understand how each pricing decision affects the company’s bottom line. Pricing analytics can help you to mitigate valuable profit dollars leak out of sales transactions and missed opportunities. Pricing analytics is a more scientific way of pricing the products/services while ensuring maximal market share.  

At AbsolutData we help companies determine the optimum price for their product by applying advanced analytical techniques like Conjoint Analysis. Conjoint analysis works by simulating real purchase decisions that customers make. 

• In a typical study, respondents are given a simple exercise that asks them to select or rank their most preferred choice from a selection of alternatives. 

• Using Hierarchical Bayesian mathematics, the results are analyzed and a predictive model is developed.   

• Once the model is developed, a number of what-if scenarios can be run to determine the optimal set of features, the best pricing strategy and the estimated market share that your product will achieve.  

• In addition, the model can also predict how your competitors may react and influence your market position.