The days when the price of a product depended on the perceived value it gives the consumers and the price of a competing product, are fast fading. In today’s digital world the customer is spoilt for choices as virtual stores offer stiff completion to the traditional physical stores. Whether you are a retailer keen on ensuring that your products stand out in a market which is filled with similar products or you are constantly endeavouring to give your customers the best value for their hard earned money, dynamic pricing is one strategy that will help you stay at the top of your game.
Contrary to the traditional system, where a ‘one price fits all’ was the norm, dynamic pricing strategy focuses on creating a personalised system of pricing which is more customer specific. In this system the price is not fixed but keeps changing depending on factors such as fluctuating demands, changes in market conditions or the difference in target customers. A personalised price is assigned based on factors such as Customer Segmentation (Demographics and Transaction behaviour), Customer Loyalty score (RFM analysis, Share and size of wallet, Customer life-time value score), Customer Price sensitivity analysis as well as the economic value of the product. By helping the retailer determine the optimal pricing point for each customer, dynamic pricing drives customer satisfaction on one hand, while on the other improves ROI for retailers.
If you analyse the maturity of the pricing strategy over the years, the first step was the conventional model where pricing system correlated directly to cost of a product and share of profits. Then came a system where the retailers started fixing prices based on the impact of changes in prices on the sales and the demand supply cycles. Pricing soon saw a stage where retailers started to compete among themselves to offer the lowest prices. This stage of offering customers lower prices was the beginning of an era where the focus was on the customer and dynamic pricing. Dynamic pricing takes customer centricity to the next level by incorporating customer angle into the pricing of products, thereby making it unique and dynamic for every consumer.
Achieving the right dynamic pricing model is not child’s play, in fact far from it. To reap the benefits, the retailers must ensure that they have the latest data regarding sales and transactions at their disposal. This would mean that they need to invest in the latest technology and software which will ensure that they have all the real time data they need at the right time. They would also need to develop a system which would integrate the pricing data with their purchase and supplychain systems to take full advantage of this dynamic pricing strategy.
Without the right approach, like all business models, dynamic pricing models are also susceptible to failure. What is required is a 3 phase approach which will enable the retailers to customise their prices for specific customer groups using PPRS(Personalised Price Recommendation system). This customer specific personalized pricing system for retailers, will offer personalized price to customer rather than blanket price for all customers. It brings together data sources like customer information and demographics, loyalty rewards and behavioural data, combines these with the right predictive modelling and segmentation methods to achieve the twin benefits of customer segmentation and customer price scoring.
However, what needs to be borne in mind is that it will do well for retailers to look forward to implementing this model in a phase wise approach by starting with a particular product/customer/store/location etc. Then slowly roll the approach for loyalty/reward customers and then for all customers (based on segmentation approach). By adopting the right dynamic pricing model and implementing it, retailers can drive the twin benefits of customer loyalty and improved sales.
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