Smart Merchandising

Maximize profits with Retail Price Optimization
  • Anuradha Kapur

  • 3 minutes

  • 1 February, 2022

Maximize profits with Retail Price Optimization

What is Retail Price Optimization?

Customers are comparing prices all the time and across channels –  online and offline. They have apps that suggest discount codes and they are always looking for offers that give them the most value for their money. Even in such a time of changing consumer behaviour, unfortunately, many retailers rely on old-fashioned pricing practices, using past trends or even gut instincts to set their product pricing. This is not an effective way forward.

Retail Price Optimization is understanding in advance how customers will react to markups and markdowns in original price. With the use of advanced software, companies can stay ahead of the curve by strategically planning the entire price cycle while meeting both sales targets and margins. 

Price Optimization is done using complex algorithms that are designed to evaluate the change of demand with dynamic pricing strategies. This is matched with the data on costs, and inventory levels, to ascertain optimal prices to maximize gross margin. The price optimization strategy is incredibly important for a healthy and growing bottom line.

Retailers that are starting to use price optimization models and markdown management techniques to automatically optimize selling prices are gaining a leading edge over competitors. Machine learning continues to evolve and advanced software solutions combine this with price optimizing algorithms that make reaction to changes faster and more robust.

Factors affecting the retail price:

Internal Factors:

  • Business Goals/KPI’s: Conventionally, businesses set prices based on sales targets which becomes the driving force in price setting and price optimization. However, setting prices based on business goals alone is not effective anymore. An array of data, like fixed costs, historical sales data, market trends, customer sentiment, needs to be accumulated in conjunction with one another to fix the most optimum selling price.
  • Input Cost: Most manufacturers use the input cost plus a markup to fix the retail price. While this is an important consideration in devising the price strategy, it should not be done in isolation. Input cost alone fails to account for consumer-led factors which are essential to fix the right price. For example, the perceived value of the brand, whether the product being sold is a luxury item and customers are willing to pay a premium for it, brand loyalty are all factors that should be taken into consideration in addition to the input cost.
  • Past Performance: Evaluating the past sales performance of the product at different price levels to analyze how customers responded. This is one of the most crucial factors in developing the optimal retail price for different times
  • Inventory Factor: The volume of inventory influences retailers to change the retail price of products. Higher volumes of inventory usually lead to a markdown and discount in retail price to encourage quicker inventory liquidation

External Factors:

  • Demand Factor – The central driving force in retail price management is an analysis of the demand. Setting retail prices rigidly too high may lead to certain products not selling. Price elasticity is a relationship between the supply and price: the more elastic the prices, the more they influence the sales.
  • Competition – Setting retail prices too low can lead to price wars where nobody is making any profits and all are continuously lowering retail prices. A robust retail price management strategy should keep a close tab on competition activities
  • Sales Channels: The nature of sales channels, both offline and online is diverse today and plays an important role in demand creation and therefore retail pricing
  • Other Factors: For products that are climate-subjective or more popular during certain months of the year, price optimization should be done considering these factors

Process of Retail Price Optimization 

  1. Business Considerations: Collect accurate data of all of the internal factors mentioned above, input costs, historical data, competitor pricing, and fluctuations in demand. This comprehensive data will put into a picture how each of these factors affects demand and therefore the price and profitability.
  2. Customer Considerations: In conjunction with the above business considerations, retail price management requires in-depth data about customers and their behaviour. Customer reviews, demand and supply trends, market trends, and most importantly, customer sentiment towards the brand and product are data points that should feed the price optimization strategy.
  3. Product Value: One of the most important considerations is the perceived value of the brand’s products. If we can understand quantitatively how much the customer values the product or certain features, the pricing strategy can effectively satisfy customers and also help maintain a healthy margin.
  4. Data Analysis: Once all the data has been collected, it can be fed into software that will predict what segment of customers are willing to pay what price, in certain market conditions. This analysis determines markdown management and thus promotions.
  5. Pricing Strategy: After the data has been thoroughly analyzed, a pricing strategy must be put in place. There are various pricing philosophies that can be explored depending on the nature of the product. The pricing plan encompasses markups and markdowns at different stages of the product lifecycle.
  6. Continuous Improvement: Putting the pricing strategy in place does not amount to a rigid pricing policy. Once the plan is in action, the prices and respective demand and sales should be closely monitored. Market conditions change rapidly and unexpectedly, and prices must be optimized accordingly. 

Benefits of Retail Price Optimization:

Data-driven price rationalization in the retail industry allows businesses to set the right price at the right time. 

  • Price optimization keeps businesses safe and customers happy. Deep discounts and profit cuts may not be the only solution to meet sales KPI’s. With price optimization, brands get better margins as they base price on smart decisions by eliminating guesswork and using real data that matters. This means actionable insights that make a big, lasting difference.
  • Helps businesses devise product portfolio pricing, dynamically setting the price for different products in the family
  • Price optimization strategies allow businesses to put into play a markdown strategy as per changes in the season and market trends. Not only does this help minimize the seasonal loss in revenue but helps capitalize on higher demand in certain seasons
  • Data analysis helps determine the optimum price at different times for products sold at brick and mortars, in various geographic locations while factoring in uniformity of pricing on online channels
  • Implementing dynamic pricing leads to better inventory turns, thereby improving cash flow
  • Helps businesses identify and capitalize on best selling products
  • If the process of retail pricing has been automated with the use of advanced software, reacting to market changes can be quicker and more scientific 

An effective price optimization strategy keeps the customers happy and the balance sheet healthy. Every brand functions in an ultra-dynamic market and the retail price of products must be receptive to these changes. Increff Markdown Optimization tool helps automate pricing decisions at multiple points of sale level and dynamically increases or decreases discounts for the right set of styles to maximize sales and optimize profits. It identifies out-performers and bestsellers, based on the sales trends, and helps brands automatically re-order the right quantity at the right time to ensure no sales loss opportunity. 

Keeps your pricing strategy proactive to not just quickly adapt to market changes but also maximize profits. Now is the right time to plan and execute a price optimization strategy! Know more about Increff Markdown Optimization: 

Author: Anuradha Kapur

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