4
Week 6 Submission
Student’s Name
Course
Due Date
Pricing Strategy
Value Pricing Strategy
Compared to other smart speakers on the market, Binga offers better sound quality, a stylish design, and a host of features. Value-driven pricing allows it to set prices that are more in line with the value it provides to clients than with the cost of goods sold or production expenses.
BEB and Implications on ROI
Assuming that the fixed cost is $10 million, the variable cost is $100 per unit, and the selling price is $299.99 per unit, the BEP for Binga is:
BEP= Fixed cost/Selling Price-Variable Cost
BEP=10,000/299.9-100
BEP=50,002units
Binga needs to sell 50,002 units to break even and start making a profit. The higher the BEP, the more sales Binga needs to make to cover its costs and start making a profit. This means that Binga has a higher risk and a lower ROI. The lower the BEP, the fewer sales Binga needs to make to break even and earn profit. This means that Binga has a lower risk and a higher ROI. Therefore, Binga should aim to lower its BEP by reducing its fixed cost, increasing its selling price, or decreasing its variable cost.
Product’s Price Elasticity
The quantity demanded changes more than the price, and the price elasticity is greater than one hence it is elastic (Ruan
et al., 2022). This depends on the availability of substitutes, the degree of necessity, the proportion of income spent, and the time horizon. The elasticity implies that lowering its price will increase its sales and revenue, while raising its price will decrease its sales and revenue.
Best pricing strategy
Value based pricing is the best pricing strategy for Binga since it reflects the value that it offers to its customers (Phillips, 2021). The strategy can be effective when there is a better understanding of the needs and preferences of the customers. Moreover, if Binga can effectively communicate its value proposition and segment its customers on their willingness to pay, it can reap the benefits of this pricing strategy.
Distribution Strategy
Distribution plan for Binga
The recommended distribution plan for Binga is a multichannel approach that incorporates both wholesale and retail distribution. By using this approach, the company can leverage the advantages of both retail and wholesale distribution.
Types of Retailers or Wholesalers
The types of retailers and wholesalers that I can recommend for Binga are online and specialty retailers, distributors, merchandisers and agents. These categories will help the company to reach its target market with ease. For example, by using online retailers, Binga will reach a large and diverse base of customers who are interested in the product. Specialty retailers will assist the company to attract customers who are looking for specific products and services. It will also enable the product create a distinctive brand image. Binga can use merchandisers to reach a large customer base that is price-sensitive; they can also provide accessibility and convenience to the customers. To reduce its inventory and transportation costs, Binga can use distributors who will also provide after-sales support to customers and expand its market coverage. Lastly, the agents will enable the company reach new or distant markets who they may not reach with the help of retailers.
Retail and Wholesale Marketing Decisions
The retail and wholesale marketing decisions will focus on the product, pricing, place and promotion. The product decisions will focus on quality, design; packaging and branding of the product reach the target market. The pricing decisions will include the use of discounts, convenient payment methods and setting of retail and wholesale prices. Some of the place decisions are selecting distribution channels, deciding in the intensity of distribution, areas to be covered and inventory management. Lastly promotion decision will focus on the objectives of promotion, budget, message and the media to use for promotion.
References
Ruan, J., Liu, G., Qiu, J., Liang, G., Zhao, J., He, B., & Wen, F. (2022). Time-varying price elasticity of demand estimation for demand-side smart, dynamic pricing.
Applied Energy,
322, 119520.
Phillips, R. L. (2021).
Pricing and revenue optimization. Stanford University Press.
