Revenue management is beneficial as it predicts the customer demand and then steps are taken so that revenue growth could be optimized. The revenue management adjust the price as per the demands. In this report, the possible target market of uber is discussed along with the methods through which data is collected. The revenue management strategy is developed by analysing the market segments, layout of business and pricing model (Ak, Kentel and Savasaneril, 2017). Additionally, various ways through which revenue of uber could be improved is discussed.
The target market of Uber is wide, it is seen that men and women between the age group of 18 to 60 tend to use the services. Apart from that, an individual travel for business purposes and use the service for traveling from one location to other. It is found that it operates in more than 540 countries and it facilities a platform so that customers can easily book cabs. The services are targeting to customers who make use of transportation services. It is found that uber has undifferentiated demand that means customers do not have any specific preference to book a cab (Chen and Jasin, 2018). They reason can be different according to the daily life scenario. From the research, it is found that the theory of revenue management that is dynamic programming down sell could be used. The objective of this theory is to capture the nature of customers in which they book a cab (Kimes and Wirtz, 2015). It was found that they take the services of uber at nominal price; if the overall price increases it is found that booking decreases. It is seen that Uber have started many facilities like pool services that allow customers to share the ride and gain values (Chen and Jasin, 2018). It has helped in targeting the customers that look for economical budgets. Various targeting strategy is used by Uber so that customers can be increased and a good brand positioning is achieved in the market.
There are various methods available for data collection and to manage the staff accountabilities. Some of the common ways of data collection is interviews in which direct questions are asked to many people so that it is analysed future. Interviews can be structured or semi structured but the questions are quiet focused and clear (Kimes and Wirtz, 2015). Interviews are mainly qualitative in nature and it is one on one conversation that helps in understanding the issue. The other way of data collection is questionnaires and surveys that support the result by analysing the response via some methods. Results generated by surveys are quiet easier to analyse (Grauberger and Kimms, 2016). The other way of data collection is observing the information from different sources and analysing the target behaviour. Observations require a lot of time as it is an interaction between the staff and the program. It is a time consuming method and a very reliable one. The other way of data collection is via focus groups that are facilitated group who gather information about combined opinions and also analyses the response into different categories (Grauberger and Kimms, 2016). Case studies can be said as a comb nation if observations, interviews and surveys. It is one of the holistic approach but associates the overall experience and find outs the solution. The other form of data collection is in the form of documents and records that consists of examining the data in the form of databases, meetings, reports, attendance logs, financial records, newsletters and others (Debutinfotech, 2016). These are an inexpensive way to gather information but sometimes offer an incomplete data.
In this report, the case of Uber is discussed that make use of big data analytics that focuses on driving the business towards success. It is a smartphone based application that connects the customers easily with the service. The business makes use of big data so that crowd sourcing could be figured (Chiu, Teoh, Zhang and Huang, 2018). It plays an important role in the success of a business as company uses an algorithm to monitor the traffic conditions and the real time estimation of booking. These data collection methods are useful so that decisions could be made easily.
Revenue management is about attracting the right clients so that profit margins could be increased. If an effective revenue management strategy is defined in way that all the resources are used. One of the revenue management strategies for uber is optimising website for mobile customers it will help in maximizing the customers (Cetin, Demirçiftçi and Bilgihan, 2016). This strategy can be said as a backbone for generating revenue as it brings the services to the global platform. Uber have also integrated their services to various channels and they focus on direct booking that adds up convenience to the customers (Pavlova, 2017). It allows customers to book a cab in a single click, make payments easily, select the location and check the overall budget. Uber markets its services for need of transportation in the city and mostly target the customers who have low and mid income range. It the main marketing chain for the company is through marketing and advertisement channels (Gallego, Ratliff and Shebalov, 2014). Revenue management undertakes pricing strategy by analysing the market conditions and then undertaking the pricing decisions. The processes are set comparatively low then the competitors so that more customers get attracted towards it. Various pricing tools are created so that value changes according to the demands. Pricing tactics improves the overall profit margins for the firm (Pavlova, 2017). Revenue management is concerned about offering best price services and increasing the capacity. Uber also make use of promotions by offering discounts to the customers so that a balance is maintained between volume growth and profitability (Gallego, Ratliff and Shebalov, 2014). An effective promotion and offers help in maximizing the revenue over the long term. Different channels are used and it represents different cost margins. The strategy assures that dynamic pricing takes place in the presence of value transparency. They use advanced technology so that detail about the customers are observed and value transparency is gained. Revenue can be increased if new pricing strategies are used and customers are increased in the business (Fiig, Cholak, Gauchet and Cany, 2015). Revenue management also requires the use of technology by identifying the area for optimization and make sure that advanced software’s are used so that functions are competed automatically (Spaceo, 2016).
The most important thing that need to be considered while designing revenue management strategy is ROI, that helps in underpinning the choice made by customers and help the supervisor to evaluate the benefits gained by taking a particular decision. Forecasting the demand is essential for revenue management (Kurdhi, Dabadghao and Fransoo, 2018). The main motive of revenue management is to improve the performance and productivity. The revenue management depends upon the size of company and the customers participating in its services. Revenue management is designed in way that pricing of competitors are considered and historical data is analysed (Kurdhi, Dabadghao and Fransoo, 2018). The use dynamic pricing, were rules and set and it automatically adjust the fares according to the demand.
The market segment that is targeted by uber is middle and lower classes people who look for mode of transportation for going from one place to other. It is seen that uber target the region where transportation services are already available (Kocabiyikoglu, Gogus and Gonul, 2015). Targeting strategy that is used by uber is cost based pricing position that attracts customers from different strata.
The business model of uber involves taxi drivers and passenger. The taxi driver can be anyone who has the licence and willing to drive in a city. The screening of the driver is done and then they are appointed as a driver in a city. Uber services assure that they connect to the demand of passengers. The passengers in the business model are the customers who have registered themselves via application (Kocabiyikoglu, Gogus and Gonul, 2015). They are allowed to track the taxi and offer low cost services. The fare and payments are kept according to the demand. They are generally kept high at time of peak hours. Apart from that, customers are also allowed to make payment through any mode and also assure that their journey is secure. It is suggested that uber should invest more in the research and development (Kimes, 2016). The layout of business model is user friendly and also offers an easy way. Uber has no competitors in the taxi service business in the past time that has established a solid infrastructure, branding and consumer trust (Wang, Deng and Ye, 2014).
It is observed that uber has tried to shift their demand according to the customers need. They make use of surging price strategy that is an efficient marketing strategy that maximizes the number of rides. The pricing strategy is kept confidential and no users are aware about their strategy so that they can make huge benefits (Board and Skrzypacz, 2016). The pricing strategy is defined by considering the supply and demand. The pricing system is calculative as prices are recalculated every five minutes. It is said that majority of the prices are independent on drives and customers (Akan, Ata and Dana, 2015). They have become popular I the market as they are committed of serving low price leader.
They segment the overall market by dividing the customers in many groups according to their needs and interest (Akan, Ata and Dana, 2015). Once the interest is found and customers are segments then they are differentiated using the quality of service they need. Segmentation helps in better planning and allows knowing about the competitor’s strength and weakness (Cetin, Demirçiftçi and Bilgihan, 2016).
It is recommended that uber should decrease the price as compared to other taxi services. Apart from that, offers and plan should be broadcasted so that customers could be attracted. Some of the ways in which revenue of the company could be increased is expanding the market. This could be done by adding complementary services so that new customers could be gained. Expanding the geographic area helps in increasing the profit margin. It is recommended that drivers’ downtime should be reduced and scheduling pick-ups should be allowed. This could be done by creating loyalty programs for the customers (Quilichini, et. al, 2016). This uber experience should be customized so that it is easy and user friendly interface so that customers can book cabs easily.
The pool services should be designed in a way that it could be tracked easily so that safety and security is attained. Some of the revenue management strategies that are adopted by Uber, that they have offered various car models different in term of size and level of luxury. Price surge technology has been implied that automatically increases the price as per the demand. The tracking system should be more powerful so that customers feel safe and can connect to the driver easily. The payments methods should be digital that adds up flexibility among customers. The reason behind their success is they make use of robust pricing technology and offer different can models for differ customers.
Conclusion:
It can be concluded that, revenue management of uber can be improved by getting more customers and offering them reliable and flexible experience. The revenue could also be improved if changes are made according the customers trend. Many customers look for options where they can get cheaper price cabs for that uber has launched with their pool services. Some customers require cab that have a great luggage capacity, thus uber make the changes according to the requirements of customer. The experiences are also prioritised according to the demand.
References:
Ak, M., Kentel, E. and Savasaneril, S., 2017. Operating policies for energy generation and revenue management in single-reservoir hydropower systems. Renewable and Sustainable Energy Reviews, 78, pp.1253-1261.
Akan, M., Ata, B. and Dana, J.D., 2015. Revenue management by sequential screening. Journal of Economic Theory, 159, pp.728-774.
Board, S. and Skrzypacz, A., 2016. Revenue management with forward-looking buyers. Journal of Political Economy, 124(4), pp.1046-1087.
Cetin, G., Demirçiftçi, T. and Bilgihan, A., 2016. Meeting revenue management challenges: Knowledge, skills and abilities. International Journal of Hospitality Management, 57, pp.132-142.
Chen, Y. and Jasin, S., 2018. Power of Dynamic Pricing in Revenue Management with Strategic (Forward-Looking) Customers.
Chiu, P.C., Teoh, S.H., Zhang, Y. and Huang, X., 2018. Using Google Searches of Firm Products to Assess Revenue Quality and Detect Revenue Management. Available at SSRN 3252314.
Debutinfotech, (2016). Uber Business & Revenue Model. Available from https://www.debutinfotech.com/blog/uber-business-revenue-model-and-development-cost Accessed on 20-11-2018.
Fiig, T., Cholak, U., Gauchet, M. and Cany, B., 2015. What is the role of distribution in revenue management?–Past and future. Journal of Revenue and Pricing Management, 14(2), pp.127-133.
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Grauberger, W. and Kimms, A., 2016. Revenue management under horizontal and vertical competition within airline alliances. Omega, 59, pp.228-237.
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Kimes, S.E., 2016. The evolution of hotel revenue management. Journal of Revenue and Pricing Management, 15(3-4), pp.247-251.
Kocabiyikoglu, A., Gogus, C.I. and Gonul, M.S., 2015. Revenue management vs. newsvendor decisions: Does behavioral response mirror normative equivalence?. Production and Operations Management, 24(5), pp.750-761.
Kurdhi, N.A., Dabadghao, S.S. and Fransoo, J.C., 2018, July. Revenue management in remanufacturing under competition, cannibalization, and customer behavior. In EURO2018: 29th European Conference on Operational Research.
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Spaceo, (2016). How Uber Grows its Popularity with This Simple Strategy. Available from https://www.spaceotechnologies.com/uber-growth-strategy-lesson-startups-entrepreneurs/ Accessed on 20-11-2018.
Wang, Z., Deng, S. and Ye, Y., 2014. Close the gaps: A learning-while-doing algorithm for single-product revenue management problems. Operations Research, 62(2), pp.318-331.
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