Quantitative forecasting techniques refers to the approaches of forecasting used for examining the future trends by analysing the historical data. These forecasting techniques are applied through static methods like time series forecasting and casual forecasting (Spedding & Chan, 2010). The casual forecasting is conducted using simple or multiple regression models. On the other hand, casual forecasting is executed through the use of autoregressive moving average models. In logistics, time series forecasting focuses on analyzing the change in business strategies over a period of time. This forecasting is done using moving average and exponential smoothing which uses mathematical formulas to identify the forthcoming claim of the consumers addressed (Dombi, et al., 2018).

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Maslow’s hierarchy of needs focuses on the basic requirement and demand for the individuals utilized by the marketers to identify the customer buying pattern (Yan, et al., 2016). The components of the theory or basic needs of the human being comprise:

• psychological needs,
• safety and security needs,
• love and belonging need,
• self-esteem and,
• self-actualization needs.

Identifying buying behaviours

The burdens and necessities of diversified customer range have been distributed through the type of products which help the marketers to select a particular group of target consumers.

The feedback and the opinion of the customers are evaluated in a structured manner to deliver a product or service to accomplish a business goal (Karahanna, et al., 2018). Maslow’s hierarchy helps to identify the difference between the external environments that affect an individual’s behaviour, trait and attributes in choosing a brand. The psychological and social demand of the customers remain fulfilled effectively by evaluating the model and the price of the products remain aligned with the regular range as it covers the basic need of human being (Harrigan & Commons, 2015).

The values provided to the consumer for sales is considered as an important factor for the marketers in a marketing strategy (Li, et al., 2017). On the other hand, the sentimental judgment of the customers remains evaluated through the Maslow’s need of hierarchy to demonstrate a pattern in the buying behaviour (Bouzenita & Boulanouar, 2016).

Case example of the use of Maslow’s hierarchy of needs

Pharmeasy, an E-commerce website and application serving pharmacy products, medical equipment and booking of medical tests (Pharmeasy, 2019). Pharmeasy has been able to deliver medicines at low cost compared to the physical stores and meet the basic psychological needs of customers. Before, the start of online pharmacy stores, medicine or conducting the medical tests relied on the traditional stores and diagnostic centres. The firm has identified lack of proficiency for understanding the name of the medicines ordered. So, they have taken the approach of uploading a copy of the prescription to identify the medicines.

Pharmeasy had offered a 40% discount on the first five orders to its new users. This addressed the consumer buying behaviour based on the Maslow theory. These types of demands and needs are frequent in nature and customer retention has become more simplified through their quick delivery and pricing (Lee & Hanna, 2015). The queries and doubts of the customers also remain fulfilled and are often replied over social media platforms fulfilling the need of social characteristics of online consumers.

References

• Bouzenita, A. & Boulanouar, A., 2016. Maslow’s hierarchy of needs: An Islamic critique. Intellectual Discourse, 1(24), pp. 25-28.
• Gbededo, M. & Liyanage, K., 2018. Identification and alignment of the social aspects of sustainable manufacturing with the theory of motivation. Sustainability, 3(10), p. 852.
• Harrigan, W. & Commons, M., 2015. Replacing Maslow’s needs hierarchy with an account based on stage and value. Behavioral Development Bulletin, 1(20), p. 24.
• Indiatimes, 2018. e-commerce-players-brace-for-big-battle-over-online-pharma/. [Online] Available at: https://economictimes.indiatimes.com/industry/healthcare/biotech/pharmaceuticals/e-commerce-players-brace-for-big-battle-over-online-pharma/articleshow/65062615.cms
• Karahanna, E., Xu, S., Xu, Y. & Zhang, N., 2018. The needs–affordances–features perspective for the use of social media. Management Review, 2(26), pp. 298-310.
• Lee, J. & Hanna, S., 2015. Savings goals and saving behavior from a perspective of Maslow’s hierarchy of needs. Journal of Financial Counseling and Planning, 2(26), pp. 14-18.
• Li, Y., Zhang, H. & Huang, W., 2017. Gender differences in information quality of virtual communities: a study from an expectation-perception perspective. Personality and individual differences, 1(104), pp. 224-229.
• Missimer, M., Robèrt, K. & Broman, G., 2017. A strategic approach to social sustainability–Part 1: exploring the social system. Journal of Cleaner Production, 1(140), pp. 32-41.
• Pharmeasy, 2019. About Us. [Online] Available at: https://pharmeasy.in/About Us/ [Accessed 08 August 2019].
• Yan, Z., Wang, T., Chen, Y. & Zhang, H., 2016. Knowledge sharing in online health communities: A social exchange theory perspective. Information & Management, 5(53), pp. 643-653.

Demand forecasting is defined as an approach used for analyzing future demand in comparison to the previous ones. The purpose of demand forecasting is to apply future planning and decision in the domain of finance, logistics, operation and sales. Companies use a qualitative method of forecasting to analyse and evaluate the opinion of experienced staff rather than focusing on numerical values (Dwyer, et al., 2012). These methods are used for predicting any short term or internal forecasting on the basis of summative feedback of departmental heads. On the other hand, quantitative forecasting technique deals with numerical data focus on projection of trends on the basis of historical figures of the business. This method of forecasting is consistent and useful for long term scenario planning of the company.

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