Hickory Outdoor is a famous retail store. Its main specialties are camping, hunting, fishing, and other outdoor equipment. The company also specialises in supplies. This also includes several items from a wide array of outdoor sports. Over a period of the previous five years, the company has maintained its customers’ database. This implies that the marketing team can utilise data mining with the focus of improving its marketing strategies.
We will write a custom Essay on Hickory Outdoor Retail Store Marketing specifically for you
301 certified writers online
Ways of using Data Mining
Majority of the companies possesses immense loads of praiseworthy customer data. The unfortunate thing is that these companies have no idea that the data is valuable and, therefore, do nothing about it.
The good news is that this data is a rich source of insight. This insight is extremely useful in minimising client churn, unlocking hidden profitability, and escalating customer loyalty. After reading this paper, Hickory Outdoor will realize how the customer’s data contained in their database is valuable. Moreover, they will learn ways through which data mining can be beneficial, and the marketing programs that can be formulated from the data (KISSmetrics, 2013).
Affinity/ Basket Analysis
Through an analysis of the items bought previously by customers, Hickory Outdoor can improve the layouts used, and acquire ideas on related products that they can sell. Basket analysis is based on the assumption of future customer behaviour’ prediction from previous inclinations, buying, and routine (KISSmetrics, 2013). Moreover, basket analysis is vital in evaluating credit card use, telephone use patterns, and recognising fraud insurance claims.
Hickory Outdoor can use data mining to assess the necessity for adding stores. The level of merchandise can be evaluated through assessing the current store’s exact layout. Moreover, it is useful for judging the necessity for portfolio warehousing and stocking choices. Data mining is useful for updating inventories, selecting the wanted products, balancing stock, and pricing.
Considering the competitiveness in outdoor businesses, customers are likely to shift to competitors offering fewer prices. Therefore, data mining can be effective in reducing customer churn, particularly in social media. Through employee innovation, insights for product development, customer engagement, and business expansion can be gathered (Dringus & Ellis, 2005).
Marketing Programs Based on Data Mining
Planned obsolescence strategies
This involves an assessment of what customers bought previously, and a prediction of what they are likely to buy in the future. This analysis aids in determining prearranged obsolescence policies. This is in addition to appraising the complimentary products to be sold. Through such strategies, the company will have a clear picture of the number of customers they have, and how many to expect at a particular time.
Through assessing customer purchasing habits and the avenues for building customer profiles, Hickory Outdoor can come up with products that will sell themselves (Dringus & Ellis, 2005). Database information is obtained from questionnaires, subscriptions, surveys, and targets. Customers can consequently be focused on, basing on this intelligence. For effective database marketing, there is a need to gather information and look for avenues for discount promotions (Clow & Baack, 2009).
Other Marketing Programs from the Database
Hickory Outdoor can introduce marketing through the use of credit cards. According to Clow and Baack (2009), the cards can be used to gather information, identify customer segments, and develop programs that can escalate acquisition, improve retention, and design process. Through scrutinizing customer buying arrangements through the use of credit cards, the company can gain insights of customer habits, which are suitable for programs for client loyalty and greater revenues, as well as promotions.
Clow, K., & Baack, D. (2009). Integrated Advertising, Promotion, and Marketing Communications (5th ed.). New York: Prentice Hall.
Dringus, L. P., & Ellis, T. (2005). Using data mining as a strategy for assessing asynchronous discussion forums. Computers & Education, 45, 141–160.
KISSmetrics. (2013). 10 Ways Data Mining Can Help You Get a Competitive Edge.