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Assignment 2 of BMA 5002: Exploratory CRM @ London Jets Hockey Team

Assignment 2 of BMA 5002: Exploratory CRM @ London Jets Hockey Team. Group No: 5. By Wee Shi Ya Serene Lau Tsz Ming Albert Liu Tiefei Govindasamy Rajasekaran Soh Chai Chung Terence. London Jets Hockey Franchise is at risks and needs to be revived with strategic marketing initiatives.

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Assignment 2 of BMA 5002: Exploratory CRM @ London Jets Hockey Team

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  1. Assignment 2 of BMA 5002: Exploratory CRM @ London Jets Hockey Team Group No: 5 By Wee Shi Ya Serene Lau Tsz Ming Albert Liu Tiefei Govindasamy Rajasekaran Soh Chai Chung Terence

  2. London Jets Hockey Franchise is at risks and needs to be revived with strategic marketing initiatives • London Jets hockey franchise would be sold if revenue is not significantly increased within the next season • Existing high-budget ad campaign ran for most of the previous year was ineffective Situation Objective Devise strategic marketing initiatives to enhance game attendance immediately Strategy • Identify the most valuable customers via data analytics techniques, i.e. Recency, Frequency and Monetary (RFM) analysis followed by Segmentation analysis • Customers with the most yearly sales • Customers purchasing the most number of tickets • Retain and attract these customer strategically via focused marketing campaigns

  3. Intuitively, focusing on monetary value alone would help achieve both our objectives to maximize total sales and total tickets. However, the RFM analysis shows that although the frequent game visitors do not purchase the most number of tickets, they will also be responsive to the marketing efforts. Therefore, it may not be right to simply focus on the customers who contribute the most to sales, i.e. monetary value = 5, as we would have ignored the fact that the less recent customers may have a different profile compared to the more recent customers. RFM Analysis provides only a framework for further segmentation analysis to target the most valuable customers accurately

  4. Customer segmentation enables a better expected returns from marketing investments • Our segmentation has created the most prestigious customer segment, named “HockeyGold” which makes up 43% of the total sales and 40% of the total ticket sales. • The 2 premium segments, “HockeyGold” and “HockeySilver”, net a total of 73% of the sales and 69% of the tickets, even though they form only 42% of the population. • HockeyGold customers bring in sales 4.2 times that of the ordinary customers, named “Hockeyer”.

  5. HockeyGold and HockeySilver composed of higher-income group • Income ($50k->$80k) • As shown in the above chart , the HockeyGold & HockeySilver customers dominate customers from the higher income group. • HockyGold and HockeySilver both are make up of 15% more of these high income people as compared to Hockeyer. • However, there is a slightly different compositions between HockeyGold & HockeySilver customers. - For the HockeyGold customers, it concentrates around the income range $50k-$60k. - For the HockeySilver customers, it spreads rather evenly over the high income segments • Income ($20k- $50k) • As shown in this range, Hockeyers comparatively dominate customers from the lower income group

  6. HockeyGold & HockeySilver customers are more mature • Age (36 years old to > 51 years old) • As observed in the above chart , the customers which make up the HockeyGold & HockeySilver customers are more mature comparative to the Hockeyers. • The composition of HockeyGold and HockeySilver customers make up of 14% more elder fans of 41+ years old. • Hence, marketing strategy which focused on the preference and needs of this group of customers will boost the sales and enhance the game attendance. • Age group (>25 years old to 35 years old) • Within this younger age group, there are comparatively more Hockyers than HockeyGold & HockeySilver customers.

  7. A distinctive buying pattern in the targeted segments allows an accurate packaging to enable effective marketing efforts • The bubble charts indicate the differences in buying patterns of the customer segments. • Our HockeyGold customers are generally ardent fans who buy an average of 6 games per year and a total of 18 tickets. • The ordinary Hockeyer buys an average of 2 games per year as they choose the major games such as the Finals or friendly games with famous international teams. Furthermore, the Hockeyers usually come with their friends and families, which explains the larger numbers of tickets purchased.

  8. Comparative Analysis of the Prestigious Segments :Married Customers Vs Single Customers • As shown in the graph, the Married Males and Married Females generates more sales than their respective Singles counterparts. • This difference is even more apparent when we compare the percentage level change in the total sales contributed by each group based on the total number of people found in each group. • As shown in the table, in the case of Customer HockeyGold, the Married Males brought about a multiplier effect of 221% of total sales while the Married Females brought about a multiplier effect of 199% . • These figures are comparatively higher than those of the Single Males & Females. • Hence, marketing strategy would have a greater impact on the Married Males & Females as compared to their Single counterparts.

  9. General CharacteristicsGenerally, there are 2 common characteristics which we observed in the population of the customer, regardless of which segment they belong to, which have an influence on our marketing strategies. • Most Customers own an Automobile • As shown in the graph, most of the customers, regardless of which segment they belong to, own an automobile. • One strategy to boost sales revenue in all customer segments is to offer free parking to customers . • Most Customers are NOT fan club members • The graph highlights that few customers are fan club members. • The existing customer retention strategies through the London Jets Fan Club Members has not been successful in increasing the sales revenue and number of tickets sold. • Therefore, the company should consider how to attract more customers to join the fan club by increasing customers’ awareness of the benefits for fan club members.

  10. Marketing Strategy • Marketing Strategies which can help to boost sales revenue:- • Premium tickets with better seats to target customers as they belong to the higher income groups. • Discount for customers using Gold/Black/Platinum credit card • Marketing strategies and advertising targeting couples and matured customers. • Group ticketing or family ticketing for those who purchase several seats, for example, buy 4 get one 1 free. • Promotion for customers coming at their wedding anniversary • Free parking coupon for those who own automobiles • Frequent buyer or loyalty programme to reward those who purchase tickets for many games e.g. 5% discount on the ticket sales for those who attend 3 to 4 consecutive games; free tickets for customers who attended more than 6 games in a year • Off-peak periods ticket promotions and discounts. • . Attract more customers to join the fan club by giving more incentives to fan club members. Discount on tickets, priority seating, phone/ internet bookings, fan club magazines and exclusive meet the players sessions for fan club members.

  11. Limitations • RFM Analysis is a useful tool to identify customers who are more responsive to marketing efforts. However, we should not neglect customers who may have a low RFM score. • The data analyzed does not include customer preference and feedback on the quality of the games and services delivered over the years. The analysis assumes that all customers can be of equal importance to profile for the most effective marketing strategy • There are many variables to consider in the database and the tools used do not allow for simultaneous analysis of the variables to try to determine the relationship between the variables. • The data set is limited as we only know about the last transaction, but we do not have time series data on history of transactions, which will provide us with more information on the customers. • It will be beneficial to have a richer data set containing information on customer preferences e.g. ticket pricing, type of seats and favorite teams.

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