MEASURING THE EFFECTIVENESS OF MARKETING INVESTMENTS USING THE METHOD OF SNEDECOR'S F DISTRIBUTION


 Oliver Williams
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1 MEASURING THE EFFECTIVENESS OF MARKETING INVESTMENTS USING THE METHOD OF SNEDECOR'S F DISTRIBUTION Nikola Vojvodic, PhD PIM University of Banja Luka, Banja Luka, Republic of Srpska, Bosnia and Herzegovina , Boro Vojvodic, PhD City of Prijedor, Prijedor, Republic of Srpska, Bosnia and Herzegovina Drazen Vrhovac, Mr City of Prijedor, Prijedor, Republic of Srpska, Bosnia and Herzegovina Momcilo Komljenovic, PhD Foreign Trade Chamber of Bosnia and Herzegovina, Banja Luka, Republic of Srpska, Bosnia and Herzegovina, , Original Scientific Paper doi: /jouproman Abstract: The environment in which insurance companies operate is all the more complex and turbulent which requires a systemic approach to business and adaptation to the constant changes on the insurance market. In order to create or maintain the competitive advantage it is necessary to study marketing in insurance as a new, scientific, meaningful, technologically more advanced and profitable approach in this field. It includes applying tools of the marketing mix and implementing the activity of analysis of: environment (external and internal), formulating the strategy of market performance, implementation of the strategy as well as its estimate and control, promotion and adequate channels of insurance products distribution. Key words: Marketing investments, insurance, measuring, effectiveness, competitiveness, Snedecor's F distribution. INTRODUCTION A special position and significance appertain to the marketing measuring, that is, the metrics representing a system for measuring which quantifies the trend, dynamics or characteristics of the investment in marketing. In reality, all disciplines practically use the metrics to explain phenomena, diagnoses and causes, to share the acquired knowledge and to design results of the future events. The managers used to admit that half the money they spent on advertising was wasted. But those days of uncontrolled increase of the budget are over as measuring and liability are introduced. The elements which are to be measured include margin, price, variable and fixed marketing, sales extent before and after the marketing investment, brand attractiveness, impressions, exposure, viewership, average of gaining and keeping an insurer, the sales manager's performance, etc. Planning the return on marketing investment (ROMI) will be presented on the example of a successful insurance company using the method of the Snedecor's F distribution. 1. STATISTICAL ANALYSIS The statistical analysis has been done on the example of an insurance company which planned its propaganda using the percentage of insurance sales method. 39
2 As the propaganda were slowly increasing, the insurance premium was also increasing because the propaganda effect was delayed, that is, the actual propaganda effects did not deliver results until the following year. The analysis has been done by the econometric model, whose rated model is as follows. The model ) are rated ( ) by the method of the least squares. Determining the validity of the model rating is best done using the coefficient of determination (R 2 ), which measures the impact of the change in the independent variable X on the change in the dependent variable Y. can be seen as the relation when explaining the independent variable Y, i.e. how many percents are explained by X, and how many by excluded factors. The significance of R 2 is tested by the method of the Variance analysis, which can be R 2 freedom. If >, then Y statistically significantly depends on the factor X. That is, we set the hypotheses: H 0 : the X variable has no significant impact on the Y variable; H 1 : the X variable has a significant impact on the Y variable. H 0 hypothesis is accepted if, and H 1 hypothesis is accepted if >. a represents the risk level, that is, the possibility of making a mistake in percents. We have calculated with a =0.5%. or parameters ( represented as follows: is compared to the table values of the Snedecor's F distribution with 1 and n2 of degrees of The scale on the Yaxis of the charts in the paper is logarithmic for better visibility and legibility of the data. In the following table the propaganda and of an insurance company are presented in order to prove the above mentioned hypotheses, that is, whether the investment in propaganda significantly affects the insurance premium increase of the insurance company. Table 1 Business revenue, propaganda and % of the propaganda in the total revenue Month Year of Total revenue I 600,000 II 700,000 III 1,100,000 IV 1,200,000 V 1,500,000 VI 3,200,000 VII 2,800,000 VIII 1,500,000 IX 1,100,000 X 600,000 XI 500,000 XII 700,000 Total 15,500,000 I IV VII X Participation of the propaganda in the 3, % 3, % 5, % 3, % 12, % 30, % 24, % 3, % 2, % 1, % 1, % 3, % 96, % Total revenue 40
3 If we mark the with Y, as the dependent variable, and the propaganda with X, as the independent variable, we can calculate R 2, according to and y from the relation, that is,, and prior to it we must calculate i, so that: the formula. We calculate x ΣY 15,500,000 ΣX 96,430 Ŷ= = =1,291, X= = = 8, n 12 n 12 x = X X = 96,430 8,035 = 88,395 y = = 15,500,000 14,208,833 Then we calculate for each month x=,s x=0 i y=,s y=0, and finally, we calculate the sumss xy, x 2 and y 2 and insert them in the formula: x² = 7,813,499,236 1,291,167 = F¹ 10 = As F¹ 10 (a = 0.5 %), the hypothesis H 1 is accepted: the X variable significantly affects the Y variable, that is, with certainty of 99.5% we can assert that the investment in propaganda in 2013 affected the total revenue of the insurance selling. Year of 2014 y² = xy = 88,395 14,208,833 = (xy)² = (Σ xy)² R² = = = Σx²Σy² I V IX Total revenue = = 9,
4 Table 2 Business revenue, propaganda and % of the propaganda in the Month Total revenue Participation of the propaganda in the I II III IV V VI VII VIII IX X XI XII Total 800,000 5, % 1,000,000 7, % 1,300,000 10, % 1,400,000 12, % 1,600,000 14, % 3,300,000 40, % 3,000,000 38, % 1,600,000 15, % 1,300,000 12, % 900,000 8, % 1,100,000 10, % 1,200,000 11, % 18,500, , % In 2014 we have the following situation: x² = y² = xy = 88,395 14,208,833 = (xy)² = (Σ xy)² R² = = = Σx²Σy² = (12 2) = 2,197,309 ( ) As > F¹ 10 (a = 0.5 %), that is, 2,197,309>55.552, we reject H 0 and accept H 1 : the X variable statistically has a significant impact on the Y variable, which means that the investment in propaganda delivered positive effects on the total revenue. In 2014 the investment in propaganda increased from 96,430 to 187,240 BAM and the for even 3,000,000 BAM. 42
5 Year of I IV VII X Table 3 Business revenue, propaganda and % of the propaganda in the Month Total revenue I 1,100,000 19,360 II 1,300,000 11,830 III 1,600,000 15,680 IV 1,700,000 28,560 V 1,900,000 36,480 VI 3,300,000 43,560 VII 3,100,000 39,680 VIII 1,800,000 21,960 IX 1,500,000 23,700 X 1,200,000 14,520 XI 1,400,000 15,540 XII 1,600,000 27,360 Total 21,500, ,230 Total income Participation of the propaganda in the 1.76% 0.91% 0.98% 1.68% 1.92% 1.32% 1.28% 1.22% 1.58% 1.21% 1.11% 1.71% 1.39% It can be noted that the percentage of the investment in propaganda increased from average 0.62% of the in 2013 to 1.39 % in 2014, whereas the total revenue of 15,500,000 BAM, achieved in 2013, increased to 21,500,000 BAM in Therefore, it can be concluded that the slow increase of propaganda has a delayed impact on the insurer's awareness so that they insure their property exactly at this insurance company, which caused the increase of the. If we analyse the data: =1,791,667 ; x = X X = 298,230 24, = 273, y = = 21,500,000 1,791,667 = 19,708,833 x² = y² = xy = 273, ,708,8333 = = (xy)² = =24, (Σ xy)² R² = = = Σx²Σy² = (12 2) = 38,759,679 ( ) 43
6 As > F¹ 10 (a = 0.5 %), that is, 38,759,679>55.552, we reject H 0 and accept H 1 : the X variable statistically has a significant impact on the Y variable. At the end, it can be concluded that as the investment in propaganda increases, the revenue of the insurance selling also increases, that is, the marketing investment is completely justified. RFERENCES 1. Louis J. DeRose, The Value Network (New York: Amacom, 1994.) str Philip Kotler, Upravljanje marketingom, Northwestern University, God. Str Nikola Vojvodić, Ekonomski efekti marketinga, Banja Luka, Dr Milan Galogaža, principi marketinga, 1998.,str Prof. dr Vesna BabićHodov vić, Prof. dr Anto Domazet, Prof. dr Emir Kurtović, Osnovi marketinga, Sarajevo str Kotler, P., Keller, K. (200 06), Marketing Management, 12 ed., Pearso on Prentice Hall, New Jersey, str Hollensen, S. (2006), Marketing Planning: A Global Perspective, The MacGraw Hill Education, London, str web.efzg.hr/dok/oim/dhruska/2012 %20strateska%20portfolio%20analiza.pdf (pristup ) /brand_glossary.asp cim.co..uk 13. Dan Herman Phd, Shortterm brands revolutionize branding, November, Lessons from cultural icons, How to create an iconic brand, Harvest Communication, New York, David Jobberu (2001, p229) erview.asp styles.htm Logo design design.htm color guide & color chart Alexander Evdakov. 24. David Aaker, Building Strong Brands, web.efzg.hr/dok/mar/rbutigan/predavanje 10, Upravljanje oglašavanjem web.efzg.hr/doc/trg//mdelic/razlike u cijeni u trgovini, marža /acta_economica_ /loyaltycards