Recognizing the Significance of Monitoring KPIs in Developing a Marketing Strategy to Evaluate the Effectiveness of Influencer-based Marketing
Nibir Khawash, Prasenjit Chakravarty, Bratini Shome, Sudeshna Pahari
Assistant Professor, Amity Business School, Amity University Kolkata Major Arterial Road, AA II,
Newtown, Kadampukur, West Bengal 700135, India.
*Corresponding Author E-mail: khwashnibir@gmail.com
ABSTRACT:
The research paper aims to examine the importance of KPIs for influence-based business marketing purposes. The research objectives and the research questions have been made based on the key components and the positive impacts of the influence of business marketing. The primary quantitative research method is adopted in this research and a survey has been conducted among 55 participants. SPSS software is used for data collection and analysis purposes from the survey responses. Research findings have stated that tracking KPIs for the development of the marketing strategy creates a positive impact on influence-based marketing.
KEYWORDS: KPIs, Influence marketing, Business and Marketing, Followers, and Motivations.
INTRODUCTION:
The increasing prevalence of internet usage and its pivotal role in e-commerce has transformed people's behavior and decision-making through the evolution of electronic word-of-mouth (eWOM) Ghouse, Reddy and Ravi Kumar J S (2023). In the dynamic landscape of modern marketing, businesses are constantly seeking innovative ways to connect with their target audiences and drive brand engagement. With the significant surge in the acceptance of online shopping in India, marketers must enhance satisfaction and trust, thereby attracting customers for repeat purchases by understanding and ensuring their repurchase intention (Gupta 2020).
A customer's decision to acquire digital marketing services is influenced positively by three factors, with "Price" having the most substantial impact, followed by "Staff quality," while the least influential factor is "Reputation," according to the study conducted by Tuyen et al (2022).
In recent years, influencer-based marketing has emerged as a powerful strategy, leveraging the reach and influence of individuals with a substantial following on social media platforms. As businesses allocate substantial resources to collaborate with influencers, it becomes imperative to assess the impact and effectiveness of these campaigns. Private label brands are steadily establishing a robust presence in both online and offline markets in India, as consumers and retailers alike embrace them for their myriad associated benefits Pragriya and Kumar (2016). Key Performance Indicators (KPIs) play a pivotal role in this evaluation process, offering valuable insights into the success of influencer-based marketing efforts. Tracking KPIs helps to evaluate the effectiveness of influencer marketing initiatives. As per the notion of Govindan et al. (2021), this helps to determine trends, spot patterns, and determine best practices for delivering great results for analyzing and tracking data for numerous campaign purposes. As per the comments of Adi, Hiyassat and Lepkova (2021), social media influencers are using these platforms for delivering and sharing products and providing services. As per the notion of Terzi et al. (2023), tracking key performance indicators allows for depth understanding purposes and delivering proper understanding for the target audiences. Therefore, engagement rate is the major key metric for influence marketing purposes that are creating a positive impact on influence marketing purposes. In this context, understanding and monitoring KPIs is not merely a procedural task but a strategic imperative for businesses aiming to optimize their marketing strategies. The significance of KPIs lies in their ability to quantify the impact of influencer collaborations, providing actionable data that informs decision-making processes. This paper delves into the importance of monitoring KPIs in the context of influencer-based marketing, exploring how these metrics contribute to the evaluation of campaign effectiveness and overall marketing strategy development. As businesses navigate the evolving landscape of digital marketing, a nuanced understanding of KPIs becomes essential for making informed, data-driven decisions that yield measurable and sustainable results.
The four major key indicators include measures, planning, analysis, and acting. Hence, there are various advantages of KPIs including managing accountability, helping to track organizational performances, and identifying issues. The negative impact of KPIs includes narrow focus, and a small number of KPIs and it is creating a negative effect on business. As viewed by LINCY, and BELLA (2023), it is leading to a lack of balance, and the negative impact of KPI is based on taking a higher amount of time for delivering meaningful data. Thus, the disadvantages of influence-based marketing include misleading content and lack of motivation for the followers. In 2022, a survey was conducted among directors, vice presidents and managers in 35 countries and 88% of responses have been tracked for revenue purposes for the KPIs business (Statista, 2023). For customer satisfaction metrics and mobile analytics purposes, the rate is 87% and the rate is as low as 67% for customers' lifetime values (Statista, 2023).
The research aims to determine the importance of tracking KPIs for the development of the marketing strategy for influence-based marketing.
RO1: To determine the importance of tracking KPIs for developing a marketing strategy.
RO2: To examine the impact of marketing strategy for increasing the efficiency of the influence-based marketing.
RO3: To evaluate the impact of KPIs for influence marketing purposes.
RO4: To determine the important key factors for influencing marketing purposes.
RQ1: What is the importance of KPIs tracking for motivating the marketing strategy?
RQ2: How does marketing strategy develop efficiency for influence-based marketing purposes?
RQ3: What is the impact of KPIs or developing influence marketing purposes?
RQ4: What are the key components of the strategic marketing aspects?
The success of online marketing in today's business environment hinges on organizations actively engaging and enhancing their operational dynamics to meet the demands of the digital landscape Kaur (2023). KPIs allow influencers to gain a proper understanding of the target audiences and successfully develop their brand in social media. In the thoughts of Battisti, Agarwal and Brem (2022), tracking KPIs helps in developing the effectiveness of marketing initiatives and delivering trends and better practices for the target audiences. On the other hand, Gackowiec et al. (2020) have stated that social engagement is the major key factor for KPIs that determine the overall performance of the marketing campaign. The study on MTN Ghana, the leading telecom company, reveals that there is a moderately high and positive estimated conditional correlation between the volatilities in revenue and other commercial key performance indicators (KPIs). Consequently, the research indicates a robust association between financial performance and the industry's commercial KPIs Maka and Suresh (2019). There are various advantages of influencer marketing, including increasing sales rate, building trust, developing brand awareness, and cost-effectiveness. As per the notion of Silva and Oliveira (2020), boosting ROI and SEO, win-win partnerships, business sustainability, and sharing potentiality are the major advantages of influencer marketing. Thus, there are various ways to measure influencer marketing, including identifying the total number of the brand followers on social media and the range of the influencer's followers.
The key components of influence marketing are based on defining the budget, creating a campaign, identifying audiences, and determining the goals. As viewed by Prakasa (2023), the components of the influencers are based on the social media manager, audience, and endorser. On the contrary, Sultan (2022) has stated that identifying proper influencers, measuring campaign performances, creating a campaign goal, and making authentic partnerships are the major key components for influence marketing purposes. The process of a marketing campaign includes planning, alignment, recognition, coordination, and motivations, which are the major success factors for developing influence marketing. Therefore, influencers play a significant role in delivering power to the people to achieve the services and products and they are delivering trust and credibility to the influencers.
Seven Ps is helping in achieving maximum results and tracking effectiveness from the marketplaces. In the thoughts of Ayodeji and Kumar (2019), this plays a significant role in delivering a roadmap and setting proper objectives for achieving the business objectives. The emergence of online retailers has significantly impacted the sales of brick-and-mortar stores, emphasizing the pivotal role of promotion as a crucial element in the marketing mix for retailers Vasudevan and Senthilkumar (2018). Among those, the product plays a significant role in helping to determine the needs of the customers. As commented by Reyes-Menendez, Saura and Palos-Sanchez (2020), this theory helps to avoid unnecessary expenses and deliver strength, and offer products efficiently.
Figure 1: Conceptual Framework (Source: Influenced by Saha et al. 2023)
Positivism research philosophy has been used in this research paper for primary data collection purposes. Along with this, deductive research approaches and descriptive research design have been adopted in this research paper. As per the comment of Kamkankaew et al. (2022), the positivism research philosophy helps researchers to deliver proper predictions for social changes and society. As per the notion of Chornous and Fareniuk (2022), the deductive research approach is a data collection method that helps to understand the hypothesis and theory. Along with this, descriptive research design is a type of research design that delivers information regarding populations, phenomena, and situations purposes.
Primary quantitative research methods have been adopted in this research paper for data analysis purposes. Questionnaires have been made based on 13 open-ended questions and 55 responses have been collected in this research paper. As commented by Choudhary, Suppramaniam and Dada (2023), the positive impact of the primary research method is based on delivering effective research and the researcher is directly collecting samples from the previous research. SPSS software has been used for statistical data analysis purposes. Therefore, the advantages of the questionnaires are based on cost saving, data accuracy, flexibility for the responses, and delivering free surveys.
ANALYSES AND FINDINGS:
Demographic analysis:
Table 1: Response based on age group (Source: SPSS)
|
|
Frequency |
Percent |
Valid percent |
Cumulative percent |
|
Valid 18 to 25 years 26 to 30 years 31 to 40 years 41 to 50 years Total |
1 8 24 7 16 56 |
1.8 14.3 42.9 12.5 28.6 100.0 |
1.8 14.3 42.9 12.5 28.6 100.0 |
1.8 16.1 58.9 71.4 100.0 |
The above figure shows the responses from different age groups people. Total 55 responses have been collected from the participants. 18 to 25 years of candidates has been delivered 8 responses, and 24 responses have been collected from 26 to 30 years. Along with this, 31 to 40 years of candidates have delivered 7 responses, and 16 responses have been collected from 41 to 50 years peoples.
The above figure represents the pie chart for different age groups of people. 18 to 25-year-old candidates delivered 14.29% responses, and 12.50 responses have been collected from 31 to 40 years age group people. Therefore, higher responses have been collected from 26 to 30 years age group people as 42.86%.
|
|
Frequency |
Percent |
Valid per cent |
Cumulative percent |
|
Valid Female Prefer not to say Total |
1 24 31
56 |
1.8 42.9 55.4
100.0 |
1.8 42.9 55.4
100.0 |
1.8 44.6 100.0 |
The above table is showing that the rate of responses from different genders. Male candidate has not responded in this case and female candidate have been delivered 24 responses. Along with this, other candidates have delivered 31 responses.
Figure 3 Pie chart for different genders (Source: SPSS)
The above figure shows the pie chart for the various genders, female candidates have delivered 42.86% of responses.
Table 3: Responses for various occupations people (Source: SPSS)
|
|
Frequency |
Per cent |
Valid per cent |
Cumulative percent |
|
Valid Business Manager Staff Employee Total |
1 16 16 23 56 |
1.8 28.6 28.6 41.1 100.0 |
1.8 28.6 28.6 41.1 100.0 |
1.8 30.4 58.9 100.0 |
The table 3 is showing various occupations and people delivering their responses for this survey. Business managers have delivered 16 responses, staff and employees have given 16 and 23 responses respectively.
Figure 4: Pie chart for different occupations (Source: SPSS)
The above figure is denoting that employees and business managers have been delivered same responses around 28%. On the other hand, higher responses have been given by staffs around 41%.
Table 4 shows a descriptive statistics test that is based on mean medium and standard deviation rates. The rate for the standard deviation is 2.845 for IV1 and 2.766 for IV2. Along with this, for IV3 and DV the standard deviation rate is 3.21 and 2.95. The mean value for IV1, IV2, IV3 and DV are 5.78, 6.21, 5.05, and 5.334 respectively.
|
|
N |
Minimum |
Maximum |
Mean |
Std. Deviation |
Skewness |
Kurtosis |
||
|
Statistic |
Statistic |
Statistic |
Statistic |
Statistic |
Statistic |
Std. Error |
Statistic |
Std. Error |
|
|
IV1 IV2 IV3 DV Valid N (listwise) |
55 55 55 55 55
|
2.00 2.00 2.00 2.00
|
10.00 10.00 10.00 10.00 |
5.78 6.2 5.0 5.34 |
2.84 2.77 3.21 2.94 |
0.499 -0.159 0.406 0.273 |
0.322 0.322 0.322 0.322 |
-1.108 -1.439 -1.563 -1.515 |
0.634 0.634 0.634 0.634 |
Table 5: Model summary and ANOVA table (Source: SPSS)
|
Model |
|
|
|
|
Change statistics |
Durbin-Watson |
||||
|
R |
R square |
Adjusted R square |
Std. error of the estimate |
R square change |
F change |
df1 |
df2 |
Sig. F Change |
||
|
1 |
0.970a |
0.942 |
0.938 |
0.73397 |
0.942 |
275.323 |
3 |
51 |
0.000 |
2.685 |
|
Model |
Sum of squares |
df |
Mean square |
F |
Sig |
|
Regression Residual Total |
444.962 27.474 472.436 |
3 51 54 |
148.321 0.539 |
275.323 |
0.000b |
The above table represents ANOVA table and model summary table. The R square value is 0.942 and the R value is 0.970. Therefore, tracking KPIs plays a significant role in the development of influence-based practices. ANOVA table shows showing F value of 275.323 and the significance value is 0.000. The significance value is less than 0.05 representing that DV is creating a positive impact on IV.
Table 6: Coefficient table (Source: SPSS)
|
Model |
Unstandardized coefficient |
Standardized coefficient |
t |
Sig |
|
|
B |
Std Error |
Beta |
|||
|
1 (Constant) IV1 IV2 IV3 |
0.655 - 0.250 0.471 0.635 |
0.251
0.073 0.120 0.072 |
-0.240
0.440 0.691 |
2.613 -3.401 3.935 8.878 |
0.012 -0.001 0.000 0.000 |
Table 6 represents the coefficient table that shows significant values, t values, and Beta values. For IV1 beta value is 0.240 and 3.401 is the t value. For this, the significant value is less than 0.05; therefore, it creates a positive impact on effective decision-making purposes. On the other hand, for IV2 and IV3 the beta value is 0.440 and 0.691. For both, the significance value is less than 0.05, that is showing IV2 and IV3 are highly correlated with each other.
|
Kaiser-Meyer-Olkin of sampling Adequacy Bartlett’s test of sphericity approx.. Chi-square df sig |
0.500 58.955 1 0.000 |
Table 7 shows validity test with the help of the KMO and Batrtlers Test. The significance value is 0.000 which is less than 0.05, and chi square value is 58.955. Therefore, it can be stated that tracking KPIs for the development of the marketing strategy is helping in influence-based marketing purposes and this test is valid.
|
Cronbach’s alpha |
N of items |
|
0.890 |
4 |
The reliability test is represented in table 8, the Cronbach’s Alpha value is 0.890 which is close to the value of 1. Therefore, both IV and DV are reliable, and they are creating positive impacts on both of them.
The positive impact of KPIs for increasing marketing efficiency for influence-based marketing practices. Primary quantitative research methods have been used and a survey has been done among 55 responses. 13 research questions have been made for the participants to collect their responses. SPSS software has been used for validity tests and reliability tests. The value of the R square and Cronbach’s alpha value have been calculated by the SPSS software. Descriptive analysis and demographic analysis have been done in this research paper for data analysis purposes. The Seven Ps of Marketing Mix have been analyzed in this research study and have delivered values regarding seven different factors.
CONCLUSION AND RECOMMENDATION:
Over the past 3 to 4 years, the landscape of luxury retailing has experienced a significant transformation driven by extensive social media marketing, campaigns, and the integration of IoT and electronic retailing technologies, resulting in a notable shift in customer shopping behavior influenced by various specialized apps Hemantha (2023). It can be concluded that the efficiency of influence-based marketing has been developed by tracking KPIs. India is on the verge of the information technology age, with the internet having become an integral component for the Indian population, enabling connectivity, email access, and the seamless ordering of goods and services (Chandan and Gupta 2018). The research objectives are based on determining the importance of KPIS and marketing strategies for the influence of marketing aspects. Along with this, the key components of influence marketing have been discussed in this research paper. Conceptual frameworks have been made to get a proper understanding of the dependent and independent variables. There are various limitations of influence marketing, including limited research, short-term impacts, cost, lack of proper control and fraudulent activities. Secondary research methods have not been used in this research paper which is creating limitations for this research study. In conclusion, the fusion of influencer-based marketing and KPI monitoring is not just a trend but a fundamental shift in how businesses approach their promotional endeavors. The symbiotic relationship between influencers and KPIs offers a holistic understanding of campaign effectiveness, guiding organizations toward more impactful and resonant brand messaging. Research supports the existing concept of literature that businesses that have embraced digitalization enjoy a substantial competitive advantage over those that have either failed to do so or have been slow in adopting digital strategies by Kumar; Amol Gawande and Brar (2023). As the marketing landscape continues to evolve, those adept at recognizing the nuanced significance of monitoring KPIs in the context of influencer-based marketing will be better positioned to not only navigate the complexities of the digital sphere but also to thrive in an environment where adaptability and precision are key. The future of marketing lies in the hands of those who can decipher the intricate dance between influencers, data, and strategic decision-making, creating a harmonious symphony that resonates with the hearts and minds of the ever-discerning consumer.
The future scope for influencer marketing is based on developing brand messages for the target audiences. For the development of the demands and increasing growth factors, these types of marketing are playing a crucial role. Teachers and students are getting advantages with the help of this kind of research paper. For future marketing purposes, influencer marketing is playing a significant role, and it is increasing audience engagement, reporting, and content creation. The marketing managers are getting advantages with the help of this research paper; it is developing influencer marketing campaigns. Along with this, for the development of engagement, communications, and brand management development purposes, social media platforms are playing a crucial role.
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Received on 22.12.2023 Revised on 13.06.2024 Accepted on 19.09.2024 Published on 06.12.2024 Available online on December 31, 2024 Asian Journal of Management. 2024;15(4):353-359. DOI: 10.52711/2321-5763.2024.00055 ©AandV Publications All right reserved
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