KPI dashboard for Customer Intelligence tasks: application and significance for business

The contribution of business is very significant in the economic development of countries, the creation of new jobs, the development of education, the improvement of the environment, and the improvement of the population’s living standards. For enterprises themselves, stable and competitive development and efficient marketing activity are vital, where the significant role is played by customer intelligence (CI). It is determined by the fact that in modern world customer focus and centricity give companies the ability to be more successful and stable on the market. The global digital transformation has provided companies with many opportunities for customizing products and services, which generally increases competitiveness on the one hand, and on the other hand, opens up new opportunities for working with consumers. Based on consumer databases in marketing activities, it is possible to start applying CA. Today, many methods and technologies allow to start using KA to collect and process consumer databases. This article aim is to present the practical approach to Customer Intelligence tasks through the Key Performance Indicators (KPI) dashboard, where the dashboard is the set of KPIs chosen based on CI tasks realizations. Using this panel will allow companies to follow the path of implementing CA with an understanding and evaluation of the effectiveness of using this technique. The systematic use and tracking of results will ultimately affect the stability and viability of companies.

1. Ali F., Kim W.G., Li J., Jeon H.M. Make it delightful: customers’ experience, satisfaction and loyalty in Malaysian theme parks. J. Destination Marketing Manage, 2018, no. 7, pp. 1–11.

2. Rygielski C., Wang J.-C., Yen D.C. Data mining techniquesfor customer relationship management. Technology in Society, 2002, no. 24(4), pp. 483–502.

3. Lu J., Cairns L., Smith L. Data science in the business environment: customer analytics case studies in SMEs. Journal of Modelling in Management, 2020.

4. Sychrová L., Šimberová I. Key Performance Indicators as as Basic Element for a Marketing Efficiency Measurement // 7th International Scientific Conference “Business and Management“ 2012, pp. 488–493.

5. Andersén J., Strategic resources and firm performance. Management Decision, 2011, no. 49(1), рр. 87–98.

6. Amado A. et al. Research trends on big data in marketing: а text mining and topic modeling based literature analysis. European Research on Management and Business Economics, 2018, vol. 24, no. 1, pp. 1–7.

7. Worldbank.org, Small and Medium Enterprises (SMEs) Finance. 2021. URL: https://www.worldbank.org/en/topic/smefinance

8. Bulletin “Main indicators of the number of subjects in the Kazakhstan Republic”. Accessed August 8, 2021. URL: https://stat.gov.kz/official/industry/13/statistic/5

9. V2019 godu likvidirovano rekordnoye chislo predpriyatiy. 2020.URL: https://kapital.kz/business/82371/v-2019-godu-likvidirovano-rekordnoye-chislo-predpriyatiy.html

10. Soldatenko T.А., Yessimzhanova S.R. Modern aspects and trends of Customer Intelligence development // Economics: strategy and practice, 2020, no. 2 (15), pp. 107–113.

11. Google Analytics. URL: https://support.google.com/

12. Kalinić Č, Vujičić M. A subnational assessment of hotel social media metrics – The case of Serbia. Geographica Pannonica, 2019, no. 23(2), pp. 87–101.

13. Facebook Business Help Center. URL: https://www.facebook.com › business › help

14. Support Google. URL: https://support.google.com

15. Bondarenko S. et al. Modern lead generation in internet marketing for the development of enterprise potential, 2019.

16. Wiegand S. AerOff Oy–in-depth potential customer analysis focusing on the southern German CNC market, 2021.

17. Baehre S. et al. The use of Net Promoter Score (NPS) to predict sales growth: insights from an empirical investigation //Journal of the Academy of Marketing Science, 2022, vol. 50, no. 1.

18. Van Lierop, D. e A. El-Geneidy. Enjoying loyalty: The relationship between service quality, customer satisfaction, and behavioral intentions in public transit. Research in Transportation Economics, 2016, vol. 59, no. 1, pp. 50–59.

19. Abdolvand N., Baradaran V., Albadvi A. Activity–level as a link between customer retention and consumer lifetime value // Iranian Journal of Management Studies, 2021.

20. Sinha A. et al. Modelling Customer Churn Rate and Its Use for Customer Retention Planning // Available at SSRN 3998408, 2022.

21. Bonyuet D. Price Delegation and the Impact on Customer Loyalty // Journal of Instructional Pedagogies, 2019, p. 22.

22. John Solomon. What is Customer LifeTime Value (CLTV). Why is it considered an important SaaS Metric. URL: https://www.chargebee.com/blog/saas-metric-customer-life-time-cltv

23. Meeker M., Wu L. Internet trends. 2018. URL: https://hybg.cebnet.com.cn/upload/internettrends-2018/internet-trends-2018-en

24. Balancing your new existing customer revenue. 2020. URL: https://www.optimove.com/blog/balancing-your-new-existing-customer-revenue-mix

25. How to calculate customer churn and revenue churn. 2021. URL: https://www.salesforce.com/resources/articles/how-calculate-customer-churn-and-revenue-churn