Unveiling Critical Success Factors for Marketing Intelligence : A Multi-Method Framework
DOI:
https://doi.org/10.17010/pijom/2026/v19i5/174928Keywords:
marketing intelligence, critical success factors, fuzzy DEMATEL, principal component analysis.JEL Classification Codes : M00, M03, L02
Publication Chronology: Paper Submission Date : August 20, 2025 ; Paper sent back for Revision : March 15, 2026 ; Paper Acceptance Date : April 5, 2026 ; Paper Published Online : May 15, 2026.
Abstract
Purpose : The purpose of this study was to identify, structure, and examine the causal dominance of critical success factors underlying marketing intelligence using a multi-method analytical framework.
Methodology : With reference to the growing importance of marketing intelligence for intelligent marketing, this study conducted an extensive literature review (N = 152) and identified 29 critical success factors of marketing intelligence. Further data was collected (n = 256) for principal component analysis and (n = 13) for employing fuzzy DEMATEL.
Findings : The results of principal component analysis segmented the 29 dimensions into 7 corresponding factors. Further, fuzzy DEMATEL (Decision-Making Trial and Evaluation Laboratory) was employed to establish Strategic Marketing Planning (SMP), Strategic Business Intelligence (SBI), Customer Brand Co-Creation (CBC), Tactical Marketing (TM), and Strategic Customer Intelligence (SCI) as cause factors, and Competitive Intelligence Analysis (CIA), Digital Dynamism (DD) as effect factors.
Originality : This study offered a novel multi-method investigation by integrating the PRISMA framework, PCA, and Fuzzy DEMATEL to identify cause and effect dimensions and enhance system-level understanding of marketing intelligence implementation.
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1) Ade, L. P., Akanbi, A. M., & Tubosun, A. I. (2017). The influence of marketing intelligence on business competitive advantage (A study of Diamond Bank Plc). Journal of Competitiveness, 9(1), 51–71. https://doi.org/10.7441/joc.2017.01.04
2) Aghazadeh, H. (2015). Strategic marketing management: Achieving superior business performance through intelligent marketing strategy. Procedia - Social and Behavioral Sciences, 207, 125–134. https://doi.org/10.1016/j.sbspro.2015.10.161
3) Alamsyah, A., & Saviera, F. (2017). A comparison of Indonesia e-commerce sentiment analysis for marketing intelligence effort. In The 8th International Conference on Sustainable Collaboration in Business, Technology, Information and Innovation. arXiv. https://doi.org/10.48550/arXiv.2103.00231
4) Al-Weshah, G. A. (2017). Marketing intelligence and customer relationships: Empirical evidence from Jordanian banks. Journal of Marketing Analytics, 5(3), 141–152. https://doi.org/10.1057/s41270-017-0021-7
5) Al-Zoubi, A. F. (2016). The impact of marketing intelligence on innovation and technological entrepreneurship in Jordan telecommunication company (empirical study). Journal of Marketing and Consumer Research, 21, 22–40. https://iiste.org/Journals/index.php/JMCR/article/view/29205
6) Ariyani, R., Yusnitasari, T., Oswari, T., Kusumawati, R. D., & Mittal, S. (2019). Consumer behaviour analysis in online music purchases in Indonesia by implementing 7P's marketing strategy using quality function deployment (QFD). American Journal of Engineering and Technology Management, 4(3), 57–65. https://doi.org/10.11648/j.ajetm.20190403.11
7) Ayub, A., Razzaq, A., Aslam, M. S., & Iftekhar, H. (2013). A conceptual framework on evaluating SWOT analysis as the mediator in strategic marketing planning through marketing intelligence. European Journal of Business and Social Sciences, 2(1), 91–98.
8) Balasundaram, E., Aranganathan, P., Annavajjala, K. S., Sivakumar, R., Arumugam, M., & Vinoth, A. (2024). A hybrid approach for customer segmentation and loyalty prediction in
e-commerce. Prabandhan: Indian Journal of Management, 17(10), 56–69. https://doi.org/10.17010/pijom/2024/v17i10/173996
9) Bermúdez-Hernández, J., Valencia-Arias, A., & Montaño-Arias, W. M. (2021). Conceptual model for innovation in the approach of market - oriented strategies. Indian Journal of Marketing, 51(12), 8–25. https://doi.org/10.17010/ijom/2021/v51/i12/167217
10) Bhagat, M., Bharadwaj, V., & Sahoo, S. (2026). Examining consumer attitudes toward personalised AI-generated product recommendations among college students. Journal of Emerging Technologies and Innovation Management, 1(1), 12–20. https://doi.org/https://doi.org/10.64006/jetim/1102
11) Bhattacharya, S., Dalal, A., & Bandyopadhyay, N. (2023). An empirical study to identify consumer brand relationships during a crisis. Indian Journal of Marketing, 53(1), 8–23. https://doi.org/10.17010/ijom/2023/v53/i1/172592
12) Brindha, G., Vidya, M., & Reshma, M. (2025). AI-driven omnichannel marketing and customer experience: A bibliometric overview. Indian Journal of Marketing, 55(11), 69–92. https://doi.org/10.17010/ijom/2025/v55/i11/175822
13) Chaudhary, K., Singh, P., & Pallavi. (2025). BUKMUK's marketing puzzle - Putting the pieces together: A case study. Indian Journal of Marketing, 55(8), 33–48. https://doi.org/10.17010/ijom/2025/v55/i8/175208
14) Chesbrough, H. (2003). The logic of open innovation: Managing intellectual property. California Management Review, 45(3), 33–58. https://doi.org/10.1177/0008125603045003
15) Crosier, K., & Pickton, D. (2003). Marketing intelligence and account planning: Insights from the experts. Marketing Intelligence & Planning, 21(7), 410–415. https://doi.org/10.1108/02634500310504241
16) Daabes, A. S., & Kharbat, F. F. (2017). Customer-based perceptual map as a marketing intelligence source. International Journal of Economics and Business Research, 13(4), 360–379. https://doi.org/10.1504/IJEBR.2017.084381
17) Das, S., Gupta, N., Kumar, V., & Yadav, R. K. (2025). Experiential marketing strategies in luxury restaurants: A Pythagorean fuzzy AHP approach. Indian Journal of Marketing, 55(11), 9–32. https://doi.org/10.17010/ijom/2025/v55/i11/175819
18) Evans, M. (1988). Marketing intelligence: Scanning the marketing environment. Marketing Intelligence & Planning, 6(3), 21–29. https://doi.org/10.1108/eb045773
19) Faryabi, M., Moradi, M., Yasrebdoost, H., & Moghadam, S. S. (2013). The effect of marketing Intelligence on customer loyalty. Vidyabharati International Interdisciplinary Research Journal, 34–45.
20) Gabus, A., & Fontela, E. (1972). World problems, an invitation to further thought within the framework of DEMATEL. Battelle Geneva Research Centre. https://www.scirp.org/reference/referencespapers?referenceid=3260217
21) Grand View Research. (2025). Artificial intelligence in marketing market. https://www.grandviewresearch.com/industry-analysis/artificial-intelligence-marketing-market-report
22) Guarda, T., Augusto, M. F., & Lopes, I. (2019). Geographic market intelligence as a competitive advantage. In 2019 14th Iberian Conference on Information Systems and Technologies (CISTI) (pp. 1–5). IEEE. https://doi.org/10.23919/CISTI.2019.8760856
23) Guenzi, P., & Troilo, G. (2007). The joint contribution of marketing and sales to the creation of superior customer value. Journal of Business Research, 60(2), 98–107. https://doi.org/10.1016/j.jbusres.2006.10.007
24) Habibi, A., Yusop, F. D., & Razak, R. A. (2020). The role of TPACK in affecting pre-service language teachers' ICT Integration during teaching practices: Indonesian context. Education and Information Technologies, 25, 1929–1949. https://doi.org/10.1007/s10639-019-10040-2
25) Hair, J. F., Black, W. C., Babin, R. E., & Anderson, R. E. (2009). Multivariate data analysis: A global perspective (7th ed.). Pearson Education. https://doi.org/10.1016/j.ijpharm.2011.02.019
26) Haverila, M., & Ashill, N. (2011). Market intelligence and NPD success: A study of technology intensive companies in Finland. Marketing Intelligence & Planning, 29(5), 556–576. https://doi.org/10.1108/02634501111153728
27) Helm, R., Krinner, S., & Endres, H. (2020). Exploring the role of product development capability for transforming marketing intelligence into firm performance. Journal of Business-to-Business Marketing, 27(1), 19–40. https://doi.org/10.1080/1051712X.2020.1713562
28) Hilal, M. I. (2019). Market orientation and innovation capabilities: Does it impact the performance of small businesses? Indian Journal of Marketing, 49(4), 37–47. https://doi.org/10.17010/ijom/2019/v49/i4/142975
29) Ivimey-Cook, R. B., & Proctor, M. C. (1967). Factor analysis of data from an East Devon heath: A comparison of principal component and rotated solutions. Journal of Ecology, 55(2), 405–413. https://doi.org/10.2307/2257885
30) Jain, M. K. (2025). The importance of market intelligence data. Dun & Bradstreet. https://www.dnb.co.in/blog/importance-of-market-intelligence-data/
31) Jamil, G. L. (2013). Approaching market intelligence concept through a case analysis: Continuous knowledge for marketing strategic management and its complementarity to competitive intelligence. Procedia Technology, 9, 463–472. https://doi.org/10.1016/j.protcy.2013.12.051
32) Jensen, J. A., Wakefield, L., Cobbs, J. B., & Turner, B. A. (2016). Forecasting sponsorship costs: Marketing intelligence in the athletic apparel industry. Marketing Intelligence & Planning, 34(2), 281–298. https://doi.org/10.1108/MIP-09-2014-0179
33) Johan, A., Isfianadewi, D., & Anwar, T. D. (2019). Sales force and intelligence strategic in SMES performance: Case study of Batik's enterprises in Bringharjo Yogyakarta. Journal of Business Studies and Management Review, 2(2), 128–136. https://online-journal.unja.ac.id/jbsmr/article/view/7222
34) Jolliffe, I. T., & Cadima, J. (2016). Principal component analysis: A review and recent developments. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 374(2065), 20150202. https://doi.org/10.1098/rsta.2015.0202
35) Kanwal, S., Samalia, H. V., & Singh, G. (2019). The role of marketing intelligence in brand positioning: Perspective of marketing professionals. In Brand culture and identity: Concepts, methodologies, tools, and applications (pp. 695–714). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-5225-7116-2.ch038
36) Kiani, M. N., Mustafa, S. H., & Ahmad, M. (2019). Does innovation capabilities affect the new service innovation success among Pakistani cellular companies? Asia Pacific Journal of Innovation and Entrepreneurship, 13(1), 2–16. https://doi.org/10.1108/APJIE-10-2018-0058
37) Kinson, C., Tang, X., Zuo, Z., & Qu, A. (2020). Longitudinal principal component analysis with an application to marketing data. Journal of Computational and Graphical Statistics, 29(2), 335–350. https://doi.org/10.1080/10618600.2019.1677244
38) Kuester, S., & Rauch, A. (2016). A job demands-resources perspective on salespersons' market intelligence activities in new product development. Journal of Personal Selling & Sales Management, 36(1), 19–39. https://doi.org/10.1080/08853134.2016.1142793
39) Kufile, O. T., Otokiti, B. O., Onifade, A. Y., Ogunwale, B., & Okolo, C. H. (2022). A framework for integrating social listening data into brand sentiment analytics. Journal of Frontiers in Multidisciplinary Research, 3(1), 393–402. https://doi.org/10.54660/.JFMR.2022.3.1.393-402
40) Kumar, V., & Mittal, S. (2020). Mobile marketing campaigns: Practices, challenges and opportunities. International Journal of Business Innovation and Research, 21(4), 523–539. https://doi.org/10.1504/IJBIR.2020.105996
41) Kusumawati, R. D., Oswari, T., Yusnitasari, T., Mittal, S., & Kumar, V. (2021). Impact of marketing-mix, culture and experience as moderator to purchase intention and purchase decision for online music product in Indonesia. International Journal of Business Innovation and Research, 25(4), 475–495. https://doi.org/10.1504/IJBIR.2021.117089
42) Labella, A., Liu, Y., Rodríguez, R. M., & Martínez, L. (2018). Analyzing the performance of classical consensus models in large scale group decision making: A comparative study. Applied Soft Computing, 67, 677–690. https://doi.org/10.1016/j.asoc.2017.05.045
43) Lackman, C., & Lanasa, J. M. (2013). Competitive intelligence and forecasting systems: Strategic marketing planning tool for SME's. Atlantic Marketing Journal, 2(2), Article no. 7. https://digitalcommons.kennesaw.edu/amj/vol2/iss2/7
44) Lackman, C., Saban, K., & Lanasa, J. (2000). The contribution of market intelligence to tactical and strategic business decisions. Marketing Intelligence & Planning, 18(1), 6–9. https://doi.org/10.1108/02634500010308530
45) Ledesma, R. D., Ferrando, P. J., Trógolo, M. A., Poó, F. M., Tosi, J. D., & Castro, C. (2021). Exploratory factor analysis in transportation research: Current practices and recommendations. Transportation Research Part F: Traffic Psychology and Behaviour, 78, 340–352. https://doi.org/10.1016/j.trf.2021.02.021
46) Lin, C.-J., & Wu, W.-W. (2008). A causal analytical method for group decision-making under fuzzy environment. Expert Systems with Applications, 34(1), 205–213. https://doi.org/10.1016/j.eswa.2006.08.012
47) MacPherson, A. (2000). The role of international design orientation and market intelligence in the export performance of US machine tool companies. R&D Management, 30(2), 167–176. https://doi.org/10.1111/1467-9310.00166
48) Makadok, R., & Barney, J. B. (2001). Strategic factor market intelligence: An application of information economics to strategy formulation and competitor intelligence. Management Science, 47(12), 1621–1638. https://doi.org/10.1287/mnsc.47.12.1621.10245
49) Mandal, P. C. (2018). Marketing information and marketing intelligence: Roles in generating customer insights. International Journal of Business Forecasting and Marketing Intelligence, 4(3), 311–321. https://doi.org/10.1504/IJBFMI.2018.092786
50) Masiello, B., Garofano, A., Izzo, F., & Bonetti, E. (2024). Inclusive marketing and disability: Value creation strategies for organisations and society in the toy industry. Journal of Marketing Management, 40(9–10), 851–876. https://doi.org/10.1080/0267257X.2024.2380252
51) Mathur, S., Vishnoi, S. K., Bagga, T., Mittal, A., & Mittal, A. (2024). Examining the impact of argument quality and source credibility on consumers' behavioral intention toward green cosmetics: The moderating role of perceived innovativeness. Prabandhan: Indian Journal of Management, 17(3), 26–47. https://doi.org/10.17010/pijom/2024/v17i3/173364
52) McKinsey & Company. (2023). What is personalization? https://www.mckinsey.com/featured-insights/mckinsey-explainers/what-is-personalization
53) Mikalef, P., Pateli, A., & van de Wetering, R. (2021). IT architecture flexibility and IT governance decentralisation as drivers of IT-enabled dynamic capabilities and competitive performance: The moderating effect of the external environment. European Journal of Information Systems, 30(5), 512–540. https://doi.org/10.1080/0960085X.2020.1808541
54) Mittal, S., & Kumar, V. (2020). A framework for ethical mobile marketing. International Journal of Technoethics (IJT), 11(1), 28–42. https://doi.org/10.4018/IJT.2020010103
55) Mittal, S., & Kumar, V. (2022). A strategic framework for non-intrusive mobile marketing campaigns. International Journal of Electronic Marketing and Retailing, 13(2), 190–205. https://doi.org/10.1504/IJEMR.2022.121819
56) Mochtar, K., & Arditi, D. (2001). Role of marketing intelligence in making pricing policy in construction. Journal of Management in Engineering, 17(3), 140–148. https://doi.org/10.1061/(ASCE)0742-597X(2001)17:3(140)
57) Moher, D., Liberati, A., Tetzlaff, J., & Altman, D. G. (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), Article ID e1000097. https://doi.org/10.1371/journal.pmed.1000097
58) Novicevic, M. M., Harvey, M., Autry, C. W., & Bond, E. U. (2004). Dual-perspective SWOT: A synthesis of marketing intelligence and planning. Marketing Intelligence & Planning, 22(1), 84–94. https://doi.org/10.1108/02634500410516931
59) Oktara, S., & Erdoǧan, E. (2012). Integrating decision-making and marketing intelligence: The roadmap to the boardroom. In Market research best practice: 30 visions for the future. John Wiley & Sons. https://doi.org/10.1002/9781119208815.ch4
60) Opricovic, S., & Tzeng, G.-H. (2003). Defuzzification within a multicriteria decision model. International Journal of Uncertainty. Fuzziness and Knowledge-Based Systems, 11(5), 635–652. https://doi.org/10.1142/S0218488503002387
61) Öztürk, S., Okumuş, A., & Mutlu, F. (2012). Segmentation based on sources of marketing intelligence, marketing intelligence quotient and business characteristics in software industry. İstanbul Üniversitesi İşletme Fakültesi Dergisi, 41(2), 227–240. https://izlik.org/JA79XA84TT
62) Page, M. J., McKenzie, J. E., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S.,...Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. The BMJ, 372, n71. https://doi.org/10.1136/bmj.n71
63) Pahari, S., Ghosal, I., Prasad, B., & Dildar, S. M. (2023). Which determinants impact consumer purchase behavior toward online purchasing of organic food products? Prabandhan: Indian Journal of Management, 16(1), 25–41. https://doi.org/10.17010/pijom/2023/v16i1/172667
64) Piercy, N. F., & Lane, N. (2005). Strategic imperatives for transformation in the conventional sales organization. Journal of Change Management, 5(3), 249–266. https://doi.org/10.1080/14697010500175094
65) Rahchamani, A., Ashtiani, B. R., & Vahedi, M. A. (2019). The impact of marketing intelligence and business intelligence on acquiring competitive advantages. Revista Gestão & Tecnologia, 19(5), 52–70. https://doi.org/10.20397/2177-6652/2019.v19i5.1794
66) Sadrabadi, N. R., Moinzad, H., & Keramati, M. A. (2025). Designing a dynamic supply chain behavior prediction model for urban electronic services (case study: Historic District Municipality of Yazd). Interdisciplinary Studies of Iranian Architecture, 4(7), 113–139. https://doi.org/10.22133/isia.2025.493694.1133
67) Salesforce. (n.d.). Marketing intelligence: A comprehensive guide. https://www.salesforce.com/marketing/analytics/what-is-marketing-intelligence/
68) Schreiber, J. B. (2021). Issues and recommendations for exploratory factor analysis and principal component analysis. Research in Social and Administrative Pharmacy, 17(5), 1004–1011. https://doi.org/10.1016/j.sapharm.2020.07.027
69) Setyani, R., & Rivai, A. R. (2025). The effect of CRM and price perception on loyalty with satisfaction as a mediation variable (a study on deposit customers of PT. BPR BKK Blora (Perseroda). Indonesian Interdisciplinary Journal of Sharia Economics, 8(3), 13487–13500. https://doi.org/10.31538/iijse.v8i3.8249
70) Sewpersadh, N. S. (2023). Disruptive business value models in the digital era. Journal of Innovation and Entrepreneurship, 12(1), Article no. 2. https://doi.org/10.1186/s13731-022-00252-1
71) Sharma, M., Gupta, P., & Joshi, S. (2025). Strengthening sustainable food systems through agri-tech startups: A fuzzy DEMATEL analysis of critical success factors. Frontiers in Sustainable Food Systems, 9. https://doi.org/10.3389/fsufs.2025.1621741
72) Trainor, K. J., Krush, M. T., & Agnihotri, R. (2013). Effects of relational proclivity and marketing intelligence on new product development. Marketing Intelligence & Planning, 31(7), 788–806. https://doi.org/10.1108/MIP-02-2013-0028
73) Trim, P. (2007). A strategic marketing intelligence framework reinforced by corporate intelligence. In M. Xu (ed.), Managing strategic intelligence: Techniques and technologies (pp. 55–68). IGI Global Scientific Publishing. https://doi.org/10.4018/978-1-59904-243-5.ch004
74) Tripathi, A., Bagga, T., & Aggarwal, R. K. (2020). Strategic impact of business intelligence: A review of literature. Prabandhan: Indian Journal of Management, 13(3), 35–48. https://doi.org/10.17010/pijom/2020/v13i3/151175
75) Venter, P., & van Rensburg, M. J. (2014). The relationship between marketing intelligence and strategic marketing. South African Journal of Economic and Management Sciences, 17(4), 1–15. https://hdl.handle.net/10520/EJC157806
76) Vishnoi, S. K., Mathur, S., & Sharma, S. (2026). Marketing intelligence for intelligent marketing: A comprehensive definition and framework. Journal of Advances in Management Research, 23(1), 121–147. https://doi.org/10.1108/JAMR-02-2024-0040
77) Vorhies, D. W., & Morgan, N. A. (2005). Benchmarking marketing capabilities for sustainable competitive advantage. Journal of Marketing, 69(1), 80–94. https://doi.org/10.1509/jmkg.69.1.80.55505
78) Wee, T. T. (2001). The use of marketing research and intelligence in strategic planning: Key issues and future trends. Marketing Intelligence & Planning, 19(4), 245–253. https://doi.org/10.1108/EUM0000000005555
79) Wu, W.-W., & Lee, Y.-T. (2007). Developing global managers' competencies using the fuzzy DEMATEL method. Expert Systems with Applications, 32(2), 499–507. https://doi.org/10.1016/j.eswa.2005.12.005
80) Xu, X.-Z., & Kaye, G. R. (1995). Building market intelligence systems for environment scanning. Logistics Information Management, 8(2), 22–29. https://doi.org/10.1108/09576059510084975
81) Yuan, Y., Xu, Z., & Zhang, Y. (2022). The DEMATEL–COPRAS hybrid method under probabilistic linguistic environment and its application in third party logistics provider selection. Fuzzy Optimization and Decision Making, 21(1), 137–156. https://doi.org/10.1007/s10700-021-09358-9
82) Zadeh, L. A. (1965). Fuzzy sets. Information and Control, 8(3), 338–353. https://doi.org/10.1016/S0019-9958(65)90241-X