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How important are behavioral analytics tools in the age of modern digital marketing?

Author

Listed:
  • Marian Olinski

    (University of Warmia and Mazury in Olsztyn)

  • Kacper Siecinski

    (University of Warmia and Mazury in Olsztyn)

  • Kuanchin Chen

    (Western Michigan University)

Abstract

This study evaluates how behavioral analytics tools contribute to short-term business objectives in digital marketing. We analyze 73 case studies from 12 brands collected on October 3, 2023, using content analysis to extract tools, outcomes, and problems addressed. Expert weighting from three senior scholars is applied to value outcome categories, with moderate agreement reported by Kendall’s W = 0.47. We then compute aggregate tool evaluations, build a co-occurrence matrix, and estimate linear and multiple regressions together with Pearson correlations. Synergies with top-rated tools are strongly associated with more outcomes achieved, the total result increases by 2.8295 for each additional co-occurrence, with R2 = 0.936, and the largest effect appears for conversion and site optimization. Tool ratings are highly correlated with the number of problems solved, r = 0.9888. Effectiveness in solving UX and optimization issues is strongly associated with gains in satisfaction and loyalty, r = 0.9646, with a positive regression coefficient for this category. Session recordings, heatmaps, A/B testing, and conversion funnels emerge as the most impactful instruments. We propose a six-category framework and provide practical guidance for integrating complementary tools within iterative, data-driven workflows. Results underline the strategic role of behavioral analytics in improving conversion, satisfaction, and short-term performance.

Suggested Citation

  • Marian Olinski & Kacper Siecinski & Kuanchin Chen, 2026. "How important are behavioral analytics tools in the age of modern digital marketing?," E&M Economics and Management, Technical University of Liberec, Faculty of Economics, vol. 29(1), pages 183-206, March.
  • Handle: RePEc:bbl:journl:v:29:y:2026:i:1:p:183-206
    DOI: 10.15240/tul/001/2026-1-012
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    JEL classification:

    • D80 - Microeconomics - - Information, Knowledge, and Uncertainty - - - General
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software

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