The method of adapting digital marketing strategies to the enterprise’s business architecture: an empirical analysis

Abstract

Abstract. The purpose of the study is to develop and test an analytical model for evaluating the effectiveness of personalized digital solutions in marketing, taking into account the structural parameters of the company that determine the logic of creating and monetizing value for the client. The starting point is that one-size-fits-all approaches to campaign planning and funnels often provide short-term improvements in individual indicators, but do not generate sustainable growth due to the mismatch between typical channel settings and the actual configuration of segments, the deal cycle, product margins, the role of repeat purchases and operational constraints in the service. Research methods include metric-oriented comparative analysis “before/after”, case analysis without disclosure of company names, normalization of indicators into comparable time windows and interpretation of changes at the level of causal-logical chains “decision → behavioural effect → financial result”. To test the performance, a system of growth indicators was used, which includes conversion at the stages of the funnel, customer acquisition cost (CAC), customer lifetime value (LTV), LTV/CAC ratio, return on marketing spend (ROI/ROAS), repeat purchase frequency, average revenue per user and duration of the deal cycle. The results of the empirical comparison showed that personalized configurations aligned with the parameters of the company showed more sustainable shifts in key metrics compared to standard schemes: in cases with a long decision cycle, the share of qualified leads increased and CAC variability decreased under constant budgets, and in models with a high share of repeat sales, LTV and revenue per user increased due to more accurate segmentation of the offer and scenarios maintenance It is additionally substantiated that the brand strategy performs the role of a framework level of alignment of personalization: it sets the invariants of the value proposition, tonality and content rules, which reduces the risk of “optimization for the metric” at the cost of trust and retention, and its “art” is interpreted as a controlled design of brand meanings and differences with verifiable consequences for repeated interactions and LTV. The conclusions confirm the practical value of the proposed model as a decision management tool, which allows to record the measurable contribution of personalization to the results and to compare the effectiveness of alternative configurations according to a single set of business metrics.