Account based marketing (ABM)vslookalike audience

Account Based Marketing (ABM) targets specific high-value accounts with personalized campaigns, focusing on known entities within a B2B context. Lookalike audiences, commonly used in digital advertising platforms, enable marketers to expand reach by identifying new prospects who share similar attributes and behaviors with an existing set of target accounts or contacts. The practical connection lies in using lookalike audience modeling to scale ABM efforts beyond the initial set of target accounts. By feeding a list of known target accounts or high-value customers into a platform’s lookalike algorithm, marketers can discover and engage with new companies or decision-makers that resemble their ideal accounts in firmographic, technographic, or behavioral dimensions. This approach enhances ABM by combining its precision targeting with the scalability of data-driven prospecting, allowing marketers to maintain account-level relevance while efficiently growing their pipeline. Essentially, lookalike audiences operationalize the expansion phase of ABM campaigns by systematically identifying 'next best' accounts that mirror the characteristics of the core ABM targets, thereby increasing the effectiveness and reach of personalized marketing efforts.