analytics og datadrevet markedsføring

/əˈnælɪtɪks ɔː dɑːtəˈdrɪvən ˈmɑːrkɪtsfɪərɪŋ/
Englishmarketingdata analysisbusiness strategydigital marketing+1 til

Definisjon

Praksisen med å bruke dataanalyse og måleparametere for å styre og optimalisere markedsføringsstrategier og kampanjer.

Synonymer3

data-driven marketingmarketing analyticsdata analysis in marketing

Antonymer3

intuition-based marketingtraditional marketingnon-data-driven marketing

Eksempler på bruk1

1

Companies increasingly rely on analytics og datadrevet markedsføring to improve customer targeting; Effective analytics og datadrevet markedsføring can significantly boost ROI; The rise of big data has transformed analytics og datadrevet markedsføring practices.

Etymologi og opprinnelse

Derived from the Greek word 'analytikos' meaning 'skilled in analysis' combined with 'data-driven' referring to decisions based on data, and 'marketing' from the Old English 'market' meaning a place for trade.

Relasjonsmatrise

Utforsk forbindelser og sammenhenger

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"ABC-Analyse (Strategic Method of Inventory Management)"

is a tool for

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Utforsk relasjon

Account executive

An Account Executive (AE) in marketing and business serves as the primary liaison between clients and the internal teams responsible for campaign execution. In the context of analytics and data-driven marketing, the AE leverages data insights to tailor client communications, set realistic expectations, and propose strategies grounded in measurable outcomes. Specifically, the AE uses analytics reports to demonstrate campaign performance, identify opportunities for optimization, and justify budget allocations. This data-driven approach enables the AE to build trust with clients by providing transparent, evidence-based recommendations rather than relying solely on intuition or generic promises. Furthermore, by understanding analytics, the AE can translate complex data into actionable business insights for clients, facilitating strategic decisions that align with digital marketing goals. This integration of analytics into the AE’s workflow enhances client retention and campaign effectiveness by ensuring that marketing initiatives are continuously refined based on real-time performance metrics.

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Ad creative

Ad creative and analytics og datadrevet markedsføring (analytics and data-driven marketing) are intrinsically linked through a continuous feedback loop that optimizes marketing effectiveness. Specifically, ad creatives—such as visuals, copy, and formats—are developed and deployed as hypotheses to engage target audiences. Analytics then measure how these creatives perform across key metrics like click-through rates, conversion rates, and engagement levels. By systematically collecting and analyzing this performance data, marketers can identify which creative elements resonate best with different audience segments. This insight enables iterative refinement of ad creatives, ensuring that future campaigns are more precisely tailored to audience preferences and behaviors. Furthermore, data-driven marketing frameworks use analytics to segment audiences, personalize creatives, and allocate budget dynamically based on real-time performance, thereby maximizing ROI. Without analytics, ad creative decisions would rely on intuition rather than evidence, reducing efficiency. Conversely, without compelling ad creatives, analytics have no meaningful content to evaluate. Thus, the relationship is a practical, operational cycle where data informs creative development, and creative outputs generate data for analysis, driving continuous improvement in marketing strategy and business outcomes.

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a/b-test

is a tool for

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Ad copy

Ad copy serves as the primary messaging vehicle that directly communicates value propositions, calls to action, and brand identity to target audiences. Analytics and datadrevet markedsføring (data-driven marketing) provide the empirical framework to measure, optimize, and tailor this messaging based on real user behavior and performance metrics. Specifically, analytics track how different versions of ad copy perform across channels—click-through rates, conversion rates, engagement metrics—and feed this data back into iterative testing processes such as A/B or multivariate testing. This continuous feedback loop enables marketers to refine ad copy for maximum relevance and impact, ensuring that messaging resonates with specific audience segments identified through data analysis. Furthermore, data-driven marketing leverages customer insights and segmentation derived from analytics to personalize ad copy dynamically, increasing the effectiveness of campaigns by aligning messaging with user intent, preferences, and lifecycle stage. Without analytics, ad copy optimization would rely on guesswork; conversely, analytics without actionable ad copy insights would fail to translate data into tangible marketing outcomes. Thus, the relationship is symbiotic: analytics quantify and qualify the performance of ad copy, while ad copy acts as the execution point where data-driven insights manifest in market-facing communication.

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Ad creative testing

Ad creative testing involves systematically experimenting with different versions of advertisements—such as variations in visuals, copy, calls-to-action, or formats—to identify which elements drive the best performance. Analytics and datadrevet markedsføring (data-driven marketing) provide the measurement framework and data infrastructure necessary to capture, analyze, and interpret performance metrics from these tests. Specifically, analytics tools collect granular data on user interactions, engagement rates, conversion metrics, and audience segments exposed to each creative variant. This data-driven insight enables marketers to make evidence-based decisions about which creative elements resonate most effectively with target audiences, optimize budget allocation, and refine campaign strategies in real time. Without robust analytics, ad creative testing would lack objective criteria for success and fail to translate experimental results into actionable marketing improvements. Conversely, data-driven marketing relies on continuous creative testing to generate the data inputs that fuel optimization algorithms and predictive models. Thus, ad creative testing and analytics-driven marketing form a feedback loop where testing generates data, analytics interprets it, and insights guide subsequent creative iterations, enhancing overall campaign effectiveness and ROI.

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Utforsk relasjon

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