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Analytics as applied to marketing strategy is a broad topic with many applications. Using analytics involves using mathematical algorithms to process data. The massive amount of accessible data available from the internet has revolutionized the amount of information we have access to, and created a demand for finding ways to use this data beneficially. Due to technological developments, such as greater storage capacity and faster processing speeds, software platforms have been and are being developed to utilize this “big data”.
In simple terms, analytics is about finding and analyzing data in order to understand it in a way that is relevant to your specific goals. This is done by finding patterns through correlating data and examining variables through the use of algorithms to determine “who, what and why” questions.
Various forms of analytics are relevant to marketers. These include predictive analytics (predicting future behavior), content analytics (to measure and analyze your content), descriptive statistics (summarize and describe data), and contextual data (prioritization, personalization, lead scoring), amongst others.
The many practical applications of analyzing data include measuring the quality of your campaigns, discovering and predicting trends and relationships, finding your best course of action based on possibilities and outcomes, testing your ideas by creating scenarios to determine possible outcomes, or gaining a better understanding of your customers. In short, analytics is automated reasoning, leading to greater knowledge and discovery, which leads to a more efficient marketing practice.
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