Integrate Data and Analytics for Marketing Efficiency

Marketers depend on analytics to make crucial decisions at all stages of the marketing lifecycle. Analytics become even more important in the age of marketing automation where the system triggers events by itself based on the defined parameters.

Conducting analytics requires gathering data on leads and prospects. Many marketers gather data first and worry about analytics later. This is a fallacy. For success, data gathering and data analysis has to go hand in hand.

In fact, data gathering has to be preceded by a framework for analytics. Marketers need to have a clear-cut idea on what to measure, and the information or insight required. The data collection exercise then needs to ensure collecting relevant information required for such analytics. Success requires a continuous and ongoing process rather than a one-time effort, for the marketer would need to fine-tune both the analytic engine, and the data collection process. Gathering large quantity of data is useless and a waste of resources unless such data is relevant.

Also, the data collected has to be put in context when applying it for analytics. This will allow marketers to factor in the situation or market situation when acting on the results of the analytics. For instance, a sports good manufacturer enjoying an extraordinarily high success in generating leads out of its marketing campaigns, may need to consider other factors – timing the campaign during a World Cup tournament or popularity of its brand ambassador. The marketer applying the results of such analytics for all times may not be able to live up to these expectations.

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