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Why Better Analytics Improves Marketing Performance

Marketing teams succeed or fail based on their ability to assess the needs of their customers. Doing that in an increasingly data-driven environment requires better tools for marketing analysis. Unfortunately for demand generation and marketing analysts, much of that data about their campaigns is hard to access and needs to be manipulated manually. Marketing tech stacks are typically made up of many loosely connected applications that make it difficult to work with information across sources. When data can be gathered and parsed, the story it often tells is not clear, recent or accurate enough to guide planning. What marketers are really after is clarity around the performance of their programs and the value of their spend. But by 2024, one-half of marketing organizations will lack the competencies and skills to utilize available data and analytics, leading to low confidence in delivering fact-based insights. Answering those core questions about performance and value require a rethink of how analysts and operations teams access and work with information, including an assessment of the tools in use.

Marketers are not data scientists. They don’t have deep expertise in predictive or statistical analysis, nor in the nuances of integrating and cleansing data from multiple systems. They are experts at using data insights to make decisions about where to put resources and how to approach customer segments. So organizations face a dilemma—how do they provide marketing teams with the necessary information to make decisions and measure results, without making that information hard to extract and manage that the process is counterproductive?


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About the Author


Keith Dawson

VP and Research Director
Ventana Research

Keith Dawson is responsible for Customer Experience (CX) research, covering technology that facilitates engagement to optimize customer-facing processes. His focus areas include agent management, contact center and voice of the customer, along with technology in marketing, sales, field service and applications such as digital commerce and subscription management. Keith’s specialization is in natural language speech tools and the wide array of customer analytics.