An In-Depth Description of Marketing Analytics
Martech Outlook | Wednesday, January 11, 2023
Marketing analytics comes with both advantages and disadvantages. Its advantages include the understanding of audiences, making organizations marketing cause-and-effect-driven, and helping to make campaigns more effective. Along with it, its disadvantages consist of having indifferences to data, and analyzing and understanding data becomes essential.
FREMONT, CA: Both marketers and consumers benefit from marketing analytics. By understanding what drives conversions, brand awareness, or both, marketers can increase their marketing ROI. In addition, analytics ensures that consumers see targeted, personalized ads that speak directly to their needs and interests rather than mass communications.
Analyzing marketing data in organizations: Data from marketing analytics helps businesses to make decisions about everything from ad spending to product updates. Data from multiple sources (online and offline) is essential to get a 360-degree view of the campaigns and to make the right decisions. Various teams can gain insights into the following by using this data:
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Intelligence about products: Taking a deep dive into a brand's products and analyzing how these products stack up in the marketplace is part of product intelligence. By speaking with consumers, polling target audiences, or engaging them in surveys, organizations can better understand their products' differentiators and competitive advantages. Then, teams can better align products to consumer interests and problems to drive conversions.
Trends and preferences of customers: Organizations can learn a lot about their consumers from analytics. What kind of messaging/creative resonates with them? In the past, what products did they research and buy? What ads are converting and which aren't?
Trends in product development: Analytics can also provide insight into the types of features consumers want from a product. Product development can use this information for future iterations.
The following are some of the biggest challenges facing marketing analytics today:
Quantity of data: Using big data, marketing teams can track every consumer click, impression, and view in the digital age. The quantity of data, however, is irrelevant if it cannot be structured and analyzed to provide insights for campaign optimization. As a result, marketers are struggling to organize data to evaluate its meaning. Rather than analyzing data, data scientists spend most of their time wrangling and formatting it.
Quality of data: In addition to the vast amount of information organizations must sift through, there is a tendency to view this data as unreliable. Forrester estimates that 21 percent of media budgets were wasted due to inferior data quality. One dollar out of every five dollars was not being utilized effectively. For midsize and enterprise-level firms, these dollars can add up to $1.2 million and $16.5 million of wasted budget per year. In order for employees to make informed decisions, organizations need a process to maintain the quality of data.
There is a shortage of data scientists: Most companies lack access to the right people, even if they have access to the right data.
Attribution Model Selection: Choosing the right model can be challenging. As an example, media mix modeling and multi-touch attribution provide entirely different insights - aggregate campaign-focused data and consumer-level data, respectively. Marketers' choice of models will determine the type of insights they receive. When it comes to selecting the right engagement model, so many channels can create confusion.
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