Marketing Analytics 101 5 Challenge

Marketing Analytics 101: 17 Challenges and How to Solve Them

In the first part of this blog series, we talked about what is marketing analytics and how can marketers use it. This second part deep dives into some common challenges and how to solve them.



Subhadeep_bhatachrjee Subhadeep Bhattacharjee Linkedin Logo

Date Published: 4th Apr 2023

19 min read


Subhadeep Bhattacharjee
Content Writer
Subhadeep Bhattacharjee is a content writer who follows the world of technology and business. With a passion for both cutting-edge tech and the fascinating world of business, he is on a mission to explore the intersection of these two worlds and share his opinion. When not poring over the latest advancements in AI, marketing automation, and cybersecurity, he is following cricketing action from around the world.

Ready to get started?

Increase your marketing ROI by 30% with custom dashboards & reports that present a clear picture of marketing effectiveness

Start Free Trial

Experience Premium Marketing Analytics At Budget-Friendly Pricing.


Learn how you can accurately measure return on marketing investment.

Additional Resources

Frequently Asked Questions

Data quality and hygiene are crucial in marketing analytics as poor data can lead to misleading interpretations and incorrect decision-making. By focusing on data hygiene, which involves cleansing raw data to ensure consistency, accuracy, and freedom from errors, businesses can avoid misleading insights. Eliminating duplicate entries, incomplete data, and outdated information is essential for maintaining data quality.

Data quantity plays a vital role in marketing analytics because it provides a clearer understanding of campaign performance and customer sentiment. Insufficient data can hinder accurate analysis and insights. However, an excessive volume of data from multiple sources, without proper quality standards, can lead to flawed interpretations. To address this challenge, it is crucial to standardize data from various sources before conducting analysis.

The absence of a skilled in-house analytics team can impede effective marketing analytics and result in inaccurate interpretations. Small and medium businesses often face challenges in finding the right people for data analysis. However, this challenge can be overcome by leveraging marketing analytics software, which can compensate for the lack of skilled personnel and provide accurate insights.

Data consolidation and integration pose significant hurdles in marketing analytics. With businesses interacting with customers across multiple platforms, data collected from different sources needs to be cleansed and integrated. Marketing analytics software can assist in overcoming this challenge by offering solutions for data consolidation and integration, ensuring a seamless flow of information for accurate analysis.

Selecting the right attribution model is crucial for businesses in order to identify the most effective marketing channels. With various attribution models available, businesses often need to experiment to determine which one works best for their specific needs. Many marketing analytics software options include built-in attribution models, simplifying the process of selecting the most suitable model for accurate data analysis and decision-making.

Your Gen-AI Marketing Data Assistant is Here—DiGGi-GPT. Get Access Today!