According to Gartner research, more than half of marketing leaders believe that despite the wealth of data available in the marketing department, analytics practices are often inadequate, resources are not being used to their full potential, and results are unsatisfactory. This is partly due to the sheer volume of data coming in from numerous platforms and the time-consuming manual consolidation of data, which results in insights that are several weeks old by the time they are actionable.
However, effective data analysis can address these issues by reducing human error, speeding up time-to-insight, and providing a comprehensive view of the customer, which can greatly enhance decision-making for the entire company. To achieve this level of success, CMOs need to be aware of five key factors regarding the current state of data analytics. This will enable them to improve their marketing operations and keep up with the latest trends.
1.Data centralization is key for efficient data analytics
In modern marketing, teams use a range of CMS and CRM tools, marketing automation platforms, lead enrichment services, and social media platforms like Twitter, LinkedIn, and Facebook for both organic and paid campaigns.
While these tools can be used independently for campaign management, data organization, and reporting, they can be even more powerful when integrated together. By consolidating data from these unrelated systems into a central location, marketers can gain a 360-degree view of their customers. This enables them to identify and address issues promptly before they have a significant impact on the business.
2. Move beyond the surface-level understanding to have a comprehensive view of the data
A comprehensive view enables marketers to identify previously undiscovered patterns and trends, and quickly identify newer ways to engage with their customer base.
Many organizations use a variety of marketing tools that were implemented with a specific purpose in mind. However, as these tools become integrated into the technology mix, users tend to focus more on what they can accomplish with the tools rather than why they were implemented in the first place. By centralizing data sources, marketers can once again ask more broad, overarching questions and gain a more holistic view of their marketing data.
3. Access to centralized data allows marketing teams to gain a deeper understanding of their performance
Access to centralized data allows marketing teams to gain a deeper understanding of their key performance indicators (KPIs) and generate more detailed reports. This is a common practice in marketing where teams regularly set KPIs and report on them. By consolidating all marketing data into one place, marketers can analyze their KPIs in greater depth and produce more comprehensive reports.
Gaining a deeper comprehension of metrics such as return on investment (ROI) analysis can lead to enhanced performance. Marketers can determine which advertising channels are producing the most leads with the lowest cost of acquisition by consolidating data from all channels. They can then allocate additional resources to the most effective channel. Attribution analysis is another area that benefits from centralized data. It is essential to know which customer acquisition method is the most effective and recognize it. By utilizing different attribution models, marketers can gain insight into customer interactions when they make a purchase.
These two metrics can also help map the customer journey and provide more insights. With more data, marketers can gain a better understanding of how a customer progresses from being unaware of their brand to becoming a customer and even a brand champion. They can analyze the customer journey, find ways to speed up the sales cycle, and recognize the warning signs of customer churn.
4. Making data-driven decisions through a modern data stack
Making data central to marketing analysis creates a culture that values data, allowing employees and stakeholders to easily access critical information and participate in strategic discussions regarding marketing expenditures and wider company initiatives.
5. Human error and manual processes are the root causes of all typical data analysis mistakes
Although creativity and emotional connections are essential for developing customer relationships, they may result in inaccuracies when analyzing data. To minimize this risk and free up valuable analysis time, marketers can adopt various strategies to eliminate manual processes that hinder productivity.
Ultimately, centralizing data creates a culture that values data and enables employees and stakeholders to easily access critical information, participate in strategic discussions, and minimize the risk of human error and manual processes in data analysis.
(The author is Viswanath C, Sr. Director of Engineering, Fivetran India, and the views expressed in this article are his own)