Intuitive and effective Marketing strategies are vital to an organization’s success. Devising these strategies requires dynamic cross-functional teams and intuitive tools and products. The tools and technologies used by the different teams comprise the Marketing Technology Stack. The modular nature of this stack allows Marketers to shift to new & robust tools and technologies. Additionally, it also helps simplify the process of unifying data and acquiring informative insights from customers. With ubiquitous options available, Marketers find it difficult to choose the right tool for the right use case.
This led to the emergence of a Modern Marketing Analytics Stack. This Stack encompasses all the latest technologies that Marketers can leverage to augment and optimize their Marketing operations throughout the customer lifecycle. Compared to the Old Marketing Analytics Stack, the Modern Marketing Analytics Stack can help Marketers bring in more leads, gather valuable & actionable insights, and boost revenue. Hence, it’s imperative for Marketers to learn about this valuable framework.
In this article, you will get an in-depth understanding of the Modern Marketing Analytics Stack and how organizations can incorporate it into their Marketing activities. It’ll also provide an in-depth comparison of the Old and Modern Marketing Analytics Stack, along with some of the challenges you might encounter while switching to/adopting the Modern Stack. Finally, this article will provide you with a birds-eye view of what a true Modern Marketing Analytics Stack looks like. Excited to learn more about this topic in detail? Before we get into the details, watch this video to get a gist of our detailed course on Introduction to Modern Marketing Analytics Stack.
P.S. This course is a part of our Marketing Analytics Masterclass curated by Global Marketing Leaders. Click here to register for this Masterclass to upgrade your Marketing skills and learn how to build the Modern Marketing Analytics Stack for your organization.
Table of Contents
Traditional vs Modern Marketing Analytics Stack
The way a Modern Marketing Analytics Stack operates is significantly different from the traditional approach. The Traditional Marketing Stack relies on a procedural approach. It requires Marketers & Engineers to build everything from the ground up & manually integrate them, thereby making their tasks challenging & tedious. The Modern Marketing Analytics Stack was designed to overcome these problems and is more dynamic & flexible for both the customers and Marketers.
Setting up a Traditional Marketing Analytics Stack requires immense engineering & infrastructural bandwidth. Following a procedural approach requires Data Engineers to build their Data Pipeline for each data source & destination from the ground up. Hence, preventing them from gathering & analyzing actionable customer insights.
A Modern Marketing Analytics Stack helps tackle the challenges posed by the Traditional Stack seamlessly. It houses a highly scalable infrastructure ecosystem that encompasses new & intuitive tools and technologies. Further, It helps significantly reduce the development and maintenance efforts of Data Engineers.
Overview of Marketing Tools
https://usersnap.com/blog/digital-marketing-tools-agency/
In today’s data-driven world, numerous intuitive Marketing tools are available in the market. Each of them has the common goal of assisting Marketers in gathering valuable customer insights and boosting performance. They are divided into several categories such as Advertising Tools, SEO (Search Engine Optimization) Tools, Customer Interaction Tools, Analytical Tools (etc).
It is essential to have an in-depth understanding of these tools and your Marketing Analytics Stack as it allows Marketing & various other teams across an organization to keep track of and gain holistic insights into their campaigns & product’s performance and at the same time improves the relationships between customers and employees. These tools are part of the Modern Marketing Analytics Stack and are becoming ubiquitous in the market today.
According to Chiefmartec.com, the Marketing Technology Stack saw a growth of 5233% growth since 2011. In 2020, the Marketing Technology Landscape saw a growth of 13.6% and a total of 8000 solutions for each type of Marketing data. This emphasizes the importance of having a proper Modern Marketing Analytics Stack set up to help Marketers decide which tools they need to use to promote their products.
https://chiefmartec.com/2020/04/marketing-technology-landscape-2020-martech-5000/
The Need to Adopt Data Culture
Data Engineers play a crucial role in developing the Modern Marketing Analytics Stack. This is because they optimize the Modern Marketing Stack by following 3 main Strategies:
- Eliminate Black Box Strategies: This is an important strategy because Data Engineers must make the Marketing Stack simple and concise so that it can be understood by all types of audiences. The Marketing Stack must be designed such that both technical and non-technical users can understand it.
- Bridge the Gap between Data Engineering and the Business: This ensures that processes executed by Data Engineers align with the business goals of the organization. Subsequently, this enhances the collaboration between the Data and Sales teams.
- Bring Data into a Decision-Making Process: Data isn’t just a technology solution. By having a proper understanding of data, organizations can make better strategic decisions as there will be a constant collaboration between all the teams.
In Modern-day Marketing, Data Culture is a new term coined to help Business and Data teams leverage their Analytics Stack in tandem. Data Culture is the process by which decisions are made strategically and the entire Marketing Stack is automated to meet the needs of every user. Adopting a Data Culture approach ensures that the Business and Data teams work together systematically and understand each other’s needs.
Challenges with the Old Marketing Stack
Now that you have an in-depth understanding of how the Modern Marketing Analytics Stack operates, in this section, you will come across some of the most significant challenges a Traditional Marketing Analytics Stack poses/ brings forth.
Due to a significant increase in the number of data sources and the variations of data used, the procedural approach of the Old Marketing Stack has become obsolete. A majority of these tools are not able to handle the excessive data payloads and hence result in and thereby provide incorrect & inconsistent insights to Marketers and other teams across organizations.
The main challenges associated with the Old Marketing Analytics Stack are as follows:
1) Formation of Data Silos
A Data Silo represents a repository of data that can be accessed only by one department of an organization but not by others. One of the main issues with Data Silos is the lack of transparency, efficiency, and trust that it brings to an organization.
2) Dependency on 3rd Party Applications
The Old Marketing Analytics Stack relies on numerous 3rd party applications to unify data from various complex data sources, transform it, and load it into the desired destination. Hence, it’s not scalable and robust enough to meet the modern-day ETL and data requirements.
3) The Rigidity of Marketing Data
Marketing data is very rigid because it dislikes any changes made to it. To reduce the Rigidity of the Marketing data, a dynamic and flexible Analytics Stack must be designed to cater to different types of data, which the Old Marketing Stack does not possess.
4) Inconsistent Customer Journey & Interactions
Customers do not get a unified journey when they use the product/service of an organization that uses the Old Marketing Analytics Stack because it reduces the interaction between the Business and Data teams which leads to not understanding the customers’ needs.
5) Slow Feedback Loop
Maintaining a Traditional Marketing Analytics Stack can be a gruesome process and often requires an immense amount of time investment. These maintainability issues result in a Slow Feedback Loop, leading to an insufficient number of customer and product insights gained & analyzed.
Implementing a Modern Marketing Analytics Stack
Any organization can implement a Modern Marketing Analytics Stack by unifying & integrating data from numerous data sources into a Data Warehouse by leveraging a robust Data Pipeline. Once that is done, the Analytics Schema can be developed by the Data team to clean and transform the data, thereby making it analysis-ready.
Analytics Schemas are created by writing multiple SQL (Structured Query Language) queries. Some of these schemas are visualized using different BI (Business Intelligence) tools helping both the Business and Data teams gather holistic insights from the unified data.
Finally, this whole framework is combined with a CDP (Customer Data Platform) for both customers and employees to access the Stack. A diagram of this Modern Marketing Analytics Stack is shown below.
Shifting from Spreadsheets to a Modern Marketing Analytics Stack
Before Marketing tools came into the horizon, Marketers would often leverage Spreadsheet applications such as Microsoft Excel to carry out an effective Marketing analysis. Spreadsheets are impeccably useful for performing quick calculations and visualizing data efficiently, provided there is a small amount of data for analysis. Beyond a certain limit, running Analytics on Spreadsheets can become quite tedious.
Spreadsheets work with disparate or scattered data and so cannot be used to create a holistic view of the data. They are also vulnerable to many security threats. Hence, migrating to a Modern Marketing Analytics Stack can help companies overcome the problems with Spreadsheets and gain more insights into their customers.
How Does a Modern Marketing Stack Look Like?
A Modern Marketing Analytics Stack is a combination of data sources, Data Integration tools, Data Warehouses, BI/Data Visualization tools and some AI/ML (Artificial Intelligence/ Machine Learning) tools. The interconnection between all these technologies drives Data Analytics and helps Marketers gain valuable customer insights. A variety of options are available in the market today, across each category of tools and data sources. Once all the tools are set up between the source and destination, the Analytics Stack will become complete.
The choice of tools solely depends on the business goals of the organization but, in general, all tools are acceptable when designing the Data Pipeline. The below figure depicts a generic model of the sources and tools that can be used to design a Modern Marketing Analytics Stack.
Conclusion
The Modern Marketing Analytics Stack is a new concept that not only bridges the gap between customers and employees but also provides both the Business and Data teams to work together to achieve both short and long-term goals. It is more dynamic, flexible, scalable, and robust when compared to the Traditional Stack and is exceptionally simple to set up and operate. As the world is becoming more data-driven day-by-day, the choice of choosing the best data sources and Marketing tools is crucial. By setting up the Modern Marketing Analytics Stack, this process will become even easier and you can gain a holistic view of your customers.
If you’re wondering the solution to how you can truly incorporate a Modern Marketing Analytics Stack, then our Masterclass on Marketing Analytics can be your one-stop-shop solution! In this Masterclass, you will also learn the latest Marketing Analytics trends, tips, and strategies directly from the global marketing thought leaders. There will be 7 on-demand video courses covering 26 different topics and 1 live Q&A session at the end of this course. Book your seat today and get ready to discover your integrated Marketing insights using the modern Marketing Analytics stack like never before.
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Aakash is a research enthusiast who was involved with multiple teaming bootcamps including Web Application Pen Testing, Network and OS Forensics, Threat Intelligence, Cyber Range and Malware Analysis/Reverse Engineering. His passion to the field drives him to create in-depth technical articles related to data industry.