Employing irrelevant data when tackling modern customer analytics challenges is akin to forcing a square peg into a round hole. Modern data stacks are capable of offering targeted solutions that streamline various processes. Let’s take a look at why this novel approach has become a tangible reality.
The Big Picture
As you may have guessed, we are referring to the role that big data plays within the larger CRM ecosystem. The issue here is that collating massive amounts of information is no easy task. If you are provided with the option to activate customer data within your modern data stack that is relevant to a specific goal, it will be much easier to develop customised solutions that are targeted towards the appropriate demographic. After all, why perform surgery with a broadsword if a scalpel is readily available?
The Proactive Edge
Legacy data stacks suffered from several possible drawbacks, and the reader may already be familiar with a handful of common issues, such as (1):
- Cost
- Complexity
- Disjointed user experiences
- Misplaced resources
Having said this, a recently published Gartner study found that latency was the primary concern. Businesses are now searching for low-latency databases that can reduce the time between when the data is collected, and when it is made available to the end user. How can modern solutions circumvent this issue?
Scalable Solutions
One core trait of modern data stacks is associated with their modular nature. In other words, businesses can pick and choose which components to install, and at what times. This ultimately results in the ability to handle different data sets, including:
- Structured
- Semi-structured
- Raw
Furthermore, the pay-as-you-go models of these systems will provide a cost-effective edge when compared to off-the-shelf alternatives. This also ensures rapid implementation, limited onboarding, and the ability to leverage user-friendly interfaces.
Migrating Into the Cloud
Another reason why customer analytics are being transformed by modern data stacks involves the ability to access fully cloud-based functionality (2). Previous iterations would normally require a significant amount of attention by in-house IT teams; potentially causing them to neglect other core competencies. Not only are cloud-based data stacks able to free up existing resources, but they offer a level of redundancy that was not possible in the past. Let us likewise remember that systems in the cloud can be integrated with other CRM platforms, and they are capable of processing information in real-time scenarios. This results in a more streamlined interface that all relevant stakeholders can access.
Challenges
Although the benefits of modern data stacks in relation to marketing are apparent, there are still some challenges that may need to be addressed. A handful of examples could include (3):
- Debugging
- Defining the sources of specific data sets
- Interdepartmental accountability
- Data debt (longitudinal problems with quality and governance)
However, we also need to remember that the architecture of modern data stacks is constantly evolving. It is likely that the issues outlined above will be remedied in the not-so-distant future. Businesses that wish to maintain a competitive edge are understandably keen to adopt these systems, and it is clear to see why.
Sources:
1. https://insideainews.com/2024/04/15/why-the-modern-data-stack-is-broken-and-how-to-fix-it/
3. https://medium.com/@praveen.rvs/challenges-within-the-modern-data-stack-681707b14d9e
The post Why the Modern Data Stack is Reshaping Marketing and Customer Analytics appeared first on Big Data Analytics News.
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