In marketing, nothing is more important than knowing your target audience and how they interact with your business. However, it is not always easy to evaluate what target groups and customers want, their pain points, or when they leave the customer journey. This is precisely where data-driven marketing comes into play.
Not all companies use data-driven marketing in the way they might like. Today, we look at which evolutionary stages companies can locate themselves on and what they need to consider to get to the next stage.
Data-Driven Marketing In Companies
In addition to target group segmentation, many entrepreneurs and marketers ask themselves how the marketing budget should best be distributed, to what extent previous advertising expenditures have paid off, or which marketing channels have the most significant investment potential. With data-driven marketing, essential insights and recommendations for action can be derived from the data collected so far, and the customer journey can be refined more sustainably.
Most companies already collect a lot of data. Data-driven marketing helps derive the right decisions and perspectives from the data obtained. Whether small, large, or medium-sized, every company can benefit from it: cross-industry and reliable.
However, this type of marketing is far more than just using additional technical solutions. In data-driven marketing, data is primarily used to learn more about customers and better understand their needs. But how can companies implement this, and what are the stages of evolution?
Data-Driven Marketing: What Are The Stages Of Evolution In Companies?
Every company has a different approach to collecting and evaluating data. Some development stages of data-driven marketing activities are presented below:
- Tier 1: Data Resistant
- Data is collected, but nobody in the company uses it. This is either due to a lack of human resources or a lack of awareness of the need for the power of data.
- To do’s:
- Establishing data awareness in the company (we also have a complete Handel’s Kraft article on this )
- Hire competent employees
- Request help through an external agency
- Tier 2: Data Aware
- Your company is aware of the added value of the data, but marketing and analytics data often lie separately in different data silos. These can be intentional or unintentional. Other departments often only have access to specific silos, so a 360-degree view of the customer is not guaranteed. In addition, data usually cannot be exchanged or merged.
- To do’s:
- Avoid/dissolve data silos.
- Merge data sources
- Make data available globally.
- Tier 3: Data-Driven
- CDP or DMP are already being used here. Companies already use the collected data is already used strategically by companies and integrate it into a central system, leading to the marketing processes’ initial automation. The data quality is already very high at this level, and a 360-degree customer view can be guaranteed.
- To do’s:
- Connect to global data warehouse
- Make data available to the entire company.
- Stage 4: Connection To A Data Warehouse
- By connecting a CDP to a data warehouse (DWH), all data from the company is linked, but other areas besides marketing can also access it. Here, all decisions are already made based on data and regularly evaluated by central reports and dashboards.
- To do’s:
- Automation of all processes
- Creation of individual campaigns and advertisements
- Use of machine learning algorithms
- Stage 5: Automation
- All marketing processes are automated and continuously monitored to make any adjustments. At this level, companies rely on machine learning and AI to generate valuable insights and manage campaigns.
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