Everyone agrees that data and CRM systems (customer relationship management systems) are important for corporate management. However, only a few B2B companies also use this insight in practice and pursue a targeted data strategy.
It's terrifying: A Harvard Business Review publication (2018) on the topic of “data growth” shows that around 60% of all decision-makers are heavily focused on investments in data analyses. What sounds good at first glance means, conversely, that as many as 40% pay little or no attention to the topic of big data and data analysis.
When it comes to the data stocks in B2B and their quality in the assessment of B2B entrepreneurs, it is appropriate to speak of a crisis. For example, a recent study by CapGemini shows that just 27% of managers are satisfied with the data quality and only 20% trust their own data (CapGemini Research Institute, 2021). This is dangerous in an environment where data is the basis for success. The quality of the data will have a decisive influence on the success of the company in the future.
Poor data quality hinders process optimization, automation, and digital transformations, which often leads to unnecessary additional work. In the digital era, where data is generated in large quantities, it is crucial to use effective methods to manage data. Even the most advanced technologies, such as machine learning, are useless if they're based on faulty data. It is therefore essential to improve the quality of the database first.
In this article, we'll show you what information you should collect for your database to strengthen customer loyalty and encourage potential customers to buy. For this, you can use CRM systems, such as Hubspot.
Introduction to Data Strategy
The Fundamental Importance of High-Quality Data
High-quality data is the foundation on which the company stands. They shape the customer relationship, the number of customers, and the effectiveness of the marketing automation systems used (e.g. Hubspot). It may be tiring to deal with long tables and statistical data, but a few, regularly compared data is enough for a sophisticated business and marketing strategy.
Defining and Differentiating the Data Strategy
A data strategy is a formulated, targeted process plan that enables a company to gain knowledge from data. This plan serves as a roadmap for using data analytics to optimize existing business and potentially develop new business opportunities. It is important to differentiate from a digital strategy, which focuses on digitizing and opening up new digital channels, whereas the data strategy focuses on the profit-oriented use of data.
Key Aspects of the Data Strategy
Objectives and Framework
The data strategy design sets clear goals, including timelines. It includes the expected use of resources and the necessary framework conditions such as technical and legal requirements (data protection, data security) to achieve the goals. It is also checked whether existing workers have the necessary capacities and qualifications or whether training measures are required.
Avoiding Irrelevant Data Collection
A well-thought-out data strategy helps to avoid focusing on irrelevant data collections and instead focus on projects that move the company forward. This prevents frustration and ensures that only relevant data supports business growth.
The Three Pillars of Data Strategy
Your strategy should be based on the following data:
- Definition of responsibilities: If it is not clearly defined who is responsible for which data and to what extent, no one will care about it in the end. This not only includes collecting and analyzing the right data but also identifying responsibility for data hygiene and data protection.
- Quality over quantity: Mere amounts of data won't get you anywhere. For a sustainable data strategy, you need a clear division that makes your data usable. To do this, you must keep the customer journey in mind and define exactly which data needs to be collected per phase.
- Timeliness: With every action, customer data also changes. You should keep an eye on this because only up-to-date data ensures a solid basis for decision-making. At this point, consistency is the most important characteristic for developing a long-term strategy with your data audit.
Of course, you can use numerous tools to collect and evaluate data. For that Customer relationship management in B2B Are CRM systems such as Hubspot useful.
Get Help from an Expert
The more extensive and complex your data volumes are, the more recommended it is to bring an expert on board at this point. That doesn't mean that you have to hire a data analyst. It is enough to get someone for the initial setup to avoid marketing automation mistakes — especially if the company does not have the appropriate competence.
A MarTech stack (marketing technology stack) comprises all technologies such as tools, CRM, and IT systems that a company or its marketing department uses to manage, execute, measure, and optimize marketing measures and can be used as a great data basis.
Conclusion
An effective data strategy is the backbone of every future-oriented company. It makes it possible to extract valuable knowledge from data and to substantiate business decisions.
By setting clear goals, defining responsibilities, and ensuring data quality and timeliness, companies can make optimal use of their resources, avoid inefficient data collection, and utilize the full potential of their marketing.
Expert support can help to effectively design and optimize this process. However, there are also numerous tools, such as Hubspot, that take over automation processes and help you with tasks such as CRM.
