Effective B2B data management is crucial for driving business success and decision-making. Here are five best practices to elevate your data management strategy.
Data management tips
1. Define and refine your B2B data management objectives
Understanding your goals is the first step toward effective data management. Start by identifying clear, actionable objectives that align with your business targets.
Use these objectives to guide your data management practices and ensure they support your business needs.
Ask yourself a few questions to outline your B2B data management objectives:
- Identify data types: Determine which types of data (demographics, firmographics, etc.) you need to collect.
- Set process methods: Decide how you will collect and process this data so you can use it in your operations.
- Evaluate time and relevance: Consider if the data collection is time-efficient and how it supports your business goals.
- Define how you will use the data: Confrim how the data you collect will be used. Will you use it for creating buyer profiles, targeting key accounts, monitoring buyer intent, or measuring business outcomes?
2. Set data quality controls
High-quality data is a non-negotiable for achieving reliable analytics and business insights. According to our recent research report, 60% of marketers say that improving data quality is a top challenge and 66% reported that improving data quality is a top priority.
How can you fix data quality issues?
Data experts advise these best practices:
- Check in on data quality: Periodically examine the quality of incoming data and validate its accuracy.
- Address data completeness: Append missing data to in your database to get a complete record.
- Deduplicate data: Remove duplicate entries to increase efficiency and accuracy.
- Standardize your data: Ensure all of the information you collect, like email addresses and phone numbers, follow a consistent format.
- Adapt to global standards: If it makes sense for your company, configure your data management system for multiple languages and metric units.
- Filter out irrelevant data: Eliminate data that doesn’t meet your predefined criteria to maintain focus on relevant information.
3. Regularly audit and clean your data
It’s crucial to periodically confirm accuracy, as the business value of outdated and irrelevant data degrades over time. So, how often should you optimize or cleanse the database for maximum benefit?
There isn’t a one-size-fits all answer. It depends on the database size. The more data you possess, the more often you should clean it. The schedule may vary by organization but it’s important that it’s a continuous, on-going process. A proper routine of data assessing, cleansing and enriching keeps your business information in good shape.
- Set a cleaning schedule: Depending on the size of your data sets, establish a routine for data cleansing—smaller databases might need quarterly reviews, while larger ones might require monthly or even bi-weekly checks.
- Maintain data relevance: Continuously assess, clean, and enrich your data to keep your database current and useful.
4. Understand and improve data security
The data within your organization should be readily accessible, but at the same time, you must also put protections into place to keep it secure. Protecting your data from breaches is essential for maintaining customer trust and regulatory compliance
Below are some practical tips to secure your customer data:
- Implement secure access: Use robust authentication methods to control access to sensitive data.
- Encrypt confidential data: Apply strong encryption protocols to safeguard personal and business information.
- Comply with data laws: Regularly review and follow data protection regulations like GDPR and CCPA.
- Develop breach response plans: Prepare for potential data breaches with a proactive incident management strategy.
- Conduct regular security audits: Test and audit your data security systems to identify and fix vulnerabilities.
5. Centralize data
Centralizing your data into a single marketing database makes it easier to handle. It helps keep data uniform, connected and complete across the organization. Additionally, it simplifies data management and analysis processes, which will help you make data-driven decisions and likely improve revenue generation.
Other benefits of data centralization include:
- Improved data quality: Use centralized systems to reduce redundancies and ensure consistency across data sets.
- Access control: Enhance security by limiting data access to authorized personnel through a controlled system.
- Easier data management: Allow multiple stakeholders to update necessary information promptly to maintain an up-to-date database.
- Reduce storage costs: Centralization can decrease the resources needed for data storage and processing.
Never stop learning
By incorporating these actionable steps into your B2B data management plan, you can ensure more systematic control over your data assets, leading to better business outcomes and operational efficiency.
