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Maximize the Value of Your Data With Data Lifecycle Management

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Maximize the value of your data with Data Lifecycle Management. Optimize storage, ensure compliance, and enhance data accessibility for better decision-making.
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Table of Contents
Introduction
1. Best Practices for Data Lifecycle Management
2. Data Lifecycle Revenue Marketing Is The Future Of B2B Growth

Introduction

B2B marketing leaders assert that adapting to changing buyer behavior is crucial, shaping the company’s marketing strategies for the upcoming year. For instance, B2B buyers are more self-guided as they are reluctant to share their personal information and are expanding their purchasing processes by themselves. This new behavior has changed how B2B marketers market their goods and services, and now they require a new approach to grow revenue competitively.

Here, the data lifecycle comes into the picture that sequences the different stages of data, i.e., creation to eventual disposal; this entire lifespan of data is called data lifecycle management (DLM).

Unlike traditional marketing, when B2B buyers took a linear approach to marketing their products, customers had limited options, little to no product knowledge, and no influence; however, the situation is a complete reverse today. Currently, B2B companies aren’t just struggling to expand their customer pool but also retaining the existing crowd. Previously, B2B marketers did not give customer retention importance, but now, looking at the current scenario, it has become an important part.

Therefore, to know more about DLM in an organization, MarTech Cube brings you this exclusive article that will understand the best practices and the future of the data lifecycle.

1. Best Practices for Data Lifecycle Management

In the initial stage of DLM, marketers are required to gather data from numerous sources to help gain more insights into customers’ behaviors, demographics, and preferences; marketers can take the help of any analytic tool to analyze this data and identify trends and patterns that can be used in marketing strategies. Once the data is collected, now is the right time to segment your audience into different groups based on common characteristics and interests. This allows you to personalize your marketing efforts and offer different services and products to specific audiences, further increasing effectiveness and relevance.
The third phase is mapping out your customer’s journey, i.e., creating messages that resonate with your target audience. Marketers can undertake this effort through personalized product recommendations, customized email campaigns, or targeted social media ads. Now comes the part where marketers need to continuously monitor the performance of data lifecycle marketing efforts and further use A/B testing to experiment with various approaches. With the use of the insights that you gained from testing, you can make strategies and also optimize future campaigns for better results.

The final and most important part is being transparent in the process of collecting and using customer data, as well as respecting privacy and consent requirements. The B2B marketing companies need to ensure that they are compliant with data protection regulations such as GDPR and CCPA, along with prioritizing the security and privacy of customer information. Post-usage of data, it is important to archive them so that you can keep them in the long term without worrying about data breaches.

2. Data Lifecycle Revenue Marketing Is The Future Of B2B Growth

The use of data analytics and customer insights is essential to understanding individuals’ behavior, preferences, and buying patterns. Through these contemporary data management strategies, marketers will get a deeper insight into the customer’s journey and evolve more to deliver the best interest. However, with time, DLM will enable more precise targeting and qualify B2B brands to provide highly relevant and personalized messages over time.

In a recent interview with MarTech Cube Michael Jack, CRO, and Co-Founder, Datadobi quotes, “A well-defined data strategy should encompass aspects such as data governance, storage optimization, data lifecycle management, and security considerations.” Further down the line, the approach will break into different silos, which will increase the ability to engage buyers’ audiences across the customer lifecycle.

Looking at the constant change in the business world, data lifecycle management is emerging to be a vital aspect that will ensure challenges such as data fragmentation and disorganization are eliminated and allow you to take utmost control and effectively utilize data for maximum efficiency.

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