The Essential Guide to Business Data Maintenance

Marketing | 5 minutes to read

17th Dec, 2021

Discover the importance of data maintenance for business growth and success and find out how to manage data effectively

Snapshot:

    • Data maintenance is fundamental to ensuring access to high-quality data for better decision-making

    • Most businesses fail to update data which impacts their sales and marketing function

    • Data maintenance constitutes different processes and functions that helps upkeep data quality and relevance

    • Clean, updated, and contactable databases helps businesses streamline their sales enablement functions and drive higher ROI

    The role of good customer data in helping businesses make better, faster, and successful decisions is indisputable. However, simply collecting or obtaining good quality data is not enough to make the most of it. Timely and regular data maintenance enables different business functions like marketing and sales use relevant, updated, and contactable data. This helps align sales and marketing efforts and minimizes wasteful costs.

    B2B businesses spend a disproportionately high amount of time, resources, and investment to procure marketing data. They however don’t realize that the data is vulnerable to decay. Estimates suggest that nearly 20% of all business data becomes obsolete within one year. As a result, despite high investment and effort, business decisions do not reap expected rewards.

    Data maintenance ensures that business-critical data remains reliable, accurate, and usable for marketing campaigns. In this blog, we take a look at what entails data maintenance, its benefits for B2B marketing and sales purposes, and some commonly-used maintenance practices.

    What is data maintenance?

    According to one estimate, enterprises generate more than 2.5 quintillion bytes of data every day. In other words, 2.5 followed by 18 zeros. A lot of this data is procured by businesses to improve their customer-facing services and functions and to enhance internal decision-making. However, this staggering pace of data generation also means that data is rendered obsolete very quickly as well.

    Data maintenance refers to a set of dedicated and systematic processes to prevent this data decay and ensure that the data collected remains useful, useful, accessible, consistent, and relevant. In the business sense, this means ensuring that customer data is updated timely, and its quality remains high.

    It is important to note that business data maintenance is not a one-off clean-up intervention; it is an ongoing process. It is the continuous process of auditing business data, identifying quality issues, and fixing them in a timely manner. This requires consistent investment, attention, oversight, and resources. Thankfully, using modern data management and maintenance tasks, many of these time-intensive tasks have been automated.

    What are the different components of data maintenance? 

    A number of different processes and functions constitute business data maintenance. Here is a quick look at some of them:

    What are the benefits of data maintenance for businesses?

    Provides insights based on real-time data: It enables businesses to stay apprised of the latest trends and behaviours exhibited by their customers. By helping businesses identify time-sensitive issues and priorities, data maintenance enhances agility and responsiveness in business decision-making processes.

    Results in higher ROI and improved efficiency: Timely maintenance of data helps reduce the overall inefficiencies and restricts cost in marketing and sales. Data collection or commissioning is usually a capital-intensive process and by ensuring that it is maintained, businesses can ensure a higher return on investment, alongside better alignment between different functions.

    Helps in better data compliance practices: Regularly maintaining data helps ensure that the data collection, management, and storage processes followed by a business are as per regulations and government policies. Not only does it help businesses stay on top of the latest changes in the law, but also strengthens security against data leaks and breaches.

    How to plan an effective data maintenance strategy

    Follow these steps to design a successful data maintenance strategy:

    Understand business requirements and allocate resources accordingly: Effective maintenance requires routine cleaning and updating of data. There is no one size fits all approach, and this must be based on the unique business requirements and importance of high-priority data. Start by finding out how often customer data is captured, the growth of the database, and rate of error, and data decay. Then, determine the frequency at which maintenance needs to be undertaken and reserve resources accordingly. Depending on the scale of operations, businesses can decide whether to do this in-house or outsource maintenance processes to external database service providers.

    Establish data quality parameters and metrics: To ensure that data remains relevant and useful, quantify different measures of data quality measures and determine the acceptable limit of error. Create management and cleaning protocols to initiate maintenance periodically or whenever the metrics dip below the acceptable level, whichever is earlier. There are essentially four types of maintenance processes:

    • Reactive: maintenance following a failure or slowdown of processes due to inaccurate data
    • Preventive: pre-planned maintenance undertaken periodically
    • Predictive: the maintenance work undertaken based on historical analysis or to arrest impending issues proactively
    • Prescriptive: the maintenance done in real-time to ensure maximum results to remedy specific data quality issues

    Identify the tipping point beyond which poor customer quality data results in roadblocks and failure and focus on preventive, predictive, and prescriptive methods. This can be in the form of a quality metric or score.

    Use smart AI-powered data validation tools: There are a variety of smart automation tools that can be used to validate data and reduce the physical effort involved in maintaining data. Many specialized tools and solutions for data cleansing, purging, validation, verification, and analysis are available. The benefit of such tools is that the investment is minimal or one-time, but the limitation is that they only serve the intended purpose, nothing more or less.

    Since maintaining data is a complex and multi-step process, relying on just tools might not be the best approach. Some of the commonly used data validation tools are Datameer, Talend, Informatica, QuerySurge, ICED, and Datagaps ETL Validator. Such tools may be helpful in solving specific data-related quality issues, or in reactive and preventive maintenance models

    Hire a data service provider: Most small and medium-sized businesses do not have the resources or talent to dedicate towards the sole purpose of B2B data maintenance. They usually partner with reputed data providers and data management agencies to ensure the sustenance of data quality. Leveraging the services and knowledge of experts helps create comprehensive maintenance protocols. It also provides access to the right partner for data implementation, development, deployment, and support services as well. If the maintenance needs are more predictive and prescriptive in nature, collaborating with a data provider might be the best way to go.

    Practices to follow for best results

    Here are some things to keep in mind while creating data maintenance frameworks and partnering with data management companies:

    Monitor high-priority data: Identify complex and high-priority customer data right at the beginning. This could be business-critical data that is indispensable to everyday processes and functioning, or more sensitive customer information. Make sure that data maintenance for this high-priority data is undertaken without fail using the most advanced techniques. Monitor the quality of this data to ensure that it continues to remain accurate and reliable. Doing this is crucial to ensure a smooth operation of the sales and marketing teams.

    Establish database recovery model: Businesses that do not back up their databases are just one accident away from a major disruption or full-blown crisis. Thus, businesses need to ensure that their data is backed up in several sources, and they are all updated from time to time to prevent duplication. The frequency and amount of data to be backed up may vary as per its importance.

    Ensure minimal disruption:  Planning ahead while undertaking maintenance and management helps ensure that minimal disruptions are experienced by business processes and functions. Backing up, verifying, removing redundant data, and maintaining indexes might lead to a temporary lack of access for some users. Hence, maintenance activities should be scheduled in a manner that does not add to the business cost. Data maintenance professionals and service providers must coordinate with marketing leaders and sales managers to ensure that customer data remains accessible during operational hours while the maintenance is underway.

    Focus on preventive and predictive maintenance: Preventive and predictive maintenance ensures access to high-quality data. Based on the time, usage, and condition of the data, businesses can plan precautionary and proactive measures in advance. This will help in minimizing the likelihood of adverse data-related accidents and reducing the need for constant oversight as well.

    Choose only reputable service providers: When partnering with data management service providers, be sure to undertake extensive market research to zero in on the best vendors. Check their area of expertise, the scope of services offered, and testimonials from existing customers to determine their reliability. Specialized B2B data services providers that offer industry-specific services can also be considered.

    Data maintenance for beginners: The final word 

    High quality data helps businesses grow, but it is maintaining data that helps supercharge that growth process. Data maintenance helps businesses and sales teams prepare for future campaigns, strategise better, align different functions, and make better decisions.  While data maintenance practices warrants the use of smart technology and dedicates resources, their returns in sales pipeline building and marketing success bolster the success of customer outreach and demand gen campaigns.

    To get expert advice and consultation on data maintenance and management, get in touch with us today.

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