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Data Management Practices Your Company Should Consider

All modern-day company, no matter how its size have to reckon data management. Data management is how one gathers, keeps, and uses data safely, efficiently, and cost-effectively.

The key purpose of data management is to support people and organizations better use data legally in order that they can make strategic decisions and take actions that maximize the advantage to the organization. It is important to have a properly structured social intelligence program that uses robust, accurate data. A well thought out data management strategy is more important than ever as companies increasingly base on virtual or intangible assets to make value.

Nevertheless, data doesn’t mean just customer records and other externally sourced information, it can be any data. Staff records, credit card information, sales leads, marketing activity, social media interactions, website content, are just some of the pieces that fall under manageable data. It takes a plenty of hard work to turn data into something usable. Brands and agencies today are having their data from countless various sources and handling them on different platforms. Nevertheless, without proper management, you can end up with duplicate records, inaccurate information, wasted time, and storage space. This also causes to challenges assessing the accuracy of social listening campaigns, among other problems that come with poor organization.

Enter Data Management

Data management’s major objective is to keep information organized in aan approach that is both practical and usable. At its most fundamental level, data management runs to make sure that an organization’s full body of data is correct and consistent, readily accessible and adequately safe. Besides being an approach to eliminate duplicates and standardize formats, data management also lays the groundwork for data analytics.

Data Management Best Practices

Pointing out data management difficulty requests a comprehensive, well-thought-out set of best practices. Though specific best practices vary basing on the kind of data included and the industry, according to Leadspace, the following best practices lead the primary data management challenges organizations meet today:

Outline Business Goals

It would be best if you began small when it comes to data management. Start by outlining what your purposes are with your company’s information. Do you have any social intelligence purpose to face? How are you making a plan on using your data to cater your customers better? Can you match any data sources to get deeper insights? getting what you plan to do with the data you gather can support you keep only the information related to your goal. This makes sure that your data management software doesn’t get overcrowded and unorganized. Too lots of business keep and go on saving way too much data for which they have no use. By keeping only the data that your business is going to use, you’re supporting to keep your data management software clean and under control. Some example purposes your business might have are:

– Enhancing decision-making

– Building or improving automation and processes

– Audience targeting or building buyer profiles to harness social listening technology

–  Looking for customer buying habits and patterns

Besides, you can do countless things with data, however, it is imperative to begin by outlining your purposes. Because your business data purposes will address your data management processes, you do not finish with heaps of information irrelevant to your business’s purpose.

Prioritize Data Protection and Security

Security is an important step to make sure your company does not fall victim to a data breach which could endanger the information of your full customer base. Consumers are generally quite unsatisfied when unknown sources achieve access to their data. Data protection and security also need to be the number one priority for your business’s data management.

The General Data Protection Regulations (GDPR) rolled out in the EU last year which makes it harder for companies to use customer data. Your business must keep track all applicable guidelines to make sure your leads and customers’ privacy. This involves respecting unsubscribe requirements on email marketing campaigns, among other actions. In addition, GDPR effects not only companies that run within the EU but all businesses that market and sell to customers who reside within the EU.

Proper data management software can support to make sure the safety and security of your data. Complying with GDPR and other regulations once it comes to collecting data can also enhance your data protection.

Focus on Data Quality

Limitation of your data to only the necessary information your company needs to face its purposes is a good way to enhance data quality. The data your business is gathering must remain clean and reliable.

Firstly, data should be frequently checked for accuracy. Old data can become outdated and irrelevant to your sales and marketing teams fast. Real-time data like that used in social listening programs can take up space, so periodically cleaning and checking is important. This process holds data from negatively impacting your analytics, automation, and other processes within your sales and marketing departments.

To support your team concentrate on data quality, train all team members to gather and input data. Some input may be automated, but for examples where users manually add data to your CRM or data management software, training needs. Because this precaution holds data from being input inaccurately, preventing issues down the line.

Make sure the data is checked and cleaned before it is got in any analytics or reporting to enhance the accuracy of all metrics. Making data quality a first priority supports keep all factorsof your company’s data use clean and reliable.

Reduce Duplicate Data

There are many methods that your business could get duplicate data from a lead or customer. Your business should have cycles in place to handle potential decreases. For instance, a lead may be interacting with several lead sources or offers or returning to make another purchase. It is significant to make sure your company has processes in place to avoid adding duplicate data to your data management system.

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