Data Quality Matters. Here’s How to Achieve It
Although organizational data has immense potential to help enterprises, specifically sales and marketing departments, stagnantly storing it is not the answer. Companies need to learn how to leverage it to its full potential. Currently, many companies are only scratching the surface of the insights that data could offer. Much of their organizational data is often incomplete, inaccurate, or duplicated. Simply put, enterprises tend to manage their data poorly. In the long run, this impacts companies’ view of their customers and business as a whole, increasing budget expenditure and revenue loss:
- Marketers spend impressive campaign budgets in the wrong places because incomplete or insufficient data impacts their demographic profile.
- Sales teams spend too much time and effort on customers that are not likely to close and potentially miss deals.
- Customer service teams are unaware of customer history and, thus, ask for repetitive data, causing customer frustration.
- Finance is unable to identify upsells and cross-sells opportunities after the initial deal closure, missing revenue.
- Wrong products or services are delivered to customers at the wrong time and in the wrong quantities.
Needless to say, addressing data quality has become of utmost importance in companies of all sizes. In this blog post, we’ll be discussing the best ways to ensure solid data quality protocols across your organization.
Data Standardization with Required Fields
Field standardization within your CRM is one of the best and quickest ways to enforce better data quality. Standardized fields offer the framework to drive process automation, thus increasing the quality of your data at an organizational level. Here are the most relevant fields that you should aim to standardize:
- Company Name
- Contact Name
- Lead Source
- Lead Owner
- Phone Number
- Email Address
- Full Location
- Company Size
- Product(s) of Interest
By establishing such fields as required within your CRM, you ensure that your employees get the insights needed to boost customer experience at an organizational level. However, these may vary based on your business’ Ideal Customer Profile (ICP). When selecting the required fields within your CRM, make sure to pay attention to the following:
- Company size, since you’ll need to be fully aware of how many employees will be using your software or products
- The type(s) of product(s) the company is interested in
- The budget the company has allocated for your services or products
- Your prospects’ location
- Company name, since this will provide a solid research starting point in your future interactions with the prospect
- Etc.
Data Cleansing with Field Mapping, Data Deduplication, and Data Integrity
Once you decide what fields your CRM requires, it’s time to start cleaning your existing database. Here are several methods you can use in the process:
- Verifying data internally by extracting it into Excel and manually reviewing it
- Addressing duplicate data when necessary
- Updating data like addresses and other company and employee information
- Undertaking an active initiative to complete records with missing data, look for duplicates, and update incorrect information.
Data Consolidation: Why It Matters and How Can You Ensure It
As a rule of thumb, your customer-facing teams are the ones that gather customer data through customer interactions, such as:
- Customer communications through email and texts that offer insights into general product needs, requests, purchase history, timeframes, etc.
- Customer interactions may include information that can be used to update records, customer profile, or their buying history. You can rely on data gathered through phone calls, chatbot conversations, or in-person interactions.
- Customer requests, complaints, and demands that shape customer satisfaction—information that’s vital to sustaining your relationships in the long run.
- Information on customer interests gathered from marketing interactions (form completions, webinar attendance, email clicks, landing page views, etc.)
Ensuring Data Consolidation: Best Practices
Data quality matters at the moment of CRM implementation, but also beyond. The data that you feed your CRM after implementation is equally important. Here are some best practices that all companies that implement CRM tools should follow to ensure data consolidation and management:
- Employee training. Ensure that all employees that interact with your data fully understand data management and how to efficiently achieve it. A good method to train employees in data management would be to design dynamic courses that take a look at historical data and its implications over time in terms of new business opportunity assessment, KPI development, and more.
- Using validation tools. Data validation is an essential part of any data handling task, whether you’re in the field collecting information, analyzing data, or preparing to present data. Although data validation can be difficult to achieve manually, certain tools will help you streamline and simplify the process.
- Data monitoring. Frequent data audits are a good way of ensuring high data management standards.
- Data prioritization. Not all data is created equal, and before investing time and resources in different data types, it’s best to assess which data is the most important and relevant to your teams and business as a whole.
- Avoid data fragmentation. Siloed data prevents your teams from collaborating efficiently and your company from achieving its full potential. This type of issue is most frequently encountered in companies where fragmented software is present. The quickest fix to this issue is properly implementing flexible, articulated CRM tools and integrations.
- Data visualization. Having a visual representation of your data is sometimes just as important as having access to data. Although this is not always the case, high-performing business automation software also have incorporated data visualization features.
Data quality is essential in CRM implementation and beyond. By following the advice above, you ensure that you have a better starting point in ensuring higher CX standards for your customer base.
Interested in learning more about how we can help in data standardization? Get in touch with us!
