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  • 4 CRM Data Management Tips to Improve Productivity

    It is vital to have a CRM (Customer Relationship Management) system in place to meet your customers’ needs. A CRM system is used to store all the important customer information, consolidated in one place where it can be easily retrieved from and helps in enhancing the service and experience you offer your customers.

    According to the State of Sales Report by Salesforce’s Research Team around 66% of the sales rep’s are spending their time on administrative activities and tasks which are not directly related to the selling during a normal week. If businesses want to see a good ROI from the CRM spend, then they should be focusing on reducing non-selling administrative tasks and quality data collection for users need to be on the top of your priority list.

    CRM data management is crucial for interacting with prospects and customers throughout the customer lifecycle.

    Maybe you are someone who has tried things differently and taken the path of using personalization in your marketing campaigns, only to find out that your CRM was flooded with data errors and standardization issues that build a bad company reputation.

    Or maybe your sales team has missed out on some crucial context when interacting with the prospect due to the presence of duplicate contact records in your CRM software.

    Below mentioned are some issues that might arise with faulty data in the CRM.

    • Faulty data can lead to inaccurate reporting and forecasting.
    • Can cause embarrassing marketing automation mistakes that hurt your brand reputation.
    • Low customer data quality will slow down your sales team.
    • Customer Data issues will waste your marketing budget.
      May break integrations with other software.

    According to a report by IBM, faulty or bad data costs US businesses 3.2 trillion dollars a year. Another study found that companies lose around 12% of their potential revenue, on average, due to bad data.

    In this article, we’ll cover some simple tips that any company can take to improve their data management and avoid the problems listed above.

    Audit Your CRM Data
    Don’t fix what’s not broken. However, we can only fix our data collection issues until we audit our CRM data. In a report by SiriusDecisions, around 10-25% of B2B companies averagely have critical CRM data errors at any given point in time.

    This means that a full examination should be done to find out common errors, improve standardization and find out the reason why the low-quality data is entering your CRM in the first place.

    Customer relationship management data errors that you should be looking for in this audit include:

    • Inconsistent Data – Data fields with consistency problems. For example, “CEO” vs. “Chief Executive Officer.”
    • Incorrectly Formatted Data – Data fields like phone numbers, cities and states can be written in different ways. For example, “California” vs. “CA” Or an email address that is not properly formatted.
    • General Low Customer Data Quality – Fields with little usable data. This can be contacted with free email addresses, contacts with wrong info or records with inadequate information.
    • Duplicate Data – Records that have the same information as another record, including fields like phone number, addresses and email address.
    • Invalid Data – Data that does not meet the validation criteria. For example, a US zip code that contains only four numbers or less, an email address without an “@” sign, or invalid phone numbers and email addresses.
    • Missing Data – Records that have incomplete data.

    It is important to identify these types of issues, without it, it would be impossible to create proper functioning processes and plans for managing your CRM data and seeing an improvement in data quality across the board.

    Improve The Data Collection Process
    Businesses can improve their quality of data by stopping the low-quality data from entering the CRM in the first place. There are a few main places where low-quality data comes from.

    First, it is generated manually by manual human data entry. Averagely human data entry have an error of 1%, meaning one error in every hundred keystrokes. Across all of your CRM data, that would lead to many errors.

    Errors for critical fields like email – when typing “john@gmal.com” instead of “john@gmail.com”. These types of errors have a negative effect on your database. Emails are bound to bounce or be picked up by the verification process and checks. Most of the companies choose to remove these records from their database rather than making small edits and adjustments.

    One way to reduce this error rate is to add proper validation to your forms. Validation ensures that data entered into these forms meet certain standards. For example, an email should follow the correct format, a zip code should be of the correct length, or that names use appropriate capitalization.

    Identify Important Fields for Personalization
    When businesses audit their existing CRM system data, usually they are shocked to find how error-filled their CRM data is. This is overwhelming for many companies that they end up putting this whole audit process on the backburners, thinking that fixing this will take a huge amount of the team’s time. Well, they are not wrong. Fixing it can be time-consuming and aggravating.

    But you can make the task seem a whole lot less daunting by breaking it down into chunks.

    The best place to start is by identifying the important fields for your marketing and sales efforts. These are the fields that you’ll use most in automated personalization. They will often include fields such as phone numbers, names, email addresses and addresses. This is a good baseline to start.

    Other fields could affect important critical systems in your business like lead scoring. For example, assuring that your business prospects have standardized and correct job titles will play a vital role in the overall success of lead scoring and prioritization among your marketing and sales teams. These propel the importance for fields that you focus on as you get started with CRM data management.

    It is advisable to focus on cleaning and standardizing one field at a time. Then it is essential to have a proper validation and data collection process to ensure that new data entering the CRM is clean and standardized as well.

    By breaking the task of data cleansing down into small chunks and handling one field at a time, can improve your data quality significantly.

    Define Standard CRM Data Management Processes
    Having a well defined and detailed CRM system data management process is a must to improve the data quality. In a report by Harvard Business Review, it was found that one of the top problems faced by employees was a lack of clear direction, especially with administrative management tasks.

    When we standardize processes, it gives employees step by step directions to follow without any lack of interpretation. The advantage is that it takes away the guesswork for fixing specific issues and help the employees to make those processes seem more approachable to those who worry about handling data on a larger scale.

    Documenting these processes well for future reference. These would provide defined workflows, examples and screenshots that will help to display how the process works but also the importance. These documents should be available for the staff both in physical and digital versions.

    The internal team training session can help businesses identify what information is needed to include in the process documentation and what data management myths might exist among your team.

    Conclusion
    A lot of companies suffer from data management issues. If you want to make the management of your CRM system data a priority within your organization and free yourself from the tedious tasks associated with managing that data, then book a free, no-obligation call with our experts today!


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