How A CRM Can Improve Data Integrity
Welcome back to the “Improving Your Business Performance With CRM” series. In this series we cover five crucial features provided by modern CRMs that help improve process efficiency and sales volume within your organization. In this article, we will discuss how a modern CRM can improve and maintain data integrity. The last installment covered the importance of data transparency with CRM.
What is a Data Model?
A data model is a template for data integrity: a set of data points collected to represent the different types of records in your database. For instance, a customer record in your database may include a field to enter each of the following: customer’s name, address, phone number, email, years in business, industry, number of employees, federal tax ID, and annual revenue.
These data points represent your customer in a manner that enables you to effectively do business with them. Data points should represent the information required for your business’s functional areas to do their jobs effectively and efficiently, and arrange that information in a way that allows that data to be accessed efficiently. Modern CRMs make it extremely easy to build the fields to store these data points for each record type.
What is Data Integrity?
As an owner or user of a CRM, how can you trust the data is accurate and follows a predefined data model? Data integrity relates to the quality and accuracy of the information entered in your database throughout its life-cycle.
Data integrity is important because of the quality of decisions that stem from analyzing data. CRM data influences crucial business decisions including which customers to target through marketing, whether there is a need to diversify the products and services you offer, whether to adjust the price of your products, and whether to hire more sales personnel.
Modern CRMs provide tools to build and configure data validation rules, many of which come right out of the box. Salesforce, for instance, allows an administrator to mark required fields. This prevents sales reps from creating incomplete records by alerting them when a required data point is missing from a new record before it can be saved.
CRMs also allow you to establish dependent criteria that flag if a record is updated with one piece of data but another related piece is missing. For instance, if a credit personnel updates a deal in your CRM as processing but the name of the processor wasn’t entered, an error message would alert the individual to enter a name for the processor before it can be saved.
Preventing Duplicate Records in CRM
Modern CRMs also have duplication tools available that detect possible duplicate records before the record is entered or edited. You can also control how these records are managed by setting the fields to compare previously entered data such as name, phone, and address.
The CRM will compare the new record against existing database records. If there is a possible match, you can decide whether you will allow the possible duplicate record to be saved and reported, or you can block the record entirely and provide the user with the matched record for reference. Duplication of records and data is a major focus of prevention for sales organizations because of the negative impact it has on reports and therefore subsequent decision making. Duplicate data can confuse your sales and marketing personnel and can result in a poor customer experience.
Making Data-Driven Business Decisions
Maintaining data integrity within your organization is imperative to making educated, data-driven business decisions. You, nor anyone in your company should feel uneasy when making crucial decisions based on the data being reviewed. A CRM allows you to establish a tailored data model and provides the tools necessary to maintain high-quality level information that can be trusted.
