To study CRM data in detail, we first need to have a handful of knowledge regarding the importance of data marketing and business strategies. It is one of the essential aspects of business methodology and projections.
However, many decision-makers are unaware of the impact data can have on making or breaking a venture. Bad data, which includes incorrect data assortment and low data maintenance, can adversely affect the various departments, including marketing, sales, and technology, etc.
Inaccurate data causes trillions of dollars of loss every year. Studies by IBM reveal US businesses nearly lose $3 trillion yearly to bad data. Disclaimer: This is not it! Some of the other bad data impacts are mentioned below:
The data quality rule 1-10-100 explains that the relative cost of fixing an error exponentially increases with time. It explains how the $1 trillion marks are reached by now.
Integration of this principle into CRM systems reveals that it takes $1 to resist bad data from entering the CRM system, $10 to correct the already existing problems, and $100 to fix the internal or customer failures caused by the situation.
Considering the facts, on average, 22-30% of lists decay annually.
Additionally, the Sales & Marketing Institute and Dun & Bradstreet Sales report highlight that 120 business addresses and 75 phone numbers are altered every half an hour, 20 CEOs change their jobs, and 30 new businesses are generated.
Ideal CRM Data Structure
To have a deep insight into the bad data and its effect, we first need to understand a CRM system's ideal structure. The perfect design involves a specific CRM data structure that is discussed below by portraying an example of HubSpot CRM.
1. The Lifecycle Stage
The lifecycle phase divides contact data information by their degree of sales-readiness. In HubSpot, CRM lifecycle stages are categorized as follows:
Subscriber – Person who signed up for updates from your organization
Lead – A person who has communicated interest in your product past a fundamental membership
Marketing and Sales Qualified Leads are customers approved by your company's marketing and sales crew.
Opportunity – An individual who is a member of an open arrangement with your organization
Customer – Someone who has purchased from your company or has closed a deal
Evangelist is a person who is kind enough to promote your products and refer you to other customers.
Other – Contacts who do not fall into any of the categories mentioned above
You can update the contact information manually and automatically according to your sales processes. It keeps your focus entirely on the contacts that are more likely to purchase.
2. Lead Status
Tracking contacts that are qualified by your sales team can offer valuable data to your CRM system. Some of the lead status options in HubSpot CRM are as follows:
New
Open
In progress
Open Deal
Unqualified
Attempt to Contact
Connected
Bad Timing
Just like the lifecycle stage, you can update the lead status. The lead status allows the new reps to start exactly where the old team member left by rationalizing communication among your sales representatives.
3. Custom Objects
Although the basic needs of sales reps are fulfilled with the available contact data options, yet there are times when teams require additional information to feed into the CRM data structure. It is where customs objects come in handy; this valuable method allows you to store all the pertinent data in your respective CRM.
Customs objects provide extreme flexibility for logging and utilizing valuable data by allowing the sales reps to categorize the data that does not matches the predefined contact alternatives.
CRM Data Structure
Classifying the data can help in determining the importance of data. The CRM data management involves different types of data which are as follows:
1. Identity Data
This type of data gives descriptive and personal details about the individual. Typically, the identity data includes; name, mailing information, email address, phone number, social media accounts, and important personal information.
2. Quantitative Data
Quantitative, measurable operational data gives you information regarding the interactions a particular customer had with your company. For instance, how many purchases the customer has made, how many times he has visited your website, their engaging data information, and inbound and outbound information.
3. Qualitative Data
This type of data gives you an idea about your customer's attitude, motive, and behavior, which in return identify their buying decisions. Direct feedback and surveys combine to formulate qualitative data.
4. Descriptive Data
As the name indicates, descriptive data associates you with your customers on a personal level. It provides you with the lead's lifestyle details, such as their education, career, and family details.
The impacts of Bad CRM Data
The bad data find its way into your CRM system either when you enter inappropriate information in the wrong field or make data duplications. No matter why the result is the same, it deteriorates your system and increases the cost required for remedies.
Low data quality, for instance, significantly influences the marketing efforts, reduces the delivery rates, and intensifies spam labeling. These minor looking mistakes can cost you thousands of dollars and defines the destiny of your campaign.
Having high-quality data within your CRM system authenticates positive experiences and expanding incomes.
Some of the effects of bad CRM data on your business are mentioned below:
1. ROI Limitations
An easy CRM calculator reveals that a company spends around $400,000 on manufacturing, add-ons, and for 50 users over three years period on their CRM system. But this amount goes to waste if the customers do not trust your product or company in the market.
As a salesperson sits around looking through copies searching for the correct record, they are more averse to accept CRM. Or then again, if the information is absent or off base, making it harder to arrive at contacts, they may choose different techniques to get the information data.
2. Fluctuations
The key is to focus on consistency. Besides, consistently robust data will engrave a sense of trust among the teams that utilize the data. They will start considering it dependable and trust-worthy.
On the other hand, if a marketing rep encounters an off-base division due to inaccurate and incomplete information, bad CRM data or email will restrict him from trusting the system.
3. Fosters Bad Habits
It works across all jobs. A user will be more hesitant to add further information if he cannot confide in the data or information presented. But if he finds the info acceptable, he will not be prone to add bad data.
A manager that is getting wrong information from the system will need to reach out to the external assets to get valid and correct data. It will lead to multiple conversations that will usually start from "CRM is not valuable."
Fortunately, there are approaches to limiting bad data by finding a reasonable interaction from accomplishing excellent and updated information. The result is a well-filled CRM machine that wins the trust of users for the system.
Conclusion
Thus, CRM data management is crucial to look into while generating and maintaining your CRM data. Bad data will lead to suspicious users and ultimately affect your business revenues. It is essential to feed your CRM system with the right kind of data that is structured appropriately.