What's the definition of data hygiene and why it's important for creators
In business, data reigns supreme.
With the high stakes that are dependent upon data, it's obvious that clean and accurate information is vital to your business's growth. Inaccurate data - known as dirty data - could lead to a failure in business efforts.
Thankfully, there's a solution - data hygiene.
In this post this article, we'll look at data storage, what data hygiene is and what it's importance. Additionally, you'll learn about the best data hygiene techniques to keep your data in good order and your business flourishing.
What kinds of databases store data?
- Contact details
- Demographic information
- Email marketing engagement
- Past purchases of your products or services
- Information on their needs relevant to your products and services
Larger companies may make use of a larger data base for business intelligence and analytics to access even more data points about their business. A clothing store could record its products' sales according to SKUs or a flight company would record data on their flights, or a software-as-a service company would record data on how customers utilize various features of their application. In some cases, the data becomes extremely detailed, and there are whole teams at large companies that maintain databases and analyze the data.
The importance of data hygiene is equal for both use cases. Since we're looking at authors in this article and not on the CRM, we'll concentrate on the information gathered by CRM.
What exactly is data hygiene?
The process of ensuring data hygiene refers to an ongoing and continuous process that ensures the integrity of information. It means that you're taking care to ensure that it's correct constant, reliable and consistent. Cleaning data prevents companies similar to yours from having issues caused from dirty information.
What is dirty data? It is considered dirty data if it has some of the following traits:
- Data that has been duplicated
- Incomplete (think missing contact fields)
- Older
- Incorrectly entered
- Typos, misspellings and multiple spelling variations
The bottom line - dirty data is incorrect.
The worst thing about filthy data is that it's way too easy to introduce mistakes in your data. If you enter data in a way that isn't correct, don't update it regularly or accidentally make a modification while you're upgrading your system, problems could be introduced anytime during your process.
What is the reason data hygiene is vital?
We'll now look into how data that is dirty can be detrimental to your business, which are just a few of the reasons why keeping excellent data is vital.
- Then you'll be wasting money and time.
Data that is not clean will be costly. In the U.S. alone, businesses suffer losses of around $3.1 trillion each year due to poor data management.
There's more than just money lost, it's also time. A Study by LeadJen research found that sales teams wasted on an average of 27% of their potential selling time by using inaccurate facts. The wrong phone number or reaching the wrong person isn't an enjoyable experience for anyone.
As we know, time equals cash, and so following poor data is an assured chance to miss out on revenues.
- Emails as well as other marketing campaigns won't have the proper tailoring.
When your information isn't up to date or is inaccurate, you may send prospects messages or other content that don't correspond with their current position on the buying journey.
These types of missteps can ruin your customer relations as well as your brand's reputation. It's a true double whammy.
The worst part is that mistakes such as these could lead to an increase in the rate of email churn. Spam reports, unsubscribes and hard bounces are a real possibility when you don't tailor your content for your intended audience. In no time, you'll begin to notice your list of email subscribers diminishing.
- There is no complete insight into the sale funnel.
Without regularly monitoring and maintaining your database, it will be difficult to get insight into the quality and effectiveness of your funnel to sales. This is why you won't be able to answer questions like:
- What are the number of leads that are qualified out there?
- What leads should you remove from your sales funnel?
- How much is your churn?
Finding the right answer to such questions will assist you determine where you need to put your marketing and sales efforts. It is possible to develop OKRs (objectives and important performance indicators) from your personal data!
Dirty data defense: data hygiene best practices
You can see that bad data could be absolutely devastating to your company. But, never fear - data hygiene best practices can be found here. Whether your business is a day or years old and these practices can be implemented at any point within the history of your business. We'll get started!
- Start with an audit.
An audit will provide you with an overview of your data's overall view. This helps determine what data is useful, and what's not helpful and also what data can be worse than beneficial. Through an audit that you can answer questions like "Which data points are needed in order to make a decision?" and "Which sectors are most in need of improvement?".
The audit must identify the areas where there are issues in your data collection , and the normalization.
- Review and enhance the methods of data collection.
During the audit or after is the best opportunity to look at every source and method by which data enters your systems.
Another consideration is how to reduce the need for manual data entry. Automation tools don't just cut down on data-entry human errors but also allow time to do greater tasks, like making your next famous TikTok (kidding or is it? ).
- Pay attention to the small specifics.
While in life, we try not to sweat the small things - this doesn't ring true with information. Small errors in data can quickly add up to big issues - like creating a marketing strategy based on inaccurate data. Yikes!
In data collection, ensure that you're following the following:
- Standardizing mailing addresses
- Verifying email addresses
- Standardizing common abbreviations and numbers
By noticing the small little details, you'll be able to catch larger, important errors. If you find a few of both, you may realize that it's time to adopt standardized operating procedures or simple guidelines for capturing and entering information.
- Establish a continuous cleanse of data.
Sorry to say, but your data hygiene journey isn't over even after you've completed the first cleanse. This is a continuous procedure that requires the commitment of a person and their determination. Remember - dirty data is easy to introduce into systems - so you must watch out for it with a keen eye.
A great way to ensure that clean data from being a problem is to implement continuous maintenance and consistency processes. Below are some of the ones we recommend implementing:
- Data entry standardization. Every data point within your system must be manually entered in a consistent way (especially when manually entered).
- Data errors are handled. Develop procedures (even if they're just for yourself) which clearly define the way errors are handled. In other words, how can correct duplicate or incorrect entries?
- Avoiding the creation of dirty data in the beginning. It could be as simple as adding vital fields to your forms to collect data and eliminating non-essential fields. In addition, you can conduct regular data audits to ensure that no dirty data is creeping back into your business with an out-of-date lead generation template, as an example.
The most important aspect of data hygiene
Solely having data isn't enough for a successful business. direct sales and marketing efforts.
To ensure that you don't lose revenue, time, and customers as well as threatening your reputation as a brand Your data must be free of errors. Making sure your data is maintained with good the highest standards of hygiene will ensure that you have actionable insights your business will be able to use with confidence!
We are believers that data is the key to success. data and not just for large multi-person businesses as well as for our most favorite type of business - those that are run by passionate, single entrepreneurs. Let us know what you think!