Messy Lead List? It's Time to Clean Up Your Data Like a Pro!
Searchbug, Inc.
Find the people and contact data you need because missing data is bad for business!
According to a popular joke among data scientists, 80% of their time is spent cleaning data, and 20% complaining about it.
It's an exaggeration to say that most businesses have dirty data. However, it is true that many businesses have customer data that is difficult to correct and plagued by data entry errors.
This is why it’s important to clean your data. One-fifth of companies believe that over half of their customer data is inaccurate, and 30% of companies have incorrect customer information on average.
Clean customer data helps you identify prospects, target them more effectively, and reach them at the right time. If you have incorrect or missing information for any of your customers, then you won’t be able to reach out to that customer and may lose the opportunity to do so.
When you clean customer data, you turn incomplete and incorrect leads into usable ones. This means:
Bad data can have a negative impact on all of these areas, so it’s worth learning about data cleaning and implementing good tools and processes to keep your data clean.
Ways To Clean Messy Lead List ?
With the right tools, cleaning your data should be a straightforward process. Good data cleansing involves using a consistent method to get the best results. Here are some effective, proven, and easy ways to clean your lead list like a pro:
Organize and format Set of Data. Before using any data cleaning tools, it's important that you organize your information. Each piece of information needs to be in its own column. Mixed information often confuses data cleaning software, and may result in inaccurate or lost data presentation.
First, export the data from your database, or if you already have it in a spreadsheet like Excel, you’re ready to clean up your data. Ensure that each piece of information is correctly formatted, and remove entries that include letters or symbols instead of numbers in phone numbers or physical addresses.
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Append Data in Bulk. Missing data and incorrect data are both useless. The difference is how you go about finding missing data versus how you fix incorrect data.
Adding missing information to a customer list is called "data append" and involves separating your customer lists based on what data is missing. For example, create separate lists of entries missing phone numbers, entries missing addresses, etc.
Data append services work by pulling data together from different sources to fill in the gaps. You’ll need to specify what pieces of information you need (i.e. addresses, phone numbers, etc.) to make sure you get exactly what you want.
To avoid losing important customer information, only remove entries from your list if a data append service can’t be used and missing information can’t be obtained by other means.
After you’ve appended all your missing data, your lists will be ready to use. The appended information will always contain the most up-to-date information available, so there’s no need to clean it up.
If you wish, you can use these lists in the next step to check the accuracy of your data.
Confirm Other Important Details. If you plan on using the email addresses or phone numbers for outbound marketing purposes, we recommend that you also verify the email addresses and phone numbers.
You also need to know if the number is on the do not call list, and whether you’re dealing with an unmonitored inbox or a spam trap, among other details that can cause issues if you’re not aware of them.
In Conclusion?
Now that you know how to effectively clean your messy lists, do yourself and your business a favor by organizing your messy data. After following all of the cleaning processes, you can finally use them in your telemarketing, email marketing, direct mail campaigns, and any other customer outreach channels you are utilizing.
If you need to clean data and append or remove records from lists, check out our bulk append services and API to skyrocket your marketing and overall business operations.