Good Quality Data is Critically Important for Email B2B Marketers
Jun 19, 2020 21:04
Every company depends on good quality data for lead generation to help grow their business. Their business database is one of the most valuable tools they have as this is their pipeline showing where they are in the sales process. That is why it’s so important that those in B2B email marketing have business data that contains good quality raw data to work from. Good quality business email lists lead to good leads.
First Let’s Understand What a Lead is!
A lead is a person or company that is interested in your product or service. In short, they want to purchase what you have to offer. When you have this information, you can use it to begin communications with the prospect on the other end of the data stream.
Companies often will send out studies, surveys, and other types of communications through business email lists. These lists are often created when you open up communication from the company or have researched through the internet and have captured your information.
You will find that often, you’ll open up a link or Web site, and shortly thereafter you will begin getting emails from that company. They now have you in their database and you are officially a lead!
When you become a lead, a company’s goal is to transition you from a site visitor to a customer. Much of this is achieved through email marketing campaigns.
Defining High-Quality Raw Data for Your Email Campaigns
You’re only as good as your data. If you have poor quality or incomplete raw data, the success of your B2B email campaign is greatly compromised. This can be very costly for a company as each business lead costs a company money to follow up and turn that prospect, hopefully, into a customer who will purchase your product or service.
Organizations need to be serious about business intelligence to garner good quality, complete leads to make a sale, grow their business, and turn that prospect into a long-time customer.
Good quality data is true/accurate information based on five key standards, according to the Data Warehouse Lifecycle Toolkit. When your data meets the five standards, your raw data should be in good shape for future outreach efforts.
High-quality data is dependent on the following:
●Accurate information: Each field should be accurate, this includes the correct spelling of names, emails, level of interest or any other key information that is captured in your pipeline.
●Complete information: Every field in your database should be complete, empty fields or incomplete information can severely impact the quality of your data. For instance, without the correct email address or phone number, your prospect will not receive your communication and you have wasted the opportunity.
●Consistency: It is important to be consistent when collecting data. The same information should be collected for each prospect, so you have comparable data, which helps refine and qualify each prospect.
●Unique fields: Having duplicate data means you are duplicating prospects. This can often appear in the name and email fields. This compromises your data as these duplicates mean you have fewer prospects than you think. Therefore, it is extremely important to garner the correct information and spelling to reduce duplication.
●Current information: People today move from job to job, so it can be difficult to keep your business data up to date and current. In order to remove old data, there should be a scheduled update process that will remove all old data keeping your database accurate and current.
The Effects of Poor Raw Data on Your Business
We have defined the different types of raw data inaccuracies that could affect the success of your business email lists and other communications.
Here are ways poor quality data can adversely affect your organization.
●Inaccurate reporting: If you have poor quality raw data, this affects your business processes that rely on the data you have collected to accurately run reports, income, expenses, and just about everything else. This severely impacts the future of business projections that can affect your business growth and income projections.
●Inaccurate business decisions: Without high-quality, correct data, you may make critical decisions based on the information you have. If that data is incorrect, you risk making inappropriate decisions. Having correct data is key to making the appropriate decisions for your organization.
●Compromised data quality: When you have poor quality data, you may be risking customer confidence and can cost your company time, money, and your reputation. How many times have you opened up an email, that has your first or last name wrong, if you’re like me, you delete the email or communication. The thought being, if the company can’t get a simple thing like my name right, how detailed and professional are they, and will they get my order wrong?
In conclusion, we’ve determined how important quality raw data is to CIO’s and others that rely on that information to project the number of high-quality leads they have in their pipeline, future sales, need for additional staff, and other key information they need to successfully run their business.
Data is extremely important, so it is critically important that all data is complete and accurate.
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