In the world of B2B sales and marketing, business data is crucial. The more accurate and comprehensive data you get, the better your chances of reaching your target audience and closing deals.
But what happens when your data is incomplete or outdated? It can lead to inaccurate analysis and decision-making. That's the point where the process of data appending becomes relevant.
In this article, we'll explore what data append is and how it can be useful for B2B companies looking to improve their data quality and increase their chances of success.
What is data appending?
Data appending is the process of adding missing information to an existing database. This is done with external data, such as mailing addresses, phone numbers and turnover.
Data appending is typically part of the broader data enrichment process.
By using B2B data appending as part of a larger data enrichment strategy, B2B companies can achieve two key benefits :
- More accurate databases
- More comprehensive databases
These benefits, in turn, make the databases better suited for targeted sales and marketing campaigns and efforts.
By having access to more complete and accurate data, B2B companies can more effectively personalize their messaging, segment their audience, and increase their chances of success.
Process for Data Appending
- Define your goals — Before embarking on a data appending project, you should first identify your business objectives. What data do you need, and how will you use it to achieve your goals?
- Assess your data quality — It's crucial to ensure that all the data you plan to append is accurate, up-to-date, and relevant to your business needs. This assessment involves identifying the gaps in your current data and verifying the data you plan to append.
- Choose a data provider — With a clear understanding of the data you need and your data quality assessment, you can then select a reputable data provider to provide the missing data. You can use a combination of data sources to get the most complete dataset possible.
- Append data — Once you've chosen a data provider, the next step is to append the data to your existing dataset. The method of appending depends on the type of data you are adding and the data provider's preferred format.
- Monitor and maintain your data — Data is dynamic and changes over time, so it's essential to keep your appended data up-to-date. Regular monitoring and maintenance of your data ensure that your business decisions are based on the most accurate information.
What type of data can be appended?
The types of data that can be appended vary depending on the industry or sector of activity, as well as the specific goals of the B2B company.
Any type of data can be added, but there are some types that are more often involved. The most common types of data that can be appended include contact information, demographic data, firmographic data, geographic data, and technographic data.
Contact information refers to the details that enable B2B companies to get in touch with their customers or prospects.
It can include a wide range of data points, from basic details like name and email address to more specific information like job title, phone number, and social media handles.
Here is a list of different types of contact information:
- First and last name
- Job title
- Company name
- Email address
- Phone number
- Postal address
- Social media handles
While all of these types of contact information can be valuable, some are more important than others depending on the specific goals of the B2B company.
For example, job title and company name are often highly important data for B2B companies that are targeting decision-makers in specific industries.
Similarly, email addresses and phone numbers are essential for companies that want to reach out to their customers or prospects directly. These two types are probably the two most searched for in the contact information category, each having their own sub-term "email appending" and "phone appending" often used
Demographic data refers to information that describes the characteristics of a group of people, such as age, gender, education, income, and occupation.
Demographic data is most often useful in B2C. However, there is some data that can be useful in B2B, especially to be able to adapt its communication.
For example, if a B2B company is targeting a particular age group or income level, then age and income data will be highly important.
Firmographic data refers to information that describes the characteristics of a company, such as its size, industry, location, and revenue.
Here is a list of different types of firmographic data:
- Company name
- SIC/NACE Codes
- Company size (e.g. number of employees, revenue)
- Location (e.g. city, state, country)
- Ownership structure
- Year founded
- Website URL
For example, industry and company size are often highly important data points for B2B companies that are targeting specific sectors or niches.
Similarly, location and ownership structure may be critical data for companies that are looking to expand into new markets or partner with other companies.
Geographic data refers to information that describes the location or geographic context of a particular object or entity, such as a business, customer, or transaction.
This type of data can be useful for B2B companies in understanding the location and distribution of their target market.
Here is a list of the different types:
- Latitude and longitude coordinates
- Postal/ZIP codes
- City, state, and country names
- Geographic regions or territories
For B2B companies, important data can include information on the location of customers, suppliers, or competitors, as well as data on regional economic trends or market opportunities.
For example, a B2B company selling industrial machinery may want to know which regions or countries have the highest demand for their products, and which competitors are active in those markets.
Technographic data refers to information that describes the technology stack or digital infrastructure of a particular company or organization, including the types of software, hardware, or digital tools that they use.
For B2B companies, important technographic data can include information on the digital tools and systems that their target customers use, as well as data on emerging technologies or trends in their industry.
For example, a B2B company providing software development services may want to know which programming languages or frameworks are most popular among their target audience, in order to tailor their marketing and sales efforts.
Benefits of Data Appending for B2B Businesses
- Increased accuracy — By appending missing data to existing customer records or prospect records, B2B businesses can improve the accuracy and completeness of their data, which can lead to more effective targeting and better engagement with customers and prospects.
- Enhanced segmentation — With more complete data, B2B businesses can better segment their customer and prospect lists, and tailor their sales and marketing campaigns. This can lead to more relevant and personalized communication, and higher conversion rates
- Improved lead generation — By appending data to incomplete or outdated prospect lists, B2B businesses can identify new opportunities for lead generation, and improve their overall sales and marketing efforts
- Cost savings — By appending data to existing records, B2B businesses can avoid the costs and time associated with acquiring new data, and can make better use of their existing resources
- Competitive advantage — By having more complete and accurate data than their competitors, B2B businesses can gain a competitive advantage in their market, and better position themselves for success.
Best practices for data appending
- Define your goals and objectives — Before beginning any data appending project, it's important to define your goals and objectives. This will help you to determine what data you need to append, and how you plan to use that data.
- Use a reputable data provider — When selecting a data provider for your data appending needs, it's important to choose a reputable provider with a track record of delivering accurate and high-quality data.
- Validate and verify appended data — It's important to validate and verify any data that is appended to existing records, to ensure that it is accurate and up-to-date. This can be done through various methods, such as email or phone verification, or by using data validation services.
- Regularly update and maintain data — Data appending is not a one-time process, and it's important to regularly update and maintain your data to ensure its accuracy and completeness. This can be done through ongoing data appending efforts, data cleansing, and data validation.
Tools and resources for data appending
- B2B Data appending services — Many companies offer data appending services, which can provide B2B businesses with additional information about their customers and prospects, such as contact information, demographic data, and firmographic data.
- CRM — Many CRM offer data appending services, which can automatically update and enhance existing customer and prospect data. However, this data may not always be of high quality and you should not use it if you need it to be accurate
Challenges for B2B Businesses
Data appending can be a powerful tool for B2B businesses, but there are also some common challenges associated with the process. Here are a few challenges you may encounter when implementing data appending in a B2B context:
- Quality of Data — One of the biggest challenges associated with data appending is ensuring the quality of the data being appended. Outdated or inaccurate data can lead to wasted resources and failed marketing efforts, so it is essential to thoroughly vet any data providers you work with.
- Data Privacy and Compliance — Data privacy and compliance is another major challenge when it comes to data appending. B2B businesses must ensure that they comply with all relevant data privacy regulations and obtain proper consent when collecting and using data.
- Integration with Existing Systems — Integrating new data with existing systems can also pose a challenge, particularly if your existing data and management processes are not well-structured or if you are working with large volumes of data.