Data refers to the collection of facts, numbers, or other information in various formats like text, images, audio, and video.
In today’s digital age, data is increasingly being generated and collected by multiple sources, such as computers, sensors, and mobile devices. This data can then be analyzed to gain insights into various aspects of our world, including consumer behavior, health trends, climate patterns, and more.
Now we all know that data is everything but
What is Data Enrichment?
Enhancing, refining, and improving existing data sets by adding new information or insights to make the data more valuable and relevant and to gain deeper insights into customers, markets, and business operations.
Data enrichment integrates data from different sources to provide a more comprehensive view of a particular topic, such as customer behavior, CLV, market trends, or business operations by adding new data fields or attributes to a dataset, such as demographics, geographic location, or social media activity. It can also link data from different sources, such as merging customer data with transactional data or integrating data from external sources, such as third-party data providers.
Various techniques, such as data cleansing, data normalization, and data augmentation, are used in data enrichment.
Data Enrichment and Sales Strategy
Data enrichment can play a critical role in developing a successful sales strategy. Businesses can better target their sales efforts and tailor their messaging to resonate with their target audience by gaining insights into customers’ needs, preferences, and behavior through data enrichment.
For example, a company that sells cosmetic products could use data enrichment to gather information on the latest trends in the fashion business, customers who are looking at them, the age of the customers, and other information. This data could then be used to develop targeted sales messaging and marketing campaigns that address the specific pain points and challenges intending to convert leads into customers.
Data Enrichment in Three Easy Steps
The enrichment process sounds overwhelming if you already have a vast customer data database from multiple sources. But here are the three essential steps to streamline data enrichment.
Step 1: Know Your Goals
Of course, data enrichment aims to improve the quality and accuracy of your data, but you need more specific goals that match your business case. Remember that data enrichment should enable your team to make good choices when nurturing leads through the buying journey.
Choose between real-time or warehouse data enrichment techniques to get the necessary data for your sales team. Real-time enrichment works well for businesses that depend on ever-changing data like weather conditions for logistics companies. Warehouse data enrichment is ideal for more static databases like mailing lists, purchase histories, and customer addresses. Data Enrichment is also helpful in setting smart goals or smart metrics to track the progress of goals.
Step 2: Choose the Right Data Enrichment Tools
A data enrichment tool can save hours of manual data processing by automatically collecting, cleansing, and formatting your data. Consider adding a customer data platform (CDP) to your CRM to harmonize offline and online data sources. These include FirstHive, ActionIQ, BlueConic, and Optimove. Also, consider data enrichment services like Clearbit, Vainu, LeadSpace, and LeadGenius.
These tools filter through your database and integrate with various CRMs to unlock your business intelligence data.
Step 3: Set A Data Enrichment Schedule
Since data enrichment is continuous, determine the best time intervals to cleanse and update your data. Consider that up to 70% of your customer data becomes obsolete annually, then estimate how much data your company generates per day, month, or quarter. Once you automate your data enrichment techniques, you’ll empower your sales and marketing team to reach their goals.
Regardless of your company size, industry, or business goals, there are four fundamental guidelines to ensure your data enrichment process benefits your organization.
1. Begin with Clear Data Criteria
As discussed earlier, the main types of data enrichment are demographic, geographic, and behavioral. Identify the sales OKRs linked to these enrichment types and the metrics that indicate that enrichment helped your sales strategy. For example, an increase of 80% in data accuracy can translate to increased customer loyalty, higher team productivity, and better return for ad spend.
2. Standardize Data Enrichment Techniques
There are many data enrichment examples to inspire you, but make sure to stick with the technique you choose. Establish the data sets that need continuous enrichment and the tools, formats, and integrations necessary to empower your team. Then, automate these processes to make them repeatable, thus ensuring an updated, accurate database throughout.
3. Scale Your Data Enrichment
As your business expands, so do your data enrichment needs. One way to avoid complexity and errors is to automate your data enrichment tool to scale with your growth. Use an established format to add new data rules as they arise. Set permissions for team leaders to approve additions or changes.
Apply Data Enrichment Techniques Across All Customer Touchpoints
Data enrichment works well for desktop web forms, but it also works for other sources of customer information like mobile apps, emails, transactions, referrals, events, in-store engagements, and more. Ensure your data enrichment tool covers these bases effectively.
With the advent of AI-powered sales tools, increased focus on customer experience, remote sales and virtual selling, personalized messaging and targeting, and data enrichment has become vital for a business’s growth and sustainability.
In her current role, she leads the content marketing team with experience in various fields, such as science, education, law, and management. She is a well-rounded individual with diverse interests and skills.