Key Takeaways
Data & analytics drive growth when they’re aligned with business goals.
Enriching data means adding relevant details like geolocation, socio-demographics, firmographics and behavioral insights.
This enrichment reveals meaningful patterns & trends and improves the quality of datasets for AI model training.
Data is today’s currency. Businesses seek to use it to their advantage, but raw, scattered data has no value.
Outsourcing data enrichment is one way to turn your unorganized information into meaningful and actionable insights.
Why outsource it, though?
To begin with, setting up an in-house team is time-consuming, expensive and difficult. The unavailability of local talent, lack of resources and workflow disruptions are just a few of the challenges you may face.
Outsourcing to remote data engineers and data scientists saves you from these troubles, while also enabling better lead generation, personalization and customer engagement.
Explore how outsourcing data enrichment services can help your business grow!
What Is Data Enrichment?
Data enrichment is the process of adding relevant information to your existing business database. This helps fill in missing details, update outdated records and gain deeper insights into demographic or behavioral data.
Before enrichment, data must be preprocessed through assessment, cleaning and categorization to ensure quality.
Many businesses outsource data entry to streamline this phase and create a solid foundation for enrichment.
For B2B businesses, data enrichment is essential to maintain accuracy, get comprehensive customer insights and make more informed decisions.
Data Enrichment vs Data Enhancement
Data enrichment is often confused with data enhancement. However, there are key differences between the two.
| Factor | Data Enrichment | Data Enhancement |
|---|---|---|
| Purpose | To expand existing data by adding new, relevant information. | To improve the quality, accuracy and reliability of data. |
| Process | Involves appending additional data from internal and external sources to current records. | Focuses on cleaning, standardizing and validating existing datasets. |
| Outcome | Enables businesses to gain deeper insights and build strategic plans for the future. | Enhances data accuracy and quality for better analysis and decision-making. |
While the two processes serve different purposes, they also overlap.
Data enhancement methods like cleaning and standardization are essential prerequisites for data enrichment.
What Data Enrichment Services Can You Outsource?
In this section, we’ll discuss the data enrichment tasks you can outsource to offshore data professionals.
Data Cleaning
Data cleaning is an essential data preprocessing task. It helps maintain the quality and integrity of data.
After cleaning, the data becomes suitable for training machine learning models, creating visualizations and performing data enrichment.
Data cleaning involves tasks like:
- Removing duplicate records
- Correcting errors and inconsistencies
- Filtering out outliers
- Handling missing data
- Matching structural requirements
- Verifying and validating information
- Converting records to standardized formats
- Maintaining data quality
You can outsource these manual data cleansing services to data entry virtual assistants.
They help maintain accuracy, consistency and completeness of data, preparing it to be combined with other sources.
This saves you time and effort by reducing the need to fix errors or deal with complications later on.
Data Appending
Data appending involves enhancing existing records by adding new information from internal datasets or third-party sources.
For example, you can combine data from your internal CRM with insights from marketing campaigns or social media platforms.
External sources can include geolocation data, contact databases or email lookup services.
When you outsource data enrichment to skilled data engineers and data scientists, you gain a fuller picture of your business, from customer insights to performance metrics.
These insights help personalize customer experiences, enhance marketing efforts, generate leads and identify your target audience.
Read more: Top Benefits of Outsourcing Data Entry for Businesses
Data Manipulation
When primary data is combined with different datasets, many records may be incomplete.
During the data cleaning process, missing or unknown data is substituted to ensure completeness. However, replacing these values with zeros or NANs can distort calculated aggregates and restrict analysis.
Using such poorly substituted data produces inaccurate predictions and insights.
This is why data manipulation tactics are adopted. Replacing missing numerical values with mean, median or mode values based on previous data is one of them. Another tactic is using regression to predict missing values.
Data scientists can also support data manipulation by converting categorical data to numerical data using encoding techniques.
This makes data usable for developing prediction or classification machine learning models.
Entity Extraction
Most raw data is unstructured or semi-structured. Data scraped from web pages, emails and social media often needs to be processed before it’s usable.
Multimedia content like images, videos and audio files also requires metadata tagging to become actionable.
Data labeling virtual assistants can parse data and recognize meaningful information. They can annotate and label raw data, combining related information to form a useful, structured entity.
Aside from manual efforts, virtual assistants can also help label data for named entity recognition (NER) models. These models are trained to understand unstructured data and classify entities in it.
Sentiment Analysis
Sentiment analysis is a technique in natural language processing (NLP) that analyzes text data to identify the emotion and tone expressed in it.
Businesses use sentiment analysis to understand how customers feel about brand products and services across social media platforms. It’s also used to sift through huge volumes of product reviews, survey responses, feedback or call transcriptions.
This technique helps companies understand their customers better and strengthen their responsiveness and brand reputation in the long term.
Outsourcing to virtual assistants can be a cost-effective way to train a custom NLP model for your business. Data annotation VAs can label unstructured text and convert it into a structured form suitable for analysis.
Data Segmentation
Data segmentation involves categorizing records based on a set of predetermined characteristics.
Business data can be segmented on different bases such as:
- Geographical (location, city, state or country).
- Demographic (age, gender, occupation, race, ethnicity or income).
- Behavioral (online activity, duration of use or search history).
- Psychometric (personality, lifestyle, hobbies or values).
Appended data contains relevant fields that can be correlated to draw meaningful conclusions.
Data scientists can analyze and map the appended data according to segments. They can also curate custom segmentation categories according to your business goals.
Derived Attributes
Deriving attributes is another key technique in data enrichment.
Appended information helps create new attributes by combining existing data columns using estimation or prediction.
For example, the average time between two purchases can be calculated using the purchase dates.
Additionally, grouping related attributes can reveal patterns or uncover fresh insights. You can group customer engagement by age, geographic location and gender to understand your target audience better.
Data analysts also help you find potential customers, filter regular customers and provide up-to-date insights to fuel your business decisions.
Types of Data Enrichment You Can Outsource
Different types of data serve different business goals. While geographic data shows where your customers are from, behavioral data reveals what they care about.
Here are the key data enrichment types you can outsource.
Socio-Demographic Data
Socio-demographic data includes information like age, gender, education, occupation and income.
Businesses use this data to understand customer preferences, segment audiences and tailor marketing messages for specific groups.
Geographic Data
This covers location-based information like country, city and postal codes.
Geographic data helps in local targeting, uncovering regional trends and identifying top spots for retail stores based on customer proximity.
Behavioral Data
Behavioral data tracks how users interact with your brand, including website visits, clicks, purchase history or social media activity.
It helps understand user behavior, predict future actions and personalize marketing campaigns for higher engagement.
Firmographic Data
Firmographic data refers to information about companies, such as industry, size, revenue and location.
This is especially helpful for B2B businesses looking to find high-potential clients and create personalized sales approaches.
Technographic Data
This involves details about the technologies a customer or business uses, from hardware and software to platforms and apps.
Technographic data can be used to target users of specific tools, analyze competitor tech stacks and improve existing products based on user preferences.
Psychographic Data
Psychographic data relates to interests, values, attitudes and lifestyle choices.
Enriching this type of data allows businesses to connect with customers on a deeper emotional level and deliver more personalized experiences.
Why Should You Outsource Data Enrichment?
Outsourcing data enrichment services offers numerous advantages. From improved data quality to more personalized customer experiences, let’s discuss the main benefits of data enrichment.
Cost-Effectiveness
Outsourcing cuts down a lot of costs for businesses. Hiring a virtual team for data enrichment instead of an in-house team saves your business from hiring, recruitment and training costs.
Some outsourcing companies like Zenius even manage your day-to-day HR activities for the outsourced employees. So, you don’t have to take care of payroll, employee benefits and taxes.
Moreover, you can reduce overhead charges on office space, utilities and equipment.
Scalability
Offshore remote teams are much more flexible than in-office employees. The amount of work they handle can be easily adjusted based on your needs.
During peak seasons, there’s a surge in sales, customer engagement and social media activity. Handling large amounts of data during this time requires more resources.
In contrast, during slow periods, business activity reduces and data processing isn’t a key priority.
When you outsource data enrichment, you can scale your team up or down as needed. This flexibility helps you manage costs more efficiently and make smarter financial decisions for your business.
Enhanced Data Quality
Poor-quality data hampers your business. It wastes time, adds extra work and slows down processes.
Outsourcing data enrichment helps you maintain data integrity throughout.
Data engineers ensure your data is error-free, standardized and consistent, increasing operational efficiency and boosting productivity.
Moreover, enriched data provides a wider perspective with more detailed attributes.
You can use this clean, high-quality data for various purposes such as data analysis, visualization, machine learning model training, marketing strategy development and customized customer engagement.
Better Outreach and Engagement
One of the main goals of outsourcing data enrichment is to extract comprehensive insights from raw data.
Data engineers and analysts help by appending datasets, cleaning data and deriving new attributes.
This enriched data reveals meaningful patterns and trends. Detailed firmographic, demographic and behavioral insights let you segment both potential and existing customers based on custom attributes.
Such insights are vital for your sales and marketing teams, helping them target the right audience at the right time.
You can also integrate enriched data into your customer relationship management (CRM) and marketing systems to get real-time updates.
This improves both customer interactions and internal communication, leading to stronger outreach and engagement.
Personalized Customer Experiences
Today’s customers expect exceptional, personalized experiences.
John R. Hoke III, Chief Design Officer at Nike, highlights the importance of personalization:
I am fascinated with the idea of the brand becoming a platform, not just for self-expression, but to create uniquely bespoke products in a one-to-one relationship that helps them feel empowered and strong and able to express.
Enriched data gives you the insights needed to craft such tailored customer experiences.
It helps you understand your audience’s needs and expectations better, allowing you to run more impactful marketing campaigns.
Personalization also fosters stronger customer relationships and builds a powerful brand image, resulting in higher rates of customer satisfaction, retention and loyalty.
Signs You Need To Outsource Data Enrichment Services
Wondering if you should outsource data enrichment? If any of the points below feel familiar, hiring a remote data professional can be the right move.
Large Volume of Data
If your business handles large volumes of data, outsourcing data enrichment can help transform that raw information into a valuable asset.
This includes data from CRM systems, social media, sales records, surveys or marketing campaigns.
With a virtual team helping you manage your data, you can save dollars on setting up an internal team and building an in-house setup.
Data Quality Issues
Raw, unstructured data is rarely usable in its original form.
While structured data in spreadsheets or databases is easier to process, both types become problematic when the data is unstandardized, unverified, unvalidated or filled with errors.
If you’re dealing with inconsistent, unreliable data, outsourcing data enrichment can be a lifesaver.
Your remote team will clean, validate and standardize your business data so it’s accurate and ready for use.
Duplicate Records
Duplicate records occur when the same information, such as a customer name or email address, appears multiple times in a database.
Besides taking up storage space, such records lead to inaccurate analysis and wasted marketing efforts. If your database is cluttered with repeated entries, it’s time to outsource data enrichment services.
Data engineers can identify and remove duplicates, helping you maintain a clean, reliable and accurate dataset or data pipeline.
Low Customer Engagement
Low customer engagement across social platforms translates to low sales and profits for the business.
This can indicate that your marketing strategies aren’t in tune with customer demands.
A dedicated data engineer can enrich your business data, providing valuable insights into your target customers, their buying behavior and peak engagement hours.
Using this information, you can personalize your marketing efforts to boost engagement.
Lack of In-House Expertise
If your current data and analytics team lacks expertise, outsourcing data enrichment can be a favourable option.
Outsourcing also helps you reach beyond local prospects and dip into the global talent pool. You can find the best fit for your business and organizational values.
Moreover, a team of future-ready professionals can leverage the latest software for data enrichment, cleaning, manipulation, organization and analysis to boost efficiency.
How Is Data Enrichment Changing in 2025?
According to Grand View Research, the data enrichment solutions market size was valued at $2.37 billion in 2023. It’s expected to grow at a CAGR of 10.1% in the forecast period of 2024 to 2030, reaching $4.58 billion by 2030.
Based on end use, IT and telecommunication led the data enrichment market in 2023, followed closely by retail businesses. As market competition becomes fiercer, the need for enriched data is expected to grow in these sectors.
This growth is largely driven by evolving customer expectations.
Surveys show that 73% of customers expect companies to cater to their unique needs. For 88% of buyers, the whole customer experience is as important as the products or services from the company.
From the statistics, it’s clear why businesses are increasingly using enriched data to meet consumer expectations and create impactful experiences.
Organizations are also beginning to treat data as an asset.
According to Gartner, “by 2026, chief data and analytics officers (CDAOs) who become trusted advisors to, and partners with, the CFO in delivering business value will have elevated data and analytics to a strategic growth driver for the organization.”
The rise of AI and machine learning is accelerating this shift. Businesses are building AI models using enriched data for predictive analytics and campaign targeting.
However, most small to mid-sized businesses still lack the resources for effective data enrichment and analysis.
Outsourcing data enrichment to data specialists overseas is a smart, cost-efficient solution for companies facing this challenge.
Wrapping Up
Whether you’re dealing with large volumes of data, poor data quality, low customer engagement or a lack of in-house expertise, we’re here to help.
Data engineers, data scientists and data analysts upgrade your data quality, helping you boost productivity, improve efficiency and maximize reach and engagement.
At Zenius, we are dedicated to finding the right fit for your business.
Through our rigorous screening process, we vet and verify candidates’ qualifications, experience and expertise.
We take care of not just recruitment but also hiring and onboarding, freeing you to focus on core business tasks instead.
