What is Data Enrichment? Everything to Know

Introduction to Data Enrichment

Modern businesses rely on data and metrics to make informed decisions on various strategies. However, collecting data is only half of the battle. Companies must refine and collaborate their datasets to ensure they have the most valuable information.

Otherwise, businesses could continue to maintain duplicate and inaccurate data. With data enrichment, organizations can refine data analytics to actionable insights to improve their services.

What is Data Enrichment?

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Data enrichment refers to a series of processes of combining various data sets from internal and external sources. This method collaborates and refines information into a more comprehensive, holistic asset. By incorporating data from within the company and third-parties, businesses can gain a well-rounded perspective on a topic. This enables managers to develop more effective strategies and useful insights.

Enriching data is crucial for businesses as information typically starts in a raw form and needs to be reformatted. Without converting the data, companies keep with large volumes of unstructured information.

With data enrichment, organizations can standardize and boil down company data to the most impactful insights. For example, e-commerce stores track online customer engagement, such as conversions, click-through rates, page bounces, and interactions. Without data enrichment, this data would simply pile up without pointing to any conclusion. By refining information, the business can detect recurring patterns and variables to detect customer pain points, interests, and product preferences.

There is no one way to perform data enrichment. Some businesses hire an external analyst to compile data, while others utilize their IT department. However, many modern management solutions have data enrichment tools that comb through databases to eliminate errors, inaccuracies, and inconsistencies. This way, when systems integrate, information can share without running into contradicting details.

2 Types of Data Enrichment

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While there are various types of data enrichment, the two most common types are demographic and geographic data enrichment.

Demographic Data Enrichment

Demographic data enrichment involves categorizing customer data based on the clients' various characteristics.

  • Marriage status
  • Age
  • Gender
  • Education
  • Family status
  • Income

Depending on the type of business and data sources, this list of determinants can expand exponentially. For example, a car dealership may also collect details about the customers' current car, mortgage value, and career. They can gather this information from in-person interactions, online surveys, and promotion engagements. By collecting demographic data, companies can perfect their marketing campaigns and pitches to their target audience. It also provides an opportunity to identify and appeal to new markets.

Geographic Data Enrichment

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Geographic data enrichment considers customers' physical locations, such as billing addresses and postal data. If businesses don't have this information, there are several third-party services that enable them to buy consumers' personal data. These vendors will release specific information depending on the purchase amount.

  • Zipcodes
  • Geographic boundaries of cities and towns
  • Mapping insights
  • Longitude and latitude coordinates

While this information may seem like overkill, it allows businesses to finetune their datasets for different contexts. For example, restaurants use geographic data to determine where they should establish their next location. Retails will also use data to develop marketing campaigns in various areas.

Benefits of Data Enrichment

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Data enrichment grants businesses several benefits that can improve overall decision-making.

Cost Savings

Studies show that one petabyte of big data can cost a business approximately $650,000 to maintain. Yet, companies often only use a small fraction of their information, making the remainder of the data useless. By refining data through enrichment practices, organizations can significantly reduce data management costs.

Improve Customer Relationships

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With enriched data, businesses can personalize the customer experience and engagements to foster business-customer relationships. Managers can even finetune communication methods so they can appeal to client's needs and preferences. When done correctly, companies can boost customer acquisition and retention.

Enhance Customer Appreciation

Along the same lines as customer relationships, date enrichment also nurtures customer involvement with the business. Based on data, companies can create customer segments and focus on different strategies for each group. While personalized initiatives, customers feel the organization truly appreciates their patronage.

Optimize Target Marketing

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Most businesses already use some form of target marketing as generic promotions have proven to be less effective. However, companies are unable to develop targeted campaigns without critical customer data. With data enrichment, organizations understand when, where, and how to appeal to their audience.

Boost Sales

Data enrichment also improves return on investment (ROI) as businesses no longer have to rely on guesswork when generating leads. Instead, companies can focus their time and investments on a calculated list of clients, boosting sales and profits. Data enrichment also opens up opportunities for upsells and cross-sells to increase the average order value (AOV).

Eliminate Duplicate Data

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Duplicate data can take up an unnecessary amount of storage, increasing management costs and decreasing operational efficiency. However, redundant information is common in companies as many are unsure of which dataset to keep. With data enrichment, businesses can integrate systems to create a master file of critical information. This method eradicates duplicate metrics, improving data integrity and consistency.

Improve the Customer Experience

Data enrichment processes are the only sure-fire way to keep up with customers' evolving needs. Otherwise, companies have to continually chase competitors' strategies. With data enrichment, managers can monitor emerging market trends to meet consumer preferences. By continuously improving the customer experience, businesses gain a competitive edge within their industry.