What Is Data Enrichment? How Companies Can Benefit From It?

Data Enrichment is the hot topic in marketing, since the advancement of technology.

Data_Enrichment

In a word, it’s the best tool for the organisation to take your business to an advanced level by enhancing the quality of your organisation’s data.

Data enhancement is crucial for assuring that your organisation’s data is up-to-date with a high degree of accuracy. A little negligence in this will have a drastic impact on your business.

Today’s digital world has changed the customers perspective to knob their day to day activities.

Every day, they need something ancillary, and meeting their demands is a daunting task for the organisations, if not aligned with the technological changes.

What do you think Data Enrichment is all about? That too, why it’s so significant for business.

Here in this article, I will help you in getting clear insight about data enrichment and its place in generating lead to your business.

Let us first define Data Enrichment-

Data enrichment is a suite of processes designed to refine and enhance information to boost its value.

Here, the main motto of the evolvement of data enrichment concept in customer data management is to get the most out of data, making it easier to access, with cut corners or without generating new risks.

Let’s take a deep insight of data enrichment-

Data enrichment roots from the concept data integration process which mainly involves three steps: Extract, Transform and Load (ETL).

To describe ETL process, it commences with ‘extract’- means pulling the data from external sources, ‘transform’- means validating the collected data and modifying it to the desired standard, and ‘Load’- means storing the data at the destination.

Data enrichment is the state of the art concept in the data integration process to get a clear and deep insight into customer needs.

And, it improves the revenue of the organization.

Well, it sounds good! That customer data enrichment is adding value to your business and improving revenue, at the end of the day we look out for the same.

How it works- An overview

Data is something which is crucial for every organization to generate leads.

Data is producing in every organization with exponential speed, and in the recently published report from IBM Marketing‘, it was stated that 90% of the data in the world today has been produced in the last two years alone, that is 2.5 quintillion bytes of data per day.

And, it’s supposed to accelerate more with the emerging new devices, sensors, and technologies.

The organization generally do this to add more precision to their existing data for more informed decisions; this is where the tire meets the road.

Usually, data comes to the organization in a raw format and flows in central data stores. It needs to be structured in some form to make it more useful. Otherwise, it’s like money to burn.

Where do I start?

It would be better to look at manual vs automated processes first.

Manual Process:

The manual strategy is the traditional way of doing data enhancement.

Yeah, humans are more ingenious than a computer in taking better insight and take steps based on the situation. Humans can better understand data and spot error. And can categorize an image according to its content than a computer.

However, adapting the manual process is fine, but, daily, we have the bulk of data and examining it by humans is something a never-ending task.

Automated Process:

The automated process follows a list of algorithms, approaches, implementations, and integrations.

For fixing-

  • spelling mistakes
  • Appending datasets
  • Checking for duplication
  • Filling missing attributes, updating information
  • Categorizing customer data based on their interest

All this can be performed automatically by using machine learning techniques.

Customer data enrichment has basic three steps-Match, Clean and Append.

In this process, data appended to the existing data from the external authoritative source.

The first step is matching, where the existing data compared with the data arrived from the external sources.

Next comes to correcting invalid data according to other data in the record.

Then the last step is appending missing attributes based on others available data.

However, there are some circumstances which are specific to some segment of the audience. For example, while we are filling the form for the pregnancy-related claim, the system might take it as a missing value for others.

Data enrichment involves collecting data attributes for several categories, but two of the most commonly used types for customer data enrichment are:

Geographic Data Enrichment:

It includes adding the postal address in more refining manner by considering-

  • Latitude & longitude
  • ZIP codes
  • Mapping insights
  • Geographic boundaries between cities and towns and so on.

In the market, you can find some vendors who provide this type of refined information.

Adding data in a more sophisticated manner can help the retailer to find their next store location. For example, they can open a store within a specific distance to grab the attention of the targeted audience.

Marketers could also use enriched data to save time and cost on bulk mailings of direct mail.

Demographic Data Enrichment:

It involves collecting more detailed information of customers based on demographic factors such as income level, debt status, credit card dues, marital status, number of children, average size of family, number of dependents, education, age, religion, average age at marriage, median home value, occupation, types of car driven, and so on.

To illustrate, data enhancement helps you to better categorize your customers based on their needs.

Let us say, If you’re offering a credit card, this demographic information might help you to get the credit status of the candidate, and you can promote more specific to targeted customers.

Some of the other factors include:

Behavioural:

It depends on the difference in expenditures of customers like their lifestyles, frequency of buying and selling, credit risk, preference for spending time and cost, preferred communication channels and similar other.

In short, its primary objective is to be more specific to the niche which requires customized promotion.

Psychographic:

Its based on analysis of customer lifestyles to build a detailed customer profile which ranges from hobbies and interests to political affiliation.

Marketing researchers implement this by taking feedback from the customers by asking –agree or disagree with activities, their opinions statements, and interests.

The psychographic feedback is integrated with the geographic and demographic factors to execute more informed decisions based on targeted customer segment.

Census:

It involves household and community data

Furthermore, there are many other factors which can add weight in customers profile by focusing granular level of attributes on targeting leads driven audience.

In the end, the granular level of customer data and golden customer record is the key for the business to take their next step ahead and survive in the market.

The more you know your customer, the more you can offer them, specific to their needs.

What do you think? Is data enrichment is one time or going on process.

Data enrichment process is not something which is done once and never do again. No matter how precisely you have collected data it needs to keep one’s eye on the ball for getting a high level of response every time.

Obviously, Customer data frequently alters like- marital status, address, surnames vary if married, increase or decrease in salary, income level, type of car they drive, number of children and many more factors; and it needs a real-time focus on customer data for targeting lead driven customers.

For instance, If you’re using six months old data, lots can happen in the life of customers during this period, and their preferences and interests may change.

And, you’re sending mail to them based on past data is like hitting head against a wall. Most of the companies spend most of their time in cleaning data than using it.

Practicing machine learning algorithms for database enrichment is best as it runs on a real-time basis & on round the clock and considerably streamline the data enrichment process.

It allows brands to be updated with customer demands on a continuous basis and can enhance the level of customer engagement.

A full swing data enrichment process is really a bang for the buck for brands. It ensures utmost accuracy in targeting leads to better experiences and guarantees your success rate with most up-to-date customer data possible.

Indeed, database enrichment is like fill the bill for their business running.

Consider an example for better understanding of the benefits of data enrichment:

In every organization, data produced every day, but above all, they don’t know that data can be a ladder to reach their business goals. How to make use of available data is something which many business people are unaware of it.

Consider, if you have some information about your customers, you can enrich it with more attributes for a better insight into your customer.

Like, if you’re marketing for some car and you want a maximum hit. What do you do? You will send promotional mail to the targeted audience or send it to all the customer contacts you have.

Of course, you prefer to send mail to some targeted audience.

How can you do that?

By knowing your targeted audience on a granular level. Look for people favorably inclined to buy a car like someone:

  •    Found of buying a car even though they have.
  •    Has a big family and the need for a car is de rigueur for them.
  •    Feel like having a car to utilize their credit limits.
  •    A sudden increase in income level.

Focus on demographic, geographic and behavioral factors to filter out your audience.

The more you focus on granular level filtration of your audience the more you can convert your audience to your leads.

Because here you’re offering them what they are looking for at the moment based on real-time data. Similarly, if you’re sending this promotion mail after they purchased a car, there is utterly futile to do so. In advance level of marketing, email data-enrichment is the key for brands to hit their targets.

To my knowledge, you are lucid with the concept of data enrichment process and its benefits to companies to corner the market.

Let’s list them out in a terse:

  •       Increased web form conversions.
  •       It ensures the accuracy of organization data on a granular level for a targeted audience.
  •       It improves business decisions in the long run.
  •       Enhanced employee productivity, reduce turnaround
  •       Improves relationship with the customer
  •       Can be updated with customer preferences and interest
  •       Enhances customer acquisition
  •       Greater cross-selling opportunities
  •       Reduced costs in settling claims
  •       Enhanced customer loyalty
  •       Improved competitive position
  •       Increased fraud detection rates

In a nutshell:

Data enrichment paved the new way for the business to be more close to their targeted audience and make more informed business decisions. It’s like something that makes business to go the extra mile by match, clean and append customer attributes on a granular level.

Data enrichment for brands is something without it they are not going to fly in the market. Database enrichment will work as a booster for the organization to survive in the competitive market and also help them stick to their goals.

Whatever the business you’re in, if you’re looking to build your brand don’t wait to adopt it. Data enrichment is crucial to take your business to a new level.

Hope you got a good insight into data enrichment. Please do comment and reply some other benefits which I might have missed in this article.

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