Home Business Marketing How To Improve Marketing ROI With Data Enrichment

How To Improve Marketing ROI With Data Enrichment

How To Improve Marketing ROI With Data Enrichment

Data drives crucial business decisions in the current industrial system. It has the power to change the fate of a business by systematically aligning various Marketing ROI departments with the firm’s growth vision through a focussed and verified database. 

But, if you have compiled a pile of loosely verified, unsupervised data, using it will only result in a waste of marketing resources. On the other hand, engaging data enrichment services or initiating data cleansing in-house can equip you with reliable information to carry out business operations efficiently.


Why Do You Need Data Enrichment

Businesses need quality data for efficient daily operations. Your firm requires data cleansing for the following reasons:

  • To remain competitive in the market
  • To enter a new market segment
  • To make informed decisions based on analysis
  • To improve sales approaches to customers
  • To remain authentic and protect against fraud
  • To improve your client targeting operations
  • You cannot rely on data entry to create a required database as it may have manual errors, outdated information, or repetitive data points


How To Achieve Data Enrichment

  • Set Your Data Cleansing Goals

How is data going to help your business? Where are you going to utilize it in your operational cycle? And what exactly is the nature of the data you need?

Answers to these questions can help you set goals for your database requirements. Set realistic parameters and identify key characteristics of data needed for your enterprise. Creating an SOP and KPI will help data aggregators inform data enrichment services of their respective requirements.

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To plan your data cleansing process:

  • Identify the objectives of your database
  • Set an SOP for data entry
  • Set a KPI for monitoring data metrics
  • Identify entry points for faulty data  


  • Data Entry Automation

Businesses are struggling with bad data, particularly at the entry point. It consumes a good percentage of their time in identifying and rectifying manual errors, incomplete entries, and outdated information. Using unscrutinized data leads to a wastage of marketing and sales efforts.

To protect against bad data from entering your database, machine learning, RPA, and AI can be utilized. Data processing services can assist you in the following ways:

  • Error correction in real-time.
  • Collecting and processing data from multiple sources.
  • Examine data for accuracy before it is fed into the database
  • Operate as per SOPs


  • Rectify Duplicate Data

Databases filled with duplicate entries are useless for business operations. Identical entries waste storage space, lead to inaccurate analysis, and put marketing and sales efforts in vain.

Examine and deduplicate your database through the process of merging and purge. It will protect you from losing important information by compiling identical entries and then deleting repetitive entries.


  • Process Outliers

Outliers are the odd data values in your database. They may lead to errors in machine learning models prepared from your database. Outliers happen due to data mutation, human or machine errors, data manipulation, mixing, execution, or extraction errors. Setting up filters, data visualization, and linear regression can help you detect outliers.


  • Do Away with Missing Value

Incomplete data disrupts the analysis findings. It also discourages marketing efforts. If you aren’t careful at the point of data entry, the only option to resolve missing information can be by dropping off the whole dataset. But, this solution can be tedious in the case of a large database. Missing values in datasets can be managed by data regression and automation.

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  • Relevance Analysis

It is done to convert data into actionable information by building a connection with its usage. It is achieved by assigning context to the data. You can use automated platforms that segment values into data quality metrics.


  • Regular Audit Review and Supervision

Data cleansing is not a one-time job. Faulty information can enter the system through human error, fake information from clients, etc. You need to keep auditing the database at regular intervals for bad data. So, set a data monitoring strategy, use automated supervision, and re-audit databases too for updates.


Benefits of Data Enrichment

Equipping your business with a clean database can be advantageous in the following ways:

  • Data enrichment helps create a valid contact list for marketing, improving email conversions.
  • It creates better analyses that provide business leaders with more ground for focused decision making.
  • B2B data cleansing empowers your marketing initiatives and protects you against the wastage of resources on irrelevant leads.
  • Data enrichment services assist in improving customer service. Based on contact list data, businesses can strategize their client approach accordingly.
  • Data cleansing helps you get rid of duplicate data. It is one of the biggest challenges for business.



Data enrichment is a necessity for businesses who aim high, wish to remain competitive, and want to outgrow their counterparts. Depending on their needs, every business does not require a full-time infrastructure and human resource setup for data cleansing. Thankfully, due to the presence of data enrichment services, businesses can simply engage a third-party vendor and get hold of a cleansed, focused database.

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