7 Data Hygiene Best Practices to Keep Your Marketplace Database Clean

Data Hygiene 7 Tips to Keep Your Marketplace Database Clean

Data hygiene helps you to maintain marketplace database free of duplicate data, inaccuracies, and inconsistent information.

7 benefits of robust data hygiene regime…..

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Develop and strengthen customer segmentation

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Ensures that you have a single customer view

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Removes data errors and inconsistencies

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Improves ROI on Sales and marketing efforts

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Reduces overall data management costs

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Improve operational efficiency and productivity

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Enhances brand credibility as a data aggregator

7 Tips to Robust Data Hygiene

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Assess existing database Automate and regularize data hygiene Develop a data hygiene plan

Standardize data entry

Append fresh data

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Remove duplicates

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Data validation

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Audit your Existing Marketplace Database

 Find out how much of your existing data is dirty  Identify dirty data fields and solutions to fix them  Use benchmarks to keep your database clean  Can the data be used to generate potential leads  Can the data be used to advance a sales pitch  Which data fields are necessary and accurate  Authenticate sources used to collect

Develop a Data Hygiene Plan

 Set quality key performance indicators (KPIs) for your data  How will you meet data quality goals?  How will you track the health of your data?  Will you use data hygiene management tools?  Will you hire B2B data hygiene experts?  How will you maintain data hygiene on an ongoing basis?

Standardize Data Entry

 List out data fields that need standardization  Convert numbers, monetary values, etc.  Convert abbreviations to long forms or vice versa  Enable/disable case sensitivity according to strategic needs  Normalize Ms. and Mrs., and spellings as per US/ UK dictionary  Mandate input values to be of a certain threshold  Specify data entry range to prevent unwanted values

Data Validation

Cross-reference validation Compare incoming data with a reliable dataset Data type validation Identify data type inconsistencies associated to the value Range checking Specify constraints on numeric data for particular fields Complex data validation Verify data as per custom parameters – all at the same time Triple Verify data Multi-level verification through web, human, and email verification

Remove Duplicates

 Develop business rules to merge and remove duplicate records  Use data cleansing tools to analyze bulk raw data and flag duplicates  Delete duplicate rows using DELETE JOIN statement  Use the ROW_NUMBER () function to suit your database

Append Fresh Data

 Use authentic third-party data to append your database  Add new data elements to enrich and make it rich  Capture information from first-party sites like LinkedIn  Use tools to clean and compile the listing database

Automate Data Hygiene Regime

 Use automated solutions to clean or de-dupe databases  Use algorithms to detect anomalies and identify outliers  Use business rules driven solutions to enrich, append  Use help of outsourcing experts to manage data hygiene

Case Study

Hitech BPO cleansed and enriched 17+ Million records for a data aggregator from France. It improved the CX and revenue of their clients in the hospitality sector.

Solution Used macros, scheduled bots and rule-based scripts to automatically validate and quality check data.

Business Impact 2 million verified records pushed into CRM every year Increased accuracy of CRM database Improved customer experience Better marketing ROI and sales revenue

Are you looking to automate the data hygiene regime for your marketplace database and optimise costs?

Outsource your marketplace data management needs to us.

www.hitechbpo.com | info@hitechbpo.com