Dirty marketplace database is the biggest hurdle that stands between your clients and their business goals. If their marketplace data is dated, what ROI on their sales and marketing efforts will they miss out on? Here are 7 data hygiene tips to keep your marketplace database clean.

1. 7 Tips to Keep Your Marketplace Database Clean
Data Hygiene

2. 7 benefits of robust data hygiene regime…..
Data hygiene helps you to maintain marketplace database free of
duplicate data, inaccuracies, and inconsistent information.
Develop and strengthen customer segmentation
Ensures that you have a single customer view
Removes data errors and inconsistencies
Improves ROI on Sales and marketing efforts
Reduces overall data management costs
Improve operational efficiency and productivity
Enhances brand credibility as a data aggregator
1
2
3
4
5
6
7

3. 7 Tips to Robust Data Hygiene
Assess existing database
Develop a data hygiene plan
Standardize data entry
Data validation
Remove duplicates
Append fresh data
Automate and regularize data hygiene
1
2
3
4
5
6
7

4. 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

5. 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?

6.  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
Standardize Data Entry

7. 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

8.  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
Remove Duplicates

9.  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
Append Fresh Data

10.  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
Automate Data Hygiene Regime

11. 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
Case Study

12. Are you looking to automate the data hygiene regime for
your marketplace database and optimise costs?
www.hitechbpo.com | info@hitechbpo.com
Outsource your marketplace data management needs to us.