• Rebecca Anderson

Blog: What Is Data Cleansing and Why Is It Important?

Updated: Nov 17

(Written for Introhive)

Optimal customer data is non-negotiable for superior business outcomes. But dirty data often messes with an organization’s success.


In fact, it’s estimated that 40% of all business objectives fail due to inaccurate data. And the resulting losses in productivity and opportunity can have a considerable impact on profitability. According to a 2018 Gartner report, organizations believe that data quality is responsible for an average of $15 million per year in losses.

So how can organizations get client data back on track? The answer is setting up a standard, repeatable process to ensure data records are clean, accurate, and complete. And with thousands or hundreds of thousands of contacts in your CRM and other databases, that is not something you can do on your own.


Data cleansing can help and it’s not as arduous as you think—especially when companies take advantage of new advances in automation and artificial intelligence (AI). But what exactly is data cleansing and how does it work? Is it done by a third-party or by a software program? And, most importantly, how much does it cost? We answer those questions for you down below.


What Is Data Cleansing?

Data cleansing, also referred to as data cleaning, is the process of identifying and correcting inaccurate records from a database or another data set.The process typically involves removing typographical errors, validating, and correcting information to match a known list of entities. Depending on the sophistication of the process, validation may be rigid and reject records with incomplete information, or fuzzy in which case the system corrects the missing information. As part of the data cleansing process, data may also be harmonized and standardized.


The status quo for organizations is sending the contact database out for cleansing once a year. However, this doesn’t quell the day-to-day decay of the data. CRM records are in a constant state of degradation. There is inevitable decay based on changes occurring in a typical year including contacts with new jobs (30%), phone numbers (43%), titles (34%), and email addresses (37%). It’s estimated that data decays at a rate of 3% per month; this may sound small, but it quickly adds up.


Data enrichment takes data cleansing to the next level, supplementing the contact with relevant information such as additional phone numbers, or email addresses. This supplemental data is typically pulled from numerous sources including email signatures and social media profiles. For data cleansing to provide business benefits throughout the year, it needs to happen on an ongoing basis. Automated CRM data enrichment can help.


Why Is Data Cleansing Important?

As noted above, there’s no question that bad data is bad for business. In fact, 77% of companies believe that poor data is affecting the bottom line. Data quality also affects overall productivity by as much as 20% and seriously threatens organizational credibility.


With data that is just one year old, about one-third of contact records will have errors, In other words, one-third of customer outreach could be destined for failure. Phone calls don’t go through, emails bounce, and this wasted effort impacts the bottom line. As just one example, non-targeted email campaigns can cost 3.6 times more than targeted ones. And, if you manage to connect despite these errors, recipients may question the logic of pursuing a partnership with a vendor that can’t get their names or titles right.


Conversely, most organizations can expect a business boost due to clean data: 66% of organizations report increased revenue and leads are 25% more likely to convert into qualified leads.


The Cost of Data Cleansing

The cost of using a service provider to clean a database with 10,000 records typically runs between $5,000 and $10,000. The cost is split between removing duplicates—typically 5-10% of your database—and adding missing data from account records.


Depending on the state of data decay, your cost for appending records may be even higher. While a cost of $10,000 a small price to pay for good data, it is important to remember that list scrubbing is typically an annual or biannual activity. And, perhaps even more important, these isolated data cleansing activities are unable halt the impact of day-to-day data decay.


The 1-10-100 rule provides a simplistic view of the cost of data management at different stages. Hypothetically, it may take $1 to verify a record before it’s entered into a database; this is the cost to prevent mistakes. To fix the record by data cleansing and scrubbing at a later point costs more: in the simplified example, it’s $10 per record. But the real impact is in the cost of failure; this example puts a $100 valuation on the reduced productivity and lost opportunity of each bad record. Oversimplification aside: the real point is that it cost more to fix errors than prevent them.


A more effective way—both in terms of cost and output—is to use AI-driven software for data cleansing. These tools can prevent errors in the initial dataset and then correct data issues on an ongoing basis. So, your company never has to pay the price for bad data.


How Software Can Enhance Data Cleansing

Automated data enrichment simplifies and expedites the process of refining contact data—both at the outset and throughout the life of the contact record. There are varying types of data enrichment tool available which offer different levels of sophistication in AI and machine learning. Some are limited to removing duplicates and correcting minor data entry errors. More advanced services append data records to complete missing fields and suggest content updates to the CRM user.


Introhive’s data enrichment algorithm doesn’t just scrape email signatures like other data cleansing tools. Instead, it automatically pulls data from over a dozen sources to create contact and account records that are more detailed, complete, and accurate. The software also flags and removes contacts that are no longer relevant or contain duplicate data, identifies relationships and contacts that have new or updated data, and discovers new contacts to add to the CRM for business development and marketing purposes.


What’s more, using the Introhive CRM add-on for data cleanse and enrichment is much simpler than exporting a list and interacting with a service provider for deduping and data cleansing. Here’s how it works:

  1. The Introhive tool connect to an existing database of contacts

  2. The Introhive tool completes and corrects contact records

  3. The Introhive tool removes duplicate records

  4. You appreciate optimal contact data all year long

Data Clean-up that Doesn’t Clutter Your Schedule

Most business leaders don’t want to spend thinking about data cleansing. Yet, contemplating lost revenue resulting from poor data is even less fun. Fortunately, advances in AI technology has transformed the data cleansing process; systems like Introhive Cleanse automatically do the dirty work of data clean-up so organizations don’t have to think about it at all.


Introhive Cleanse combined with our signature scraper and data enrichment services ensures that your contact data is good from the initial import through all future data exports. In fact, Introhive Cleanse extracts 70% more data than traditional signature scraping technology, resulting in data that is 90% accurate. Contact us to learn more about Introhive Cleanse.

 

©2018 by Rebecca Ann Anderson