The old saying “garbage in, garbage out” has been around since the early days of modern computing. Code for operator error or bad data, the adage implies that the output of a program is only as good as the input supplied by the user. With more data being collected, stored, and used than ever before, data quality at the point of entry should be a top priority for all organizations.
Now that data is informing more aspects of our businesses, it’s not difficult to imagine a future where data accuracy is vital. Think of delivery drones, which have been tested all over the US and UK in recent years. If a contact’s bad address information goes unchecked, it could feed a drone the wrong coordinates resulting in misdeliveries and lost products.
Data quality affects every aspect of your business, from sales and development to marketing and customer care. Yet a 2017 survey by Harvard Business Review found that “47% of newly-created data records have at least one critical (e.g., work-impacting) error.” So, what constitutes garbage input? It depends on the data and how it enters your system.
What Is Bad Data?
Of course, there are many kinds of data an organization may choose to collect, but here we will focus on one of the most critical – contact data. This includes a contact’s name, address, phone number and email, all of which are crucial to marketing, sales, fulfillment, and service.
Some common issues that make a contact record bad:
- Inaccuracies like bad abbreviations or missing zip code
- Typos caused by speed or carelessness
- Fraudulent information
- Moving data from one platform to another without appropriate mapping
- Data decay as contacts move, get new phone numbers, and change positions
So, how does a bad contact record make it into your database?
Contacts entering their data online, whether downloading a whitepaper or ordering a product, are usually the first to commit a data quality error. Filling out an inquiry form on a mobile device, rushing through a purchase, or providing inexact information (such as missing “West” before a street name) are all examples of bad data leading to inaccurate contact records.
Your sales and customer service team can compound poor data quality by manually updating information that looks incorrect and making mistakes in the process. Good business practices can help mitigate operator error, but if a record was poor to begin with that likely won’t matter – you already know what happens to garbage when it ages.
What Is the Cost of Bad Data?
Much like garbage, bad data only gets worse over time.
Poor data quality can cause an organization’s sales team to waste time and effort chasing bad leads. According to a 2018 study by SiriusDecisions, B2B databases contain between 10% to 25% of critical contact data errors. That means up to 1 in 4 leads could have bad phone or email information attached, so follow-up communications may never reach the intended contact.
The customer service department loses time and money first in dealing with unhappy customers – even if they provided poor contact information, they’ll still blame your business for a package that never arrives. Additional time is spent troubleshooting problems and clarifying bad information, leading to major inefficiencies and frustration.
Overall costs to businesses include reputation related losses that occur when upset customers take to the internet to air their grievances. Time is lost due to the hidden data factories that arise within an organization when individuals working with bad data take it upon themselves to make “corrections” without understanding why or how the data is incorrect. Lastly, poor data robs a business of the ability to take full advantage of business tools like marketing, sales automation systems, and CRM.
How Can My Business Fix Bad Data?
Tightening up business policies around collecting and managing data is a start, but implementing data validation services will help ensure your data is as genuine, accurate, and up-to-date as possible and keep contacts current through frequent updates. Contact data validation can be integrated in a number of ways to best meet the needs of individual organizations, including:
- Real-time RESTful API – cleanse, validate and enhance contact data by integrating our data quality APIs into your custom application.
- Cloud Connectors – connect with major marketing, sales, and ecommerce platforms like Marketo, Salesforce, and Magento to help you gather and maintain accurate records.
- List Processing – securely cleanse lists for use in marketing and sales to help mitigate data decay.
- Quick Lookups – spot-check a verbal order or cleanse a small batch.
Service Objects’ validation services correct contact data including name, address, phone number, and email and cross-checks it against hundreds of databases to avoid garbage input. The result: cleaner transactions and more efficient processes across all aspects of your business.
Contact our team to determine which of our services can help you collect and maintain the highest quality data and kick the garbage to the curb.
