Data Accuracy: Don’t Let Bad Information Cripple Your Marketing

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Don’t take a chance with inaccurate data and miss your audience.

Key Takeaways:

  • Bad data costs your company staff time, money, reputation, and consumer trust
  • Consumers say more than 50% of their data was wrong
  • 40% of company initiatives fail to meet their goals
  • There are steps you can take, internally and externally, to assure data accuracy

Accurate data is the lifeblood of any marketing campaign. Bad, inaccurate data is a time-waster. It carries a cost that can more than double the spend on an effort and consign your best creative campaign to the dust heap. 

The quality of data varies vastly by supplier, and lousy data performs no better than random chance when it comes to creating a targeted campaign, says a 2020 study by the Harvard Business Review. 

The biggest challenge? Human error, but that’s just part of the problem. Another study, this one from Deloitte, found that the second largest cause of bad data is poor communication (or no communication) between an advertisers’ internal departments.

Sadly, more than two-thirds of consumers who participated said their data was more than 50% incorrect, and bad data means one-in-five companies have lost a customer.

There are some alarming stats about data quality

Businesses understand that they need accurate data to do accurate targeting, and today’s consumer is more demanding and has more buying choices than ever before. This means businesses must accurately anticipate their needs. Getting current, accurate data is complicated by the fact that 31 million Americans moved in 2019 alone, averaging about 8.1% per month, and 3% of those are interstate moves. 

Recent data quality statistics prove the rule of garbage in, garbage out. So just how does bad data impact your business?

For one thing, bad data is likely costing your marketing department staff approximately 550 lost hours, and about $32,000 per salesperson, per year. On top of that, 25% to 30% of data becomes inaccurate every year. And what about that lost 20% of total revenue due to sub-par data quality?

Additionally:

  1. Proper processing of data takes a toll: It costs about $1 to prevent a duplicate, to correct a duplicate costs about $10, and an untreated duplicate will cost you $100 to store if it’s not corrected.
  2. Mundane data quality efforts can waste up to 50% of staff time.
  3. Inaccurate data is part of 40% of leads, and 15% of those have duplicate records.
  4. Inconsistent data quality across technologies like CRMs and other automated systems plague 41% of companies. 

The impact to the bottom line is considerable. The average yearly financial cost to businesses in 2017

was $15 million. But there are soft costs as well to a company’s competitive standing and consumer trust. It also puts a damper on digital initiatives. 

Some 40% of all company initiatives fail to achieve their goals, and one in three business leaders say they make decisions based on information they don’t trust. On top of this, bad data creates regulatory noncompliance risks, poor business decisions, and alienated customers when you send them incorrect communications.  

Stop poor data quality from subverting your business efforts

Now that you understand what bad data quality is costing you, you’ll be encouraged to know that there are steps your business can take to improve data quality so it can meet revenue projections and have engaged and happy customers. 

The first step, of course, is to acquire high-quality data from a trusted supplier that has its own internal process to ensure accuracy and quality. The rest is up to quality processes implemented inside your business data quality is at risk as soon as it enters your doors.

Another fix is to avoid broad profiles, such as all of one gender or everyone interested in a certain item. Instead, narrow your audience to make your campaigns more cost effective. 

Almost half of marketers, publishers, and tech developers surveyed responded that centralizing data ownership would be one of the most essential changes they had to make to the way they process data. Other important changes included dismantling silos between groups and departments and standardizing data use and sharing protocols, both internally and with external partners. 

Value measurement is also important. Most organizations nearly 60% do not measure the cost of poor-quality data, which means reactive responses to any issues, missed opportunities for growth, more risk, and, of course, a lower ROI. Proactive measurement is recommended, and these should be linked to performance metrics. 

Setting internal data quality roles to meet objectives is essential, starting with the chief data officer, and then establishing positions such as data stewards and quality analysts in an IT-business combination to foster cross-organizational collaboration.

As added encouragement, recent research estimates that even a 10% increase in data usability would increase revenue for Fortune 1000 companies by more than $2 billion annually

BDEX Data Quality You Can Trust

The tools at BDEX help you get the quality data you need, right when you need it, which means less waste and increased ROI.

We have over 5,500 data categories, more than 800 million mobile ID-to-email matches, and over 1 trillion data signals. With BDEX, you’re empowered to create your own custom audience, so all you have to do to get your messages in front of the right people at the right time is to build your ideal customer to target and download the data.

BDEX data is always clear, high-quality, and current, which isn’t easy to find in the ever-expanding world of big data.

To improve your ROI, you have to get the most out of your data. Otherwise, you’re wasting time, money, and resources by marketing to the wrong audiences at the wrong time with the wrong messages. BDEX can give you the information you need to better connect with the person behind the data signal.

Make real human connections with BDEX. Contact the team today to get started transforming the quality and accuracy of your data.