5 Top Challenges Facing Marketers When Gathering Consumer Data

Poor-data quality is everywhere. Marketers have to navigate internet bots and click farms, not to mention human error, and it’s hard to know what suppliers to trust.

One of the most significant challenges facing today’s marketers is bad data. It’s an inescapable fact that data drives marketing decisions, and so campaigns become dependent on the consumer data gathered and analyzed. When this data is of poor quality, marketers lose money and lots of time spent trying to target the right audiences.

This is why bad data is an ongoing problem that hasn’t yet been solved, though platforms like BDEX put practices in place to minimize the spread of false consumer information.

So, what are the biggest challenges getting in the way of quality consumer data?

The key points we’ll be discussing include:

  • Lack of transparency by data brokers
  • Cost of bad data
  • Inaccurate graph data and click farms
  • Human error
  • Finding trustworthy data sources

1. Lack of transparency by data brokers

The data buying and selling marketplace is wrought with secrecy. Brokers who sell data don’t disclose their process for gathering, appending, and cleaning data. That makes it nearly impossible to accurately segment audiences marketers depend on to try to reach the right consumers based on specific profile attributes like gender, age, and location.

Because of this lack of transparency, which is in place so these brokers can stay competitive, it’s hard to know whether any data segments are completely accurate.

One study of audience segments from the Harvard Business Review found that just 42.5% of male gender segments were accurate and that age tiers were incorrect in 77% of evaluated cases. The research found that data quality varies wildly in the marketplace.

2. The real cost of bad data

Unfortunately, marketers pay a lot for consumer data. When it’s not certain if the data is high quality, these investments see only minimal returns. It’s particularly expensive to buy detailed profiles of certain audiences.

Poor data quality costs an estimated $3.1 trillion each year for the U.S. economy, according to IBM research. These high costs trickle down to marketers in the form of negative brand reputation effects, poor decision-making, and wasted time and money spent on marketing campaigns undermined by bad data.

3. Inaccurate graph data and click farms

There’s also a lot of bad data in ID graphs on the market. This data is inaccurate, incomplete, out of date, or inaccessible. BDEX has found that 45% of device graph data is bad. And when this bad data is placed in the marketplace, it infiltrates the entire ecosystem.

One reason there’s so much bad data being spread around is because of click farms. Click farms are fraudulent operations where workers create a lot of false clicks on websites so false unique visitors are generated in attempts to cheat pay-per-click (PPC) campaigns.

Because these clicks are fraudulent, it creates a lot of bad data about consumers and website visitors. This data is then gathered and sold to marketers.

4. Human error

Of course, not all errors are intentional. Human error happens frequently, and these errors, however small, contribute to poor data quality. Errors could be anything from a transposed phone number to a missing character in an email address.

When a piece of contact information is inaccurate, it’s impossible to successfully reach the people marketers are trying to target. Their messages either go to the wrong person, or they go to no one if an email address is defunct or nonexistent.

5. Finding a trustworthy data source

It’s hard to find a data marketplace or platform you can trust in this climate of ubiquitous bad data. All brokers are trying to sell their data with the same urgency, and many of them don’t put as much emphasis as they should on ensuring that data is accurate and up-to-date.

But the good news is, it’s not impossible to find a reliable source of high-quality data. There are signs to look for when choosing a data supplier. First, if a source uses unfiltered data from secondary vendors, be cautious. Your supplier also needs to have a process in place, that they’re willing to share with you, for identifying bad information like click farm data.

BDEX is a data source you can always trust. Our Data Exchange Platform is the first of its kind on the market, and our Data as a Service (DaaS) solution ensures you’re always getting high-quality data. Our BDEX ID graph incorporates an advanced ID check that automatically filters out bad data so you can depend on ongoing data quality. The BDEX ID Check eliminates data like invalid MAIDs, bad linkages, and improperly hashed emails.

Learn more about our commitment to data quality by contacting the BDEX team. We’re ready to help you make better human connections with high-quality data about your audiences.