Why Bad Data is Spoiling Your Marketing Efforts

The amount of money spent on marketing is growing and the way we spend it is changing. Statistics to prove this are now plentiful and are becoming more convincing year after year.

 

 

 

 

 

 

 

Here are two very compelling examples:

  • By 2016, we expect the amount of money spent on digital marketing to consume 35% of total marketing budgets, according to the CMO surveyDoyle01

Businesses are investing more in online strategies, and changing their game plans. Sitting on your hands is no longer an option. The data in your database is becoming worthless by the minute if you have no data quality strategy in place.

In order to compete in tomorrow’s business landscape, you’ll need to use your marketing budget more efficiently than ever before. It will need to be optimised, honed, and adjusted at every stage of the process.

However, a killer marketing plan can only get you so far if it’s founded on poor quality data.

Data Flaws Are Costing Your Business Money

Experian research found that flawed data is costing UK businesses £197 million per year. This is a huge amount of money to spend on messages that never reach an audience.

In the same company’s 2014 data quality survey, it found that 99 percent of businesses are actively tackling data quality in some way. Yet, clearly, we have a bigger problem if so many businesses are still losing money.

The problem is that we’re not tackling it effectively enough, or quickly enough, and we’re not investing enough money.

The biggest cause for concern for marketers is invalid contact data, which is a risk for every business that uses a CRM. Once we put a contact record into a CRM, we rarely look at it again until we next need to deal with that person, which leaves a very large scope for mistakes.

The problems Experian reports as a result are staggering:

  • 67 percent of businesses say some of their marketing emails bounce back after a campaign
  • 70 percent of businesses report data quality problems in loyalty programs
  • 22 percent of contact data is thought to be inaccurate

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How can marketers market to people if they don’t have the right contact information? How do we know if someone is loyal if we can’t trust the data that the whole program hinges on?

The biggest cause of these data quality issues is human error, particularly in a contact centre environment. It’s not rocket science: people make typing mistakes, spell things wrong, type nonsense in a field to get around an error message, or save the same thing twice by mistake.

Over time, data also naturally decays as people change their job role and contact details. Even if a database were pristine, we’d expect data to decay at 2.1 per cent, per month. That’s 25% (1/4) per year!

We All Know Data Quality is a Problem

According to this report from Experian, 83 per cent of CIOs believe that their data is not being fully exploited.

And in the Experian survey we’ve referenced in the previous section, 94% of the 1,206 organizations surveyed acknowledged that they have data quality problems.

We can see that the epidemic of poor data quality comes as no surprise to anyone.

In fact, the proportion of inaccurate data in a database has risen from 5 percent to 22 percent from 2013 to now, with human error being blamed for more than half of the issues. Specifically, 42 percent of respondents to Experian said they believed poor data quality was causing problems in their marketing campaigns.

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If we allow this situation to go unchecked, marketing departments are going to become less and less effective, since the number of valid contacts is continually shrinking. The marketing list will wither away as the data quality is eroded, and marketers are going to keep pushing up their budgets and pouring money down the drain.

We’re Improving Data Quality too Slowly

A quarter of the respondents to the Experian survey are still reviewing data manually, looking at spreadsheets line-by-line to pick out things that are wrong.

Manual pruning of data is an unreliable, inefficient and expensive way to tackle poor data quality, and it only compounds the wasted effort in the business’ marketing department.

To get a CRM to a reasonable state using human intervention, it would be horrendously time consuming – if it were even possible to guarantee a good result. Some databases contain millions of contacts.

Businesses are starting to realise that data quality is worthy of more serious investment. 81 percent of those surveyed believe good data is key to marketing success. And Experian found that 34 percent of businesses are using data quality and deduplication software. While this is a small number, it is likely to grow as more businesses recognise the need for it. After all, data quality software is not simply a mechanism for passive review; it can also continually monitor data and help to purify it over time.

Employees that can find data quickly, and rely on its validity, tend to be more enthusiastic in using and adopting data quality processes. That means the teams that rely on pure data will be better engaged with maintaining its quality.

Data Quality Yields Results

Marketers need high quality, complete, valid, and accurate data to make good quality decisions, and to avoid the need to scrap a project and start again from scratch. The more data we have, the bigger the potential for waste, and the more expensive it is to put off the data quality initiatives we need.

If you need further proof of the value of data, look at the way it is traded. Some entrepreneurs have actually built their business on maintaining high data quality. If your own marketing data is eroded, the only option left will be to buy from a list supplier who has spent money checking the validity of its contact records.

 

This article was previously published on the author’s web-site – dqglobal.com.

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About Martin Doyle

Armed with qualifications in mechanical engineering, business and finance, and experience of running engineering and CRM businesses, Martin founded a successful CRM (Customer Relationship Management) software house in 1992, supplying systems to large, medium and small sized companies. Developing a deep understanding of the value of data, he became concerned that many organisations were making decisions based on poor quality data. To fill this gap in the market, he sold the CRM company and started DQ Global in 2002 to provide data quality solutions, with a mission to detect, correct and prevent data defects which undermine business decisions. Since then, DQ Global has become a global market leader, delivering enterprise-wide data solutions utilising leading edge technology. Martin has gained a wealth of knowledge and experience and has established himself as a Data Quality Improvement Evangelist and an industry expert.

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