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The Importance of Data Quality Assurance in Media Planning Tools

Last updated: December 16, 2019

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Marketers need to have a precise view of customers across their media planning initiatives. This has caused marketing technology that promises this visibility to explode in popularity over the past several years, with 42 percent of marketing and advertising budgets being allocated to some form of technology. However, marketers are only recently beginning to focus on the value of high-quality data.

This awakening is long overdue – even the best marketing analytics solutions need a strong foundation of high-quality data. Marketers across industries need to realize that in the world of data analysis, good outputs require good inputs. According to Richard Joyce, a senior analyst at Forrester, a mere 10 percent increase in data accessibility can create an additional $65 million in income for the average Fortune 1000 company.

A successful data quality initiative has far-reaching effects on marketing teams. When marketers have complete confidence in their data, they can understand and segment customers that have a high lifetime value for their media planning strategy. In addition to this, they can measure the impact and overall effectiveness of marketing plans, assisting in overall media mix optimization.

By implementing a few measures of quality assurance in their media planning tools, marketers can enjoy a range of benefits. Let’s take a closer look at how data quality assurance is key to a successful media planning initiative.  

How Data Quality Bolsters Media Planning Tools

By feeding high quality data into their media planning tools, marketers can better understand where to invest their media dollars for the best return, predict the success of their campaigns, and overall enjoy greater confidence in their marketing investments.

Failing to implement quality assurance measures into media planning initiatives can lead to inaccurate targeting and poorly optimized messages. Not only will this result in wasted spend, it can lead your larger media planning strategy astray.

There are several ways that data quality can help create successful media plans:

  • Improving Accuracy – By setting basic data quality standards, organizations can ensure that their data falls within a realistic range. When companies have confidence in their data, they can laser-target customers on a person-level – and even see how a campaign is performing while it’s in motion.
  • Eliminating Inefficiencies – By standardizing your data collection processes and creating standardized data templates, it is possible to optimize your data collection and implementation processes. Organizations should strive to implement basic automated data checks, and use methods like A/B testing to identify which parts of a campaign work.
  • Understanding Your Market – With high quality data, you can take a deep dive into audience behaviors and better understand how customers tend to interact with your brand. When organizations can trust this customer data, they can find what resonates the most with their target audience.
  • Setting Realistic Goals – Media plans can become complicated – and when you have a complicated goal, its helpful to properly envision the end result. With high quality data, you can accurately forecast the potential, realistic outcomes of your campaigns.

It’s no wonder why decision-makers identify access to high-quality data as the number one factor driving their marketing performance success. With so much value to gain, marketers cannot afford to make data quality considerations an afterthought.

Data Quality Assurance Checks to Consider

Over the course of a year, 21 percent of marketers’ media budgets were wasted due to poor data quality. This translates into a $1.2 million and $16.5 million average annual loss for a midsize and enterprise firm, respectively. This means it’s more important than ever to intertwine marketing processes with your data governance policies.

Your media planning strategy should involve the use of an effective media planning tool, alongside the following quality assurance measures:

  • Third-party Involvement – Even if your media planning tool and marketing team can assist in advanced data quality initiatives, it helps to have a third party that provides ongoing data quality assurance. Third-party data quality experts should have specialized expertise and the ability to efficiently check data upon arrival, ingestion, and consumption – or, on a consistent, always-on basis.
  • Market Performance Measurement Solution – With the right market performance measurement (MPM) solution, marketers can ensure they’re using high quality data to fuel their marketing campaigns. Marketers can automatically validate that data is within a normative range, update their media mix models and subsequent insights, and validate files in standardized formats. Data has shown that leaders in data quality also seek out MPMs that can prove data is ready for analysis, reveal insights across the entire customer journey, or ingest data in a timely manner.
  • Data Analytics Vendors – Some data analytics vendors package data quality services into their offering. If you already have an existing data analytics vendor, ask if they offer these services, and ensure it’s included in your package. If they do not provide these services, consider searching for a vendor that can provide data quality assurance.

Marketers must check the quality of their data often – after all, the onus is ultimately on the internal team to ensure that high-quality data is being used in their media planning tools. However, marketers should consult outside sources to ensure their data quality assessment is accurate.

Final Thoughts

Marketers need to take data quality into account when they leverage data tools. If marketers put poor quality data into their media planning tools, they may experience an unexpectedly low performance from their campaigns. However, by enacting the right data quality assurance measures, marketers can enjoy far more successful campaigns in the long-term.

Written by Marketing Evolution