When it comes to data, the old saying "garbage in, garbage out" couldn’t be more appropriate. To get quality results, you need to start with quality data. As the world becomes increasingly digitized, the importance of data quality increases accordingly. In a business setting, data is used for everything from marketing to product development to human resources. It's crucial this data be as high-quality as possible. Yet according to a study by Talend, 97% of data experts are facing challenges in using data effectively. Another 46% don’t feel their data has the speed and flexibility to satisfy business demands. So, what exactly does "quality data" mean when it comes to marketing?
In general, quality data is data that is reliable, accurate, and trustworthy. However, it's not enough for data to simply be good. It also needs to be usable. That's why data quality also refers to a business's ability to use its data for operational or management decision-making.
Data quality is important for many reasons. First, poor data quality can lead to inaccurate results. Second, it can make it difficult or even impossible to make sound decisions based on that data. Finally, it can damage a company's reputation if customers find out the company is using unreliable or inaccurate data or using customer data unethically.
With the vast amount of data now available to organizations via digital properties, the latest technology is essential to data quality efforts. AI and ML are becoming more popular for assisting with and ensuring data quality because they’re literally designed to manage massive quantities of data at scale. Far more efficient than any human. But that’s ok, because when humans are freed from filtering and wrangling the data, they can spend more time actually using it.
There are a few key ingredients of data quality, which we’re going to call “the fab four”. The best data is:
Reliable
Data reliability demands your data follow the 3C’s - consistent, clean, and complete. Consistency across all systems is important to ensure data reflects the same information across the enterprise. No more data silos or outdated info! This means data syncs automatically across different data sets and everything is kept up to date. It’s ok to use multiple systems as long as they share information – ideally in real-time. To assist with this, all your data should be formatted in the same way for easy comparison and unification. Establish clear and consistent guidelines for how data should be collected and formatted then stick to it. A perfect example is a data point for “country” – this can be full text or two-digit abbreviation, but it should be the same on all records.
Reliable data is also clean and unique. Duplicates cause all sorts of chaos for businesses, so ensuring clean data is essential for maintaining a single source of truth. This involves matching, linking, and merging data to eliminate duplicates and keep data clean. Data orchestration can help unify your data to ensure consistency and reliability across the enterprise, especially when it’s used as a single source of truth.
Finally, for your data to be considered reliable it must be complete. This doesn’t mean every single field is filled in for every individual, it means the basic minimum is met. Every organization must establish what information is required to consider a record complete. This will vary depending on the business's needs. While a customer profile/identity is never truly complete - because it’s always evolving – establishing a minimum standard enables lead distribution and makes it easier to identify any gaps in the data.
Accurate
Data accuracy issues top the list of complaints from data experts with a mere 28% reporting their data as up-to-date and only 39% rating it as highly accurate – both significant decreases from a year ago. Having accurate data means it’s free from errors – whether human or technical. To ensure accuracy, businesses should have validation procedures in place and make sure their data is always up to date. This ties back to consistency and deduplication – you can’t have accurate data with customer data spread across various systems, or that overwrites new data with old data. Accurate data also means it’s valid and usable. Again, businesses should set organizational standards and develop systematic business rules for assessing data. This includes checking for correct format; for example, a phone number should contain X digits, email should be in the proper format, etc. There are plenty of data validation tools available to assist in this effort. Create a process for monitoring and auditing your data on a regular basis and have a plan in place for dealing with bad data when it inevitably crops up.
A true real-time data capture solution can greatly improve the accuracy of your data by acting as a single source of truth, and capturing data instantly across channel, device, domain, and time. This is a key component – if your data source is only sending you information once a day or doesn’t update for 8 hours then you don’t have accurate data. Remember, data for marketing includes behaviors and interactions which can change in a heartbeat as visitors are navigating a website or mobile app.
Trustworthy
Trustworthy data is not only reliable and accurate, but relevant and compliant. In marketing, data relevancy is critical to effective personalization, targeting, and ROI. Again, real-time data is essential – if it’s stale or outdated it’s useless. Think of a consumer browsing a retail site for a holiday gift. They could easily look at 10 different items for a person on their list in the space of one minute. If you don’t get that insight for 30 minutes they could have already moved on to the next site – your competitor. Likewise, if there’s a delay between your data capture and your data activation, you may not only lose your opportunity, you could also irritate your customer. One of our retail clients operates 20 successful independent brands. Without cross-domain data capture they wouldn’t know the visitor on Brand A who was looking at red jackets clicked from that site to Brand B’s site and purchased one. If they didn’t have Celebrus, they’d be lucky to get that data in 30 minutes. Then they’d fire off a personalized email with an offer on the red jacket from site A. Ineffective for the brand, and annoying for the consumer. With our true real-time, first-party data capture this retailer has no problem gathering real-time insights like these, so they can make a better decision for personalization – maybe a nice pair of gloves to complement the jacket.
Let’s not forget compliance. With growing data protection and privacy concerns, it’s essential for organizations of all shapes and sizes to ensure their data can be easily traced and connected if needed. This is especially important for compliance and regulatory purposes. In terms of your customer data capture, it’s impossible to manage compliance if your data is constantly being erased every seven days (as in the case of fake first-party CDPs). By maintaining data integrity throughout the enterprise, businesses can avoid any potential compliance issues down the line.
Actionable
The final ingredient to data quality is that it’s actionable! What’s the good in all this fabulous data if you can’t do anything with it? The first three ingredients – reliability, accuracy, and trustworthiness – will greatly improve the usefulness of your data, but you still need it to be compatible with your downstream systems. This means integrating cleanly with your CRM, visualization, decisioning and activation platforms, any data clean rooms or data warehouses you use, etc. Your data solution should be able to facilitate the seamless transfer of data in real-time, while acting as a central source of truth. This means less data wrangling for your teams, faster discovery to fuel data models, and real-time decisioning to deliver personalization in-the-moment. Yet again, if the path to your delivery systems takes 30 minutes, you lose the benefit of real-time data capture.
When data is actionable it can be used to inform marketing and data decisions that drive results. Rather than relying on the outdated tag management approach, a real-time “capture everything” approach ensures all data is available as needed. Whether it’s for the marketing team to inform strategy and messaging, the operations team to improve digital experience, or the fraud team working to prevent fraud while reducing friction – having all possible data at your fingertips with real-time access is the only way to ensure your data is actionable.
With the amount of digital data increasing, and the quality of data decreasing, marketing and data professionals are at a crossroads. It’s time to reevaluate traditional approaches to data capture, maintenance, and compliance. While CDPs are often viewed as an identity and personalization engine, a data solution can be so much more – with the right one of course. Your customer data solution should act as the foundation of your data strategy to not only capture, contextualize and profile your data, but also to ensure and monitor data quality – in real-time and at scale.
While most CDPs hoard data, collecting and piling it in random stacks that inevitably gather dust, Celebrus is more like a professional organizer meets transformer/chameleon – making sense of it all and delivering a clean, consistent, actionable system that can adapt and evolve to various business needs.
There’s no question data quality is more important than ever in today's digitized world. To ensure your business's data meets high standards, keep these four ingredients in mind. By paying attention to all four of these areas, you can ensure the data you're using is reliable, accurate, and usable—and your results will be too. Trust us, your marketing and data teams will thank you!
