Marketers rely heavily on data and analytics. So, it’s no surprise that customer database issues can cause even the most unflappable marketer to break out in a nervous sweat. If you are worried about your consumer data, you’re not alone. According to Forbes Insights and KPMG, 84% of CEOs are concerned about the quality of their data1. And a recent report revealed that one in five businesses lose revenue and customers due to incomplete or inaccurate information2.
Accurate consumer data is crucial to successful marketing execution, yet data management and analysis often does not get the focus it deserves – leaving brands exposed to data quality issues. What are some of the most common customer database mistakes and how can marketers overcome them?
With more data sources than ever to collect and store information, brands still struggle with gaps in their consumer data. Whether it’s due to consumers’ browser settings, devices making it difficult to match back browse behavior, or challenges connecting online and offline behaviors, many marketers are missing important data about their audience.
They say there are three certainties in life: death, taxes, and change. In the next 30 minutes, 120 businesses will have a change of address, 20 CEOs will leave their jobs, and 75 phone numbers will change according to Dun and Bradstreet3. And because brands now have so many more data points on each consumer (multiple cell phone numbers, social handles, devices and email addresses) their information becomes outdated faster than ever.
It is estimated that in 2023, we will generate nearly 3 times the volume of data generated in 2019. By 2025, people will create more than 181 ZB of data4. In addition, data is now collected from many self-reported sources increasing the likelihood of errors. Data is growing at an astounding pace, which complicates matters for the marketer. In fact, the average organization estimates that 22% of all its contact data is inaccurate in some way. And 42% of brands say that inaccurate contact data is the biggest barrier to multichannel marketing5.
The influx of information and variety of data sources makes it more difficult to match and consolidate records from multiple sources in order to provide correct, clean data. Because of this, attempts to analyze your customer data to develop retention models, personas or other strategy-defining insights that help you identify your best customers may be ineffective.
If you can’t identify or get to know your best customers, how can you find good prospects that look like them? Incomplete and inaccurate data limits your ability to maximize acquisition efforts (and budget) with analytical tools like lookalike models.
Regulatory changes, like GDPR and recent U.S state data protection laws, indicate a shift to a more privacy protected world. Consequently, brands are increasingly concerned about privacy issues. In a recent survey by KPMG, 62% of business leaders say their companies should be doing more to strengthen existing data protection measures.6.
Even if you aren’t there yet, make it a core value of your organization to work towards having the technology and processes that allow you to create a single view of your customers and prospects, wherever they are – at home, at work, on their cell phone or computer, online, offline, etc. Have processes in place that will help you resolve duplicate or incomplete records for example:
Having additional information from outside of your organization can fill in the blanks for missing data and help your organization verify and update records that have become out of date. For example:
Brands that make quality-control a priority can set themselves up for success. Follow these proactive policies to fix problems before they happen:
Forty-one percent of business leaders say that no one in their organization is responsible for the data management8. It’s difficult to maintain a clean database without clearly defined ownership. Dedicated resources (and budget) for data management can keep things in line. If your brand is in need of a data quality overhaul, you can always call for back-up from data hygiene experts to get you back on track.
CRM (Customer Relationship Management), CDP (Customer Data Platform), DMP (Data Management Platform) – there’s a dizzying array of acronyms for database technology solutions that can help you manage your data. No matter which route you choose, there is likely a solution that fits your business needs. Find a reliable provider with a good reputation and service support to supplement and assist your team when needed and make sure your partner can scale to your data needs as they evolve.
Gartner defines CDI as “the combination of technology, software, processes and services needed to achieve a single, accurate and complete view of the customer across multiple sources of customer data, databases, and business lines.” It is the masterplan for how to extract, cleanse, append, store, access, and gain insights from customer data.
Whether your brand develops this framework on its own, or enlists help from an external provider, having a plan for your customer data helps to establish and maintain the right environment to provide you with a 360 degree view of the customer. This plan serves as the rails to keep your customer data train on the right track.
A brand can have the best technology and marketing capabilities, but inaccurate data will always derail business results and revenue. For marketers to reach their true potential, they must focus on data management and quality.
Data Axle can help with your unique customer data challenges. Ask us how today.
Editor’s Note: This blog was originally published in August 2020 and has been updated for accuracy and comprehensiveness in August 2023.
In his role as Senior Vice President of Technology Solutions, Sal is engaged in managing a corporate-wide product vision and strategy to create and maintain leading-edge marketing products and services that are consistent across all divisions. He is known throughout the industry for his consultative approach to identifying solutions for clients’ database marketing and data processing needs.