If You Need More Reasons to Believe in the Importance of High-Quality Data, Here are Three

By Stuart Watt, Commercial Director for Loqate, a GBG solution

With each passing year, data becomes increasingly central to customer acquisition, retention and growth. The growing importance of data was amplified as the pandemic accelerated mass digital adoption and created new challenges for marketers. From an unprecedented influx of new digital customers to changing compliance regulations and emerging technologies, data will be the key to creating meaningful interactions with customers, increasing market share and driving engagement through the rest of 2021. The following trends promised to deliver big results with a solid data strategy in place. 

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The Shift to First-Party Data 

CCPA forced marketers to rethink data and especially, privacy compliance. Designed to aggressively target third-party data providers, CCPA drastically restricted how companies acquire and use consumer data. Marketers who relied on third-party data providers were driven to explore other avenues. At the same time, the importance of relationships with existing customers was amplified as CCPA effectively turned consumer data into a privilege that could easily be revoked. 

The pivot to first-party data presents an opportunity. However, a recent survey by eMarketer revealed that on average, marketers are only tapping into 47 percent of their company’s first-party data. By leaving over 50 percent of first-party data on the table, these marketers are missing out on a significant opportunity for customer engagement and retention. 

First-party data is where the magic happens. It’s relevant, high quality and proprietary. It’s also the key to understanding behavior and trends across customer segments for delivering tailored, meaningful content that drives engagement, establishes trust and leads to long-term loyalty. 

With CCPA making it very difficult to use third-party data to acquire new customers, retention among existing customers is incredibly important. With the frequently-changing nature of consumer data, it is critical that marketers have regular, but relevant, contact with customers and ensure that customer data is current. 

Direct Mail’s Comeback 

In today’s digital age, direct mail campaigns have less competition. Among the big brands that are taking advantage of direct mail to drive sales is Amazon. The company’s 2020 catalog featured 100 pages of toys, games and electronics and incorporated QR codes and special in-app pricing. 

eCommerce businesses in particular are noticing that direct mail isn’t dead. The Direct Marketing Association recently analyzed direct mail vs email and found that direct mail averaged a 4.4 percent response rate, compared to email’s average response rate of 0.12 percent. Research also shows messages delivered via direct mail can be powerfully motivating with 92 percent of people driven to digital activity and 87 percent influenced to make an online purchase. 

As is the case with nearly every other aspect of marketing, direct mail is becoming more and more data-driven. When using direct mail to target customers, personalization is vital and therefore, dependent on accurate, clean and up-to-date data, which affects not only the efficiency of the data process and analytics, but also deliverability.

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The effort and energy put into direct mail are wasted if the mail fails to reach its intended target. Cleansing an address, standardizing its components and adding important attributes, such as zip+4, will improve delivery. Furthermore, remember that people move, and they do so often. The Postal Service processes 121,452 address changes daily. Thus, for 75M people, approximately 20 percent of the American population, addresses are potentially incorrect. In the case of a catalog mailing of 500,000 records in which addresses have not been cleansed within 12 months, 100,000 catalogs are at risk for failing to reach their destination. Think about the impact this would have on revenue and marketing metrics.

Artificial Intelligence (AI) and Machine Learning

Data science isn’t just for tech companies anymore. Poised to get the greatest benefit from AI and machine learning, marketers are also in the midst of a massive digital transition. Manual methods and antiquated software are being traded-in for innovative technology that promises powerful analytics, deep customer insights, optimization and automation. However, this promise is based on the assumption that they’re coming to the table with clean, structured data. Predictive models are only as good as the data used to train them.  

According to Forrester, forty-five percent of decision-makers say trusting their AI system is either challenging or very challenging. Investing in AI and machine learning will be a waste and can’t possibly deliver accurate insights and results if the models are based on data that isn’t up to date, properly structured and optimized. 

Data quality is more vital than ever. While the past 12 months introduced new challenges for engagement, a data maintenance strategy will help marketers emerge with deeper customer relationships, increased retention and strong growth in the years ahead. 

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