Why Customer Data Maintenance Matters for Marketers

After a uniquely challenging year, many companies are looking to marketers to turn their fortunes around. According to a recent survey of global CEOs, 83% expect marketing initiatives will drive growth in the year ahead. Delivering on these high hopes will require marketers to update their strategies.

Increasingly, effective marketing is a data-driven initiative, allowing companies to optimize communications and maximize return on investment (ROI). That’s why, in a year-end analysis of marketing best practices, McKinsey identifies “strategy and insights” as a marketing capability in need of improvement. Specifically, the report calls on marketers to develop “brand vision and strategy informed by real-time insights that are integrated into operations and the front lines.”

Of course, customer data is an abundant resource in today’s digital economy, delivered in a deluge that can propel effective campaigns or produce radical inefficiencies.

Customer data maintenance can keep efforts on track by ensuring that marketers have the best, most relevant information to drive decision making. For marketers looking to deliver big results in 2021, here are three ways data maintenance can support their efforts.

Cost

Marketing professionals will undoubtedly be asked to do more with less in 2021. Therefore, it’s increasingly critical that data-driven marketing efforts are based on the best customer data possible. However, a Forrester Consulting survey found that marketers waste more than a fifth of their budgets on bad customer data, undermining their ability to execute on critical priorities. Collectively, IBM estimates that bad data costs the U.S. economy $3.1 trillion annually, making it a costly but correctable misstep for many companies.

Simply put, bad customer data is a big problem when marketers rely on it to drive revenue-generating initiatives.

Meanwhile, data maintenance and cleansing services improve data quality and ensure:

  • accurate contact information including addresses, email addresses and phone numbers.
  • authentic database records by eliminating duplicate entries, deceased individuals and outreach preference changes.
  • audience-specific outreach opportunities through demographic and geographic data.

While bad data costs money and decreases operational capacity, the best information maximizes resources at a critical time.

Risk

Bad data quality puts organizations at risk. Most prominently, it leads to poor decision-making, which undermines everything from messaging to outreach.

Of course, bad decisions inevitably inflict brand damage as misplaced advertising appears untimely, tone deaf and irrelevant. This causes customers to leave, reduces revenue and further strains already stressed businesses.

This reality has specific relevance for ecommerce businesses. The holiday shopping season heightened consumer appetite for perks such as free shipping, while their concerns over timely, accurate delivery reached an all-time high.

Armed with accurate data sets, marketers can assuage these concerns with targeted messaging and, most importantly, a worry-free shopping experience. In contrast, bad data may cause retailers to over-promise and under-deliver, diminishing the opportunity for recurring revenue from returning customers.

Thus, bad data isn’t just an inefficiency or a missed opportunity, it’s an existential risk for companies already struggling with shifting customer demand and an increasingly crowded competitive landscape.

Effectiveness

In the digital age, data creation, collection and analysis is a constant practice. Unfortunately, that information quickly becomes outdated. It’s estimated that up to 20% of consumer data and 40% of organizational data become irrelevant each year, primarily due to home moves, job changes and mortality.

When bad data drives decision-making, companies become less effective. For example, how customers feel about a brand is a primary factor in the buying process. Increasingly, branding and customer experience are inextricably linked, and both are cultivated through data-driven outreach efforts.

Notably, the 2019-2020 Nielsen Annual Marketing Report found that marketers consistently deprioritize data quality, ranking it behind audience targeting, ad creative and audience reach, three assets that are informed by data quality.

In other words, as the Nielsen survey concludes, “Basing marketing decisions on low-quality data can have a huge, negative impact on the effectiveness and ROI of marketing campaigns. Trying to sell the right product or service to the wrong consumers at the wrong time using the wrong channel is bound to result in a lower return than going through the same process with high-quality data.”

In 2021 and beyond, marketing best practices need to be data-driven, and those customer data sets have to be accurate to be effective.

Conclusion

For marketers looking to make an impact in the year ahead, enriching data quality is essential. Data availability is ubiquitous, but accuracy is often fleeting and always temporary. Data maintenance solves this problem, giving marketers access to the right information at the right time and empowering them to craft compelling messaging in real time. For marketers unsure of the quality of their data, partnering with an expert resource to conduct a data health check is a great first step.

2020 posed unique challenges for companies in every sector, and many are looking to their marketing teams to help drive success in 2021. These mission-critical, bottom-line efforts will help determine whether last year was an aberration or a new normal.

Better data doesn’t guarantee success but it does give marketers the right tools to help companies accelerate and succeed.

Stuart Watt is Commercial Director for Loqate