Brands Lack Strong Data Quality Approaches

Because overall data quality is only as good as the company's data management strategy allows.
Customer Experience

Experts and executives have been talking about the Big Data "explosion" for years, however many companies still lack the strategies to strongly manage and maintain data quality to earn the most "bang" for their buck.

Experian Data Quality's recent benchmark report explores how today's practitioners are managing and using valuable data to generate actionable insight. The study, which polled more than 1,200 global data management professionals across varying industries, examines current data perceptions and the present state of data quality. Researchers note that, without proper strategies and technologies, most companies will suffer from perpetual inaccuracies and inconsistencies, causing them to lag behind in this increasingly important space.

The following statistics highlight present data practices and how they will likely evolve alongside consumer expectations and brand requirements:

  • Overall, 74 percent of brands don't have a sophisticated data quality approach, while 63 percent lack a coherent, centralized strategy, highlighting the need for structural improvements.
  • While 88 percent of companies have implemented some sort of data quality solution-including profiling (43 percent), monitoring and auditing (42 percent), standardization (33 percent), and cleansing (33 percent)-51 percent plan to prioritize and improve solutions they already have in place. Conversely, 64 percent will focus on a new solution in 2015.
  • Ninety-two percent of brands suspect their customer and prospect data might be inaccurate in some way, as 97 percent of companies suffer from common errors associated with contact data, such as incomplete or missing data (51 percent) and outdated information (48 percent).
  • Though human error (61 percent) accounts for the bulk of data inaccuracies, many respondents also cite lack of internal communication between departments (35 percent) and inadequate data technology (28 percent) as primary components of such data insufficiencies.
  • On average, brands aim to maintain high-quality data in an effort to increase efficiency (58 percent), support their mobile websites (55 percent), and enable more informed decisions (51 percent).
  • Leaders seek to turn data into insight so they may understand customer needs (53 percent), find new customers (51 percent), and increase the value of each customer (49 percent).
  • Email remains vitally important to marketing success, as 90 percent of companies conduct email marketing campaigns. However, 78 percent of businesses have experienced email deliverability problems within the last 12 months, with 28 percent losing revenue consequently, indicating the distinct need to repair and remove inaccuracies from subscriber lists.

Key takeaway: Ultimately, brands cannot deny the correlation between sophisticated data management and high-quality data. Based on these findings, researchers recommend companies consider the following four steps to align said strategies with their end goals:

  1. Centralize data management under one single director.
  2. Hire talented staff to maintain data and create actionable insights.
  3. Implement data management tools consistently across departments.
  4. Be proactive and anticipate data challenges.

Companies are increasingly data-driven. Thus, inaccuracy breeds inefficiency, for this influx of information cannot drive revenue or strategic development. Now its own form of valuable currency, brands must care for and protect data, as this vital resource drives decisions and improvements across all departments and facets of any given organization.