Critical B2B Database
Challenges to Surmount in 2022

Modern day businesses rely heavily on data and BI analytics to successfully execute their marketing and sales campaigns. Insights obtained from the customer data can provide a better understanding into the customer lifecycle, inform sales outreach efforts, and help align the sales and marketing efforts towards a common set of objectives. However, as with other good things, B2B data comes with its fair share of challenges that threaten to impede an organization's rev

According to recent studies by Forbes and KPMG, 84% of CEOs are concerned about their data quality. Furthermore, one in five businesses lose revenue owing to inaccurate and incomplete information. Today, businesses have truckloads of data available at their disposal waiting to be processed and analyzed for actionable intelligence. However, many enterprises lack proper data management processes leaving them exposed to data quality issues. Let's look at some of the biggest database challenges and the right solutions to overcome them.

The most common B2B database challenges that can tank sales success in 2022. While the specific challenges with data will vary depending on the organization's size, industry, infrastructure, and the types of data they are dealing with, these core problems show up repeatedly when managing them:

Missing key information

With more data sources available at companies disposal than ever, brands struggle to effectively collect and store information in their data systems. This leads to gaps in their customer data. There is much information available for everything- customer's interests and intent, website visitors, churn rates, financial data, conversion rates, and much more. Marketers often find it difficult to organize all their data sources and connect online and offline behaviours.

Collecting inaccurate or outdated data

If there is too much data in a company's database, it is likely that they have inadvertently collected inaccurate data, or that some of their data have gone stale. This problem begins right at the collection process of company's data lifecycle. It is more prevalent when companies collect their data from a multitude of sources and formats. If the data collection process is not standardized, marketers will face challenges while analyzing the data and extracting actionable business intelligence from it.

Storing data in silos

Data silos are another major bottleneck faced by B2B enterprises while dealing with customer and corporate database. If all the information is stored in separate databases that don't communicate with each other, then it can create data silos. Not having a single source of truth for all the business departments can lead to poor execution, cross-functional misalignment, and limited understanding of customer's needs.

Lack of insight

The influx of information and multitude of data sources makes it difficult to match and consolidate records to provide correct and clean data to sales reps. Therefore, any attempt to develop retention models, build customer personas, or other insights-driven decision-making will be rendered ineffective. This problem typically manifests when unfiltered and unstructured data is sourced through different channels.

Solutions to surmount these data woes

Let's identify some best practices to overcome the common B2B database challenges:

Missing key information

A brand can have the best products/services, technology, and demand generation capabilities, but bad data will always derail their business results and revenue. It is essential for brands to quickly identify revenue-sapping challenges within their database and use industry-proven tactics to plug them before they can damage sales outreach efforts. Additionally, every B2B organization needs the help of best B2B data providers to effectively handle, manage, and ensure optimum usability of the data.