Critical B2B Database Challenges to Surmount in 2022

Sales | 5 minutes to read

05th Apr, 2022

Modern B2B enterprise’s demand generation campaigns are only as good as their database. However, the path to maintaining an accurate and usable database is riddled with potholes. Many common challenges like disparate data, siloed information base, and poor data governance process sneak into the database and hinder the path to sales success.

Snapshots:

    • B2B customer and corporate data comes with a host of data quality and management challenges that can derail a company’s demand generation and sales efforts

    • Discover the best practices and solutions to overcome those challenges and streamline the path to sales success 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 revenue generation strategies.

    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 analysed 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- customers’ 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 analysing 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 customers’ 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.

    Leverage the best B2B database services and get the most accurate, relevant, and contactable database of different industry verticals across the globe. Contact our experts today!

    Solutions to surmount these data woes

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

    #1 Establish a single source of truth

    Enterprises must leverage tech-enabled database management solutions that allow them to create a single of their customer data across all departments. They must implement data standardization processes with the help of database service providers to standardize data obtained from multiple sources. It will also help resolve duplicate, incomplete, and incorrect records. They must deploy data validation and profiling processes to identify and eliminate conflicting and outdated information.

    #2 Enlist the services of reliable B2B database providers

    Enlisting the services of reliable third-party B2B database providers will help organizations fill gaps for missing data, verify, and update records. Working with external database service providers delivers brands the data that is validated and refreshed continuously using data management best practices and quality control. B2B database providers also offer additional customer information to append missing data. Discrepancies between company data and third-party data can help them flag incorrect and outdated information.

    #3 Commit to validation best practices

    B2B enterprises must make quality control a priority to set themselves up for success. They must follow these proactive steps to fix problems before they happen:

    • Validate data as soon as they get into the system.
    • Leverage real-time automated data validation tools to make sure all the data entering into the system is accurate and valid (e.g., ensure that online lead generation forms only accept valid email addresses and phone numbers with accurate pin code and digits.)

    #4 Implement a robust data management strategy

    Enterprises must begin with auditing their current processes, tech stacks, and online lead generation tools to identify gaps in their systems. A thorough database management strategy starts at the collection stage. A company must leverage future-forward data solutions that fit their business needs even when they scale. Next stage is to thoroughly scan the database and eliminate all outdated, duplicate, inconsistent, and invalid data. Then build a uniform data integration system with AI/ML capabilities to ensure automated data maintenance.

    #5 Integrate data for best results

    No matter how good the database is, without integration it will create data silos and misaligned information sharing within departments. Having real-time automated tools and CRM systems is essential to enabling everyone to have accurate, updated, and 36-degree of customer data.

    Get additional insights on how smart enterprises can leverage purchase intent data to tap into the undiscovered demand and expand their volume of qualified leads. Read the full blog here.

    Conclusion

    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.

    Contact us to kickstart your demand generation campaigns with an accurate, updated, and human-verified database across industries.

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