B2B marketers leverage digital channels because that’s where most B2B buying journeys happen today. In order to fine-tune and deliver relevant messaging to their B2B target audiences, marketers are using ever-increasing amounts of customer data and data management technologies.
It's more clear than ever before that old-school "spray-and-pray" outreach doesn’t work. Period. More mature B2B marketing teams are investing in a strong data foundation to generate the insights that fuel targeted engagement. Simply put, high-quality data is the fuel propelling today’s B2B marketing revenue engines. It’s therefore no surprise that nearly 7 out of 10 (69%) of B2B marketing teams plan to increase their investment in database strategies throughout 2023, according to Demand Gen Report.
So where specifically are B2B marketers investing in their “data ecosystems,” and what steps are they taking to ensure their data quality? Answering that key question is the focus of this blog post. To dive even deeper into this topic, you can read Demand Gen Report's full report, What’s Working in Database Strategies?, which covers some of the same ground we’ll cover below.
#1: Integrate your data to ensure a “single source of truth”
More data, by itself, is never the right answer - unless that data is properly governed across your organization’s customer-focused stakeholders. When you have data siloes embedded in multiple departments, you have the ingredients for data chaos, not data-fueled customer engagement. It’s often better to have less data, used more efficiently (i.e., with the approach described in this blog post) than to have tons of data that remains unorganized and badly managed.
Incoming customer data needs to be put in the right format and be managed through a standardized process/workflow (including for fields and other naming conventions) across your organization. Moreover, data needs to be integrated across your systems so that changes made to data in one system are automatically updated in all other systems. You can’t maintain high quality data for long with data siloes, and random acts of data governance.
Why does having a “single source of truth” represent the first step towards ensuring data quality? Because it’s the only way to effectively manage data internally and also maintain a consistent, unified customer experience/CX. For instance, when a customer calls your customer success/customer service department to complain about the product they purchased a month ago, the sales department should not be calling said customer later that day trying to upsell or cross-sell your latest offering. That’s just embarrassing for the company and infuriating for the customer. When your data is unified, shared, and updated automatically, those revenue-killing CX moments disappear.
Unsurprisingly, many B2B companies deploy their CRM platform as their centralized, shared, and single source of truth. You simply cannot maintain data quality and leverage your data to fuel engagement unless you’re operating from a single source of truth. When your data turns to garbage, so do your insights/analytics, reporting, segmentation, strategies, planning, and overall decision-making.
Bad data costs you money. IBM estimated that bad data cost the US economy $3.1 trillion (with a t) in 2022 in manual rework/cleansing, wasted investments, and lost business opportunities.
#2: Deploy automation to cleanse and transform your marketing data
Ensuring quality data is a bit like chasing the sun – it’s an elusive activity that’s never done. The “high-quality data” you used last month can become absolute garbage next month. Maybe the VIP at your biggest account changed companies . . . maybe the big account pivoted their strategy and no longer needs to buy your offerings. Like life, data has a way of continuously moving and changing. When you use inaccurate, outdated data to build customer segments or create analytics or make business decisions you’re only amplifying the waste caused by bad data.
Data quality can erode by as much as 20% per year. Never forget the oldest maxim in data science: garbage in means garbage out. Bad data leads to bad engagement. Many savvy B2B organizations are using automated tools like data washing machines to continually maintain their data quality.
Automation and AI-powered custom solutions can constantly sift through your database to cleanse and update data, dynamically segmenting your database based on updated data, and more. Having your B2B data fully integrated and using automation/AI to constantly cleanse data and maintain its quality is foundational for any effective data management and data governance approach.
#3: Use first party data + appended data to fuel insights
First-party data is data that customers provide by visiting your “owned” digital assets, such as your website. It is the single most valuable type of data because it tells you how customers are interacting with your content. So if a customer goes to your site and looks at a specific product page and then accesses your latest webinar on the product, you’d probably want to follow up quickly on that first party data.
B2B marketers are also looking to leverage data providers in order to enrich their data sets. Sojourn, for instance, has recently launched a new Marketing Data & Analytics Service to help customers do this and more. The practice of incorporating enriched data into B2B databases is growing: about 33% of B2B marketers used data providers in 2021, but that number grew to about 50% in 2022, according to Demand Gen Report.
Of course, marketers need to do their due diligence before partnering with any data provider and when incorporating enriched data into their databases. Understanding the data quality offered by these providers is absolutely critical. Where are providers getting the data? How often do they refresh their data? What processes do they have internally to validate their data? Ask and find out to avoid issues and optimize your results.
For help with ensuring your ongoing data quality - the foundation of effective B2B marketing - contact us today.
