How to create a culture of data to drive your B2B Marketing: 4 steps to success

By Chuck Leddy

Data is the fuel that propels B2B marketing today, but reaching your destination takes more than just data. It takes building an organizational culture that leverages data to inform decision-making and blends people, processes and technology across the business.

Our colleagues at Salesforce’s Tableau, a data and visual analytics platform, have recently released The Data Culture Playbook (free download), a comprehensive guide to building a data culture. The Playbook defines a data culture as “a shared mission to enable the entire workforce with data, backed by leadership, a supportive community, and flexible technology.”

As digital engagement becomes the overwhelming majority of customer engagement, a trend accelerated by COVID-19, data has never been more important. Data-leading B2B organizations, the Playbook says, “can pivot when necessary, innovate constantly, and refine consistently, giving them a distinct competitive advantage when times are tough.”

Data cultures drive better B2B Marketing & ROI

The Playbook explains that companies with the most mature Data Cultures (more on that later) drive better business results, such as:

  • 89% improvements to customer retention and acquisition.
  • 45% greater improvement in employee retention.
  • 41% greater improvement in production time to market.

“Data culture” must obviously be evaluated on a continuum that embraces many factors: your technology stack and data management maturity, the skills and capacities of your people, buy-in from leadership, the use of data across the business (is it uneven or integrated and standardized?), and more.

While it’s difficult to analyze exactly where your B2B organization might be on the continuum of data culture, the Playbook offers several relevant questions to help you evaluate where you are today:

  • Do your people know how to interpret data?
  • Can your people get help from colleagues with analytics or data-related questions?
  • Do you give your people access to all the data and data tools they need?
  • Are your people accountable for the data they access and create?
  • Do your people and your organization require data to support decisions?

4 steps to building a culture of data

Building a data culture is a process. Here’s how to begin, according to the Playbook:

1: Align leadership metrics to business priorities. “Leaders from across the organization [must] align on the most pressing business needs to determine where the organization should be focusing resources around data,” explains the Playbook. Focus on measuring what matters.

Buy-in from your top leadership on priorities and metrics ensures that all your functional/business units are moving together towards the same goals and assigning data resources to areas that have the biggest impact. The Playbook suggests that a data leadership committee be set up to “create a key set of metrics and work with the right people—typically an analyst team—to locate, create, and align data sources to support these metrics.”

Some tips the Playbook offers to achieve this first step include: (1) define a set of key guiding metrics so you can evaluate progress toward pre-defined goals; (2) develop data to support your guiding metrics; (3) track and analyze these metrics regularly; and (4) redeploy and focus data resources on the most urgent and high-potential projects so you show initial value.

2: Build data sources to address critical decision points. Data owners and business owners must work together “to identify or create a few key data sources that have a direct impact on organization-wide metrics,” says the Playbook. Let’s assume that one chosen priority is customer growth. The data source built to support this priority might include information about customer behavior/buying intent or about the customer journey.

For each chosen priority, identify and map out critical decision points — points where you choose to start, stop, continue, or change aspects of your approach. Utilize your data sources to inform each of these points, explore and model potential outcomes, and measure the impact. Going back to the priority around customer growth, would efforts to remove friction from the customer journey result in higher website engagement and product sales? Build a map for this priority and then experiment with different points on that map, using data as a compass to navigate towards your goals of less friction and more revenue growth.

Some tips the Playbook offers to achieve this second step include: (1) identify a few data sources that closely align to key decision points; (2) prioritize and do experiments to achieve incremental improvements at these decision points (adjusting one factor, assessing impact, and repeating); (3) measure the ROI of business improvements by analyzing the impact on your strategic metrics; and (4) share your successes and learnings to promote buy-in.

3: Grow value with specific use cases. Create immediate value through priority use cases, plucking your low-hanging fruit (projects with the most obvious and immediate potential impact). The Playbook recommends creating use cases “aligned to priority areas to encourage interaction with data. These use cases take the form of data assets—visualizations, reports, dashboards, and/or workbooks—that are useful, engaging, and offer insights to help solve immediate business needs.” Share examples of success to help create a virtuous cycle that deepens and builds engagement across the entire organization.

Some tips the Playbook offers to achieve this third step include: (1) identify subject matter experts in each department who can provide quick feedback and ensure that data and analytics teams have the business context they need; (2) identify use cases where teams could benefit from access to key data sources; (3) create purpose-built data assets like interactive visualizations, addressing key business processes and decision points; and (4) bring data assets into important meetings with stakeholders to encourage data-based approaches.

4: Promote widespread data discovery. You’ll want people at all levels of the organization to follow the data discovery cycle on their own as directly as possible. That takes data literacy: the ability to explore, understand, and communicate with data. Training and community programs can give people a dedicated space to learn, ask questions, share best practices, and encourage engagement.

Some tips the Playbook offers to achieve this step include: (1) prioritize collaboration in department-level goals and initiatives, empowering individuals to own decisions within their area and take data-informed action; (2) expand data exploration by making data sets and assets available through a common BI platform; (3) institute community-building programs like lunch-and-learns or user groups; and (4) document leading practices for data discovery to capture successful methods.

Following the 4 steps described above will advance you in a continuous journey of building and maintaining a data culture. For more insights about creating a culture of data within your marketing organization (and beyond), and/or about using Saleforce’s Tableau, please reach out to us!

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