Building out your audience and then segmenting that audience to ensure you’re delivering the right message to the right people is critical. However, it can be confusing to determine how best to improve your efforts.
Oracle’s Marketing Maturity Model can help you determine where your organization is in developing its various capabilities and what should be done to enhance them. In Part 1 of this series, we talked about how to uplevel your capabilities to Stage 2. Let’s quickly review what B2B audience building and segmentations looks like at that stage.
Stage 2: Cross-Channel
Businesses at this level have data that’s still largely siloed within systems and departments, but they’ve put some manual integrations in place that allow them to see the bigger picture in terms of behaviors and trends. Data privacy and governance is siloed as well.
Marketing, commerce, sales, service, and other departments augment their first-party data with second- and third-party data, giving them a better understanding of their customers across channels. Aggregate-level performance dashboards are available, and decisions are based on historical data. Customer experience efforts are marketing-centric and don’t involve other departments in a significant way.
If your business doesn’t operate at that level yet, then let’s take a step back and look at how to enable cross-channel B2B audience building and segmentation. But if your business is already achieving that, then let’s talk about…
How to Uplevel to Stage 3: Data-Driven
Moving up to a data-driven approach entails centralizing your data from all channels and departments so you can ask WHY questions, not just WHAT questions. It also means having access to enriched and real-time data, so your analytics and targeting efforts become more flexible and actionable.
Let’s look at how your organization might level up its audience building and segmentation efforts.
The major shift here is that you’re moving from having an audience for each of your channels to having a single audience for your company. With the silos broken down, you have much better visibility into customer behavior and trends across your engagement touchpoints.
Centralizing Data Sources. Transforming your business into a data-driven organization starts with centralizing data and having platforms that speak to each other in a common language. Disparate data sources often lead to a wide range of challenges, including siloed teams and misrepresented data points.
Start by identifying sources of critical customer information that you need to drive your key performance indicators (KPIs). Having connected IDs or a shared Globally Unique Identifier (GUID) across platforms will provide you with a more comprehensive view of your contact and accounts.
Centralized Data Governance. Centralizing your data isn’t just a technological change. It’s an organizational change. Create accountability for your data’s accuracy, privacy, and governance by naming a head of data. The exact title doesn’t matter—we’ve seen a huge range of titles!—but having someone be responsible for your data management is key.
Without that, data inaccuracies, improper data access, and other issues will continue to be a problem. We work with our clients on not only building a single source of truth to manage data across all their systems, but also on delivering a single version of the truth where they can consolidate analytics across various systems.
Having better audience-building capabilities, powered by a centralized data pool, sets you up to be able to demonstrate to your audience that you understand them and their needs on a deeper level. Now that most of your manual data aggregation has been replaced by an integrated central repository, segmentation is easier and faster than ever.
Dynamic and Connected Customer Profiles. Having a synchronized database that’s integrated with new applications and systems provides you with access to a richer set of data. Having first-, second-, and third-party data and information from both back- and front-office sources gives your company the ability to send segmented messages to increasingly sophisticated target audiences.
You aren’t yet able to address audiences based on predictive scoring such as the propensity to churn or purchase, but you have access to a rich view of your audience and their historical behaviors. Leveraging this data from across the organization will give you the opportunity to implement new A/B testing strategies, identify new insights, and ultimately build more engaging content.
Real-Time Data. Historical data is great, but adding real-time data allows you to respond to trends of the moment. This kind of data is incredibly valuable during peak selling seasons, product launches, and other times when audience behavior is unpredictable and fluid.
Cross-Departmental Behavior. Orchestrating your messaging across your marketing channels was the first step. Now you’re expanding that orchestration across at least one other department, whether it’s sales, service, or something else. You’re developing a voice that’s a little less marketing-centric and one that does a better job of speaking for your entire company and the interactions that your customers have with it as a whole.
Data equals success in modern marketing, especially when you use real-time data and digital analytics to inform your campaigns. See how you can “Go Further with Digital Analytics.”
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