Many large organizations are missing an effective governance model for digital analytics. The critical need for governance usually appears when new campaigns are launched with great expectations and hype, but end with little or no defined measurement plan to satisfy the business owners. Assigning roles and responsibilities, identifying and documenting operating procedures, and defining overall standards for digital analytics – these are the main tasks of developing a successful governance model. This model can help you socialize and institutionalize the value and adoption of digital analytics for decision support throughout the organization.
- How will you make effective and timely decisions, using enough relevant data to manage the increasing complexity of your digital investments?
- How does your website data map to your existing critical business metrics?
- Do you communicate lessons learned and share knowledge across teams and business units in order to avoid the silo effect?
- Are you learning more about how your prospects and customers are interacting with your company on the desktop, with mobile devices, through social media, and in offline sales and marketing channels?
A successful digital analytics governance program can help find answers to these critical questions. Good insights come from good data. Good data comes from good people, processes and systems that are coordinated through a good organizational structure – in other words, through good governance.
What is Digital Analytics Governance?
Digital analytics fits into the broader context of analytics across the organization. Sales records, call center data, logistics records, supply chain metrics, customer satisfaction surveys, inventory and other financial data all combine at various points to form the corporate data supply chain. This idea of a supply chain for your data runs from the point at which the data record itself is generated, all the way through the organization, to the ultimate point when someone gains actionable insight from this information.
Our systems are generating more data than ever before. With limited resources to manage the increasing quantity and complexity of this data deluge, it’s critical to gain senior management involvement and guidance. This helps to avoid inaccurate, inconsistent, and incorrectly interpreted data. It is no longer enough to just slap the “data-driven” label on the website and the annual report. In order to remain competitive, we must invest time and resources into our data supply chains to maximize the strategic, tactical, and of course, profitable benefits of all this information.
What can you do with Digital Analytics?
To better understand a best-in-class digital analytics governance model, we should first look briefly at some of the main uses of digital analytics:
- Calculating, understanding, and increasing return on investment for digital and offline, drive-to-web initiatives
- Increasing, monitoring and improving visitor (customer and prospective customer) satisfaction
- Measuring and improving content and web application effectiveness
- Gaining deeper understanding of website visitor behavior
- Enabling measurement of the user experience
- Measuring social media activity and impacts
- Measuring and evaluating the competitive landscape • Business reporting and analysis
- SEO & SEM tracking, reporting, analysis, testing, and optimization
- Campaign tracking, reporting, analysis, testing, and optimization
- Segmented channel tracking, reporting, and analysis (Channel mapping / Referrer segmentation)
- Segmented funnel tracking, reporting, and analysis
- Email marketing tracking, reporting, analysis, testing, and optimization
- A/B and multivariate testing
- Content strategy tracking, reporting, analysis, and testing
- Marketing ROI tracking, reporting, analysis, testing, and optimization
- Continuous improvement process tracking, reporting, analysis, testing, and optimization
- Prioritizing development initiatives
And that’s just a sampling of what we can and should be doing in our digital analytics projects. But how can we set ourselves up better for success in planning, executing, and managing these projects? In the next blog post in our Governance Series, we will explore the components of a successful digital analytics governance program.