How Self-Service Analytics Leads to Digital Maturity

“Give a child a fish, and you feed them for a day. Teach them how to fish, and you feed them for a lifetime.” 

This nugget of wisdom may have had a wildly different application in the past, but the adage holds incredibly well when talking about how organizations share knowledge today. 

Think of it as a vast body of water, where every fish is a valuable resource waiting to be pulled from the depths for the whole village to be fed. In the same way, businesses today sit on vast data lakes consisting of all their digital properties, and yet, there’s only a few villagers fishing for valuable insights that are so readily available to them.

What if every villager knew how to fish?

Self-Service Analysis as a Way of Business, Not a Tool

Oftentimes, organizations will seek out consulting services because they lack the human resources or the know-how to implement business analysis workflows that follow a clear plan. We see them reach this state when the business gets to a point where it can’t wait any longer to move toward full-on digital transformation. Be that as it may, we are also starting to see a trend with businesses becoming more closely tied to the data they own. 

This shift is enabling organizations to empower their teams to utilize their own data, transform relationships with their consultants and partners to start taking on a more investigative role, explore innovation in their digital infrastructure, and lean on their expertise for strategy rather than an ad-hoc report-building approach.

Enter self-service analytics. 

Corporations are starting to adopt self-service analytics to transform their operations and empower their teams to leverage the data at their disposal. The requirements for this new way of business can be grouped into three large buckets.

• Ownership: Giving the right owners the right set of tools.
• Direction: Optimization and growth are the main compass, but it all starts with defining the data architecture.
• Collaboration: Foster an ecosystem that enables internal and external input.

Let’s dive into each of these points in more detail. 

Ownership and Defining the Data Architecture

Connecting your most relevant data sources into one reporting tool that warehouses the data, combines it, transforms it, and helps you visualize it is a key step in this enablement process. 

For instance, your organization could leverage a centralized system like the Google Marketing Platform, which rolls up several products to build your stack. 

Some of these may include Google Analytics to study website behavior; product linking to other clouds such as Salesforce or AdSense; BigQuery for complex data explorations; or Data Studio for visualizing all of the data from your online (and even offline) touchpoints. Combining all of these tools into one warehouse allows teams in your organization to connect the different data points and centralizes them to inform cross-business-unit teams via self-serve reports.

In defining the data architecture, we also look into data integrity, which ensures the data is as accurate, recent, and structured as possible. This allows users who are heavily involved in data analysis to trust they can make the right business decisions and empowers them to use the right data points to make choices relevant to them and the teams they impact directly. 

Collaboration and Data Literacy

Aim for communication over isolated independence.

The outcome is optimization as a result of incremental collaboration, rather than total autonomy. Think of it as the island of Manhattan – it stands on its own, but the multitude of tunnels and bridges connecting it to New Jersey and the other NYC boroughs make it the economical heartbeat of that coastal region. 

In a similar fashion, your self-service reports and dashboards act as a Manhattan to your sales team, web designers, strategic leads, and executives who are primarily concerned with day-to-day business operations. These reporting vehicles, once stood up, are easily accessed by different teams to leverage insights.

More importantly, these self-service tools stand as a magnifying glass for team members who are not necessarily data savvy but need to understand how the organization is evolving to make better, more informed business decisions. 

This facet of self-service analytics then promotes growth by empowering any and all users to access data and put on their thinking hats with the resources that are readily available as a result of day-to-day operations. 

Continuous Improvement and Maintenance

The work doesn’t stop there.

Once your teams can access data and understand how to derive actionable insights from the data they own, the opportunity is laid out to leverage consulting services to sustain the environment and ensure a high level of data quality. 

This is particularly important when you need to resolve problems in the back end, such as those created when third-party vendors update their data retroactively, causing ingestion issues in your dataflows.

An alternative scenario requiring maintenance is when you need to add new data sources to add more color to existing data points.

Consulting services can also help you make changes when there are disruptors to the marketing plan and the current setup no longer makes sense – for example, when macro factors such as COVID or inflation cause shifts in ad spend. 

This process of continuous improvement and scheduled maintenance speaks strongly to the other side of the collaboration coin, where your teams are enabled to work closer together within your organization and can collaborate closely with third-party agencies to foster a healthy data environment. 

Self-Service analytics is an ongoing process of refinement

Building towards Digital Maturity

In a previous article, we illustrated how a reporting framework sets the stage for defining metrics and dimensions that will allow us to measure performance via reporting vehicles. 

Once this system has been stood up, the findings and insights unearthed from a dashboard or an automated report, or any other self-service vehicle for business analytics, then start to provide guidance for key areas of the business. It is then when our teams become fully empowered to craft compelling ad strategies, optimize budgets, or set up effective A/B tests, to name a few examples. 

The Google Marketing Platform accelerates this process by rolling it all under one umbrella of services. Running your ads via Google Ads or Google DV360 allows you to roll it up directly into Google Analytics, combine it with Salesforce data by linking to the Salesforce Marketing Cloud, and ultimately enable you to set up self-service reports in Data Studio. 

Regardless of your marketing strategy, the entire process of creating a self-service environment should be actionable and lead to clear outcomes that translate into business momentum that accomplishes your organization’s goals.