Adobe Data Workbench: Success Is in the Details

I’m going to run the risk of stating the obvious, but it’s worth reminding everyone that Adobe Data Workbench is a powerful tool. Its boundless use cases and flexible, customizable nature are an analytics practitioner’s dream. But why does that dream seem to be so stressful at times? Let me propose the following theory: too many Adobe Data Workbench users are focused on “multichannel.” And by multichannel, what I really mean is that they want as many data sources as possible … and they want them yesterday.

Please don’t get me wrong; Adobe Data Workbench’s multichannel capabilities are one of the many reasons that it is such a powerful tool. The problem, as I see it, is that users place too much focus on the number of data sources in a dataset, when they should be focused on the data points — or, more importantly, on the quality of those data points. And most importantly, they should focus on the degree to which their organization is capable of acting on the findings that those data points are sure to yield.

In other words, multichannel is the vehicle that carries you to success, but success is realized in the details.

My suggestion? Don’t make “multichannel” the details.

Instead, focus on customers and properties, both online and offline. Adobe Data Workbench will always be most effective when properly aligned with the overarching strategies and objectives that drive your business. In fact, I would argue that without ensuring that alignment, your organization runs the risk of encountering inefficiencies as an analytics organization — and that is due to the very features that make the tool so powerful. In other words, without direction, the tool’s flexibility and versatility could lead an analyst on a wild goose chase.

By following a logical, structured process — not dissimilar to a strategic planning session — you’ll find yourself in a much more efficient state of operations. A state that will accelerate your ability to realize value through Adobe Data Workbench. And better yet, a state that serves as a foundation from which your analysts can conduct more creative, improvisational analysis that has a higher likelihood of being actionable and adding value to your organization.

In that spirit, I’ll leave you with the following four-step recommendation for setting sail in the right direction:

  1. Hold a brainstorming session to outline the overarching goals and objectives for your firm as a whole, or at least for the stakeholders that you support as an analytics organization. Remember, while clichéd, no idea (or goal) is a bad idea. Writing down and visualizing these goals will help you to think creatively about how your organization can positively influence the firm’s larger objectives. Which leads me to Step 2 …
  2. Based on those goals and objectives, identify all of the variables (customer behavior, messaging, online/offline properties, etc.) that might influence the likelihood of your accomplishing those goals. This is your standard who, what, when,__ and where. And don’t stop at identification. Think of ways that those properties interact with and influence each other, and ultimately create cause/effect relationships. This will help your team build competencies around multichannel analysis because it’s a different exercise than traditional siloed, assumption-based analysis. As an example, how might order delivery, customer satisfaction, and/or customer service interactions influence future customer transactions? Adobe Data Workbench allows you to see that relationship.
  3. Match those variables to the available data sources/data points in your Adobe Data Workbench profile, and try to identify new data sources that should be added to address data gaps. This exercise will help provide definition around the data points that are available and will build consensus around the ability of those data points to answer your business questions. It will also open up the possibilities of acquiring new data from different parts of the firm and support cross-functional collaboration.
  4. Finally, develop Workspaces within Adobe Data Workbench that allow you to meaningfully analyze those data points in an efficient and impactful manner, while always asking the questions, “What are we prepared to act on?” and “What is the intended outcome of this analysis?”

Implementing this structured process can help you maintain operational efficiency by keeping your organization focused on data points that matter. Doing so is the fastest way to realize the true power of Adobe Data Workbench, which comes from helping you find and focus on goal-oriented data points rather than flounder in endless possibilities. There will always be time for adding new data sources, but you might find that you haven’t fully utilized the current data sources. Doing so will make for a happy bottom line, happy management, and happy stakeholders.****