Okay, so you just purchased a subscription to Domo. Congrats! You have taken the first step into becoming a more data-driven business professional. You now have this incredibly powerful tool that can transform raw data into beautiful visualizations and insights right at your fingertips. It might even seem a bit overwhelming. Where do I start? What am I trying to accomplish? How can I put the investment I just made into action?
Your urge at this moment is to dive headfirst into connecting Domo to every data source at your disposal. Although it’s tempting, you will have longer lasting success if you develop an implementation plan.
Planning your Domo implementation in advance ensures that precious time and energy isn’t wasted. By creating a plan, and getting buy-in from executives, every dataset will be built to solve a business question. The following 3 planning steps planning steps will help you get the most of Domo, and keep you from getting lost in a vast sea of data.
Step 1: Articulate the business questions you are trying to answer.
Always start with the key business question you’re attempting to answer with data. Although it sounds straightforward, teasing business questions out of executive requests can be difficult. “How many visits did the microsite receive?” is not a great business question because it doesn’t elicit action. Knowing the number of visits will not help you move your marketing strategy forward. Determining “what” or “why” data is important will help you build better visualizations. “Where am I getting the most value on marketing spend?” and “What are the most profitable products online?” are perfect examples of questions that are tied directly to a desired outcome. Knowing the answer to these types of questions will generate business insights that drive action.
The diagram above shows the interrelation between business questions, metrics, and the data sources.
Step 2: Map Out Your Metrics
Once you have established your list of key business questions, the next step is to map out the metrics needed to answer them. Often times a good business question will require several metrics to develop a succinct answer, so it’s important to list out all the data points that are needed. For example, if I’m trying to determine ecommerce profitability, I’ll need inventory information, products sales, and product cost of goods. Another reason it’s important to list the metrics needed is to avoid bringing in too much unnecessary data. By streamlining your data requirements, the subsequent data refreshes will occur more quickly and you can stay focused on what matters most.
To help create a full story of the data, it’s also critical to map out your data dimensions. Dimensions describe the characteristics of your data. This gives context to the data once visuals are generated. A few examples of data dimensions include geographic region, marketing channel, and even time of the year. Although the metrics will tell you what is being measured the dimensions will deliver value as you analyze the data.
Step 3: Map Out Your Data Sources
Finally, we need to map out the data sources needed to return the selected metrics. Often times it will require two or more data sources to create the necessary metrics. For example, website engagement data might be kept within your web analytics platform, while ad spend data is in your bid management tool. Therefore, to answer the business questions of “What campaigns have the highest ROI?” would require spend from the bid management data source and conversion data from the web analytics platform.
Planning your implementation might be one of the biggest time-savers when it comes to working with Domo. Not only does it force you to focus only on the pieces of data that matter to your company, but also ensures you are driving towards answering key business questions. Answering questions in real-time to drive real change without wasting precious time and energy – that’s the Domo value proposition.
Still have questions or need support planning a large-scale implementation, drop us a line! We’re always looking for the opportunity to talk data.