First things first: should you even automate your marketing reports?
The answer is probably yes, unless (a) most of your reporting is ad hoc, detailed drill-down analysis rather than routine, and (b) you enjoy spending hours copying and pasting data from multiple platforms and attempting to create a visually appealing format using a spreadsheet.
Automated reporting can deliver massive efficiency gains by streamlining and simplifying data integration and visualization. That gives teams back hours they can use for more strategic tasks.
Automated reporting also reduces errors caused by manual data entry and can provide refreshed data without anyone's having to update a spreadsheet.
That said, automating marketing reports requires careful planning and up-front decisions. The discovery phase, which covers deciding what to include and sorting out data to bring into the reporting dashboard, will likely consume 80% of the project timeline, with the remaining 20% spent on the actual building of it and the QA related to data and functionality.
The following 10 tips can help you think through the entire process and ensure you've considered all elements of automating your marketing reports.
1. Understand the basics
Define the business goals your team expects the data to track in your report:
- How does it help your team make better business decisions?
- Who are the stakeholders?
- How often does everyone need to see the report?
- What value does it have for each stakeholder?
Depending on the answers, you'll know whether you need a simple report or something more complex—i.e., a business intelligence tool.
2. Map goals to KPIs
Figure out which KPIs you need to track progress toward the business goals and what data sources they come from that you defined in step one.
For example, if you're mapping sales goals, do you need to measure them overall, on a regional basis, or both? Look at data sources and make sure they can be captured automatically; if they cannot be, find out what it would take to automate those processes. This is where you carefully drill down to uncover the real need.
Most frequently, a stakeholder will be presented with an immediate challenge that she needs to deal with, but it's really a question on a larger scale that will change how a report is created.
For example, a marketing manager may be concerned about visits and conversions in the previous week for paid media. If you dig deeper, however, the real question to be uncovered is that the stakeholder recently changed media vendors and she needs to track whether the new solution is getting a better ROI. That deeper question calls for a very different report from the original ask.
3. Find the right cadence
How often does your report need to come out: daily, real-time, weekly, monthly, quarterly? Do your data sources have updating cadences that have to be considered when integrating that information into the report that match back to report delivery?
Keep in mind that automated reporting makes sense for routine information; ad hoc reports like one-time asks may or may not be a suitable candidate for automation.
4. Think about AI/machine-learning tools
Incorporating artificial intelligence and machine-learning applications into your report can provide insights that help you make better decisions.
Depending on the type of data involved in creating your report, it might be appropriate to incorporate AI and machine-learning to analyze large datasets and bring to the surface patterns that human analysis might miss.
5. Determine the report medium and visual elements
Will your report be delivered in an email, in print, or via an online portal? The medium will affect some of the decisions you'll make about what context to include and the font type (serif vs sans serif fonts based on digital or print), weight, depth, and spacing based of the visual elements of your report.
Many automated dashboard platforms account for viewing on mobile, but also consider that as you identify how your stakeholders will be viewing the reports. In addition, a great thing about automated reports is that you can produce eye-catching graphics that tell a story at a glance.
Also, think about the use of white space and color usage to improve readability and accessibility; be cognizant of the needs of people who have trouble distinguishing between certain colors.
6. Add automated alerts
If the information in the report you're automating is important enough to produce on a routine basis, chances are you'll want to know right away if there are significant swings in the numbers. Define automated alerts, determining the threshold for triggering a notice and identifying stakeholders who need to receive an alert.
7. Keep it as simple as possible
During the discovery process, it's likely that stakeholders will identify elements they'd like to see, and you may uncover new data sources that could add to the report's utility or ideas for visual representations.
Try to balance those choices with the need to keep the report clean and simple. Keeping your report simple tends to maximize its utility.
8. Decide whether to build or buy
Your report can be built in-house, purchased, or developed with the help of an outside expert. Making the right decision on whether to build or buy depends on an honest assessment of organizational capabilities, the complexity and compliance issues involved with the data sources you'll be using, the story you'd be telling with the report, and in-house access to expertise and/or tools.
9. QA, QA, QA; and set it but DON'T forget it
It's impossible to overemphasize quality assurance. Make sure your KPIs map back accurately to your data from the original source. Check it, and check it again, and then check it one more time.
Also, revisit your report regularly with stakeholders to make sure it's still achieving the tasks you identified during the discovery phase. The user journey changes over time, so the report may need to be updated.
10. Tell (not just show) a data story
The way the automated dashboard is structured should be clear and concise, and flow in a way that tells a data story. But the stakeholders who are viewing the reports wear different hats, and their strengths may not include the ability to draw conclusions from data.
Text insights are a complement to automated dashboards. That text accompanies the visuals with not only what the data/visuals mean but also what action to derive from it; that is critical to include in report delivery.
At a basic level, there are automated insights tools that will assist in providing text about what the dashboard is telling the stakeholder; on a more advanced level, AI-directed narrative insights are provided.
However, the human touch is an important component: looking at the visuals, analyzing what is happening, assessing what needs to be done, and making recommendations for improvement.
Though maximizing efficiency is essential, there is something to be said for human discernment in the evaluation and interpretation of evolving data.
* * *
Automated marketing reports are a great way to save time so you can focus on important tasks, such as planning campaigns and generating leads. If you routinely find yourself copying and pasting data from martech platforms into a spreadsheet and fiddling with graphs, automating your report is probably the right move.
Automated reports are also a terrific way to demonstrate the value that marketing provides on a regular basis, complete with visuals that tell the story of the progress you and your colleagues are making toward achieving business objectives.
And thanks to advances in automation technology, that doesn't have to be an uphill climb.
