This is the subhead for the blog post
Many marketers use “reports” and “analysis” interchangeably, which places undue burden on what a report should do and doesn’t give enough credit to analysis. Simply, a good report shows you what happened; good analysis provides answers for why it happened and helps you plan what to do in response.
Let’s dive a little deeper into each, starting with…
The basics of reports
There are two main reporting requests:
- An ad hoc request
- Recurring reporting requests
Ad hoc requests are for a very specific question; marketers should strive to answer these quickly and with precision. Should these questions lead to many more questions, what’s really needed is analysis, not more reports.
Recurring report requests can be used to answer tons of business questions: daily spend report, weekly performance report, quarterly look-backs, etc. Reports should be simple and consistent so that users know where to find the necessary info; try to use the same metrics and put them in the same spot every week.
Basically, reports are meant to present important data. Of course, sometimes the data provokes questions, e.g. Why was there a drop in traffic? (That’s where analysis comes in.)
It’s always important to step back and determine which data is most important to show in reports. Just because we have touchpoint-level data doesn’t mean that we should use it in every visualization. Keep reports uncluttered and focused on a meaningful picture. For instance, we don’t need every single day of the year broken out into results…that can only allow you to answer what happened on one day but won’t show trends.
A good report is by nature limited but focused. Which leads us to…
The basics of analysis
According to Businessdictionary.com, one definition of analysis is “An examination of data and facts to uncover and understand cause-effect relationships, thus providing basis for problem solving and decision making.”
So, basically, analysis takes reports to the next level, digging into the data to come up with whys and what-nows. At 3Q, we achieve much of this by connecting our data warehouse to a reporting tool (most commonly Tableau) to combine data visualizations with multiple layers of data to bring more questions to the surface – and provide answers. (This would be a great place for a screenshot of an insightful example.)
Some of the common questions we can answer with our analysis:
- Where low-hanging fruit exists
- Where to spend the next dollar/what to do next
- How to develop a plan of action and get alerts when strategic changes need to be made
Of course, tools and data alone won’t give you the full picture; marketers need to be willing to dig into the data, test and defend their hypotheses, and either exercise patience or think outside the box when the data isn’t conclusive enough for a clear analysis. And that’s where the real value – one that far outstrips anything even the most finely crafted Excel report can show you – comes in.
An example of analysis
So, given all of that, it’s probably most helpful to show you an example. Check out this visualization:
This view has a lot of actions, although we would still need to use the filters to determine the exact next steps. An easy way to think of this visualization in quadrants:
Top right: High-performance campaigns that receive a lot of traffic and generate a lot of conversions
Action: continue to invest here!
Bottom right: I would investigate these campaigns because many people are engaging with the ads and visiting the site, but those visits are not leading to conversions.
Action: Revisit strategy to decide if these campaigns are wasting money by generating potentially unqualified traffic, or if the awareness is worth the investment.
Top left: High-potential campaigns that are generating relatively little traffic but converting at a higher rate.
Action: Increase budgets on these campaigns to ensure we give the users every possible chance to convert.
Bottom left: Low-traffic, low-conversion campaigns.
Action: Confirm that this is valuable traffic and that these campaigns fit into the broader strategy.
Now imagine layering in things like geo and demographics…the insights you can glean are incredibly deep and rich and might make that Excel workbook you’re using look pretty meager in comparison.
Any questions or favorite data visualization tools to share? Drop a comment.