Sharing Analytics Reports Internally
As a web analyst, one of your job functions is to share reports and data with your internal stakeholders. There are obviously many different ways to do this. Ideally, you are able to meet with stakeholders in person, share your insights (possibly using some of the great techniques espoused in this new podcast!) and make change happen. However, the reality of our profession is that there are always going to be the dreaded “scheduled reports” that either you are sending or maybe receiving on a daily, weekly or monthly basis. I recall when I worked at Salesforce.com, I often looked at the Adobe Analytics logs and saw hundreds of reports being sent to various stakeholders all the time. Unfortunately, most of these reports are sent via e-mail and end up in a virtual black hole of data. If you are like me and receive these scheduled reports, you may use e-mail rules and filters to stick them into a folder/label and never even open them! Randomly sending recurring reports is not a good thing in web analytics and a bad habit to get into.
So how do you avoid this problem? Too much data has the ability to get your users to tune out of stuff all together, which will hurt your analytics program in the long-run. Too little data and your analytics program may lose momentum. While there is no perfect answer, I will share some of the things that I have seen work and some ideas I am contemplating for the future. For these, I will use Adobe Analytics examples, but most should be agnostic of web analytics tool.
Option #1 – Be A Report Traffic Cop
One approach is to manually manage how much information your stakeholders are receiving. To do this, you would use your analytics tool to see just how many and which reports are actually being sent by your users. In Adobe Analytics, Administrators can see all scheduled reports under the “Components” area as shown here:
Here we can see that there are a lot of reports being sent (though this is less than many other companies I have seen!). You can also see that many of them have errors, so those may be ones to address immediately. In many cases, report errors will be due to people leaving your company. Some of these issues can be addressed in Adobe by using Publishing Lists, which allow you to easily update e-mail addresses when people leave and new people are hired, without having to manually edit the report-specific distribution list.
Depending upon your relationship with your users, you may now be in a position to talk to the folks sending these reports to verify that that are still needed. I often find that a lot of these can be easily removed, since they were scheduled a long time ago and the area they address is no longer relevant.
Another suggestion is to consider creating a report catalog. I have worked with some companies to create an Excel matrix of who at the company is receiving each recurring report, which provides a sense on how often your key stakeholders are being bombarded. If you head up the analytics program, you may want to limit how many reports your key stakeholders are getting to those that are more critical so you maximize the time they spend looking at your data. This is similar to how e-mail marketers try to limit how many e-mails the same person receives from the entire organization.
Option #2 – Use Collaboration Tools Instead of E-mail
Unless you have been under a rock lately, you may have heard that intra-company collaboration tools are making a big comeback. While Lotus Notes may have been the Groupware king of the ’90s, tools like Chatter, Yammer, HipChat and Slack are changing the way people communicate within organizations. Instead of receiving silo’d e-mails, more and more organizations are moving to a shared model where information flows into a central repository and you subscribe or are notified when content you are interested in appears. Those of you who read my “thesis” on the Slack product know, I am bullish on that technology in particular (since we use it at Analytics Demystified).
So how can you leverage these newer technologies in the area of web analytics? It is pretty easy actually. Most of these tools have hooks into other applications. This means that you can either directly or indirectly share data and reports with these collaboration tools in a way that is similar to e-mail. Instead of sending a report to Bill, Steve and Jill, you would instead send the report to a central location where Bill, Steve and Jill have access and already go to get information and collaborate with each other. The benefit of doing this is that you avoid long threaded e-mail conversations that waste time and are very linear. The newer collaboration tools are more dynamic and allow folks to jump in and comment and have a more tangible discussion. Instead of reports going to a black hole, they become a temporary focal point for an internal discussion board, which brings with it the possibility (no guarantee) of real collaboration.
Let’s look at how this might work. Let’s assume your organization uses a collaboration tool like Slack. You would begin by creating a new “channel” for analytics reports or you could simply use an existing one that your desired audience is already using. In this example, I will create a new one, just for illustration purposes:
Next, you would enable this new channel to receive e-mails into it from external systems. Here is an example of creating an e-mail alias to the above channel:
Next, instead of sending e-mails to individuals from your analytics tool, you can send them to this shared space using the above e-mail address alias:
The next time this report is scheduled, it will post to the shared group:
Now you and your peers can [hopefully] collaborate on the report, add context and take action:
These are just a few ideas/tips to consider when it comes to sharing recurring/scheduled reports with your internal stakeholders. I am sure there are many other creative best practices out there. At the end of the day, the key is to minimize how often you are overwhelming your constituents with these types of repetitive reports, since the fun part of analytics is when you get to actually interpret the data and provide insights directly.