How You Can Jumpstart Self-Service Analytics

The core principles for getting the self-service analytics engine started are document, simplify, tool up, and train. Here are a few ways to get your business' stakeholders on the path to data driven decision-making.

What is self-serve analytics?

Self-service analytics (SSA) is the enablement of business stakeholders (non-analysts) to answer basic questions about the performance of the business themselves without having to rely on more technical peers. Fundamentally, self-service analytics is about streamlining your data collection and reporting so that it is easy to understand and utilize for people who aren't necessarily in the data day in and day out.

How can self-serve analytics help my business?

It's easy to see the phrase "self-service analytics'' and think "that's just another buzzword", however, nothing could be further from the truth. One of the tightest process bottlenecks in any organization is requesting work through the dedicated analytics team. Even for large enterprise organizations the analytics teams are traditionally too small to service every request for data the organization has. By making data easier to access and understand, stakeholders who would normally have to wait for their analysis to be completed can use the reporting and visualization tools themselves to get insights faster. Faster insights means faster decisions and benefits your organization's ability to respond and adapt to changing market conditions. Because these stakeholders now have the ability to get data for themselves when they need it rather than having the added friction of relying on an analyst for a simple request it means these stakeholders are more likely to have their decisions driven by data rather than guesses.

Beyond making your business more data driven, democratizing your data has one other frequently overlooked benefit; it allows your analytics team to do less “low skill” reporting and spend more time focusing on “high skill” analysis like clustering and predictive models. This benefit by itself can be game changing for organizations because it can unlock new growth potential that was previously unavailable.

How can my company set up self-serve analytics?

Given that analytics or business intelligence teams would have more time for interesting and brain stretching analysis you would think that many of them would be all aboard the self-service analytics train. The reality is that many analytics teams are so used to doing this low-level analysis that they worry they won't be useful if other stakeholders are able to do that reporting. They may couch that fear in statements like “we're worried about the integrity and consistency of company KPIs” or that stakeholders won't be able to do the reporting correctly. These sentiments are typically expressed because the analysts are worried about their job security. Given the typical response from many analytics teams, step one for rolling out self-serve analytics is to help the analysts in your organization see how it benefits them.

Winning hearts and minds is a key part of the journey to self-serve analytics but it isn't the whole story. Making the data easy to use is the next big hurdle. Easy to use has a few different components but they roughly correspond to three tenants:

• Document: Provide good documentation about what events and attributes are available and what they are used for.
• Simplify: Only expose the events and attributes that are absolutely necessary to limit confusion.
• Tool Up: Pick tools that are easy to learn for visualizing data.
• Train: Provide adequate ongoing training to stakeholders that covers 1, 2, and 3.

Your documentation should include a full map of all your analytics events and attributes but there should be specific documentation for business stakeholders that only covers the essentials so they can focus on those; this is one area where Anamap can help. Anamap allows you to visually layout your customer experience so stakeholders understand the flow through your site or app and allows you to control which events and attributes are exposed to users. Having control over which attributes are shown to users can have a big impact on the adoption of SSA. If the documentation seems daunting and overly complicated users are likely to be overwhelmed or experience frustration finding important events resulting in disengagement from the self-serve analytics process. Check out the free trial of Anamap to get started.

As far as easy data visualization and reporting tools go I can recommend a few: Amplitude: it's expensive but I think it generally provides a good UI that is easy for non-analysts to use with a bit of training. My only gripe is that Amplitude needs a way to hide events and attributes for specific user groups so the dropdowns are more streamlined. Additionally, Amplitude can be pretty expensive. Looker: acquired by Google a while ago this is baked into the Google Analytics environment now. It provides a good interface for reporting but it can be a bit more complicated and similar to more advanced BI tools such as Tableau. Adobe Analytics: as much as I would love to move away from Adobe Analytics I have heard so many analysts and stakeholders say they like how the UI operates. The drag and drop nature and straight forward table interactions make this a potentially good choice. Again, the biggest problem here is cost. Adobe charges a pretty penny for a sizable analytics footprint; they also suffer from the inability to hide events and attributes for certain users.

The last but arguably more important piece is training. Proper training is so often overlooked that I covered it in my common analytics mistakes post. For training the best option is to create small tailored training sessions for groups of business stakeholders within your organization and support those with a weekly drop-in Q&A or brown bag session. Most tools cannot be properly taught in a single session even with targeted training.

For the initial course of training I would recommend at least three 2 hour long sessions all squeezed into a two week period if possible. Under ideal circumstances you would have short “homework” assignments for the users that could be walked through as part of the next training session. These training sessions and homeworks can be encouraged through the use of workplace rewards such as recognition, badges, etc.

The weekly drop-in Q&A or brown bag session can provide a low barrier for users to come and get help if they forget specific aspects of a tool or your company data schema. This low barrier is important because it makes your self-serve analytics users more likely to come to you with problems and continue using the tool versus having a problem and just silently giving up.

What are some tools to help with democratizing my data?

• Documentation:
  • Not surprisingly we recommend Anamap here because we built it for the express use of making it easier for everyone in your business to understand everything being tracked in a visual analytics map.
  • If you're not sold on Anamap the next best option is a wiki using Confluence, SharePoint, Notion, or something similar. These wiki pages can have links to other pages which can be maintained by separate teams to distribute the work of maintenance.
  • Your last option, though it's not recommended, is a spreadsheet. Having seen just about every format of analytics tracking spreadsheet I can tell you that if you use one you're going to be hard pressed to get self-serve analytics off the ground. Spreadsheets are hard to maintain as your data schema gets larger and more complicated and they are challenging to read even for technical users.
• Easier to learn reporting tools:
  • Amplitude, Looker, or Adobe Analytics would be my choices here. There are probably other great options out there that I haven’t used just yet.
• Training incentive program:
  • Vantage Circle, Work Human, Kudos, and Cool Leaf have an internal reward / recognition system that allows employees to earn points as well as badges. It can be used to help incentivize company employees to perform specific actions that further your self-serve analytics initiative.