Imagine this: after months of waiting for the new dashboard with promises of “actionable insight” and “democratized data” you click on the link and silence.  A numb feeling takes over as you stare  at the buttons and drop-downs as if they were from a commercial airline cockpit and wonder, what do you do with these fancy things do?

As the pace of business quickens, customers need data solutions that are truly self service and not self solve. Organizations continue to deliver solutions masquerading as self service, which offer extreme levels of flexibility and put the burden of solving the problem on the user. There is no service reflected in these solutions. A data product or solution should make the value of the data and how to answer a user’s questions readily apparent to truly be self service.  

Much of what we see in the consumer marketplace isn’t self-serve, rather it is self-solve. Take for example Trunk Club, an online men’s clothing retailer, where it asks customers a few questions about lifestyle, work-life, budget and sizes. Then, Trunk Club becomes their personal shopper and puts together wardrobe options, mailing them directly to the customer each month. This is a self-serve approach.


A self-solve experience, in contrast, will require more of your time.  The self-solve approach to clothing shopping is to turn buyers loose at the mall or on Ebay, where there is very little direction or guidance given to the shopper’s specific needs. Self-solve requires you to figure out the process yourself.   Self-solve involves an instruction manual or many rounds of trial and error.  

How do you know if your solution is self-solve or self-serve? Here are four clear points to help you distinguish the difference.

1. No Instruction Manual or Training Required. Remember the point of self-serve is to make life easier. Most users are not looking to invest more time, but less. Embed your training within the dashboard or application at key points.

2. Built to Answer Specific Questions. A self service solution is intended to answer specific questions. It’s not a means of just dumping information on someone.

3. Encourage vs. discourages exploration. While a long series of drop down menus may feel like it offers lots of exploration, it really doesn’t. Think of the paradox of choice. Offer a few options with interactivity, so the user sees immediately the fruits (or juice) of their efforts and wants to try more.

4. Make Steps Sequential. In the web analytics world you often want to see paths or steps the users took to make sure they’re guided down the intended flows. The same can be said for your dashboard. Make the flow or steps sequential and easy to follow.

What makes YOUR data powerful is creating an experience for the user that informs, instructs, and leads to smart discussions. Keep your audience engaged and deliver real value with a REAL self-serve solution. Don’t make them figure it out, because chances are, they won’t.

Review our design principles for a helpful guide and review examples of effective self-service models.

Schedule a demo to see how Juicebox can transform the information experience that your audience needs and values.