5 Critical User Experience Problems with SaaS analytics today
Posted On 31/03/2022
Your software product contains tons of valuable data and insights. And still, it’s likely many of your product users still make decisions based on their gut. A staggering 58% of companies do, according to recent surveys. Why is that?
The top reason is that people aren’t finding the insights they need. And popular software reviews confirm it. Reporting is one of the most common complaints among software users. To quote one of them:
But why is the analytics experience so frustrating to software buyers?
Below are 5 critical problems with SaaS analytics today, and more importantly, how you can solve them.
1. No added value
You would think basic analytics are better than having none at all. But creating analytics to tick off a feature checkbox is a dangerous play. Because you’re not creating a value-added customer analytics experience.
Insights have the potential to support business-critical decisions. Your customer’s success could depend on it. If you don’t consider the impact of your software on their business, your analytics could be useless.
Impactful analytics starts with your customers. How does your software support their business goals? What data points do they need from you to be successful? What next action can you tee up? Add these data points in your interface, right where your users need them. Only then, you’ll truly support their business strategy.
Let’s say a marketer wants to understand which subscribers have the highest engagement. They want to target their emails to all subscribers with the same characteristics. For most platforms, the experience would look like this:
They review multiple dashboards to analyze their most engaged customer segments. Once they’ve identified their targets, they head back to the campaign builder. They need to create a new filter containing the exact same parameters.
But wouldn’t this be even better?
They are in a dashboard showing engagement statistics by demographics and campaigns. In a few clicks, they filter their ideal target group. With one click from the dashboard, they create a campaign with the same filters. No more disruptions, it’s all in one single workflow!
Done well, your product analytics can reduce time-to-action from hours to minutes. You free up time for your customers to focus on other important tasks. In turn, your product becomes a more valuable asset.
2. Slow and dated
Slow analytics load times stress out your users. One in four visitors will abandon a website that takes longer than 4 seconds to load. A fast, performative analytics experience improves your product experience and can increase stickiness.
Imagine a high-stakes Wall Street trader. What if his financial charts take a split second longer to load? It could mean the difference between earning or losing thousands of dollars.
Besides speed, customers also expect real-time information. For time-sensitive matters, a data refresh every 24 hours just won’t cut it.
Think of trucks that transport perishable foods. They need to track freezer temperatures constantly to avoid serious health hazards.
The key to a fast and smooth experience is a good data model. Without the right analytical data infrastructure in place, your experience is doomed to be slow. You can’t build a house when the foundations are broken.
3. Too complex
A cumbersome interface drives bad user experience. And therefore, a big source of frustration. But what exactly makes it so difficult for customers to use a dashboard? Here are a couple of examples:
Dashboards are cluttered with too many charts
The dashboard has data tables instead of visual, intuitive graphics
There’s no logical order or structure to the dashboard widgets
A user needs 10 clicks to perform a simple action
Users are pushed to a different app before they can use analytics
Or even worse: there is no dashboard, only an ‘export to CSV’ button
A complex interface hinders your customers to find the information they need quickly. Unfortunately, it’s a reality for many. And it scares your users away. If you’re making at least one of these mistakes, it’s time to revisit.
A great customer analytics experience provides answers in one click, right within the customer’s workflows. It is stupidly intuitive and doesn’t require training. Anyone should be able to make smart decisions. Whether it’s the CEO of a Fortune 500 company or an intern who’s starting out.
4. Customers find it boring
The most boring analytics can still get the job done, but it may be hurting your platform usage. A “dull” experience won’t trigger dopamine release, a brain chemical that is associated with pleasure and reward. The same chemical is what leads to repeat experiences. Below’s an example from one of our marketing team members.
“As a marketer, I’ve used many advertising platforms. All with varying degrees of analytics. Google Ads and Capterra are perfect opposites.
I always dread using Capterra’s analytics. I end up exporting the data and manually creating a report. But in Google Ads, I could spend hours in their interface reporting. It’s addictive. With each little campaign tweak, I want to explore how my changes impacted our campaigns.”
An engaging and interactive analytics experience makes your product attractive. When exploring data becomes fun, your users will spend more time on your platform.
Appearance matters too. A good-looking dashboard makes your analytics experience more appealing to customers. It adds a wow effect, meaning extra ammunition for your sales team to impress and convince prospects.
5. Failing to surface your customer’s blind spots
A good dashboard exposes blind spots your customers don’t even know they have. For example, an electronics retailer found out that 23% of their inventory had never been on sale. Imagine you can expose hidden cost centers like this to your customers.
Sounds like a great idea in theory, but hard to make a reality, right? Here are a few mechanisms your customers will love:
Filters and slicers. Give users different ways to look at the same group of information to find their blind spots.
Customization. Let customers modify which data they visualize on a chart.
Personalization. The best software platforms adjust their insights to different user profiles.
Let’s circle back to the retailer’s situation. Their inventory manager will want to see how the inventory evolves, so they can restock at the right time. A salesperson, however, will want to know which products have the highest value, so they can focus on selling the right products. With the mechanisms above, you can build one experience that uncovers the blind spots of both.
A good customer analytics experience is tailored. With custom KPIs per user, your product will make a lasting impact. And that inevitably leads to more customer retention.
A fresh start to your customer-facing analytics
It’s never too late to take a fresh start with analytics. And it doesn’t have to be difficult or time-consuming. Embedded analytics software helps SaaS providers tackle all the customer analytics challenges discussed above in less than 2 months. And you can do it, with less engineering resources than building from scratch.