What's Covered
Adding user-facing analytics to your product has many benefits. It can significantly increase real and perceived value for your customers as well as help you hit your KPIs. Making data available to your users can also engage them and allow you to bring in new business.
If you’re reading this article, then you’re probably planning to add analytics to your product and are exploring the different delivery options. There are several options available and many companies have been down this road before. So, we spoke to three engineers who added customer-facing analytics to their products to understand how they approached it—and summarized some of the takeaways in this article.
Read the stories of Sindri, Justin, and Michel Felipe to get the lowdown on the challenges they faced and the lessons they learned. We hope that this article will save you the time, money, and hassle of making the same mistakes.
Design and build fully bespoke user-facing analytics in 10% of the usual dev time. Learn More.
Three experts share their experiences
What do an online ticket vendor, a shipping intelligence platform, and a talent scouting tool have in common? Each one has been on a journey to find the right solution to deliver their customer-facing analytics and struggled to find the one they dreamed of for their customers.
Like us, the engineers behind these solutions know how complex it is to custom-build user-facing analytics into an app. Let’s read the stories of Tixly, Revelo, and an anonymous shipping intelligence company we’ll call ‘Shipintel Co’, so you can learn from their experience.
1. Tixly: A ticket-selling platform for cultural houses and art performing venues
Tixly is a ticketing service for cultural venues, theaters, operas, symphonies, and concert halls. It’s different from similar solutions for two reasons:
- It doesn’t promote big concerts or sporting events
- It gives venues and producers access to all ticketing and sales-related information
According to Sindri Már Finnbogason, Founder of Tixly, the platform features five user-specific dashboards. For instance, box office personnel can check upcoming event ticket availability, while managers access data such as daily sales and revenue comparisons.
How Tixly develop its user-facing analytics experience
Sindri always envisioned user-facing analytics for Tixly. Initially, he worked solo as a backend developer, relying on design components from top charting libraries.
One of the reasons he initially chose to build it in-house was because embedded solutions took away control. “I looked at a lot of products for embedding dashboards for my users. Embedding works fine, but you can't control the user experience,” he says.
He needed to ensure a consistent UI which he couldn’t do with embedded systems. “You might create a fancy dashboard in some embedded application fast, but it looks out of sync with the other elements in your system. You have different buttons, calendars, and letters. You can probably style some of it, but it's never the same,” Sindri adds.
Three years later a front-end developer joined the team and now there’s a creative director, design, and product teams responsible for iterating on the solution and designing and developing new features.
Developing in-house gives some great benefits that fit many companies in Sindri’s position, but it’s still the more costly option in terms of developer hours.
Sindri and his team are now introducing Embeddable to build their customer-facing analytics. This toolkit delivers on their need for a native experience, whilst saving them the cost of building and maintaining their analytics with internal developer hours. As beta partners of Embeddable, the Tixly team is one of the first to adopt the new technology.
Challenges Tixly faced when developing customer-facing analytics
At some point, Sindri tried Amazon Quicksight as an embedded solution to see if he could simplify product development. While he managed to make it look good and similar to Tixly, he just wasn’t convinced with the result. It was costly and hurt the UI/UX.
“I just knew that if I was going to create a beautiful product, I had to do this myself because if not, the consistency would be bad. I couldn’t really be stuffing things into the product that isn’t our solution.” —Sindri Már Finnbogason, Founder of Tixly
How user-facing analytics helped Tixly increase word-of-mouth-recommendations
One of Tixly’s most important KPIs is simplicity: Is it easy for end users to use the system and perform their daily tasks?
It certainly looks that way, since Tixly has never lost a customer. “We don't have a big sales department, our software has sold itself in a way, we sell by word of mouth. The key factor that people mention when they talk about our solution is its simplicity, usability, and user experience,” says Sindri.
2. Revelo: A staffing agency for developers
Revelo is a talent agency that interviews and vets developers and connects them to potential clients. Three months ago, it launched a data analytics product called Team Analytics. “It helps tech leaders manage their teams by letting them easily track team performance metrics and delivery capabilities,” says Michel Felipe de Sena Nassif, Senior Product Manager at Revelo.
Revelo was well aware of the benefits of customer-facing analytics and chose to launch this module to increase the value for its customers. In Michel Felipe’s opinion, there are three ways in which customer-facing analytics can provide value:
- Reinforcing the product's value proposition by demonstrating its impact on users' lives. For example, a navigation app like Waze shows users the time saved on recommended routes.
- Providing strategic data for benchmarking and informed decision-making, like LinkedIn's "Talent Insights" which helps recruiters make informed hiring choices.
- Offering performance insights. Team Analytics empowers tech managers to enhance their teams’ performance by extracting valuable data insights. This could translate into higher performance and better business outcomes.
“Our goal was to employ a product-led growth strategy to provide an exceptional value proposition to our primary user segment including tech managers," explains Michel Felipe. "For this, we conducted research and saw that they wanted to know how their team was performing. We found that tech managers found it difficult to extract and use the data for measuring improvements.”
How Revelo built its Team Analytics product
“We built it in-house using an open-source front-end library because it accelerated the development,” says Michel Felipe. The development team at Revelo also had to make sure the interface offered the same experience and functionality for the end-user. This means they had to customize the analytics experience for each specific use case, which wouldn’t have been possible if they chose to embed a dashboard from a BI tool.
Challenges the Revelo team faced when designing the Team Analytics solution
“One of our main challenges in developing this analytics product was to see how the graphs and insights would behave with actual data,” says Michel Felipe. When he and his team were prototyping the interface it was steep to picture how the data would actually behave and look.
They wanted the user interface to make it easy for end users to interpret and extract insights, but didn’t necessarily know how it would look with real data. “We had to make several adjustments to the charts after deployment because we noticed it could confuse users, especially in cases with outliers,” adds Michel Felipe.
How user-facing analytics helped Revelo increase sales leads
Revelo wanted to capture the attention of tech managers and knew it was possible with powerful data analysis. Coming up with a user-facing analytics portal on top of its core business helped Revelo reach its goals.
While free, this new product has already helped Revelo gain new leads. “We launched Team Analytics at the beginning of August. Even though it's the newest product led-growth (PLG) launch, it’s already responsible for increasing the number of sales-qualified leads coming from free products by 25% between August and October,” says Michel Felipe.
3. Shipping intelligence company ‘Shipintel Co’
This anonymous shipping analytics and invoicing company we’re calling ‘Shipintel Co’ compiles data from all carriers such as UPS, FedEx, DHL, or the USPS (United States Postal Service) for shippers to know exactly where their packages are at all times.
The problem it solves is that carriers often lose the packages, have delays, or invoice them incorrectly. Looking at the data from each individual carrier can be overwhelming and it makes it hard for businesses to keep track of all shipping information. This tool compiles all data and makes it available for end users in an easy-to-use dashboard. They make it all available at a more affordable rate than competitors, democratizing access to shipping analytics.
“We want to make it really easily accessible to any SMB (small and medium business). If you're knitting socks in your living room and selling them on Etsy.com, you also need to review if your packages are getting where they’re supposed to and if you're getting charged properly,” says Justin, CEO of ‘Shipintel Co’.
To make sure analytics are truly useful to all customers, Justin and his team match each user with a dashboard that goes from novice—showing around 6 KPIs—to expert—showing around 50 KPIs. This way, even first-time users can see exactly the amount of detail they need without getting overwhelmed or lacking detail.
How ‘Shipintel Co’ built its user-facing analytics experience
Justin quickly discarded the idea of building a custom solution because he knew he’d need to invest tons of money on a solution that only his company was going to use. “I don't want to spend millions of dollars building this out and then not being able to sell it as a product,” he says.
After trying multiple different BI tools and embedded analytics solutions, Justin decided to opt for Apache Superset because it gives you more flexibility than most third-party embedding tools, and it’s free.
“But it's open source, so there's no support,” says Justin. “So, when something doesn't work, there's no one to call. You either have to learn how to fix it yourself, or wait for the community to identify the problem or acknowledge the problem and then fix it sometime in a future release.”
Challenges ‘Shipintel Co’ faced when adding user-facing analytics
Justin tried at least 15 different BI tools and embedding platforms. From big names like Looker, Tableau, and Sisense, to open-source solutions like Apache Superset. “These tools all worked ‘ok’, but their models weren't really designed for embedded first, they basically were like, ‘Hey, here's an iframe,’” says Justin.
These tools didn’t allow him to offer a consistent user experience, were very expensive to scale, lacked control, or took a long time to load. He used Explo for a while because the design looked good and was thought out to be embedded first. “But [Explo’s] pricing model got really weird. They were targeting smaller customers and the way they structure their pricing would bankrupt any big company,” says Justin.
Then he switched to Plotly because it promised to be very customizable. But it still didn’t cut it.
Plotly was also expensive and would cause his engineers to be overworked: “The way its integration works handcuffs your engineering team, so they have to do everything: Come up with every little KPI color filter, sizing, wiring the data, managing the flow in the back end, and so on. It's taking on a big chunk of additional technical debt that you can never really escape,” says Justin.
Meanwhile, Justin is still looking for the perfect user-facing analytics solution—and plans to try out Embeddable next. “Embeddable seems to be the promise of the hyper customization of Plotly with the ease of use of something like Tableau or Explo. It may be the best of all those worlds,” Justin says.
Design and build fully bespoke user-facing analytics in 10% of the usual dev time. Learn More.
Best practices for building analytics: What experts recommend
Sindri, Justin, and Michel did a lot of research before coming up with successful examples of analytics experiences. Here are their recommendations, based on everything they learned:
1. Sketch your prototypes using real data
Michel Felipe mentioned that the Revelo team struggled to imagine the dashboard during the prototyping stage. He recommends “creating some prototypes on Excel or another BI tool with real data from multiple users. [That way,] the team can explore the best graph before creating the interface for the developers to code.”
Sometimes your designers might think the best way to show certain data is by adding a pie chart. In reality, you can’t read certain data easily in that format. That’s why it’s helpful to use real data even at the prototype stage: You’ll have a better chance of choosing the visualizations and filtering options your customer needs to get the most out of their data.
2. Think of your end-user
Sindri tells us the story of a ticketing competitor that showed its box office workers how many people were online and looking at the event in real time. It was a cool feature, but not necessarily useful for people who are trying to sell tickets and want to see how many available ones are left.
“It’s not just about developing a beautiful dashboard; the information has to make sense for the end user. Put yourself in the shoes of the people who will be using your software and try to get into their mindset. If you can't, go out and work there.” —Sindri Már Finnbogason, Founder of Tixly.
3. Have a clear vision
When you’re developing or have an idea in mind, you might find everything appealing and end up adding too much complexity. Having a clear plan that’s defined by user objectives can save you a lot of time.
“Have a clearly defined vision of what the end product should look like. In our case, we were letting already existing platforms define what we wanted because we didn't know what could be done,” says Justin. Visualizing what your analytics experience will look like will help you design unique solutions, instead of trying to adapt to the tool’s available views.
How to build dashboards for customer-facing analytics
If you’re thinking about building customer-facing analytics into your product, you probably already know that your options are limited to:
- Building it in-house
- Embedding dashboards from a BI tool like Trevor, PowerBI, or Looker.
But, there’s now a third option: Embeddable.
This software development kit (SDK) wraps data models and charting components that you can define in your own code repo, giving you full control over how they look and behave. Then, it makes them available in a no-code builder so anyone on your team can build interactive dashboards that go perfectly in line with your UX.
Through years running Trevor, we knew that embedding cookie-cutter charts through an iframe wasn’t enough for amazing user-facing analytics. But not everyone can afford to build charts from scratch. So, to help you take analytics out of your backlog and push it live, we built Embeddable.
It comes with a:
- Front-end toolkit that significantly reduces the time it takes to build charting components and modifiers, and seamlessly integrates with open-source libraries like ChartJS, Highcharts, Google Charts, and Tremor.
- Backend engine that efficiently manages your performance, security, caching, and infrastructure needs while providing real-time data that loads instantly. It establishes secure read-only transactions with all major databases and allows you to customize caching refresh rates for optimal customer performance, while minimizing calls to your database.
- No-code builder to empower non-technical individuals within your design, product, or customer success teams by letting them create and iterate on dashboards using an intuitive point-and-click interface.
TL;DR: What you need to know before building user-facing analytics (tips from experts)
After reading Justin, Sindri, and Michel’s stories, we can conclude that while they all took different routes to build their analytics experiences, their stories have common learnings. These are:
- User-facing analytics can help you boost customer engagement and hit your KPIs
- Using an embedded solution or BI tool limits you as these don’t allow you to design experiences with the same look and feel as your product
- Analytics need to add real value for your customers and when they do, they can bring you more word-of-mouth referrals
- BI tools and embedded solutions might seem like an easy, plug-and-play solution, but can get expensive really fast and reduce your level of control
- Free, open-source tools may save you money, but can cause headaches down the line as they’re not accountable to you for service, bug fixes, or support
Sindri from Tixly concluded that the best option is an alternative to building it in-house or embedding an iframe, and has joined the beta program for Embeddable: The SDK that lets you build bespoke, highly-performant analytics in a fraction of the time.
Design and build fully bespoke user-facing analytics in 10% of the usual dev time. Learn More.
Frequently asked questions about building customer-facing analytics
What can I build with Embeddable?
Embeddable is a tool for building fully bespoke analytics (charts, graphs, and dashboards) into your application for end users and other stakeholders. It lets you build any visualization you need by combining a front-end toolkit, a backend engine, and a no-code builder. It gives you full control over the charting components, while saving sprints of developer time compared to building dashboards from scratch. If you can imagine it, you can build it with Embeddable.
How is Embeddable different from other embedded analytics tools?
Embeddable is different from other embedded analytics tools for many reasons:
- You own the code for your charting components, so you have full control over the design
- It’s optimized for performance, with 2 layers of cache and a performant JS snippet embed (instead of a slow, clunky iframe)
- You can toggle on/off the ability for your users to customize the dashboards you build for them (if you want to!)
What are the 4 main things to consider when building analytics?
The four main things to consider when building analytics into your product are:
- Customization. Can you deliver the native-feeling UI/UX that you want?
- Performance. Ensure you’ve considered caching, and avoid embedding with an iframe
- Price. Do you have developer capacity for a custom build, or budget to pay for an embedded tool?
- Security. A secure database connection, permissions, and row-level security (RLS)