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Customer or User Facing Analytics: Why You Shouldn't Be Building?
Oct 27, 2024
Ka Ling Wu
Co-Founder & CEO, Upsolve AI
Thinking about building user facing analytics for your SaaS product?
I totally get it. Adding customer-facing analytics sounds like a great idea, and it feels like the next big step to impress your users.
But what if I told you that this path might lead to unexpected problems, big expenses, and lots of wasted time?
In this blog, I'm going to share why building user-facing analytics yourself might not be the best move.
I'll show you the hidden challenges, the pitfalls others have faced, and better ways to give your users the insights they want.
Here's what's waiting for you inside:
What user-facing analytics actually means and why it’s different.
Why building it yourself can be harder and more expensive than you think.
How third-party tools can make your life easier and save money.
Tips to help you pick the best customer-facing analytics platform.
By the end, you'll know the smart way to give your users the necessary analytics without the headaches.
What is Customer Facing Analytics?
Customer facing analytics are data insights you share directly with your customers through your product or service.
Instead of keeping all the data analysis within your company, you let your users see relevant information that helps them understand and use your platform better.
For example, if you have a fitness app, you might show users their workout statistics, progress charts, and health metrics right inside the app.
Related Read: Customer Facing Analytics vs Customer Analytics
Customer Facing Analytics Features and Benefits
Customer-facing analytics offers more than just showing data. It helps you to engage customers, personalize their experience, and open up revenue opportunities.
Here’s a breakdown of the major benefits and how they add value:
Using user-facing analytics smartly enhances customer engagement, strengthens loyalty, and creates new revenue opportunities, making it a strong strategy for driving growth.
Customer-Facing Analytics Examples
Let’s look at customer-facing analytics—how businesses use data to create amazing experiences for you.
Peloton Leaderboards
Peloton turns workouts into a game. Their leaderboard shows who’s ahead and motivates you to pedal faster.
Fitness Tracker Weekly Summaries
Your fitness tracker doesn’t just count steps; it gives weekly summaries of your activity. “You’ve burned enough calories for three pizzas!” That’s analytics keeping you motivated (and hungry).
Duolingo Streaks and Rewards
Learning languages is tough, but Duolingo makes it fun. It tracks your progress, rewards your streaks, and cheers you on.
How Does It Differ from Internal Analytics or Business Intelligence Tools?
User-facing analytics are different from internal analytics in a few key ways:
Related Read: 10 Best Business Intelligence Dashboards
Why is Customer Facing Analytics Necessary for Modern SaaS Businesses?
Because they play a crucial role in enhancing the customer experience:
By providing insights, you help users make informed decisions.
Interactive analytics keep users engaged with your product.
Offering analytics can make your product more valuable compared to competitors.
Transparency through shared data builds trust with your customers.
Customer Facing Analytics vs Traditional Business Analytics
Before we highlight making a difference between "How are customer-facing analytics different from the traditional analytics we use internally?" let me simply tell you what they are.
Customer-facing analytics are insights and data that you share directly with your customers through your product or service. This helps them understand their own activities, progress, or any relevant information that adds value to their experience.
For example, if you run a project management tool, showing users their project timelines and task completions is customer-facing analytics.
Traditional Business Analytics, on the other hand, are the insights your company uses internally to make informed decisions. This data helps you understand market trends, sales performance, operational efficiency, and more.
Below is the table for you to get a better understanding of how customer-facing analytics differ from traditional business analytics:
Related Read: Customer Facing Analytics Vs Traditional Business Analytics Detailed Comparison
Challenges of Building User Facing Analytics In-House
Building your own user-facing analytics system might seem appealing, but it comes with significant challenges. Here’s what you might encounter:
Technical Challenges
Data Integration: Combining data from different sources can be complicated, requiring careful planning to ensure seamless operation.
Real-Time Updates: Users expect real-time data, so you’ll need an efficient system for instant updates without slowing down performance — a complex and resource-intensive task.
Scalability Issues
Handling High Traffic: A scalable solution is essential, as you potentially serve thousands of customers, not just a small team.
Maintaining Speed: As user numbers grow, you’ll need to ensure that loading times remain fast and the system doesn’t slow down, preserving a smooth experience for everyone.
Ongoing Costs and Maintenance
High Maintenance Costs: Beyond the initial build, there are ongoing expenses for servers, updates, and bug fixes, which can add up quickly.
Constant Upgrades: Technology evolves rapidly, requiring regular updates to keep the system up-to-date, which means ongoing work and additional costs.
Security and Compliance
Data Protection: With customer data at stake, suitable security measures are essential to prevent breaches, as even a minor incident could cause major issues.
Legal Compliance: You must adhere to data usage and sharing regulations, which can be challenging but necessary to avoid legal trouble.
Building Trust: Your customers trust you with their data. Any mishap could harm that trust, impacting your brand’s reputation.
Why You Shouldn’t Build Customer Facing Analytics from Scratch? [3 Reasons]
Building customer-facing analytics from scratch might sound like a solid plan.
But trust me, there are several reasons why taking this route can be costly, time-consuming, and tricky experience.
1. High Cost of Development and Maintenance
Developing customer-facing analytics isn’t just about writing code and making charts. It involves:
Costly Infrastructure: You’ll need powerful servers, databases, and tools to handle large amounts of data securely and quickly.
Ongoing Maintenance: After building the system, keeping it up-to-date and fixing any bugs adds up. These costs can quickly blow up your budget.
2. Long Development Timelines and Launch Delays
Creating analytics features from scratch takes time, and not a little. You could face:
Extended Development Time: Analytics isn’t a quick add-on. It requires planning, testing, and careful execution.
Potential Delays in Product Launch: Building this feature could delay your entire product timeline, meaning customers have to wait longer.
3. Difficult User Experience for Non-Technical Users
Customer-facing analytics should be simple enough for anyone to understand. But building a user-friendly design from scratch brings its own challenges:
Complex User Interface (UI) Needs: Creating a clean, intuitive UI that’s easy for non-technical users takes extra work.
Balancing Simplicity with Detail: You want to give your users insights without overwhelming them, which isn’t easy to achieve without a lot of testing.
Real-Life Example: Paxafe's Struggle
Let me share a story about Paxafe, a company that tried to build customer-facing analytics on its own and got several expected problems:
Unexpected High Costs: They spent much more money than they initially thought.
Significant Delays: Their product launch was delayed because building the analytics took too long.
User Frustration: Customers found the analytics hard to use and didn't get the value they expected.
They eventually realized that building from scratch wasn't working and switched to a third-party solution, which saved them time and money.
You can read more about their experience in the Paxafe Impact Study.
So, when it comes to creating user-facing analytics, using third-party tools can make life a whole lot easier.
Instead of building everything yourself, you can save time, cut costs, and deliver a better user experience.
Benefits of Leveraging Third-Party Tools for Customer-Facing Analytics
Let’s look at the benefits of using these ready-made analytics solutions.
1. Saves Time and Speeds Up Launches
Building an analytics system from scratch can take months, even years. Third-party tools, like Upsolve.ai, come pre-built, meaning you can get your analytics up and running quickly.
Quick Setup: Get started in days instead of months.
No Long Development Phases: You skip the need for coding and testing complex analytics systems.
2. Reduces Costs
Using a third-party tool can be much cheaper than building your own. With third-party solutions, you avoid paying for extensive development, server infrastructure, and ongoing maintenance.
Lower Upfront Costs: You don’t need a full team of developers.
Fewer Maintenance Expenses: The provider handles updates, so you save on maintenance costs.
Flexible Pricing Plans: Many tools offer subscription models, so you only pay for what you need.
3. Improved Performance and Reliability
Third-party tools are designed to handle large user bases and provide reliable data analytics, which means you’re delivering a smooth, consistent experience for your users.
Optimized for Scalability: Third-party platforms are built to grow with your business.
Better Uptime: These tools are managed by dedicated teams to keep everything running smoothly.
Built-in Security: Providers ensure data is protected, saving you from compliance headaches.
4. User-Friendly Features
When choosing a third-party tool, you want one that makes it easy for your customers to understand their data. Tools like Upsolve.ai have features designed for easy integration and great user experience.
Customizable Dashboards: This lets you display data that matters most to your users.
Simple Interface: Clear visuals and simple navigation make analytics accessible to everyone.
Real-Time Data Updates: Keeps users engaged with up-to-the-minute insights.
Using user-facing analytics smartly enhances customer engagement, strengthens loyalty, and creates new revenue opportunities, making it a strong strategy for driving growth.
7 Factors While Choosing a Customer Facing Analytics Tool
Picking the right analytics tool helps you add value for customers and support your business’s growth. Here are some factors to consider:
Ease of Integration
Find a tool that easily embeds into your existing product. A quick setup saves time and requires less technical effort, so you can get up and running faster.Customization Options
Every user is different, so customization is key. Choose a tool that lets you adjust dashboards, visuals, and features to match your brand and provide a tailored experience.Scalability
As your user base grows, your analytics platform should handle increased traffic and data smoothly. Scalability means your product’s performance stays reliable as you expand.Security and Compliance
Data privacy is a priority when sharing insights. Make sure the platform follows industry standards and complies with regulations to keep user data safe.User Experience
A simple, intuitive interface is essential for non-technical users. Look for clean, easy-to-navigate dashboards that help users understand insights without hassle.Support and Resources
Access to reliable support and helpful resources can be a lifesaver for troubleshooting and guidance. Choose a tool with strong support options.Cost
Consider both upfront and ongoing costs. Make sure the tool fits your budget and offers essential features without unexpected expenses.
Selecting a customer-facing analytics tool that aligns with your goals can literally improve the way your users interact with your product. So, take time to assess each option against these factors to make the best choice for your business.
3 Best Tools and Platforms for Customer Facing Analytics
Choosing the right tools for customer-facing analytics can effectively deliver valuable insights to your users.
Let’s check the best platforms/tools available and why each could contribute more to your business.
1. Upsolve.ai
Upsolve.ai is a powerful tool designed to simplify and enhance customer-facing analytics. It allows you to easily embed insights directly into your product, ensuring your users get meaningful data without having too much complexity.
By choosing Upsolve.ai, you get a platform that handles data processing, visualization, and security, making it ideal for delivering insights to customers in real-time.
Here's a quick demo of Upsolve.ai Customer Analytics Tools:
Features of Upsolve.ai
Seamless Integration: Easily add analytics to your product without needing complex development or integration processes.
Customizable Dashboards: You can personalize the look and feel of dashboards to match your brand, providing a seamless user experience.
Real-Time Data: Offer users up-to-date insights that keep them engaged and help them make timely decisions.
Scalability: Upsolve.ai scales effortlessly to maintain performance and reliability as your user base grows.
Robust Security: Protects customer data with strong security measures, keeping your business compliant with privacy regulations.
User-Friendly Interface: Simple navigation and easy-to-read visuals ensure that both technical and non-technical users can benefit from the analytics.
Pros and Cons of Upsolve.ai
Pros:
Get analytics up and running quickly.
Avoid the high costs of in-house development.
Handles large user bases without lag.
Create dashboards to match your brand and user needs.
Keeps data current for improved user experience.
Cons:
Pricing details are not readily available, which may require contacting sales.
Real-time data requires an internet connection.
Requires relying on Upsolve.ai’s customer support for troubleshooting.
Best For?
Upsolve.ai is best for SaaS companies, tech startups, and businesses needing to add customer-facing analytics to their product quickly and securely.
Pricing
Upsolve.ai pricing starts at $300/month for early-stage startups and $1000+ monthly for growing businesses. Also, they provide flexible plans, making them accessible for larger enterprises.
Success Story: Paxafe’s Journey with Upsolve.ai
Paxafe initially faced challenges building analytics in-house, running into high costs and extended development times. By switching to Upsolve.ai, they found a faster, more affordable solution.
The integration was smooth, allowing Paxafe to offer real-time insights without technical complications. Their customers responded positively, appreciating the user-friendly dashboards and timely data.
With Upsolve.ai, Paxafe cut down on support costs and reduced user frustration, as customers could now access their own data without help. Paxafe saved both time and money, allowing them to focus on their core product rather than building analytics.
In the end, Paxafe's experience shows how Upsolve.ai can transform customer engagement and satisfaction, providing a scalable, secure, and effective analytics solution.
2. Tableau
Tableau is a powerful tool known for its high-quality visualizations and user-friendly interface. It helps businesses turn complex data into engaging visuals.
Tableau is ideal for companies looking to make data easily digestible for end-users through dashboards, charts, and graphs.
Features:
Interactive Dashboards: Users can explore data through detailed, interactive dashboards.
Real-Time Data Updates: Provides up-to-the-minute insights, keeping data relevant and fresh.
Advanced Visual Analytics: Offers a variety of chart types and data visualization options.
Mobile Compatibility: Allows data access on mobile, enhancing flexibility for users.
Drag-and-Drop Interface: Simplifies data analysis, even for non-technical users.
Pros and Cons of Tableau:
Pros:
Strong visualization capabilities
User-friendly interface
Real-time data support
High customizability for reports
Compatible with multiple data sources
Cons:
High pricing for small businesses
Performance issues with large datasets
Limited data preparation features
Needs a little bit of learning to use advanced features
Best for?
Companies of all sizes need high-quality visualizations, which are especially helpful for data-heavy industries like finance, retail, and healthcare.
Pricing
Tableau offers multiple pricing options, including Creator, Explorer, and Viewer licenses. Pricing starts at $70 per user per month for the Creator license, while custom enterprise plans are available upon request.
3. Sisense
Sisense is an end-to-end analytics solution that combines data preparation, analysis, and visualization in one platform. It’s designed for companies seeking deep insights from multiple data sources.
Sisense offers flexible integration options, making it easy to embed analytics into any application, web portal, or product.
Features:
Full-Stack Analytics: From data preparation to visualization, Sisense covers it all.
API-Driven Customization: Deep customization options allow tailored solutions for unique needs.
Scalable Architecture: Efficiently handles high data volumes, ensuring smooth performance as businesses grow.
Multi-Cloud Support: Works across various cloud platforms, adding flexibility.
Self-Service Analytics: Allows users to access data without heavy IT support.
Pros and Cons of Sisense:
Pros:
Powerful and full-stack solution
High scalability for growing companies
Strong API customization options
Multi-cloud and on-premises compatibility
Supports data blending from multiple sources
Cons:
Expensive for small businesses
May require technical skills for customization
Limited advanced visualizations compared to competitors
Best for?
Medium to large enterprises who needs customizable, embedded analytics with scalability to support complex data needs and fast growth.
Pricing
Sisense provides custom pricing based on business requirements, with options for both cloud and on-premise solutions. You can contact their sales team for a quote.
If you still need more business intelligence tools to solve the customer facing analytics. Find out the Top 5 Embedded BI Tools that are even good for 2025!
Cost-Reduction Strategies When Implementing Customer-Facing Analytics
Implementing customer-facing analytics can seem pricey, but you can cut costs easily.
Start by using third-party tools instead of building from scratch. Sure, custom solutions sound ideal, but they’re expensive and require ongoing maintenance.
With third-party tools, you can:
Save on Costs: No need to build your own system.
Launch Faster: Easy integration means quicker results.
Get Support: Providers handle updates and security for you.
Additionally, cloud-based platforms can slash infrastructure expenses. Pay only for what you use and scale as needed. Simple and budget-friendly!
Conclusion: Why It’s Better to Outsource Analytics?
The more energy you invest in building analytics systems from scratch, the less you have for growing your business. That’s why outsourcing customer-facing analytics is a practical, smart choice.
Managing development, maintenance, and technical complexities doesn’t need to weigh you down.
By turning to expert platforms, you streamline the process, reduce costs, and focus on what truly matters—delivering value to your customers and driving your business forward.
Embed AI-powered dashboards into your product effortlessly with Upsolve AI.
Launch Fast: Deliver analytics on day one.
Empower Users: Real-time insights, self-serve customization.
Focus on Growth: Let Upsolve AI handle analytics while you focus on your core product.