This content originally appeared on DEV Community and was authored by rohit
Once your customers start seeing value in your Saas product, the next thing they want is visibility — analytics that show them exactly how your product is delivering that value. They want to track key metrics, spot trends, and patterns around the “thing” your software helps them manage, whether it’s calls, schedules, shipments, or something else.
In the B2B world, this need for analytics is universal, whether it’s an internal or a customer-facing product.
Building high-value analytics right into your product can set you apart from the competition and even open up new revenue streams. But launching customer-facing analytics isn’t as straightforward as it seems.
1) The Analytics Scope Snowballs
What starts as a simple feature request often evolves into a substantial project — sometimes even larger than the core product itself. For startups and mid-sized companies, this can be a real problem. Every time a customer asks for a new visual or a tweak to a dashboard, it turns into a new product feature request (PFR) for your engineering team and requires a full code build, test, release cycle.
2) Analytics isn’t one size fits all
From my consulting days, I’ve learned that every organization, team, or client wants a slightly different view of the same data. And they’re not wrong — users have their own goals to meet and have preferences on how they want to see their data, or narrow down to only what’s relevant to them. A read-only canned dashboard is hardly ever useful.
3) Security and Performance: Non-Negotiables
When you externalize analytics, you have to make sure that only right people have access to the right data. With multiple users — and potentially multiple organizations — using your app, you’ll need to invest in a multi-tenant architecture that spans multiple analytical stores. If you are presenting data from object stores like S3, you need to have on-demand caching to maintain high-performance.
A lot of companies think they can handle this in-house. After all, how hard can it be to add a few charts, right? But here’s the thing: when you give users a chart, they’ll want a dashboard. Give them a dashboard, and they’ll ask for filters. Before you know it, they’ll be asking for custom views, and then AaaayEyee (AI). Suddenly, you’re spending more time on analytics than on your actual product.
One of our customers put it perfectly:
“Analytics is a necessary part of our product, but it shouldn’t come at the expense of slowing down our core roadmap.”
The Common Approach (And Why It Doesn’t Work)
So, what do most companies do? They turn to their old-guard BI tools. The legacy BI vendors are more than happy to shrink wrap their whole product into an iframe and tell you to just drop it into your app. This approach works if you are embedding a dashboard in wikis or small internal apps. But if you’re building a customer-facing app, this approach can lead to some serious issues.
Bloated Apps: Those iframes come with a lot of unnecessary code, which can bloat your app. Why? because all those legacy BI tools were NEVER built to live inside of your apps. They were built as stand alone apps for internal BI needs.
A Frankenstein Experience: Your app can end up looking like a disjointed mess, with limited styling options and a user experience that doesn’t respond well to different screen sizes. Every small customization seems like a band-aid fix, piling on more inconsistencies and leaving your app feeling more fragmented with each change.
Opaque and Restrictive: These tools often hold your data hostage, requiring proprietary tech to view analytics. You might not even be able to see the underlying business logic of the chart, let alone modify it. Plus, managing users in both the BI tool and your app can become a nightmare.
The Right Approach
Decouple Analytics from Product Code: Keep your analytics separate from your core product code. This way, you can move faster. Your product team can focus on the core features, while your customer success team can handle analytics requests without touching the product code.
Go for Open Standards: Choose technologies where you can see and control the code behind your analytics. This transparency gives you the flexibility to deliver exactly what your customers need.
UseUse Framework-Specific Components: Choose a tool that’s designed from the ground up to live inside of your app as a first class citizen. Use native components such as React, Vue, or Web Components. This approach lets you create a responsive, cohesive experience for your users.
Stick to Modern Web Standards: HTML, JavaScript, and CSS aren’t going anywhere. While nifty Python-based wrappers are great for quick prototypes, when it’s time to ship, native web technologies perform better and are easier to maintain and customize. Do it the right way the first time.
Keep It Simple and Flexible: Most BI tools are overly complex, requiring too many steps to do something simple. Less is more when it comes to customer-facing analytics. The experience should be intuitive — no need for training. And when you hear the term “Unified BI,” think “Bloated BI.”
There’s a new wave of products — like Semaphor — that are taking this approach.
Introducing Semaphor
Semaphor is a fully customizable analytics package for delivering user-facing analytics in your apps.
We took our inspiration from Stripe! Just like when you want to collect payments in your app, you don’t build a full-blown payments collection infrastructure from scratch. You use something like Stripe! With just a few lines of code, you can start collecting payments. This way, you can focus on what makes your product unique.
We do the same for analytics. If you want to launch fully-responsive, AI-powered, interactive analytics in your app, you use Semaphor. With just a few lines of code, you can deliver branded analytics in your app. You can style almost everything to precisely match the look and feel of your app.
Semaphor offers a canvas experience where users can view a set of visuals and engage with a dashboard conversationally. As they discover new insights, they can easily add them to the existing dashboard and personalize the experience. This is fundamentally different from the read-only dashboards provided by legacy BI vendors.
Here’s what Semaphor brings:
Open Standards: We understand SQL and Python and you get complete transparency and control over how every insight is generated. No lock-in, just flexible, powerful analytics.
Plug and Play: Use framework-specific components like React, Vue, or Web Components to render insights directly into your product — no clunky iframes!
Deep Customization: Tailor every aspect of your dashboard — styles, fonts, colors — to match your brand. Bring your own visuals if you like and create layouts that look great on any device.
Real-Time Insights: Deliver insights at the speed of your business — as fast as your data comes in, and wherever it comes from, whether it is databases, APIs, or other sources.
Dashboard-as-Code: Manage your dashboards as code — version control and automate deployments just like any other software. Your dashboards always remain secure, version-controlled, and consistently backed up.
Ready to see Semaphor in action? Set up a demo here.
This content originally appeared on DEV Community and was authored by rohit
rohit | Sciencx (2024-08-15T02:42:30+00:00) The Right Way to Approach Customer-Facing Analytics. Retrieved from https://www.scien.cx/2024/08/15/the-right-way-to-approach-customer-facing-analytics/
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