The Hidden Forces Reshaping Embedded BI

Three key trends are changing how organizations approach embedded analytics. Companies that recognize these shifts gain competitive advantages while others struggle with outdated strategies.

Ramin Jahanbani has watched this transformation from the front lines. As Senior Divisional Vice President at insightsoftware Data + Analytics, he’s guided hundreds of organizations through analytics decisions over the past decade.

From his early days as the fifth employee at a startup and through acquisitions by Logi Analytics and insightsoftware, he brings extensive experience to insightsoftware’s Data + Analytics global customer base.

His perspective reveals something important: while technical capabilities get most of the attention, the real changes are happening in how buyers evaluate and adopt embedded BI solutions.

With thousands of hours helping organizations make analytics decisions, Jahanbani sees three critical trends that are reshaping the embedded BI landscape.

1. Users Want Conversational Data Interaction

User expectations have shifted dramatically in recent years, making it difficult for organizations to keep up.

“The shift is, I’m lazier, for lack of a better term,” Jahanbani says, describing typical user behavior. “Let me type [the question] in. Tell me about where’s the highest concentration of growth, why is it there? And then keep asking those questions, like a curious kid. Why? Why? Why?”

Users no longer want to navigate through dashboards to find insights. They expect to ask natural language questions and get immediate, contextual answers. This represents a complete shift from dashboard-first to question-first analytics.

Organizations building dashboard-heavy experiences are solving yesterday’s problems while users move toward conversational interfaces.

2. Specialization to Complete Feature Menu

While independent software vendors compete on comprehensive capabilities, buyers increasingly choose specialized solutions for specific use cases. The “do everything” approach that once defined success is no longer enough to satisfy the needs of today’s users.

“We always differentiate ourselves by being specifically for embedded use cases,” Jahanbani notes. “We are laser-focused on product teams and development teams, because we know how to speak to them.”

Generic BI tools promise broad functionality but often excel at nothing specific. Purpose-built platforms win by solving targeted problems exceptionally well. Embedded analytics requires understanding how product teams think, how developers work, and how end users experience analytics within their existing workflows.

3. Too Many Options Create Decision Paralysis

Decision cycles that once took months now stretch into years. Buyers compare dozens of vendors across hundreds of features, but this abundance of choice can become overwhelming to even the most discerning buyer.

“There is a lot of buyer indecision,” Jahanbani observes. “The fear of messing up drives a lot of buyer indecision.” Organizations often stretch existing systems beyond their limits. Switching to something new can lead to unforeseen risks.

“People want to test against more vendors, and they want to test more features. They want to compare a list of 100 features, and that gets benchmarked across 10 or so different other vendors.”

This exhaustive evaluation process rarely produces better decisions. Instead, it creates analysis paralysis where maintaining the status quo becomes the default choice.

Smart vendors now guide buyers through complexity instead of adding to it, positioning themselves as the safe, specialized choice.

Why Traditional Competitive Strategies Fall Short

Most organizations still compete using decade-old playbooks: build more features, climb analyst rankings, and promise lower costs. These strategies assume buyers make rational decisions based on objective criteria.

Reality looks different.

When customers compare feature lists, they’re missing the point of securing the most useful software. They need to take a step back and prioritize what they’re trying to accomplish. Customers are often attracted to a cheaper option with a long list of features that seems comprehensive. This is a risk mitigation strategy but will not address your specific needs. A product that does 1,000 things just fine may not be able to serve your most crucial business need.

It’s crucial to find the right tool for specific use cases.

Three Growth Opportunities Others Are Missing

While competitors fight feature wars, Jahanbani’s experience reveals three growth areas that remain largely unexploited:

Target Mission-Critical Use Cases

Organizations with life-or-death analytics needs can’t afford generic solutions. What consistently surprises Jahanbani: “there are so many applications that are truly life or death for what customers are trying to do.” These buyers value expertise over features and partnership over price. They need partners who understand their specific requirements and deliver reliable, specialized capabilities.

As a result, it’s important to position your solution around more than technical capabilities, but instead, critical business outcomes, and continue to support them with domain expertise

Address the Build-Versus-Buy Question Honestly

Organizations systematically underestimate the true cost of building custom analytics. “Think: What happens when I need to maintain it? I need to fix that. I need to add features,” Jahanbani explains. “Instead of being a company that focuses on a specific market that you sell to, you’ve now turned yourself into an analytics company.”

Hidden costs include long-term maintenance, feature additions, and resource allocation that diverts focus from core business objectives. To address the build-or-buy debate, help your users, understand the total cost of ownership clearly, focusing on opportunity costs and resource drain. Frame the choice as becoming an analytics company versus partnering with one.

Design for Invisible Integration

The best embedded analytics disappear into the user experience. Users shouldn’t need to know specifics about underlying technology. Analytics should feel like a natural extension of your application, not a separate system added on top.

Deep product expertise is what generic BI tools fall short of delivering. This means understanding not just what users want to know, but how they want to discover it within their existing workflow. Design for native feel, not feature richness. Make analytics feel like a natural extension of the application.

Navigating the New Reality

Success in today’s embedded BI market requires abandoning traditional competitive strategies and embracing new realities. To stay competitive and future-facing, focus on use case alignment over feature completeness and design for specific user experiences. Generic capabilities will not give you competitive advantage in the long term as users seek out analytics tailored to fulfill their unique needs. To avoid adding to the analysis paralysis they already face in the decision-making process, guide buyers through complexity instead of adding to it. These users can especially benefit from you as a specialized expert instead of a one-size-fits-most solution provider.

The embedded analytics landscape has evolved beyond simple feature comparisons. Organizations that recognize these behavioral shifts and adapt their approach accordingly will capture market share from competitors still fighting yesterday’s battles.

Logi Symphony is a foundational analytics solution that puts dashboards, reports, and intelligent insights directly inside the tools your users already work in. Instead of forcing people to jump between applications, you get analytics that fits your product like it was built there from the start. Provide your users with the specificity and expertise they need to satisfy their unique use cases with intelligence baked into every layer of the platform.

Users can easily ask questions, spot trends, and get explanations right in their workflow, even in on-premises deployments where other vendors can’t deliver AI capabilities. Every AI-generated answer comes from live data with full context about what users can and can’t see.

Ready to learn more? Watch our on-demand webinar on the future of BI.

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