How to understand the obsession with “advanced Excel”

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At the 2025 Global Excel Summit, Ken Puls made an observation that struck a chord with attendees, many of whom were themselves trainers, content creators, and Excel business owners. He noted that when clients reach out to him for services, they’re almost always seeking “advanced Excel” skills. This sparked a broader discussion: what does “advanced Excel” really mean?

While I’ve shared my thoughts on this topic in a separate blog post, here, I want to delve into our collective fascination with the term “advanced Excel.”

Is this alledged obsession supported by data? To explore this, I’ll turn to Google Trends to analyze the search interest in “advanced Excel” and compare it with other technical training topics. After examining the data, I’ll offer some speculations on why this trend persists. Let’s dive in!

A quick note on methodology: I’m analyzing worldwide Google Trends search data covering approximately June 2020 through June 2025.

To kick things off, let’s compare search terms for “beginner Excel,” “intermediate Excel,” and “advanced Excel.” It’s immediately clear that searches for “advanced Excel” dramatically surpass the other two categories, a pattern that’s remarkably consistent over our entire observation period:

When I notice a striking pattern like this, I usually like to investigate further by comparing similar trends for related tools. This helps provide context and clarity around whether the observed behavior is unique or part of a broader pattern. Perhaps all software searches show a similar skew toward advanced-level queries. If that’s the case, it’s still intriguing… but maybe not uniquely fascinating for Excel.

To test this, I’ll start by comparing Excel to fully-fledged technical languages like JavaScript and Python. Will we see a similarly significant gap between beginner, intermediate, and advanced searches for these popular programming languages? Let’s find out.

While “advanced” is still the most commonly searched skill level for Python and JavaScript, it’s not nearly the overwhelming preference we see with Excel. That difference alone is intriguing, and suggests we might be observing distinct underlying phenomena. From here, we move into some pure speculation about why these patterns differ and whether they reveal anything significant about how users perceive their own proficiency or training needs.

Why is “advanced” Excel training so dominant?

Excel’s “advanced” search popularity likely stems from the tool’s ubiquity and user familiarity. Most people encounter Excel early in their careers and feel comfortable with basics, quickly self-identifying as “intermediate.”

Thus, those seeking training often assume they need “advanced” techniques to differentiate themselves, driving more searches at that level. Conversely, Python and JavaScript users are frequently learning these languages anew as specialized technical skills. They clearly identify as beginners or intermediates and progress incrementally, leading to more balanced searches across skill levels.

This difference could also reflect the ambiguity of what “advanced Excel” means. Users assume it’s the key to productivity or job advancement, even if they’re unclear what specific skills it includes. With programming languages like Python and JavaScript, the skill progression and competencies tend to be clearer, leading to balanced search interest as users intentionally select training levels aligned with their experience.

Is this similar for other Office tools?

Perhaps it makes more sense to compare Excel search trends to another widely-used, non-coding office productivity tool like PowerPoint, rather than technical languages like Python or JavaScript. When we do this, a similar (actually even more pronounced) pattern emerges, with searches overwhelmingly skewed toward “advanced PowerPoint” compared to beginner or intermediate. This suggests users perceive themselves as competent in these familiar productivity tools and believe that incremental gains in their value come mostly from learning advanced techniques rather than basics.

Speculatively, this trend might reflect the nature of general office software: users feel they’ve mastered foundational tasks through regular exposure and seek out “advanced” content as a means of professional growth or differentiation. Unlike coding languages, where learners often acknowledge clear skill progression, familiar office tools create a perception that only “advanced” knowledge can meaningfully boost performance and career opportunities, driving disproportionate search volumes at this higher skill tier.

Maybe it’s not so uncommon

Power BI and SQL offer fascinating middle-ground comparisons in this analysis. Surprisingly, searches for “advanced Power BI” are even more skewed toward advanced levels than Excel or PowerPoint. Given that Power BI is a relatively newer tool, one might expect more balanced beginner or intermediate interest.

However, this pattern might suggest users adopting Power BI often already have foundational experience with related tools like Excel and perceive that the real value of learning Power BI comes from accessing its advanced analytics and visualization capabilities. They may assume that mastering advanced techniques immediately differentiates them in a competitive professional environment.

Similarly, SQL searches are notably advanced-biased, though perhaps slightly less dramatically than Power BI. SQL, despite being a programming language, often serves as a supplemental skill rather than a primary role-defining competency, especially among professionals whose main focus isn’t software engineering but data analysis or reporting. Thus, users might quickly achieve basic proficiency and soon seek advanced skills for career progression or higher-value analysis tasks, reflecting a perceived fast skill progression from basics to advanced SQL, similar but not identical to the pattern seen with Power BI and traditional office tools.

What does this mean for skills development

In conclusion, these search trends reveal something fascinating, and perhaps a little concerning, about how we view our own skills, particularly with ubiquitous office productivity tools like Excel and PowerPoint. The overwhelming emphasis on “advanced” suggests a widespread assumption that we’re already good enough with the basics and that the real benefits lie exclusively in mastering advanced features. But this assumption may not always be accurate. In fact, it could be indicative of the infamous Dunning-Kruger effect: users overestimating their proficiency because they simply don’t realize the depth of Excel’s capabilities or the foundational gaps in their knowledge.

It might also reflect a pride or stigma issue. Few people want to publicly admit they need remedial Excel help. It feels akin to needing remedial reading lessons. Yet, paradoxically, acknowledging these foundational gaps is precisely what can transform your productivity. To combat this blind spot, it’s crucial for organizations to implement clear capability tracking and structured skill assessments. Only by objectively measuring skills can organizations accurately identify and address the hidden gaps, ensuring all team members genuinely benefit from targeted training, whether foundational or advanced.

If this resonates with you and you’re looking to set up capability assessments or structured training programs, I can help you with that:

I’d also love to hear your thoughts about what these data points might mean. Let me know in the comments!