Excel: Create a Dynamic Search Bar

Key insights

• Fully dynamic search bar: A search input lets users type a term and see matching rows update automatically without reapplying filters.
  Use Excel’s dynamic arrays and a formula-driven layout to return only the rows that match the search.
• Core functions to build it: FILTER, SEARCH, UNIQUE, and text/regex helpers like REGEXTEST.
  Combine these to find exact or partial matches and to create suggestion lists or unique value menus.
• Stepwise improvements covered: start with an exact-match using FILTER, add partial matching with REGEXTEST or SEARCH, then search across multiple columns.
  This gradual approach keeps formulas simple and makes debugging easier.
• Multi-term and multi-column search tricks: use SUBSTITUTE to turn spaces into an OR operator so queries like “Nike Adidas” or “France Nike” match any listed term.
  Concatenate or test multiple columns so the user can search the whole dataset from one input.
• Live interactivity and UI polish: use an ActiveX text box or similar control to update results as you type, add conditional formatting to highlight matches, and move the search UI to its own sheet for clarity.
  These steps improve usability and make the tool feel responsive.
• Why use a formula-first approach: formula-driven solutions reduce reliance on macros, refresh automatically with data changes, and scale better with growing tables.
  Convert your source to an Excel Table so new rows are picked up automatically and the search stays current.

Overview

Kenji Farré (Kenji Explains) [MVP] demonstrates how to build a fully dynamic search bar in Excel in a recent YouTube tutorial. The video walks viewers from a simple exact-match filter to a polished, live search experience by adding successive layers of functionality. Along the way, the author combines native formulas and interface controls to show a practical path for many common search needs in spreadsheets.

The demonstration begins with a basic approach and then improves the tool step by step, making it easier for non-experts to follow. As a result, viewers can see both the mechanics of each change and the reasoning behind it. This piece summarizes those steps and highlights the tradeoffs that teams should weigh when choosing an approach.

Step-by-step technique explained

First, Kenji uses a formula-driven approach centered on the FILTER function to return matching rows when a user types an exact term. Then, to allow partial matches, he layers a function that evaluates text content, shown as REGEXTEST in the video, which enables substring searches across the dataset. Next, he combines multiple columns into a single search stream so that users can search anywhere in a row rather than a single column.

After that, the author converts spaces in the search input into an OR pattern so terms like “Nike Adidas” return rows that match either word, by using SUBSTITUTE to insert the regex pipe operator. He then makes the search live by embedding an input control—a form-style field that updates results without pressing Enter—so the list filters as the user types. Finally, conditional formatting highlights matching rows and converting the source range to an Excel Table ensures new rows are included automatically.

Tradeoffs: formulas versus controls and macros

Kenji highlights a clear tradeoff between a modern formula-first solution and older macro-driven interfaces. Formula-based methods using functions like FILTER and SEARCH tend to be easier to maintain and audit, and they work well with dynamic arrays, but they require up-to-date Excel versions to run smoothly. Conversely, using an ActiveX text box or VBA offers more UI flexibility and live event handling, yet it increases maintenance burden and may cause compatibility issues on different platforms.

Moreover, while VBA or ActiveX controls can create a smooth experience on Windows desktop Excel, they can break in Excel Online or on some Mac setups, which limits portability. Therefore, teams must balance the need for a polished user interface against the requirement for broad compatibility and simple maintenance. In many cases, a formula-first approach gives the best long-term return for collaborative workbooks.

Performance and practical challenges

Making a search bar robust introduces technical challenges, especially with large datasets and complex patterns. Using regex-style tests across many columns can become slow on big tables, so optimizing formulas and minimizing volatile calculations becomes important. Additionally, converting spaces into OR operators can produce unintended matches unless the pattern is carefully constrained, so thorough testing is required.

Another challenge concerns user expectations: some users expect instant suggestions or autocomplete, which can be awkward to reproduce with pure formulas. Likewise, keeping formatting consistent when search results change requires a careful combination of conditional formatting and table structure. Consequently, builders should test the tool with realistic data volumes and user habits before rolling it out broadly.

Practical tips and deployment advice

Kenji recommends turning the source range into an Excel Table so new rows appear automatically in search results, which improves scalability. Also, he suggests using simple named input cells and clear visual cues so non-technical users understand how the search works, and applying conditional formatting to highlight hits for quick scanning. These small design choices make the solution friendlier without adding code.

For organizations that need a cross-platform solution, prioritize formula-based methods and avoid platform-specific controls. However, if tight desktop integration and polished interactivity are essential, a controlled use of VBA or ActiveX may be justified, provided the deployment environment supports it. Training and documentation reduce the cost of more complex implementations.

Conclusion and takeaway

Kenji Farré’s tutorial shows a pragmatic path to a flexible, dynamic search bar in Excel that scales from simple filters to a refined live experience. By combining functions like FILTER, search testing, and simple UI controls, creators can deliver a responsive tool that meets most business needs. Still, teams must weigh compatibility, performance, and maintenance when selecting among formula-driven, control-based, or macro solutions.

Ultimately, the video provides a helpful roadmap: start simple, test with real data, and iterate toward more advanced features only when the benefits outweigh the extra complexity. Consequently, readers can adopt a solution that fits their users and environment without taking unnecessary risks.

Keywords

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