How Our Name Matching Algorithm Works: The Science Behind Finding Your Perfect Baby Name

The Challenge of Finding the Perfect Baby Name

Choosing a baby name is one of the most personal decisions new parents face. With thousands of possibilities, how do you find names that truly resonate with your style, values, and preferences?

Traditional baby name apps give you endless lists to scroll through. We took a different approach: what if the app could learn what you like and suggest names tailored specifically to you?

Our Solution: A Preference-Learning Quiz

Instead of overwhelming you with choices, our Discovery Quiz presents names one at a time. You rate each name with a simple swipe:

• Love it (swipe right) - This name really speaks to you
• Like it - It's nice, but not a standout
• Meh - It's okay
• Not for me (swipe left) - This isn't your style
• Skip - You'd rather not judge this one

Behind the scenes, our algorithm is learning from every rating you make.

What We Learn From Each Rating

Every time you rate a name, we're capturing multiple signals about your preferences:

Sound Preferences

When you love "Sophia," we notice:

• You might like soft-sounding names
• The "-ia" ending appeals to you
• You prefer 3-syllable names
• Names starting with 'S' catch your attention

Style Perceptions

Names carry cultural associations. "Sebastian" feels classic and refined. "Maverick" feels modern and strong. We track which style dimensions resonate with you:

• Classic vs Modern - Traditional names like Elizabeth, or contemporary names like Luna?
• Strong vs Gentle - Powerful names like Alexander, or soft names like Lily?
• Simple vs Refined - Straightforward names like Jack, or elegant names like Genevieve?

Origin Preferences

We learn which cultural origins appeal to you. If you consistently love Irish names like Aoife and Siobhan, we'll surface more names with Celtic roots.

Popularity Fit

Some parents want unique names their child won't share with classmates. Others prefer established names with familiar spellings. We learn where you fall on this spectrum.

The Magic: Exploration vs Exploitation

Here's where it gets interesting. Our algorithm balances two competing goals:

Exploration: Showing you diverse names to understand your preferences Exploitation: Showing you names we're confident you'll love

Early Quiz: Discovery Mode

In the first few ratings, we prioritize exploration. We need to understand your taste before we can make good recommendations. You'll see names from different origins, styles, and sounds.

After You Love a Name: Follow the Thread

When you love a name, we know something powerful. If you adore "Aurora," we immediately show you similar-sounding names. Why? Because sound is always a factor in loving a name - even if you cite the meaning as your reason.

Building Confidence

As the quiz progresses, we shift from exploration to exploitation. Once we've confidently mapped your preferences, we focus on finding your perfect matches.

Sound Similarity: The Secret Sauce

Our sound analysis goes deeper than simple spelling patterns. We use phonetic encoding (similar to how Siri understands different pronunciations) to find names that sound alike even if they're spelled differently.

"Sean" and "Shawn" sound identical. "Catherine" and "Katherine" are phonetically the same. Our algorithm understands these relationships.

We analyze:

• First sound - Hard consonant (K, G) vs soft (S, F) vs vowel
• Ending pattern - How the name trails off (-ia, -en, -son)
• Rhythm - The syllable count and stress pattern
• Vowel balance - Ratio of vowels to consonants

When you love "Isabella," we can find "Arabella," "Gabriella," and "Mirabella" - names that share that flowing, melodic quality.

Feedback Reasons: Fine-Tuning

After each rating, we ask why you felt that way. This feedback fine-tunes our model:

If you loved a name because:

• "Great sound" → We double-down on similar phonetics
• "Love the meaning" → We boost that meaning category
• "Classic feel" → We increase the classic style weight
• "Unique choice" → We expand our popularity range to find rarer gems

If you didn't like a name because:

• "Too common" → We filter out Top 100 names
• "Too long" → We narrow to shorter names
• "Feels dated" → We reduce classic style weight
• "Hard to pronounce" → We prioritize intuitive spellings

The Scoring Formula

When generating your results, every name in our database gets a preference score. The formula considers:

Dynamic Weight Shifting

Early in the quiz, we weight learned sound patterns highly (they're our best signal). As you love more names, we shift weight toward similarity to those specific loved names - a much stronger signal.

Pool Health Monitoring

To ensure we always have great suggestions, we monitor the "health" of our name pool:

• Viable names: At least 50 names scoring above our threshold
• Excellent names: At least 10 names scoring really high

If the pool gets too narrow (maybe you have very specific preferences), we automatically expand to include more options.

The Result: Names You Actually Love

After just 10-15 ratings, our algorithm has built a surprisingly accurate model of your naming preferences. The results page shows your top matches, scored and ranked by how well they align with everything we've learned.

Many users tell us the recommendations feel almost magical - like we read their minds. That's the power of preference learning through simple, intuitive interactions.

Privacy Note

All preference learning happens on your device. We don't upload your ratings to any server. Your naming journey is completely private.

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Ready to discover names perfectly matched to your style? Download the app and take the Discovery Quiz.