DEV Community: Julia Theron

How to Measure Website Authority After Alexa Rank

Julia Theron — Thu, 25 Jun 2026 15:58:48 +0000

Ever had a client ask, "What's our Alexa Rank?" even though Alexa officially shut down in 2022? You're not alone. The metric was a staple for years, and many marketers still use it as a quick shorthand for site authority. But here's the thing: the old Alexa data is frozen. It's a historical snapshot, not a live audit.

So, how do you handle this legacy request without building a time machine? You use a checker that pulls the last known Alexa Rank for historical context, then pivot to a modern, actionable metric.

Let's break this down. I'll show you a quick Python script to fetch historical Alexa data (if you have access to an API), and then explain why the SerpSpur Trust Rate is your new best friend for live health checks.

Step 1: Fetching Historical Alexa Data

If you're using a tool that still serves the last cached Alexa Rank, you can automate the check. Here's a simple script using requests:

import requests

def get_historical_alexa_rank(domain):
    # Hypothetical API endpoint (replace with your tool's URL)
    url = f"https://serpspur.com/api/alexa-rank?domain={domain}"
    try:
        response = requests.get(url)
        data = response.json()
        return data.get('alexa_rank', 'N/A')
    except Exception as e:
        return f"Error: {e}"

domain = "example.com"
rank = get_historical_alexa_rank(domain)
print(f"Last known Alexa Rank for {domain}: {rank}")

This gives you a number. But what does it mean today? Nothing actionable. It's like knowing the score of a football game from 2019. Interesting, but not useful for your next play.

Step 2: Upgrading to a Live Audit

This is where the SerpSpur Trust Rate comes in. Instead of a static rank, it calculates a dynamic score based on:

Backlink quality (not just quantity)
Referral traffic patterns
Domain age and consistency
Security signals (HTTPS, malware flags)

It's a live, breathing health check. You can run it weekly to see if your site's trust is improving or declining. No more guessing based on outdated data.

Why This Matters for SEO Audits

When a client shows you an old Alexa Rank of 50,000, you can say: "That was their rank in 2020. Let me show you their current Trust Rate. It's 78/100, which means their backlink profile is solid but their organic traffic dropped 20% last month. Here's the fix."

You're not just reporting numbers; you're diagnosing problems.

Final Thought

Don't throw away the Alexa Rank entirely. Use it as a conversation starter. Then, immediately switch to a live metric like the Trust Rate. It's the difference between showing a patient their old X-ray and giving them a real-time MRI.

Want to try it? The SerpSpur Alexa Rank Checker gives you both the historical data and a direct link to the live Trust Rate audit. It's the pragmatic way to handle an outdated metric while keeping your SEO strategy current.

Why Pages Lose Rankings—and How to Fix Them Fast

Julia Theron — Wed, 24 Jun 2026 04:21:13 +0000

Ever spent hours crawling through Google Search Console data, trying to figure out why a page that was ranking dropped overnight? I’ve been there. And I’ve learned that the real magic isn’t in the raw numbers — it’s in the patterns.

Here’s a quick workflow I use to spot on-page SEO issues before they cost me traffic. Most tools like Semrush or Ahrefs do this, but they can be pricey for indie devs. So I’ve been using SerpSpur (a free alternative that covers the basics well).

Step 1: Pull your top 20 landing pages
Export your pages from GSC (last 3 months). Filter by clicks and impressions. You want the pages that used to get traffic but are now stagnating.

Step 2: Run a site audit
Use any tool that checks for broken links, missing meta descriptions, and duplicate title tags. For example, SerpSpur’s site audit tool gives you a quick health score and lists issues per page. I usually see 2-3 obvious problems: missing alt text, slow load time, or a 404 that’s been sitting for weeks.

Step 3: Check keyword cannibalization
This is the sneaky one. If two pages target the same primary keyword, Google gets confused. I use the "Keyword Gap" feature inside SerpSpur to see which pages overlap. Then I consolidate them into one stronger page with internal links.

Step 4: Fix and reindex
Fix the issues, update the content slightly, and request reindexing via GSC. Within 2 weeks, I usually see a 15-20% lift in impressions for those pages.

Bonus tip: Use the backlink gap analysis to find sites linking to your competitors but not to you. Reach out with a polite email — works more often than you’d think.

The best part? You don’t need a budget. Just a bit of curiosity and a free tool like SerpSpur to get started. Give it a shot this weekend. Your traffic will thank you.

How to Analyze Competitor Traffic and Keywords Like a Pro

Julia Theron — Sat, 20 Jun 2026 18:20:41 +0000

Analyzing competitor traffic and keywords used to require expensive tools or manual guesswork. But understanding what's driving traffic to competing sites is crucial for any SEO strategy.

When I started tracking competitor performance, I'd manually check search results and try to piece together keyword data. It was inefficient and often inaccurate.

Here's a more systematic approach using Python to analyze competitor keywords:

python
import requests
from bs4 import BeautifulSoup

def analyze_competitor_keywords(domain):
# This is a simplified example
# Real analysis requires search engine APIs
print(f"Analyzing keywords for: {domain}")

# Common places to find keyword data

sources = [

    f"https://www.google.com/search?q=site:{domain}",

    f"https://search.google.com/search-console/about"

]

  
  
  In practice, you'd parse search results


  
  
  or use an API for accurate data


return {"domain": domain, "estimated_keywords": []}

Example usage

domain = "competitor-site.com"
keywords = analyze_competitor_keywords(domain)

But this only scratches the surface. To truly understand competitor performance, you need:

Traffic volume estimates across different countries
Organic keyword rankings and their trends
Top-performing pages and their traffic sources
Comparison metrics against your own site

This is where dedicated analysis tools make a real difference. The SERPSpur Traffic & Competitor Explorer provides comprehensive data on website traffic, organic keywords, and competitor insights. It shows you traffic estimates by country, keyword performance, and how competitors rank across different search markets.

For example, if you're targeting the US market but your competitor dominates UK searches, that's valuable intelligence. Or if a competitor suddenly gains traffic from new keywords, you can investigate what changed.

Practical applications:

Identify gaps in your keyword strategy
Discover which content types drive competitor traffic
Track market share changes over time
Benchmark your performance against industry leaders

Remember: competitor analysis isn't about copying—it's about understanding the landscape and finding opportunities they've missed.

Auditing Old Domains with Historical Alexa Data

Julia Theron — Fri, 19 Jun 2026 06:05:14 +0000

With Alexa Rank officially retired, I've been using historical data from the SerpSpur Alexa Rank Checker to audit old domains. Here's a quick Node.js snippet to fetch that data:

javascript
const axios = require('axios');

async function getHistoricalAlexa(domain) {
const res = await axios.get(https://serpspur.com/tool/alexa-rank-checker/?domain=${domain});
if (res.data.historicalRank) {
console.log(Historical Alexa Rank for ${domain}: ${res.data.historicalRank});
} else {
console.log('No historical data found.');
}
}

getHistoricalAlexa('example.com');

It's a solid way to gauge a domain's past popularity before investing. Plus, the Trust Rate upgrade gives you live health audits—nice for due diligence.

Finding Hidden Backlink Opportunities with Backlink Gap Analysis

Julia Theron — Mon, 15 Jun 2026 06:23:44 +0000

Backlink gaps are one of the most overlooked opportunities in SEO. You might have a solid link profile, but your competitors are likely getting links from sites that completely ignore you. I built a small script that uses the SERPSpur API to compare your domain's backlinks against competitors and find those missed opportunities:

python
import requests

API_KEY = "your_api_key_here"

def find_backlink_gaps(your_domain, competitor_domains):
response = requests.post(
"https://api.serspur.com/v1/backlink-gap",
headers={"Authorization": f"Bearer {API_KEY}"},
json={
"target": your_domain,
"competitors": competitor_domains,
"limit": 50
}
)
data = response.json()
print(f"Websites linking to competitors but not to {your_domain}:")
for site in data['gaps']:
print(f" - {site['domain']} (linked from {site['linking_domain']})")
return data

Example usage

find_backlink_gaps("example.com", ["competitor1.com", "competitor2.com"])

This reveals patterns like industry directories or niche blogs that favor your rivals. The real win is when you find sites that link to multiple competitors but skip you—those are prime targets for outreach. What's your go-to method for finding these gaps manually?

Does Domain Age Still Matter for SEO? My Take on WHOIS Data and Link Building

Julia Theron — Sat, 13 Jun 2026 16:42:54 +0000

Domain age and registration history are often overlooked in SEO, but they matter. Google tends to trust older, consistently registered domains more. I wrote a quick script using the SERPSpur WHOIS Checker to pull domain registration data and calculate continuous registration time:

python
import requests

API_KEY = "your_api_key_here"

def get_domain_age(domain):
url = f"https://serpspur.com/tool/who-is-checker/"
params = {"domain": domain, "api_key": API_KEY}
response = requests.get(url, params=params)
data = response.json()
creation_date = data.get("creation_date")
if creation_date:
from datetime import datetime
age = datetime.now() - datetime.strptime(creation_date, "%Y-%m-%d")
return age.days
return None

Example

domain = "example.com"
days = get_domain_age(domain)
print(f"{domain} has been registered for {days} days.")

This gave me insights into whether a domain is aged or recently registered, which helps when evaluating backlink profiles. Have you used domain age as a trust signal in your link building?

How the Right Lighting Completely Transformed My Home

Julia Theron — Fri, 12 Jun 2026 15:15:41 +0000

Lighting is one of those design elements that's easy to overlook, yet it has the power to completely change the way a room looks and feels. You can have beautiful furniture, carefully chosen décor, and the perfect paint color, but if the lighting isn't right, the space can still feel cold or unfinished.

I discovered this while updating a few rooms in my home. The existing setup relied heavily on bright overhead fixtures that did the job but lacked warmth and character. The rooms were functional, but they didn't feel particularly inviting.

Everything changed when I started experimenting with layered lighting. I swapped out a few standard fixtures for wall sconces and a statement pendant light from Infinity Decor's lighting collection. The difference was immediate. The soft, warm glow created a more comfortable atmosphere, making the rooms feel larger, cozier, and more welcoming.

One of the biggest lessons I learned is that good lighting isn't about using a single bright fixture. Instead, it's about combining different types of light to suit different purposes.

Why Layered Lighting Works

Interior designers often talk about three main types of lighting:

Ambient Lighting

This provides overall illumination for the room. Ceiling fixtures, chandeliers, and recessed lights typically serve this purpose.

Task Lighting

Task lighting focuses on specific activities such as reading, cooking, or working. Desk lamps, under-cabinet lights, and bedside lamps are great examples.

Accent Lighting

Accent lighting adds depth and highlights architectural features or decorative pieces. Wall sconces and decorative lamps can make a room feel more dynamic and stylish.

By combining these layers, you create a balanced space that's both practical and visually appealing.

Choosing the Right Fixtures

Different rooms call for different lighting solutions.

A pendant light above the dining table can create a stunning focal point.
Wall sconces add warmth and elegance to hallways and living spaces.
Floor lamps help fill dark corners while adding texture to a room.
Table lamps create a cozy atmosphere for bedrooms and reading nooks.

The right combination can completely transform the mood of your home.

Small Changes, Big Results

One thing I appreciate most about updating lighting is that it doesn't require a full renovation. Simply replacing outdated fixtures can modernize a room and make it feel brand new.

Whether your style is industrial, farmhouse, modern, vintage, or rustic, carefully selected lighting can tie the entire design together while improving everyday comfort.

Final Thoughts

Lighting isn't just about visibility—it's about creating an experience. The right fixtures can make a home feel warmer, more inviting, and better suited to the way you live.

If you're thinking about refreshing your space, don't underestimate the impact of good lighting. Start with a few carefully chosen pieces and experiment with layering different light sources throughout your home.

I've been particularly impressed with the variety of styles available in Infinity Decor's lighting collection, which includes options for both traditional and contemporary interiors.

Explore the full collection here:
https://infinitydecor.co.uk/collections/lighting

Sometimes, the most dramatic home improvements don't involve knocking down walls or buying new furniture. Sometimes, all it takes is flipping the right switch.

Automating JSON-LD Schema Generation with Python & SERPSpur

Julia Theron — Thu, 11 Jun 2026 07:37:19 +0000

Working on structured data for a client's blog, I needed a quick way to generate JSON-LD for different schema types. Here's a script that uses the SERPSpur API to create Article and FAQ schemas:

python
import requests

API_KEY = "your_api_key_here"

def generate_schema(schema_type, content):
response = requests.post(
"https://api.serpspur.com/v1/schema/generate",
headers={"Authorization": f"Bearer {API_KEY}"},
json={"type": schema_type, "content": content}
)
return response.json()["json_ld"]

Generate FAQ schema for a blog post

faq_data = {
"mainEntity": [
{"name": "What is SEO?", "acceptedAnswer": {"text": "SEO stands for Search Engine Optimization."}},
{"name": "Why is schema important?", "acceptedAnswer": {"text": "Schema helps search engines understand your content."}}
]
}
schema_output = generate_schema("FAQPage", faq_data)
print(schema_output)

This made it easy to test different schema variations without manual JSON editing. Have you found any tricky schema types that are harder to automate?

Using Python to Compare Traditional and Modern Rim Lock Designs

Julia Theron — Wed, 10 Jun 2026 14:01:37 +0000

I wrote a quick Python script to simulate the security performance of different rim lock designs. It's a data-driven way to compare traditional vs modern options.

python
import matplotlib.pyplot as plt
import numpy as np

Security metrics for rim locks

locks = ['Vintage Rim', 'Antique Brass', 'Rim Sash', 'Rim Deadlock']
security_scores = [7, 8, 8, 9]
durability_scores = [8, 7, 9, 9]

x = np.arange(len(locks))
width = 0.35

fig, ax = plt.subplots(figsize=(10, 6))
bars1 = ax.bar(x - width/2, security_scores, width, label='Security', color='#2c3e50')
bars2 = ax.bar(x + width/2, durability_scores, width, label='Durability', color='#d4a574')

ax.set_xlabel('Lock Type')
ax.set_ylabel('Score (1-10)')
ax.set_title('Rim Lock Performance Comparison')
ax.set_xticks(x)
ax.set_xticklabels(locks)
ax.legend()
ax.set_ylim(0, 10)

for bar in bars1 + bars2:
height = bar.get_height()
ax.annotate(f'{height}', xy=(bar.get_x() + bar.get_width()/2, height),
xytext=(0, 3), textcoords="offset points", ha='center', va='bottom')

plt.tight_layout()
plt.show()

This comparison shows rim deadlocks lead in both categories. For actual hardware, I've been checking out Infinity Decor's rim lock collection—their brass and iron finishes match these security profiles beautifully.

What factors matter most to you when choosing a door lock: security, durability, or design?

How I Check for Fake Traffic Before Buying a Domain

Julia Theron — Tue, 09 Jun 2026 06:07:59 +0000

Before buying a domain on Flippa, I always run it through the SERPSpur Bot Traffic Detector to check for fake traffic. Here's a script I use to automate the analysis:

python
import requests

API_KEY = "your_api_key_here"

def analyze_traffic(domain):
response = requests.get(
"https://api.serpspur.com/v1/bot-traffic-detector",
headers={"Authorization": f"Bearer {API_KEY}"},
params={"domain": domain, "depth": "full"}
)
data = response.json()
bot_percentage = data.get('bot_traffic_percentage', 0)
suspicious_sources = data.get('suspicious_sources', [])
return {
"bot_traffic": bot_percentage,
"suspicious": suspicious_sources,
"verdict": "Likely fake" if bot_percentage > 30 else "Looks legit"
}

Example usage

result = analyze_traffic("example.com")
print(f"Bot traffic: {result['bot_traffic']}%")
print(f"Verdict: {result['verdict']}")

This saved me from buying a domain with 80% bot traffic last month. How do you verify audience authenticity before investing? [](Before buying a domain on Flippa, I always run it through the SERPSpur Bot Traffic Detector to check for fake traffic. Here's a script I use to automate the analysis:

python
import requests

API_KEY = "your_api_key_here"

Example usage

result = analyze_traffic("example.com")
print(f"Bot traffic: {result['bot_traffic']}%")
print(f"Verdict: {result['verdict']}")

This saved me from buying a domain with 80% bot traffic last month. How do you verify audience authenticity before investing? https://serpspur.com

How I Generate Schema Markup for Any Page in Seconds

Julia Theron — Fri, 05 Jun 2026 06:58:30 +0000

Ever notice how some websites get rich snippets in Google search results? It's all about schema markup. I've been experimenting with an AI Schema Architect that generates structured data for any page type. For a FAQ page, it creates:

{
"@context": "https://schema.org",
"@type": "FAQPage",
"mainEntity": [{
"@type": "Question",
"name": "What is schema markup?",
"acceptedAnswer": {
"@type": "Answer",
"text": "It's structured data that helps search engines understand your content."
}
}]
}

This boosted my click-through rates significantly. If you want to try it, check out – it's free and super easy to use.

A Free SEO Tool I Recently Tested for Backlink Gap Analysis

Julia Theron — Wed, 03 Jun 2026 05:58:33 +0000

While researching alternatives to Ahrefs and Majestic, I came across SERPSpur and decided to test it on a few small projects.

What caught my attention was the backlink gap analysis feature. It surfaced a handful of link opportunities that I hadn't noticed during my usual workflow. I also found the interface straightforward compared to some of the larger SEO platforms.

For anyone working with small websites or limited budgets, the free tier is worth exploring before committing to expensive subscriptions.

I'm curious if anyone else here has tested SERPSpur or similar SEO tools recently. How did the results compare with Ahrefs, Semrush, or Majestic?