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If you're new to Ahrefs and want to run your first SEO audit, the fastest path is: open Site Explorer, enter your target URL, review the Overview for a health snapshot, then dig into Organic Keywords, Top Pages, and Site Audit to find specific problems. From there, build a short prioritized to-do list instead of trying to fix everything at once.

This tutorial walks through that workflow using a realistic starting scenario, explains what the numbers mean, and shows how to turn findings into actions.

Before You Start: Pick a Narrow Scope

A common beginner mistake is auditing an entire large website on day one. The reports become overwhelming, and you can't tell which issues matter.

Instead, choose one of these starting points:

• A single important page (your homepage or a key product/service page)
• A small site (under ~50 pages, e.g., a personal blog or small business site)
• One section of a bigger site (e.g., /blog/)

For this tutorial, assume you're auditing a small business site with about 30 pages. The same steps scale up later.

You'll need an Ahrefs account to follow along. Ahrefs offers paid plans, and pricing and feature limits change over time, so check the current Pricing page for what's included in each tier before committing.

Step 1: Enter Your Target in Site Explorer

Site Explorer is Ahrefs' core tool for analyzing any website or URL.

1. Open Site Explorer from the top navigation.
2. In the search box, paste your domain (e.g., example.com).
3. Choose the Exact URL or Domain mode depending on scope. For a full-site view, use Domain or Prefix; for a single page, use Exact URL.
4. Press Enter.

You'll land on the Overview report. Don't try to absorb everything — focus on four numbers first.

Reading the Overview Snapshot

Important caveat: Ahrefs' traffic and keyword numbers are estimates based on its own data. They won't match Google Search Console or your analytics exactly. Treat them as directional, not absolute.

Step 2: See What You Already Rank For

Go to Organic Keywords in the left sidebar. This shows queries where your site appears in search results.

Sort by Traffic (descending) to see which pages bring the most estimated visitors. Then look for:

• Keywords ranking in positions 4–15 — these are often the easiest wins. A small content or on-page improvement can push them onto page one.
• Keywords with high volume but low position — potential opportunities if the topic is relevant.
• Irrelevant keywords — if you rank for something off-topic, it may signal thin or mismatched content.

Write down 5–10 of the position 4–15 keywords. These become your first optimization targets.

Step 3: Find Your Best and Weakest Pages

Open Top Pages. This ranks your URLs by estimated organic traffic.

Look for two things:

1. Your top performers — understand what topics and formats work. Can you create more content like this?
2. Pages with traffic but poor rankings — these may need on-page fixes (title, headings, internal links).

If a page gets zero traffic and targets a topic you care about, it's a candidate for a rewrite or consolidation.

Step 4: Run a Technical Site Audit

Now move to Site Audit. This crawls your site and flags technical and on-page issues.

1. Click Site Audit → New project.
2. Enter your domain and set crawl settings (default is usually fine for a small site).
3. Start the crawl and wait for it to finish.

Once complete, you'll see a Health Score and a list of issues grouped by category.

Which Issues to Fix First

Not all issues are equal. Prioritize in this order:

Ignore low-impact warnings (like minor meta description length) until the big items are handled.

Step 5: Turn Findings Into a To-Do List

You now have raw data. Convert it into a short, actionable list. Example:

1. Fix 3 broken links found in Site Audit.
2. Rewrite title tags on 5 pages with duplicate titles.
3. Improve 4 pages ranking in positions 6–12 by adding missing subtopics and internal links.
4. Remove or update 2 thin pages with no traffic.

Keep the list to 5–10 items max for your first audit. Finishing a short list beats starting a long one.

Common Beginner Mistakes

• Chasing every red flag. Site Audit flags many minor issues. Fix what affects rankings and users first.
• Trusting estimates as exact numbers. Ahrefs data is modeled, not measured from your analytics.
• Auditing a huge site too early. Start small to learn the interface.
• Ignoring search intent. A page can be technically perfect but still fail if it doesn't match what searchers want.
• Forgetting to re-crawl. After fixes, run Site Audit again to confirm improvements.

Where to Go Next

Once your first audit is done:

• Compare with competitors using Site Explorer's Competing Domains and Content Gap reports.
• Track keyword rankings over time with Rank Tracker.
• Explore backlink opportunities in the Backlinks and Link Intersect reports.
• Set up recurring Site Audit crawls so new issues surface automatically.

Your first audit isn't about perfection — it's about building a repeatable habit: enter a target, read the key reports, pick the highest-impact fixes, and act. Do that once a month and your site's health compounds.

GMAO data is the collection of atmospheric, land surface, ocean, and ozone datasets produced by NASA's Global Modeling and Assimilation Office (GMAO) at Goddard Space Flight Center. You can use it for research and applications spanning weather, subseasonal-to-decadal prediction, and reanalysis — provided you understand that these products come from models combined with observations, not from direct measurement alone. This guide explains what the data covers, how assimilation produces it, and how to pick and access the right product.

What GMAO Data Covers

GMAO's stated research scope spans several Earth system components and timescales. Based on the office's own description, its work and data products address:

• Atmosphere — atmospheric state and dynamics
• Land surface — land-atmosphere interactions and surface fields
• Ocean — ocean state as part of the coupled Earth system
• Ozone — atmospheric ozone and related chemistry
• Subseasonal to decadal — prediction and analysis across timescales longer than typical weather forecasts but shorter than climate projections

This range matters when choosing a product: a dataset built for subseasonal prediction has different strengths and caveats than one built for short-range weather analysis.

How Data Assimilation Produces These Datasets

Data assimilation is the core mechanism behind GMAO products. It combines observations (satellite, in situ, and other measurements) with a numerical model of the Earth system to estimate the state of the atmosphere, ocean, land, and chemistry at a given time.

The practical consequence for users:

• Assimilated products (reanalysis) blend observations and model physics to create a consistent, gridded record. They fill gaps where observations are sparse, but the model's influence means the result is an estimate, not a pure measurement.
• Forecast products start from an assimilated initial state and evolve it forward in time. Skill generally decreases with lead time.

Understanding this distinction is the single most useful thing for interpreting any GMAO dataset correctly.

Finding GMAO Data and Documentation

GMAO data products and their documentation are hosted on the GMAO site at gmao.gsfc.nasa.gov. To locate what you need:

1. Go to the GMAO research site.
2. Navigate to the data products or datasets section (products are organized by system and timescale).
3. Open the documentation for a candidate product before downloading — it describes variables, resolution, time coverage, and known issues.
4. Confirm the product matches your required variables, spatial resolution, and time period.

Because GMAO maintains multiple modeling and assimilation systems, the same variable may exist in more than one product with different characteristics. Always check the specific product page rather than assuming consistency across datasets.

Choosing the Right Product

Use the same dimensions to compare candidates:

If your goal is a consistent historical record for research, a reanalysis product is the usual choice. If your goal is prediction, a forecast product initialized from assimilation is appropriate — and you should expect accuracy to vary with lead time.

Common Limitations and Caveats

• Model influence: Assimilated data reflects both observations and model physics, so it is not a direct measurement.
• Sparse-observation regions: Where observations are limited, the model contributes more, and uncertainty is typically higher.
• Forecast skill decay: Forecast products lose skill as lead time increases; subseasonal-to-decadal products are inherently probabilistic in nature.
• Version differences: Different GMAO systems and versions can produce different values for the same variable. Cite the specific product and version you used.

Quick Decision Guide

• Need a gridded historical record across atmosphere, land, ocean, or ozone? → Look for a GMAO reanalysis product.
• Need predictions beyond typical weather range? → Look for subseasonal-to-decadal forecast products.
• Unsure which product fits? → Start from the GMAO site's product documentation and match variables, resolution, and time coverage to your task before downloading.

For current product names, versions, and access details, consult the GMAO site directly, since these are maintained and updated by the office.