# How to Forecast SEO Traffic and ROI From a Keyword List

> An SEO forecast is a chain of four assumptions: monthly search volume, the share of searchers who click the position you expect to reach, how long it takes to get there, and what a visit is worth. Make each one visible, build a conservative, a likely and an optimistic scenario, and check the result against your own Search Console data rather than trusting a single number.

Source: https://tonaily.com/guides/forecast-seo-traffic/
Last updated: 2026-11-06
Checked against sources on: 2026-11-06

## Can you really forecast SEO traffic?

Yes, as long as you treat the forecast as a range built from assumptions you can see, not as a promise. Four numbers do most of the work: monthly search volume, the click-through rate (CTR) at the position you expect to reach, the time it takes to get there, and the value of a visit.

A marketing manager has to defend a content budget in front of her CEO. An agency sent her a deck: "+12,000 visits a month within a year." She cannot tell where the number comes from, so she cannot defend it, and she cannot tell whether it is too high. The method below is the opposite: every step is a multiplication anyone in the room can redo, and every assumption is written next to the result.

You can run every step by hand or in the free [SEO ROI calculator](/resources/tools/seo-roi-calculator/), which chains volume, position, conversion rate and cost and shows each intermediate number.

## What is the formula for an SEO traffic forecast?

Forecast monthly visits for a keyword = monthly search volume × expected CTR at the target position × an adjustment for the search results page. Then visits × conversion rate × value of a conversion gives revenue, and time to rank tells you when that revenue starts.

```mermaid
flowchart LR
  A[Search volume] --> B["× CTR at target position"]
  B --> C["× SERP adjustment"]
  C --> D[Visits at cruising speed]
  D --> E["× time-to-rank ramp"]
  E --> F["× conversion rate × value"]
  F --> G[Revenue vs cost = ROI]
```

Each link in the chain has its own source of error:

| Step | Where the number comes from | What makes it wrong |
|---|---|---|
| Search volume | Keyword Planner or an SEO tool | Rounded, averaged over 12 months, close variants grouped |
| CTR by position | A published study, or your own Search Console data | Varies by query type, device and SERP layout |
| SERP adjustment | Your observation of the results page | Ads, featured snippets, AI Overviews, video, local pack |
| Time to rank | Your site's history on similar pages | Competitors, authority, updates you do not control |
| Conversion and value | Your analytics and CRM | Blog visitors convert less than pricing-page visitors |

## Where does search volume come from, and how reliable is it?

Most volumes trace back to Google's own data, and Google is clear that they are approximations. In Keyword Planner, average monthly searches is "the average number of times people have searched for a keyword and its close variants", averaged by default over 12 months, and the [Google Ads help page](https://support.google.com/google-ads/answer/3022575) states plainly: "Your search volume statistics are rounded."

Two consequences for a forecast. First, a 12-month average hides seasonality: a keyword that averages 1,000 searches can do 2,500 in its peak month and 300 in its trough, so a monthly forecast built on the average will be wrong almost every month even if it is right over the year. Second, close variants are grouped, so adding "payroll software" and "payroll softwares" as two lines double-counts the same demand.

## What click-through rate should you expect by position?

It depends on the study, the year and the query, so any CTR table is one set of averages, not a law. As one reference point, Backlinko's analysis of around 4 million Google results (page last updated April 2025) reports:

- "The #1 result in Google's organic search results has an average CTR of 27.6%."
- "second and third-ranking results get 18.7% and 10.2% respectively."
- "The #1 organic result is 10x more likely to receive a click compared to a page in the #10 spot."

The page does not state when the underlying data was collected, which matters: SERPs have changed a lot since, especially with AI Overviews. Advanced Web Ranking publishes a [monthly CTR series](https://www.advancedwebranking.com/free-seo-tools/google-organic-ctr) built from anonymized Search Console data on US results, split by desktop and mobile, which shows how much these rates move from month to month.

The [SEO ROI calculator](/resources/tools/seo-roi-calculator/) uses a working baseline (27% at position 1, 15% at 2, 11% at 3, 6% at 5, down to 2% at 10). Read it as a set of assumptions in the same range as these studies, not as a measurement.

**The best CTR table is your own.** In Search Console, CTR is "the click count divided by the impression count", per the [Performance report documentation](https://support.google.com/webmasters/answer/7576553). Filter the queries where your average position sits between 1 and 3, then 4 and 10, and you have CTRs that reflect your brand, your snippets and your market.

## Why are SEO forecasts so often wrong?

Because the volume × CTR chain assumes searchers click, and a growing share of them do not. Zero-click searches, SERP features and AI Overviews all take clicks before your result, and the share varies by query.

**Zero-click searches.** SparkToro's 2024 study, based on Datos clickstream data from September 2022 to May 2024, found that "In 2024, 59.7% of European Union Google searches and 58.5% of American Google searches resulted in zero clicks." This is an average across all searches, including navigational and weather-type queries, so do not apply it to every keyword; but it explains why volume alone overstates the opportunity.

**AI Overviews.** The most direct measure we found comes from Pew Research Center, which tracked the browsing of 900 US adults in March 2025 (68,879 Google searches):

```quote source="Pew Research Center, Google users are less likely to click on links when an AI summary appears in the results (July 2025)" href="https://www.pewresearch.org/short-reads/2025/07/22/google-users-are-less-likely-to-click-on-links-when-an-ai-summary-appears-in-the-results/"
Users who encountered an AI summary clicked on a traditional search result link in 8% of all visits.
```

Those who did not see a summary clicked a result in 15% of visits. Advanced Web Ranking's Search Console–based series points the same way: on SERPs with an AI Overview, the reduction in CTR at position 1 has "typically been on the order of half", with variation by month, device and intent.

Note how Search Console counts this. A link from an AI Overview to your page counts as a click, and the Overview itself takes a position:

```quote source="Search Console Help, What are impressions, position, and clicks?" href="https://support.google.com/webmasters/answer/7042828"
An AI Overview occupies a single position in search results
```

So a page "at position 2" may sit under an Overview that answers the question. Being cited inside it is a different game, covered in the guide [AI share of voice](/guides/ai-share-of-voice/) and in [GEO: get cited by ChatGPT, Gemini and Grok](/guides/generative-engine-optimization/).

**Other reasons.** Time to rank is underestimated on young domains; competitors publish too; positions fluctuate rather than settle; and conversion rates borrowed from a landing page are applied to blog traffic.

## How do you build conservative, likely and optimistic scenarios?

Change the assumptions you are least sure of, one scenario at a time, and keep the rest fixed. Position, SERP adjustment and time to rank are the usual suspects; search volume and conversion value move less.

| Assumption | Conservative | Likely | Optimistic |
|---|---|---|---|
| Position reached | Bottom of page 1 | Positions 3–5 | Positions 1–2 |
| SERP adjustment on informational queries | × 0.5 | × 0.5 | × 0.75 |
| Time to reach the position | 9 months | 6 months | 4 months |
| Conversion rate and value | Same in all three | Same in all three | Same in all three |

Keeping conversion fixed is deliberate: if every assumption is pessimistic in one column and optimistic in the other, the gap becomes so wide it no longer helps a decision. The goal is to see which assumption swings the result, so you know what to verify first.

## A worked example: four keywords, three scenarios

**This is an illustration with assumed numbers, not data from a real site.** A small payroll software company targets a cluster of four keywords. Volumes are monthly averages; CTRs are the calculator's baseline; the 0.5 adjustment on informational queries is an assumption inspired by the Pew and Advanced Web Ranking figures above.

| Keyword | Volume | Intent | Conservative (pos. / visits) | Likely (pos. / visits) | Optimistic (pos. / visits) |
|---|---|---|---|---|---|
| payroll software for small business | 2,000 | Commercial | 9 → 2.5% → 50 | 5 → 6% → 120 | 2 → 15% → 300 |
| how to run payroll | 2,500 | Informational | 6 → 4% × 0.5 → 50 | 3 → 11% × 0.5 → 138 | 1 → 27% × 0.75 → 506 |
| payroll checklist | 1,000 | Informational | 5 → 6% × 0.5 → 30 | 3 → 11% × 0.5 → 55 | 1 → 27% × 0.75 → 203 |
| payroll software pricing | 500 | Commercial | 7 → 3.5% → 18 | 3 → 11% → 55 | 1 → 27% → 135 |
| **Visits per month at cruising speed** | **6,000** | | **148** | **368** | **1,144** |

Now the money side, with the same assumptions in every column: 2% of visits become a lead, a lead is worth $120 on average, and the content costs $600 a month (four articles, updates and tooling).

| | Conservative | Likely | Optimistic |
|---|---|---|---|
| Leads per month | 3.0 | 7.4 | 22.9 |
| Revenue per month at cruising speed | $355 | $883 | $2,746 |
| ROI at cruising speed | Negative | 47% | 358% |
| Break-even month | Never | Month 8 | Month 1 |

Break-even is the first month where revenue earned since publication covers cost since publication, with traffic growing in a straight line until the target position is reached. In the likely case, cumulative revenue reaches $4,858 in month 8, against $4,800 of cost.

What the example teaches is more useful than the numbers. The conservative scenario never pays off: at bottom-of-page-1 positions, this cluster does not cover a $600 monthly cost. The optimistic one pays off from month 1, which is a reason to distrust it, not to celebrate. And the commercial keyword with the smallest volume, "payroll software pricing", brings as many visits in the likely case as "payroll checklist", which has twice its volume, and those visits convert better.

You can reproduce each keyword in the [SEO ROI calculator](/resources/tools/seo-roi-calculator/) by entering its volume, target position, conversion rate and cost; for the informational lines, multiply the volume by the SERP adjustment first. The calculator uses a fixed 6-month ramp, so its break-even month matches the likely column only.

## How do you compare SEO with the cost of paid search?

Multiply forecast visits by what the same clicks would cost in Google Ads, then compare cumulative cost per visit over a long period. Keyword Planner gives a top-of-page bid range per keyword: the low end is "an approximation of the 20th percentile" and the high end of the 80th, based on the last 30 days.

Continuing the example, assume a top-of-page bid range of $2.50 to $6 for this cluster (again an assumption, not a quote). The likely scenario's 368 visits a month would cost $920 to $2,208 in ads. Over 24 months, with the 6-month ramp, the likely scenario brings about 7,900 visits for $14,400 of content: about $1.82 per visit, below the low end of the bid range. The conservative scenario, with its 9-month ramp, brings about 2,960 visits for the same cost: about $4.86 per visit, inside the range, so ads would not obviously be worse.

Two caveats. An ad-equivalent value is only money saved if you would really have bought those clicks; few companies buy clicks on "how to run payroll". And paid traffic stops the day the budget stops, while a page that ranks keeps working, so the comparison favors SEO the longer the horizon.

## How do you forecast traffic from improving existing rankings?

Start from your own Search Console data: it is the most reliable forecast you can make, because the volume and the CTR are already measured for your site.

1. In the Performance report, open the Queries tab and show impressions, clicks, CTR and position.
2. Keep queries with steady impressions and an average position between 4 and 20: these are the ones where moving up changes something.
3. For each one, forecast clicks at the target position = current impressions × your own CTR at that position (take it from queries where you already rank there).
4. Subtract current clicks to get the gain, and apply the same scenarios for time and position.

Remember that impressions are only counted when your result appears on the page the searcher sees, per [Google's definitions](https://support.google.com/webmasters/answer/7042828): a query at position 15 understates the real demand, because many searchers never reach page 2.

```checklist title="Before you present a forecast"
- Every volume comes from a named source and a date
- Close variants are not counted twice
- The CTR table is named, dated and presented as an assumption, or comes from your own Search Console data
- Queries with an AI Overview or heavy SERP features carry an explicit adjustment
- Seasonal keywords are checked month by month, not only on the 12-month average
- Three scenarios are shown, not one number
- The conversion rate matches the page type (article, comparison, pricing page)
- The cost includes writing, updates, tooling and team time
- The paid comparison uses Keyword Planner bid ranges for the same keywords
- A date is set to compare the forecast with actual Search Console clicks
```

## How do you check the forecast once the content is live?

Compare forecast and actual clicks per page and per query every month, and update the assumption that was furthest off rather than the whole model. If impressions are on target but clicks are low, your CTR or SERP adjustment was too generous; if impressions are low, the position or the time to rank was.

```tonaily
Tonaily estimates what a keyword cluster could bring before you write a line: visits if your pages reach the top 10 or the top 3, and the ad-equivalent value of that traffic. Once the articles are published, [Search Console is connected](/features/track/) on every plan, Free included, and each article's clicks, impressions and positions sit next to the keyword it targeted, so the forecast meets the actual numbers.
```

The first forecast is always rough. The second, built on your own CTRs and your own ranking delays, is much better: that is why the most useful thing a forecast does is fix a date to check it. Run your first scenarios in the free [SEO ROI calculator](/resources/tools/seo-roi-calculator/), then keep the three columns and compare them with Search Console three and six months after publishing.

## FAQ

### Can I forecast traffic from ranking improvements?

Yes, and it is the most reliable forecast you can make, because you start from real data. Take a query you already rank for in Search Console, note its impressions and current position, then apply the click-through rate your own site gets at the target position. Your own CTRs beat any industry average.

### What click-through rate should I assume for each position?

There is no universal figure. Backlinko's analysis of about 4 million results reports an average CTR of 27.6% for the #1 result, 18.7% for #2 and 10.2% for #3, but the rate drops when ads, featured snippets or AI Overviews sit above the organic results. Treat any published table as one study's averages and replace it with your own Search Console CTRs as soon as you have them.

### How accurate is an SEO traffic forecast?

Rarely accurate to the visit. Search volumes are rounded 12-month averages, CTRs vary by query, and the time to rank depends on competitors you do not control. A good forecast gives an order of magnitude and a range, and tells you which assumption to check first.

### Do AI Overviews reduce the traffic I should forecast?

On many informational queries, yes. In Pew Research Center's March 2025 data, users who saw an AI summary clicked a traditional result in 8% of visits, against 15% for those who did not. Apply a reduction to the queries where Google shows an AI Overview, and keep it as a visible assumption.

### Should I compare SEO with the cost of Google Ads?

Yes, as a sanity check. Multiply forecast visits by the top-of-page bid range Keyword Planner gives for the same keywords to get an ad-equivalent value. It only means money saved if you would actually have bought those clicks.


## Sources

- [Performance report (Search results) (Search Console Help)](https://support.google.com/webmasters/answer/7576553)
- [What are impressions, position, and clicks? (Search Console Help)](https://support.google.com/webmasters/answer/7042828)
- [Use Keyword Planner (Google Ads Help)](https://support.google.com/google-ads/answer/3022575)
- [Google users are less likely to click on links when an AI summary appears in the results (Pew Research Center, July 2025)](https://www.pewresearch.org/short-reads/2025/07/22/google-users-are-less-likely-to-click-on-links-when-an-ai-summary-appears-in-the-results/)
- [We Analyzed 4 Million Google Search Results. Here's What We Learned About Organic Click Through Rate (Backlinko, last updated April 2025)](https://backlinko.com/google-ctr-stats)
- [2024 Zero-Click Search Study (SparkToro, with Datos)](https://sparktoro.com/blog/2024-zero-click-search-study-for-every-1000-us-google-searches-only-374-clicks-go-to-the-open-web-in-the-eu-its-360/)
- [Google Organic CTR History (Advanced Web Ranking)](https://www.advancedwebranking.com/free-seo-tools/google-organic-ctr)