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SEO forecasting allows you to estimate the potential traffic—and revenue—you could generate by targeting relevant keywords with appealing content.
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Search engine optimization can sometimes feel mysterious. Results are slower to appear than those from other channels, such as social media, and SEO doesn’t offer the guaranteed traffic of pay-per-click advertising. So how do you create some sort of prediction for what results to expect and when?
SEO forecasting helps you model this, so you can make decisions about what efforts—for example, technical optimization or creating new pages—to prioritize.
Learn more about what SEO forecasting is, which SEO metrics matter when forecasting, and how to forecast like a pro.
Search engine optimization (SEO) forecasting is the process of using current and historical data to predict how your organic search efforts will perform over time.
Typically, forecasting includes organic traffic, conversion rate, and revenue metrics. In ecommerce, this means understanding how much traffic to expect for key product and category pages, when traffic might spike, which keywords will attract qualified website traffic, and how much revenue all of this could translate to.
A strong forecast includes multiple metrics, generally projected over a 12-month window to account for seasonal changes and time delays between publishing content and capturing keyword rankings. At its simplest, an SEO forecast should include:
Shopify senior SEO specialist Arthur Camberlein recommends combining first-party and third-party data when forecasting. “First-party gives you insights into where you are currently appearing or ranking. Third-party data will enrich these data with opportunities,” he says.
First-party data is your own business data, collected from tools like Google Analytics 4 (GA4), Google Search Console (GSC), a customer relationship management system (CRM), and Shopify Analytics. This data includes:
Third-party data is collected by tools like Ahrefs, Semrush, and Google Trends, all of which crawl the web and aggregate user behavior. This includes:
Although you can get granular with statistical forecasting models and other analyses, Arthur advises keeping it simple, especially if you aren’t a data scientist. “Data from analytics tools such as Google Analytics, Shopify Analytics, Adobe Analytics, Google Search Console, or Bing Webmasters is enough to start with.”
Here’s how to forecast four essential SEO metrics:
You can measure search volume using keyword research tools like Ahrefs or Semrush—but bear in mind, search volume can change over time. In fact, some keywords have major seasonal fluctuations in volume, like “Black Friday shoe deals,” which jumps from 428 searches in October to more than 26,000 in November.
To forecast keyword search volume, enter your target keyword into a keyword research tool like Ahrefs or Semrush and export the past 12 months of search volume data. Look for patterns: Is volume increasing, decreasing, or flat? Calculate month-over-month increases or decreases for each keyword.
You can also look at Google Trends for more context. Plug in the keyword and adjust the time frame to two to five years to spot seasonal demand, such as holiday spikes or summer slumps.
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CTR is influenced by your search results ranking position, metadata (title tag, meta description), and search engine results page (SERP) features like featured snippets, ads, and image packs.
Use industry benchmarks to estimate CTR for your target keywords based on ranking position:
For example, if your target keyword has 10,000 monthly searches and you rank in the top spot, you can forecast roughly 2,800 visitors per month. To assign the top spot in search results, Google considers a combination of relevance, authority, and usability. Pages that answer the query comprehensively, generate natural backlinks, and are easy to navigate tend to be more successful. To estimate your ranking chances, analyze the current top results. If they’re weak in content or authority, you have an opening. If they’re dominated by legacy brands with hundreds of backlinks (visible in tools like the Ahrefs backlink checker), focus on lower-searched keywords instead.
You also need to drill down into the layout of specific SERPs for the keywords you’re targeting. SERP features like ads, images, or a featured snippet could push search results down the page, decreasing the CTR of high-ranking organic results. AI Overviews can also decrease CTR by up to 35% even if you’re in the number one position, as they quickly answer most users’ queries without requiring a click, reducing the potential traffic to your site.
To forecast conversion rate (CVR), pull historical data from Google Analytics (GA4) or Shopify Analytics, filtering by organic traffic. Look at the past six months of conversion data across key pages (e.g., product pages, high-intent landing pages). Calculate a baseline CVR using this formula:
CVR = (Conversions from organic traffic / Total organic sessions) × 100
For example, if you had 2,000 organic sessions and 50 conversions, your organic CVR would be 2.5%.
However, not all pages will have this conversion rate, as CVR varies by conversion funnel stage. For example, blog pages usually have lower conversions than product pages. With that in mind, segment the URLs in your traffic forecast by page type or intent. For the group of pages with a similar level of intent as those in your CVR calculation, apply the CVR to the forecasted traffic for those pages. If you’re projecting 5,000 organic visitors to those pages next month with a conversion rate of 2.5%, you can estimate 125 conversions.
To forecast how much revenue SEO brings in, filter your traffic source for organic only. Then find your total revenue and total number of orders for the past six months in Shopify Analytics. Calculate your average order value with this formula:
AOV = (Total revenue from organic transactions / Number of organic transactions)
For example, if you made $50,000 from 1,000 organic purchases, your AOV would be $50.
Then, combine AOV with your traffic and conversion forecast. This lets you translate SEO growth into dollar value and project revenue impact. If you’re predicting 5,000 organic visitors with a 4% conversion rate (200 sales), and your AOV is $50, you can expect $10,000 in organic revenue.
Here is an example of 12 months of estimated traffic used to project revenue via the method above, assuming you’re able to rank in the top spot for the target keyword (with a CTR of 28%).
In January, for instance, the keyword has a monthly search volume of 5,000. Assuming your page ranks in the top spot with an industry-standard CTR of 28% and a conversion rate (based on hypothetical prior performance for your site) of 4%, the result is 56 purchases. If each purchase has an average order value of $100, you can anticipate $5,600 in revenue from this keyword.
Suppose your SEO efforts are just starting and you don’t have organic conversions yet. In that case, you can use industry conversion benchmarks from Shopify reports or a proxy AOV, such as overall site AOV, rather than organic only. However, this becomes a directional growth model rather than an accurate forecast. Once you have gathered a minimum of 20 conversions, update the model with real numbers.
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Here are four tips to keep in mind when forecasting:
Use first-party data from sources like Google Analytics and Shopify reports as a baseline to see which pages and keywords are already driving SEO performance, then layer on third-party data from SEO forecasting tools like Ahrefs and Google Trends to identify opportunities beyond your current footprint. According to Arthur, first-party data serves as your reality check, while third-party data serves as your opportunity map.
Consider a hypothetical example for an ecommerce shoe brand:
Two key challenges of gathering SEO data are volume and time frame. “If the sample is too small, it could point you in the wrong direction,” Arthur explains. For example, pulling data for only a few months (rather than a year) could show results skewed by a short-lived trend.
Arthur also advises accounting for outlier years like 2020, when nearly every industry was affected by the COVID-19 pandemic. A single anomalous year (whether good or bad) can skew your projections. Sometimes it’s best to omit anomalous years from your projections if not accounted for properly.
A common mistake made when forecasting is assuming SEO growth is linear. In reality, SEO is shaped by various moving parts, so your forecast needs to be flexible. Seasonal fluctuations can significantly impact your SEO forecast as certain keywords and product pages may perform exceptionally well during specific times of the year, such as back-to-school landing pages.
Arthur says the easiest way to apply seasonality to your forecast is to think in annual terms. Forecast your total organic traffic or revenue for the year, then divide by 12 to get a monthly baseline. “If you want to go further, check any seasonality you may have from external tools such as Google Trends,” he explains. “That way, you will be able to add more weight to the month you are planning to release the page.”
For example, a summer-focused category page might have a traffic spike in July that’s twice the average, so you would apply a seasonal weight of 200% to that month.
Traditionally, businesses would review and update their forecasts annually; however, the SEO world is constantly evolving, most recently with the adoption of large language models (LLMs) like ChatGPT and AI integration. For this reason, Arthur suggests reviewing your forecast every month. “Pivoting to adapt was always the case in the SEO world, but the pace has multiplied over the last two years or so,” he notes.
Uncontrollable variables make it difficult to forecast SEO growth. For example, Google’s algorithms are constantly updating, and user behavior can change based on cultural trends and seasonality. Forecasting also relies on data estimations, so there’s no such thing as a perfect forecast.
SEO is not becoming irrelevant; however, it is constantly evolving. AI Overviews and featured snippets are leading to zero-click SERPs. This means marketers need to think strategically beyond simply ranking on Google to maximize visibility across platforms.
To forecast return on investment (ROI), you need to connect organic traffic, conversion rate (CVR), and average order value (AOV), using this formula: Forecasted ROI = (Organic traffic × CVR × AOV) – Cost of SEO.
With platforms like TikTok, Reddit, and ChatGPT, SEO isn’t just about ranking No. 1 on Google, but showing up where your audience looks for information. While the fundamentals, like producing great content and improving user experience, still matter, SEO strategy is now platform-agnostic.
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