Changes in seasons can trigger changes in the number of searches that people use for certain queries and topics.
For many website owners, understanding those seasonal variations may lead to more visits from people who are interested in what they offer upon their pages.
By seasons, I don’t just mean winter, spring, summer, and fall. There are many different seasons that can affect how and what people search for, such as seasons for baseball, football, basketball, and hockey.
Or seasonal variations based upon recurring holidays such as Christmas, Valentines Day, Mothers Day, and Thanksgiving. The start of a school year can trigger certain searches, and the summer break from school can impact other searches.
If you own an eCommerce business, you are probably familiar with the value of creating content and offering products that take advantage of periodic changes that happen at different times of the year. More informational sites, such as online newspapers or magazines, blogs, can also benefit from an awareness of patterns that people use in searches.
One of the difficulties of planning for seasonal traffic has been with the tools available to try to research the amount of volume that different search terms might possibly bring to a website, or at least allow someone researching those words to compare different choices that they might use. Microsoft unveiled a beta keyword research project a little over a year ago – the Search Volume Seasonality Forecast – which showed seasonal trends for keyword usage.
Microsoft’s program is still in Beta, and the searches you can perform are very limited. It’s difficult to tell if they will ever expand the tool, but it’s possible that they might. Microsoft had a patent application published that appears to describe that tool, and how it might work:
Keyword search volume seasonality forecasting engine
Invented by Lee Wang, Li Li, Shuzhen Nong, and Ying Li
Assigned to Microsoft
US Patent Application 20070239703
Published October 11, 2007
Filed: March 31, 2006
A method and system are provided for forecasting keyword search volume. Keywords are categorized by concept and by the amount of data available for use in predicting future behavior. The keywords and/or the categories can also be categorized as seasonal or non-seasonal.
A category level seasonal variation pattern can then be calculated based on keywords in the category that have sufficient historical data. A search volume can then be predicted for one or more keywords, with an appropriate calculation algorithm being selected based on the concept category, seasonal classification, and historical data available for the keywords.
The patent application describes a way to generate forecasts of keyword search volume. While this kind of forecasting can be useful for paid search, it’s not unusual for search marketers to also look at search volume information when looking for keywords to use for search engine optimization.
It appears that some of the technology behind the methods are described in a Microsoft paper that shares a number of authors with the patent filing – Similarity of Temporal Query Logs Based on ARIMA Model.
For some keyword phrases, where there is a couple of years worth of data on searches using those terms, it may be possible to classify them as seasonal or non-seasonal terms using a statistical model like the one described in that paper.
For keyword phrases where such data doesn’t exist, it might be possible to see if those phrases fit into concept categories with other phrases where there is data regarding how influenced they are by other seasons. If a phrase can’t be classified in that manner, a seasonal forecasting method might fall back on looking at the search volume for the term for the previous month.
There’s no telling if or when the Microsoft Seasonality Forecasting tool might come out of Beta, but I’d like to see it released. Perhaps now that the patent application has been published, we might see it move out of the Microsoft Adcenter Labs sometime soon.
There are some keyword research tools, like Keyword Discovery, that do provide years worth of Seasonal Trends, though it would be nice to have more than a single year worth of data to look at. Being able to identify similar phrases that may also be seasonal (but don’t have a history of data to use to tell) would also be a good option if it worked as well as the Microsoft patent application seems to suggest.
7 thoughts on “Microsoft Search on the Seasonality of Keywords”
Seasonal traffic is a big issue when developing educational websites. I view seasonal and holiday material as a chance to get new people to a website in the hope that they’ll return frequently for more of the non-seasonal offerings, too.
Looking forward to hearing more on this subject.
Nice sunflower, BTW.
I’m not sure that online sites pay as much attention to seasonality as they could, because it might not bring steady traffic to their websites throughout the year.
Beyond the difficulty in doing keyword research for terms that might attract traffic only for a part of a year – a few days or weeks, or a month or two, it can also be hard figuring out how to incorporate seasonal elements into your web site.
Do you redesign the whole site for the season? Do you create special pages that you only keep online for part of the year? Do you make pages that stay online all year round?
I’m glad that you mentioned the sunflower. I thought the image was appropriate because it’s growing on my front porch right now, somewhat out of season. I think that it’s possible to incorporate different parts of a site that consider seasonality that can provide value even out of season. It’s just a matter of being creative in creating those pages.
I love to test the tool… Is it available now? Better forecasting of seasoned keywords I think could help a lot in promotion.
This is a risky strategy. You’re investing a lot of time for just one shot at success.
The tool is in beta right now, and it’s not possible to tell when and if it might be available.
There are lots of risks, and they need to be weighed against each other. A lot of folks have built successful businesses based upon understanding seasonal trends within their industry. I’m not quite sure that I would call that risky. If you have a strong foundation to begin with, then that knowledge of seasons can be more of an opportunity than a risk.
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