How To Do Market Research with Search Data

We often think of search as a direct marketing channel (and it’s a great one) but it’s so much more than that.

A Search Engine is a database of intentions – and the data that search engines release to us can be some of the best market research and planning data available.

With this process you can map search demand in your markets, and understand how to use search volume data for market intelligence and insight.

Mapping Search Demand in a Vertical

As with any SEO-drive process, you need to begin with some quality keyword research. You’ll want to start by gathering an extensive list of keywords that represent searches in the vertical you are looking to dissect.

To start your mapping research, use this process:

Brainstorm a Seed Keyword Set

The best SEO tool is always – and will always be – your brain.

Put it to work , and start brainstorming a list of relevant keywords.

For example, let’s say we’re working with a company in the mechanical keyboard space. Mechanical keyboards are very loud, high-end keyboards. They’re tend to be very popular amongst programmers, writers, gamers, and other folks with serious keyboard needs.

For this assessment, we’ll start with terms like:

  • Mechanical Keyboard – a generic head term, and
  • Cherry MX Keyboard – a base product term.

And some other terms closely related to them.

Expand Your Set Using Google Suggest

Next, I’ll expand your list with Google Suggest.

You can just use Google itself, or you can save some valuable time using some of the most popular autosuggest web apps like or Ubersuggest.

ubersuggest keyword term brainstorming

Expand Further and Gather Keyword Data with Term Explorer

One of my favorite new SEO tools is Term Explorer. This tool enables you to both expand keyword lists, gather search volume, and get competitiveness data. It is an excellent market research tool.

I’ll drop keywords from my previous exercise into TE’s Bulk Keyword Tool (a research and autosuggest engine capable of grabbing search data on up to 90,000 keywords) – so it will go out and find more relevant keywords in addition to our seeds.

mechanical keyboard in term explorer

Now Add in Brand Modifiers

While search marketers are typically primarily concerned with non-branded traffic, or brands and modifiers, in many scenarios )especially ecommerce) it’s worth adding them into your keyword research to get an understanding of how their volume compares to that of non-brand terms.

It’s also helpful to take a look at these different brands in Google Trends (especially if you can niche down to the product level), to get an idea of who’s growing and who’s not:

brands trends

This is great data to use to get some historical perspective on the Term Explorer data.

Now let’s do some analysis, and hopefully gather some insights.

To get all the data you’ll need you will want to pull down everything from Term Explorer’s keyword analysis tool, and throw it into Excel (or Tableau, or R, or Python, or your favorite data visualization tool).

You can use whatever you’d like – I’ll use Excel for simplicity in this example.

table of keyword search volumes

I’ll go ahead and copy and paste it all into a table so I can pivot it later.

Additionally, I’ll want to go ahead and add a “type” column, referring to what sort of search intent is behind the keyword phrase.

In this case, I’ll add:

  • Brand (for searches referring to a specific brand)
  • Usage (for searches like “Mechanical Keyboard for Programming”)
  • Comparison
  • Features
  • Informational
  • Switches (in this case, a category unique to the space, but if there’s a certain attribute lots of people search for, make it it’s own category.)

Now if you’re a search marketer, you’re probably already plotting how to use this data. But let’s start by using some basic visualization techniques to get our head around what people value in the Mechanical Keyboard space.

Let’s start by looking at switches. Different mechanical keyboards have different types of switches, each with their own pros and cons.

I’ll pivot my table into showing only switches, and then take a look at the volumes for each with a simple bar chart:

switches bar chart

As you can see, blue switches are dramatically more popular than brown switches, which are more popular than red switches, and so on.

Now this information is tremendously useful in conventional SEO campaigns – after all, if there’s no search volume, there’s little to optimize for – but it’s also useful for:

  • Inventory analysis – what should we order, especially if we don’t have historical data to draw on?
  • Merchandising – Which switches should be at the top of the switch page? Probably the blue ones. Using search volume analysis in parallel with traditional techniques like market basket analysis can give you new insight into how to merchandise your site/store.
  • Offer Creation – Knowing that blue switches are 4X more popular than red switches is a valuable insight when you’re creating campaigns, give-aways, social media updates, and more.

Market Analysis

Let’s take a look at another example, dear to our hearts as marketers.

So what do people do with these mechanical keyboards? This is closely related to the question “Where can I find people who buy mechanical keyboards?”

mechanical keyboards for X

Now this search data is very interesting – while our brains may immediately go to “I will sell mechanical keyboards as office supplies, and enable mass purchasing of them by IT departments”, our search data actually tells us a different story:

  • ~3x more people want to use a mechanical keyboard for gaming then work
  • Programming is the second most popular use case after gaming
  • iPad and office searches are not worthwhile targets

This means that instead of advertising to say, purchasers of office equipment or IT departments, we’ll want to go after two target groups: programmers and gamers. (Probably something of a Venn diagram.)

From a site merchandising perspective, we would want to create category pages around both of these topics – with very different marketing and messaging. We’ll also want to drive traffic to both of these hubs from websites and forums related to gaming and programming.

Additionally, if we’re developing our own mechanical keyboards (which would be amazing), we’ll want to include features that target these core audiences, like supporting multiple key presses and macros for gaming, or particularly excellent implementations of brackets and special characters for programming.

Looking at the Whole Landscape

In addition to niching down to the specific searched attributes, we’ll want to look at the whole landscape – how do individual brands compare in volume versus categorical searches? Are people more interested in a quiet mechanical keyboard or a cheap mechanical keyboard?

aggregated mechanical keybaord searches

This can be tough to visualize on larger sets of search terms – consider using an interactive tool that will let you drill down into individual results like Tableau.

Mechanical keyboard guide has so much volume – so much – that it is an outlier.

This tells us that either there is really significant searches for a mechanical keyboard guide – and we should aspire to produce the very best one we can and use a promotional strategy like Brian Dean’s SkyScraper technique.

Alternatively, queries that are outliers like this one may be navigational, or may represent large-scale rank tracking or other synthetic search volume, so we’ll exclude that one and conduct the same analysis:

average monthly searches - outliers removed

Search Intent is King – Not Just Traffic

If you’re reading this publication, you know and love search as a traffic generation strategy and a direct marketing channel.

But data from search engines can help with everything from inventory planning, to product development, to merchandising – basically anything that requires understanding consumer psychology.

Smart usage of this data gives search marketing practitioners a chance to make an even bigger impact for their clients – and drive even more revenue.

It all starts with keyword research and analysis – so put in the time to gather a representative data set, and then really work to understand the directional data that lies therein.