Estimating Word-of-Mouth Activity from Search Query Data

While most digital marketers embrace the wealth of data generated by their campaigns, one of their biggest challenges is to leverage that data beyond the specific channel in which it’s generated. It can be a great frustration to make sense of numbers at the highest, most general level — but within that problem there’s a significant opportunity.

Let’s use discount wine retail as an example. A store owner may be proud of their e-commerce site, but if they aren’t connecting with the clientele on a more personal level, a lot of potential value is left untapped. This is frequently a motivator for having a social media presence.

Adding a blog as a complement to the e-commerce experience is a great way to build a presence in these word-of-mouth (WOM) channels. We know that WOM is highly trusted by consumers (McKinsey estimated it’s the primary factor in up to 50 percent of purchase decisions), but how do we identify the relevant conversations going on?

Tapping into related search query activity is one easy way to do this. Google’s AdWords Keyword Tool is a free resource offering a robust view of how frequently people search for different keywords. Let’s take it for a spin.

(Note: Earlier in May, Google updated its AdWords Keyword Tool interface. You’ll find it is easier to use the old version; just click Previous Interface.)

To start, go to the Keyword Tool and type “discount wine”. (Make sure “Use synonyms” is checked, and both options beneath “Filter my results” are unchecked.)

You’ll get two lists (Related terms, Additional terms). Click “Add all” for each, so that both show in the green section on the right.

Related/Additional Terms

Output that list to a text file; this is now your seed list. You’ll then take this and drop it back in where you typed “discount wine” beforehand. (This time, make sure “Use synonyms” is unchecked, and “Don’t show ideas for new keywords” is checked.)

Export this new list to CSV, and open in Excel.

Excel Export File

Extract “discount” and “wine” from the whole list (first, go for related terms like “discounts,” “discounted,” “wines”). This leaves you with the most common search modifiers related to discount wine.

Re-sort the list by keyword to remove blanks, and sort again, descending by Global Monthly Search Volume. At this point, it’s useful to cap the list to only those terms with a search volume X or higher (for “discount wine” my cutoff was 1,000).

Next to the search volume column, divide the number by 1,000 for each term. You’ll understand why in a second. Let’s call this Adjusted Search Volume.

Create a column next to the keywords where you fuse each term with a space (use the CONCATENATE function with the keyword followed by a space in between quotes. Example: =concatenate(A1,” “)

Now create one last column for your final output, where you multiply the keyword by the number shown in Adjusted Search Volume. This will give each keyword the proper relativity in the finished product. You can use the REPT function in Excel to do this. It will look something like this:

Adjusted Search Volume

Take that output and drop it into your favorite tag cloud generator (such as Wordle). And voilĂ€! Here’s a visualization of the top search modifiers related to discount wine:

Tag Cloud Generator

Is the word “red” cluttering things up too much? You can go back, and paste everything but the top keyword. Watch how the cloud changes:

Tag Cloud Generator

Still not inspired? You could just limit to the terms that have monthly search query volumes between 1,000 and 10,000:

Tag Cloud Generator

This process offers an objective, relative view of the conversation surrounding a root keyword, as reflected in search activity. It’s a scalable approach as well, with room for conversion, geography, seasonality, and other filters.

When adding search-enabled WOM insights to the other creative priorities surrounding new content development, the net result is an airtight method for populating an editorial calendar and positioning its content for maximum visibility in search engines.

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