500% Difference In Search Term Performance

The usefulness of keyword marketing intelligence cannot be overstated; with keyword research you can predict shifts in demand, respond to changing market conditions, and produce the products, services, and content that web searchers are actively seeking. However, subtle changes in terms and keywords can make a dramatic difference in performance. In this article we correlate a selection of search terms to reveal a surprising trend in Interest Over Time.

Keyword research is one of the most important, valuable, and high return activities in the field of Internet Marketing. Marketers are familiar with measuring the frequency different terms are searched for in identifying which terms to optimize around. By researching your market’s keyword demand, you can not only learn which terms and phrases to target with SEO, but also learn more about your customers as a whole. Content Marketers use a similar approach in identifying subjects for content, and the titles to use with that content. The idea being that you want to optimize around terms that get searched for frequently, or have the highest interest among your target audience.

We analyzed a collection of 40 search terms for the tourism industry. The collection of terms followed two different patterns. One set all began with the phrase “top 10…”, and the other set all began with the phrase “10 best…”.

The line chart below (figure 1) is the terms correlated with their search frequency over time.

It seems like a minor difference, and you might assume that the terms “top 10” and “10 best” can be used interchangeably.

However, terms beginning with the phrase “top 10” had over 500% more searches than the terms that began with the phrase “10 best”.

This simple example demonstrates how important it is to use data to drive your marketing decisions.

A Primer On Data Correlation for Marketers

BriteWire uses data science to drive intelligent marketing decisions. When making a presentation to a new customer, I like to include a quick primer on Data Correlation to help them understand how powerful it can be in revealing trends, patterns, and characteristics of success for their business.

When two sets of data are strongly linked together we say they have a High Correlation. The classic textbook example used to demonstrate correlated data is height / weight data sets for human beings. The data indicates that a person’s weight is dependent on how tall they are, with shorter people tending to weigh less than taller people.

BriteWire uses correlation in many ways. We first use it to validate data sources. This is done by using known data values to check if they correlate with the data set we are analyzing but have not yet validated. This is best demonstrated using some simple data sets with known public data.

The following chart (figure 1) is a data set that measures visitor interest in Yellowstone National Park correlated with Glacier National Park.

Both of these parks publish Visitation Statistics, so we can use these known values to validate the data set we are working with. Visitors per year to Yellowstone National Park are approximately just over 3 million per year, with visitors to Glacier National Park averaging slightly lower at just over 2 million. Analyzing the published data in more detail reveals that there is seasonality, with the summer months being the period of highest visitation.

Looking at the chart we see that the data set indicates interest in Yellowstone National Park is higher than interest in Glacier National Park, and that interest peaks during the summer months. The data set correlates with the published data from the National Parks.

Scatter Plots are often used to visualize correlated data because they indicate how strong the correlation is. In the next chart (figure 2) web wearch activity for Yellowstone National Park and Glacier National Park are displayed in a scatter plot.

The scatter plot in figure 2 is showing a Strong Positive Correlation between Web Search Activity for Yellowstone National Park, and Glacier National Park. A user searching for information on Yellowstone National Park also appears to be searching for information on Glacier National Park. This makes sense because they are both located in the state Montana, and many people are interested in visiting both during their vacation.

As a result, your content marketing strategy should group these two subjects together, and perhaps cross link / cross promote between them. If you are a tour opporator perhaps you create a travel package that includes visiting both parks. These are very basic take-a-ways, but you get the idea.

A week correlation is easy to visualize with a scatter plot. The last chart(figure 3) is the scatter plot for web search activity for Yellowstone National Park and Katy Perry.

Not surprisingly the scatter plot indicates a week correlation between these two data sets.

In addition to validating data sets, Data Correlation can be used in many different ways to drive intelligent decisions for marketers, including social marketing strategy, content marketing, and interpreting data sets derived from Buzz Monitoring.

We will explore Data Correlation in greater detail in future articles as we explore these topics and more.

Big Data – Why It Is Important For Marketing

Big data is a term used to describe the exponential growth in the amount of data generated and stored. The analysis of big data will become increasingly important to marketers because it leads to more intelligent decision making.

The software industry has been defined by major shifts or transitions in the technical landscape. Having been in the tech industry for over 25 years, I have been involved with many of these waves. The PC wave, which was followed by the Client Server wave that revolutionized Enterprise Computing. This was followed by the Open Source wave, followed by the rapid rise(and brief collapse) of the Internet wave, Social Networks, and Mobile Computing.

One of the most exciting developments is the rise in Big Data and Cognitive Computing. In the last 2 years humans have generated more data than they have in the history of mankind. To put that in perspective you need to consider that humans have been around for over 200,000 years!

In the last 2 years humans have generated more data than they have in the history of mankind. To put that in perspective you need to consider that humans have been around for over 200,000 years!

Some of this data is being put to good use, but most of it isn’t being used in meaningful ways… yet.

I see a huge opportunity to use all the data and organize it in meaningful ways for data driven decisions, especially when it comes to marketing decisions.

That is the idea behind BriteWire…. Big Data analysis to drive Intelligent Internet Marketing.

BriteWire ingests large amounts of data and analyzes it to reveal trends, patterns, and characteristics of success. Just as important as the vast volume of data being generated is the timeliness of the data. Real time or near time analysis and monitoring of data can provide valuable information about emerging trends. When impending crises are identified you can be alerted before the situation becomes damaging.

In a world in which knowledge is power, what you don’t know can hurt you.

In future blog posts I will be diving into these topics and more. If you are interested in Big Data, Internet Marketing, Brand Development, and Internet Technology then follow along as I explore these topics in greater detail.

I will also be writing articles and posts about Competitive Intelligence, Social Networks, Cloud Computing, Content Marketing, and “Buzz Monitoring”.