Why Marketing Teams Need Dedicated Data Scientists

by Dan Matthews, Guest Contributor

When you think of the word "marketing," there are many preconceived notions on what it actually entails. For some, marketing is a collection of creative bodies and company initiatives, designing campaigns for product launches, trade shows, and brand engagement. For others, though, marketing has taken on a whole new meaning over the years, comprising deep market research, investigative analysis, and strategic content generation.

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The reality is, as society continues to rely heavily on digitized environments, the latter definition of marketing has become ever more relevant. Modern marketing departments now employ data scientists as part of their foundational team structure, helping to drive better decision making around target audiences and how to reach them effectively. 

But why is data science such a critical factor in marketing success, and how can incorporating this concept in your organization make a difference? Below we'll touch on a few reasons why hiring a data scientist for your organization could be your next best decision. 

Keyword Selection and SEO Importance
While word of mouth and overall brand recognition certainly help to sustain businesses that are already well-established, for many, discovering new verticals and reaching larger audiences can be a challenge. This is where the magic of SEO keyword selection comes in.

SEO keywords and semantic searchability are the foundations that every internet search engine is built on. By creating your web content around specific words or terms your audience is searching when looking for relevant products and services, you're much more likely to have search engines rank you organically on the SERPs (Search Engine Results Pages).

There are a variety of keyword types to choose from, and data scientists play a crucial role in helping to analyze and identify the ones that will bring the best results. Some of these include:

Main Keywords — These are one-word terms that typically describe the product or service your organization provides. These can also be referred to as “head terms.”

Short-tail Keywords — These are short keyword phrases made up of three words or less and are generally the starting point of an SEO campaign.

Long-tail Keywords — These more specific keyword phrases are made up of more than three words. The goal of these terms is narrow down more specific search instances that are generally less volume, but also less competitive to rank for.

LSI (Latent Semantic Indexing) Keywords — These keywords focus on fitting a broader theme and can generate multiple topics and interests from one keyword. For example, if a marketing team was to focus on the keyword "apple," LSI keyword options could be "apple nutrition," "apple recipes," "organic apple," etc.

Utilizing Google Analytics
Keyword selection and optimization, however, are only the starting points for data scientists. Using powerful analytics tools like Google Analytics, data scientists can help organizations get a better understanding of how their customers are finding and interacting with their organization's web properties. They do this in several ways:

Funnel Analysis — By tracking the customer's journey after landing on a web property, data scientists can provide essential details to sales and marketing teams about web page bounce rates, cart abandonment, poor linking structure, and other important user experience design issues.
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Customer Segmentation — Being able to segment is an integral part of catering content and advertising to the right audience. Data scientists can break down website traffic into different market segments that help to identify whether visitors are new or returning, what their search preferences are, where they are searching from, and their topics of interest.

Predictive Analytics — Proactively measuring and adjusting your marketing tactics is an important part of any successful campaign. Using tools like Google Analytics, data scientists can start to predict their customer's behaviors before and after they click on advertisements. This allows them to significantly improve their ability to convert more sales and help to improve the organization's web presence.

Social Media Engagements
Web properties, however, are not the only place where customers are found. Social media is an essential component of every marketing campaign, and there are several strategic components involved when engaging with new or potential customers.

Data scientists can conduct a variety of analyses when focusing their efforts on social engagement. For one, data science helps organizations discover the type of communities that individuals belong to, dissecting interests, hobbies, product and brand preferences, and geography. All of this information establishes the groundwork necessary for "cluster analysis" — the grouping of data into related groups, useful for pay-per-click advertising campaigns, and targeted outreach.

Another beneficial task that data scientists perform is monitoring and analyzing social media chatter. By pulling in data from user conversations, organizations can gain critical insights into relevant topics around their industry. This type of data collection can also be focused around customer reviews, opinions, and general feedback around the company. 

While the concept of data science isn't well-known to every organization, it's relevance and importance in today's marketing landscape is becoming increasingly vital. By investing in the resources necessary to compile and analyze the available market and customer data, organizations can maintain an edge over their competition and find more effective and sustainable ways to grow their brand.

About the author:

Dan Matthews is a writer with a degree in English from Boise State University and nerds out on tech news. He generally writes at the intersection of business, tech, and culture.

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