How You Can Use Data-Driven Strategies To Optimise Your Content Marketing Efforts

There has been a huge increase in online content platforms in the last 10 years, making information retrieval much easier than ever before. Most businesses use some sort of content marketing, in the form of blog articles, social media posts, a combination of images and infographics, or industry reports to engage with their audiences. This also provides them with the opportunity to keep track of user activities on their content platforms. They understand that in order to reach their target audiences, they need to be where their audiences are spending most of their time – online.

In addition, by publishing relevant content on a regular basis, companies can position themselves as thought leaders in their industries, which can help to differentiate them from their competitors. At this point of time, Web Analytics are mainly being used by digital marketing professionals to keep track of their performance.

Why using Web Analytics data alone is not enough

Website Analytics for Content Marketing
Figure 1: Website Analytics for Content Marketing

As we can see above, web analytics are being used for tracking traditional web traffic data e.g. number of users, sessions, pageviews, bounce rate, traffic from mobile devices, social media, and email campaigns. We can get a good high level overview of website performance. In addition, we can also measure the performance of individual pages and identify areas for improvement.

Website Analytic information as seen above is often limited to the capture of very few data points and doesn’t represent actual analysis. In order to get the full picture, you need to supplement your Analytics data with other sources of information. One of the most important things to keep in mind is that not all website visitors are created equal. Just because someone visits your site doesn’t mean they’re interested in what you have to offer.

Data-driven digital strategies based on sophisticated data analytics and insights are still not common. However, creating more engaging content by using data science practices is slowly gaining momentum. Data science is an interdisciplinary field where scientific methods, processes and algorithms are used to extract knowledge and insights from any type of data, whether structured or unstructured. The gathered knowledge and actionable insights are applied across the application domains. Below are some of the benefits that it brings to the table.

Core Areas for Data Science

Data science can help in two major areas:

  • Providing insights for content creation.
  • Evaluation of post-distribution performance with different metrics.

Below are some specific details about the value of data insights for digital marketing

Time-Series Forecasting for Better SEO Results

How does it work?

Time-series data is a collection of data points gathered over a period of time that allows us to examine changes over time. Changes in time-series data can be tracked in milliseconds, days, or even years. This allows us to better analyse trends, accurately report totals, and take action by tracking each aspect of data over time. It might sound like something very complicated but it’s really not and many people have seen its examples already. Google Analytics also shows data in a time-series format.

To maintain consistency and dependability, time series analysis often requires a high number of data points. A large data collection guarantees that we have a reasonable sample size and that our analysis can cut through noisy data. It also guarantees that any found trends or patterns are not outliers and can account for seasonal variation.

How can it be applied To Content Marketing?

For content marketing, we can segment user data (e.g. web sessions, sales, or other Key Performance Indicators by day, weeks, or even by months to assess marketing strategies) in Google Analytics. By use of Data Science, we can go one step further by using this data for making helpful predictions. Below is a simple visualisation of “time-series” analysis done with Microsoft Power BI (It can be done by Python language and other data science tools):

Time Series Forecasting to Analyse Keyword Search Volume
Figure 2: Time Series Forecasting to Analyse Keyword Search Volume

Benefits For Content Marketing Efforts

We can reveal the weakness of keyword research by applying predictive time-series forecasting to analyse search queries during specific seasons. It helps in predicting where the content might underperform as compared to market competitors. Data scientists and marketing teams can work together to improve the content based on insights gained from data. The same approach can be applied to social media or any other type of content. By SEO Forecasting, we can make predictions like future traffic levels and prospective value of that traffic by learning past data. This helps in allocating resources, prioritising SEO efforts and making suitable adjustments ahead of the compeititon. In a nutshell, time-series forecasting can be used to predict anything having historical data.

Social Media Content Sentiment Analysis for Reputation Management

How does it work?

Sentiment analysis is a machine learning technique that can be used by many businesses to identify user feedback and extract sentiments from it. Gone are the days when the marketing team had to go through every message, comment, or reaction to identify what the users are thinking about the product. Machine learning algorithms like SVM (Support Vector Machine), Decision Trees, Naive-Bayes, etc can conduct sentiment analysis very quickly and effectively.

How can it be applied To Content Marketing?

For example, we can use the Naive-Bayes method to categorise predefined words into different sentiment groups – positive, negative, and neutral – and assign values to them.

Social Media Content Sentiment Analysis
Figure 3: Social Media Content Sentiment Analysis

Below are some examples of the most common words used in sentiment analysis.

Positive words (value “+1”): Brilliant, fabulous, awesome, great, premium, fantastic, satisfied, wow.

Negative words (value “-1”): Poor, sad, terrible, boring, waste, annoying, worst.

Neutral words (value “0”): Okay, normal, fair.

Machine learning is the quickest way to assess tons of social media content within minutes to find about public sentiments. A data scientist can help to make a detailed report on the impact of social media content being produced by companies. The sentiment insights provide the opportunity to adjust digital strategies and find new ways to increase brand recognition on social media platforms.

Benefits For Content Marketing Efforts

Reputation management is an integral part of content marketing and businesses are using different emotion-based content strategies (one of them is brand storytelling to improve reputation) to achieve brand-related goals. Marketing teams can assess the performance of the different types of content by understanding the opinions and feedback given by the niche-specific audience.

Effective Customer Segmentation by Data Analytics

How does it work?

Customer segmentation is among the most essential marketing methods for making content more impactful, relevant and engaging for potential audiences. It gives businesses the opportunity to segment their audience using important indicators like purchasing patterns, website behaviour, age-wise geographical location, touchpoint engagement, etc. Segments are also created based on interests, spending habits and needs. These groups might overlap in most cases and this overlapping eventually allows marketers to create advertisements that fulfil the needs of different segments.

Customer Segmentation in Banking
Figure 4: Customer Segmentation in Banking

There is where machine learning algorithms come in handy.  They can help marketing teams to speed up this process and also define more data-driven precise categories of customers. A machine learning engineer or data scientist can use state-of-the-art algorithms to predict the segment of a particular customer group according to their similarities in behavior and habits.

How can it be applied To Content Marketing?

When it comes to content marketing, customer segmentation can be a powerful tool. By dividing your audience into subgroups based on shared characteristics, you can create more targeted and effective content. For example, if you sell products for both home and office use, you might target your content differently to each segment. Customers who are buying for their home office might be interested in content that helps them boost productivity, while those who are buying for their personal office might be more interested in stylish products that fit their décor. By understanding the needs of each segment, you can create content that is more likely to resonate with your audience. In turn, this can lead to higher engagement rates and more conversions.

Benefits For Content Marketing Efforts

Segmenting customers can provide a number of benefits, including a better understanding of customer needs, improved customer service, and more targeted marketing campaigns. By segmenting customers, businesses can create content with distinct customer profiles that allow them to meet their unique needs and challenges. Marketing teams can create targeted campaigns to resonate with and convert specific segment of customers. Additionally, it can help businesses to increase customer loyalty with customised content. Ultimately, customer segmentation is an essential tool for any business looking to improve its customer relationships and boost its bottom line.

So, what does this mean for content marketers? Simply put, it means that in order to be successful you need to make sure your data-driven strategies are underpinning your content marketing efforts. This includes using time-series forecasting to better predict SEO results, sentiment analysis to determine how customers feel about your brand on social media, and effective customer segmentation so you can target the right people with the right content. Digital marketing teams can also use the above insights to optimise their content and make it more relevant for their customers. If you need help with your marketing strategy, contact us today!

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