Modern digital marketers have a wide range of powerful tools and practices at their disposal that can make them more effective than ever before.
But there is one practice that can be a real game-changer: big data analytics.
The constantly growing number of marketing tools has created numerous opportunities for growth, but it’s also brought challenges for marketers.
Collecting data from all these sources and keeping them up-to-date is a significant challenge for marketing professionals in companies of all sizes and industries. Without proper data management, marketers must rely on less precise methods to determine what's working and what's not in their campaigns.
However, if you manage to tame this data beast and create a centralized repository of information from all your marketing channels, you'll be taking the first step towards enjoying the benefits of big data analytics.
With the help of augmented analytics and data aggregation tools, you can uncover new insights, add value to your clients and your business, enhance your creativity, and gain the proactive data-driven marketing approach that will put you ahead of the competition.
In this article, we’ve highlighted four ways you can use big data to optimize your marketing activities. But first, let's take a moment to define what big data analytics really means in the context of marketing.
What is big data analytics?
Before we dive into the ways big data analytics can transform your marketing, it's important to understand the distinction between big data analytics and traditional data analytics.
Traditional data analytics typically relies on structured data, which is organized and easily searchable within databases. While this type of analysis can provide valuable insights, it has limitations in terms of the volume, variety, and velocity of data it can process.
On the other hand, big data analytics goes beyond structured data and unlocks the power of unstructured and semi-structured data as well. Unstructured data includes information from sources such as social media posts, customer reviews, and video content - whereas semi-structured data includes information from emails, web pages and XML.
By using data aggregation tools to consolidate big data, marketers can analyze vast amounts of structured, unstructured and semi-structured data in real-time, uncovering deeper insights and patterns that traditional analytics might miss.
One powerful example of big data analytics in action is the approach taken by the Philadelphia 76ers.
They used Adverity as their data aggregation tool to consolidate structured, unstructured and semi-structured data from more than 130 different sources, to help them build predictive models for stadium attendance.
Harness big data analytics to create highly targeted campaigns
Successful marketing campaigns rely on accurate, high-quality, and timely data. Insights from this data are essential to create ads that will reach the right customers with the right offer at the right time, via the right channel, and with the most appropriate messaging.
This is where your big data becomes useful, providing each of the different facets you need to build an accurate picture of your target users and create customer micro-segments that you can reach with tailored and highly sophisticated campaigns.
Big data from various sources, such as advertising channels, customer data platforms (CDPs), and other tools, can provide in-depth insights into customer cohorts or specific customer profiles.
By analyzing and cross-referencing data on location, demographics, psychographics, and buying behavior, you can uncover valuable insights about different customer segments.
For instance, Carter's, a children's clothing company, used big data analysis to identify that a specific customer cohort in Chattanooga was particularly responsive to their marketing efforts at a certain point in time.
Based on this insight, they made a data-driven decision to allocate more advertising budget to that region, targeting their most receptive audience and driving improvements in marketing performance.
This is a great example of how big data analytics enables you to create highly targeted micro-segments and tailor your marketing messages to resonate with each group, significantly improving the effectiveness of your targeted campaigns.
To achieve this level of targeting, you need to integrate marketing data from multiple sources, such as ad servers, online and offline advertising reporting platforms, web analytics, and app analytics.
Data aggregation tools play a crucial role in this process, allowing you to collect, harmonize, and analyze vast amounts of structured and unstructured data from your disparate sources and load it into a centralized location.
By consolidating this data into a centralized marketing reporting or business intelligence tool, you can unlock the power of big data analytics to gain actionable insights and optimize your campaigns for the best possible marketing ROI.
Enhance content marketing with data-driven insights
The second advantage you gain by utilizing aggregated big data from various marketing sources is the ability to create better content for your content marketing efforts.
This data gives you a detailed understanding of how different customer segments and cohorts engage with the content you produce, which platform they prefer to use, and how long they spend reading, watching, or listening to your content.
These insights can inform your content marketing strategy, allowing you to create targeted, relevant, and valuable content that addresses their needs and preferences.
Content marketing is a fine art involving intricate nuances to copy tone, style and messaging, image size and positioning, and video length.
There are many reasons why particular content resonates with particular customer segments at particular times. Some demographics will prefer to watch a short video, while others will make time to take in long-form copy, such as an opinion article, a brochure, or a whitepaper.
By leveraging big data analytics and data aggregation tools, you can discover which of your prospects you need to target with specific content.
This data can help you optimize your content creation and distribution efforts, ensuring that your content reaches the right people at the right time, ultimately improving customer engagement and conversions.
Improve your A/B testing with the power of big data
Another marketing activity that big data can transform is A/B testing.
While A/B testing of websites and landing pages is fairly commonplace and offers business benefits, the results are often one-dimensional - simply identifying a winner and a loser from the tests.
However, by using big data analytics, you can combine multiple first-party data sources to gain a deeper understanding of why specific results occurred.
First-party data is information that you collect directly from your audience, which includes data from your website, app, CRM, social media, or surveys. This data is more valuable and relevant than third-party data - especially considering the upcoming changes to third-party cookies.
For example, you can go beyond surface-level insights by combining data from your CRM system (demographics, interests preferences, and interactions) and your eCommerce platform (purchases, and lifetime value) with your A/B tests.
This enables you to understand which specific customer segments are responding better to each variation in your A/B test and what actions they are taking.
Using this more comprehensive data-driven approach to A/B testing, you can make more informed decisions and optimize your website and landing pages for maximum impact.
Taking things a step further, you could potentially segment your A/B testing audience based on various factors like demographics, behavior, or lifetime value.
By tailoring your tests to these specific groups, you're able to deliver more relevant content — leading to stronger engagement and improved marketing performance.
In addition to website tests, data-driven A/B testing can be applied to various other marketing elements, such as email campaigns, banner ads, newsletter sign-ups, site searches, social media engagement, and mobile CTAs.
As you conduct more tests and gather more first-party data, you can refine your marketing activity, ensuring that you are delivering the most effective messaging and user experience to your audience while respecting their privacy.
Achieve higher ROI with the help of AI
As mentioned above, highly targeted marketing campaigns require having a lot of insightful information about prospective customers.
But since we’re talking about vast amounts of data, it’s sometimes not so easy to get a grasp of its potential and see individual opportunities in a pile of raw data.
Artificial intelligence can really take things to a new level in terms of analyzing the data and suggesting how to create the right marketing asset or a targeted ad for the right person.
Machine learning is a field of AI that applies algorithms to big data to discover patterns and insights. For marketers, this means they can harness the power of all the data at their disposal and focus on interactive charts and dashboards that provide suggestions and ideas on how to improve campaigns rather than wasting time sifting through numbers.
AI also enables marketers to access predictive analytics and scenario analysis, aiding better decision-making to improve marketing ROI.
Predictive analytics uses big data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data. This allows marketers to anticipate customer behavior, preferences, and trends, enabling them to make more proactive optimizations.
By combining the power of AI, machine learning, and data aggregation tools, marketers can make smarter, faster, and more data-driven decisions that lead to improved marketing performance and business growth.
Big data analytics brings new opportunities for marketers
Big data analytics enables modern digital marketers to bring greater value to their businesses than was previously possible through targeted campaigns, better content, improved A/B testing, and, ultimately, more profitable campaigns and activities.
Armed with insights from big data, marketers can create more sophisticated campaigns, offers, and communications. Through automation, they can tailor them to hundreds or even thousands of customer micro-segments, thereby significantly improving their marketing ROI.
However, before achieving this, you need to get all the data into a single location, harmonize it, and make it ready to be analyzed.
And for this, you need a market-leading data aggregation tool, such as Adverity.
Find out how Adverity can help you with big data
Adverity is a market-leading data integration platform that empowers marketers to harness the full potential of their data.
With connections to more than 600 different marketing data sources, Adverity can seamlessly integrate all your business data, including structured, semi-structured, and unstructured data.
This versatility makes Adverity the ideal data aggregation tool for your big data analytics needs.
To see how Adverity can help you unlock the full potential of big data, book a demo today.
