There are many use cases for big data analysis, ranging from simple tasks to solving problems on a global scale by analyzing patterns of human behavior and proposing more meaningful solutions. In addition to the opportunity to fight world hunger, water scarcity, and pollution, big data also offers good results on a simpler level.
It helps marketers create more powerful advertising strategies, automate routine tasks, and gain more insight into customer expectations and needs.
This article explains how big data improves email marketing and helps marketers get better ROI from their email campaigns.
Generate Product Suggestions
Most modern customers are already used to data-driven product recommendation systems. The mechanisms of their work are quite simple. An artificial intelligence algorithm analyzes users’ behavior patterns, takes into account their purchases and browsing history, compares this data with the behavior of users of the same target group, and draws conclusions about the products that can attract this customer.
Such a simple algorithm is a treasure trove for product promotion emails as it kills multiple birds with one stone. First, recommendations based on artificial intelligence are highly personalized and more relevant, and second, such a recommendation is fully automated. Consequently, with such a marketing tool for your business, you can get a better ROI on email marketing while increasing sales.
Automate Repeatable Email Chains
Although most email marketing campaigns are designed to be as customized as possible, most of them are repetitive. For example, following today’s email marketing best practices, brands send thank-you letters after users place an order, chains of welcome letters to new subscribers, order confirmation emails, and other newsletters tailored to a specific behavior.
The use of big data and special e-mail marketing solutions enables these processes to be automated at the highest level and reduces operating costs. This allows marketers to avoid repetitive tasks and human error while achieving better ROI at a lower cost.
Help with user segmentation
This is another use case where big data helps make email letters as personal as possible. With AI-based email tools, a marketer can segment the audience and create more relevant letters for each of the user groups. For example, big data and AI can automatically segment users based on age, location, preferences, creditworthiness, customer lifecycle, and other important factors. Advanced tools can also be used to set up very individual campaigns for the individual user segments.
Identification of key performance Metrics
Identifying and analyzing performance metrics is one of the most important tasks that big data and artificial intelligence help with in email marketing. Most dedicated tools offer the ability to create customized reports, collect performance data for a specific period of time, analyze trends and patterns, and depending on the identified KPIs, suggest possible errors or campaign deficiencies.
For example, most data-driven email marketing solutions can help automatically calculate the open rate, click-through rate, percentage of letters delivered and deleted, conversion rate, how long users stay on the website, and more.
Contribute to the collection of data-driven information
In addition to big data and artificial intelligence that help create better-tailored chains and campaigns, the data analytics process gives marketers the opportunity to discover and delve into user behavior patterns.
Furthermore, the scope of discernible patterns is not limited to how users interact with your letters, but also what designs, calls to action, products, and graphics suit them best. But also their behavior beyond the interaction with your brand.
Thanks to the analysis of Big Data, it becomes possible, for example, to predict sales trends and peaks, identify specific preferences of users based on their behavior on social media, suggest the advantageous price for each segment of users, and so on.
The importance of big data analysis for your digital marketing strategy
What exactly is big data? According to InfoWorld, big data is characterized by the three Vs:
- An extreme volume of data
- A wide variety of data types
- The speed at which the data must be processed and analyzed
Analyzing the data gives meaning to the collected data. Without analytics, where data is examined to identify patterns, correlations, insights, and trends, data is just a collection of ones and zeros with limited business value. By applying analytics to big data, companies can achieve benefits such as improved customer service, greater efficiency, increased sales, and an overall increase in competitiveness. Data analysis involves examining datasets to obtain detailed information or draw conclusions about the content, e.g. B. Predictions about future activities and trends.
By analyzing the information stored in data lakes using big data analytics tools, organizations can make more informed business decisions such as B. when and where to run a marketing campaign or launch a new product or service. Analysis can relate to basic business intelligence applications or to more advanced predictive analytics such as those used by academic organizations. Through data management and technologies like machine learning, companies can unleash enormous potential.
The more advanced analysis includes data mining, in which analysts examine large data sets to identify relationships, patterns, and trends. Analysts often rely on open source data, to large datasets available to you, me, or anyone with an internet connection.
Data analysis can include both exploratory data analysis (to identify patterns and relationships in the data) and confirmatory data analysis (the application of statistical techniques to determine whether a hypothesis about a particular data set is correct). Another distinction is quantitative data analysis (or numerical data analysis with quantifiable variables that can be statistically compared) as opposed to qualitative data analysis (which focuses on non-numerical data such as videos, images, and text).
How can analytics improve your marketing strategy?
Data analytics can provide a detailed analysis of the latest trends in customer behavior with a high degree of accuracy, including all sub-groups such as gender, age, geographic location, etc. This allows marketers to tailor their strategies to target each of these groups differently.
The future of email marketing 2023
While trends come and go, the evidence suggests that email marketing will be around for a while yet. The use of email marketing is expected to continue to grow in 2022 and beyond. As the digital world continues to grow, so does the need for digital communication.
What is the role of big data in marketing digital marketing?
Insights from big data help create more effective targeted ads. Companies that want to do online marketing use third-party sources to show ads to users. This, in turn, helps to increase brand awareness, and revenue through increased sales and ultimately brand loyalty.
The list of use cases for big data in marketing channels is endless. The main task it performs is to discover user behavior patterns by analyzing the data they generate when they interact with the brand, thus providing marketers with more valid ideas on successful marketing strategies. When it comes to email marketing, Big Data solutions are also great for automation, saving you time and money. So feel free to use it for advertising your brand.