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How Predictive Analytics Will Change Digital Marketing in Coming Years

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Max Liul, Data Science Specialist
How predictive analytics will change digital marketing in coming years

The global predictive analytics market size is estimated at almost $12 billion in 2022 and expected to reach $27 billion in 2026. A growing number of businesses embrace elaborate tools designed to produce forecasts. These days, it is hard to overestimate the role of predictive analytics in digital marketing, as it provides invaluable insights into customers’ behavior.

Using predictive analytics marketing services and AI-driven tools, companies can make their marketing efforts more effective and increase ROI. Experienced and reliable technology partners such as Integrio Systems provide digital marketing software development services and AI development services to boost their efforts.

In this article, we will examine the key benefits of predictive analytics in digital marketing and advise how to build a custom marketing analytics dashboard. Read on to discover how you can enhance your business performance by leveraging predictive analytics tools.


What is Predictive Analytics

Predictive analytics is a method of processing large sets of statistical data with the help of modeling techniques to make predictions.

Artificial Intelligence technologies allow professionals to predict customer behavior and optimize marketing strategies, boosting their effectiveness. It makes the role of predictive analytics in marketing even more important.

Using predictive analytics tools powered by AI, ML, data mining, and data modeling technologies, companies increase their profits by minimizing their expenses. With the help of advanced algorithms and information from multiple data sources, digital marketing professionals can identify historical patterns. It allows them to provide recommendations that help companies to keep up with recent trends.

Keep reading if you are wondering “What is predictive analytics in marketing?” and how to make the most out of such tools.


Role of Predictive Analytics in Digital Marketing

So, how is predictive analytics used in digital marketing?”.The role of predictive analytics in marketing strategy becomes increasingly important. It transforms the way marketing professionals organize their campaigns and use customer behavior data.

AI-driven tools allow marketers to predict future trends and understand which products are in high demand. Predictive analytics enables professionals to change their marketing campaigns depending on the customer's reaction to ads.

Below, we have listed the use cases of predictive analytics in digital marketing.

  • Customer Behavior Analysis

    By analyzing how clients interact with products and services, digital marketers can segment a target audience, anticipate the behavior of various segments, and make their marketing efforts more effective. It allows companies to improve the client experience and establish long-term relationships with customers.

  • Resource Optimization

    Predictive analytics enables companies to select the most suitable time for their marketing campaigns and avoid wasting resources when the demand for the products is low. Besides, this type of analytics enables businesses to choose the most appropriate advertising channels.

  • High-Quality Leads

    After analyzing a set of data about customer behavior, a company can select the segments of the target audience that have the highest conversion rate. Predictive analytics enables businesses to see how likely their potential clients are to make a purchase. By focusing on high-conversion leads, companies can reduce their expenses on marketing campaigns.

  • Customer Retention

    By sending a generic message, a company may waste money on inefficient advertising campaigns. Predictive analytics allows marketers to study the purchase history of a consumer and launch targeted marketing campaigns based on customers’ preferences. It allows businesses to establish long-term relationships with their clients.


Benefits of Predictive Analytics in Digital Marketing

The most successful marketing campaigns are based on customer behavior data and thorough market research. Predictive analytics provides businesses with a cutting edge over their competitors and enables them to improve all the steps of a customer journey.

Below, we listed the main benefits of predictive analytics in digital marketing and demonstrated how it could be used for making advertising.

  • Improved Content Distribution

After analyzing the ways a target audience interacts with content, marketers can provide companies with tailored recommendations for each segment. Predictive analytics makes it easier to select a target audience, choose the best time for a marketing campaign, and decide on a promotion channel.

It provides invaluable insights into what types of content drive target customers to purchase a product. Using the key technologies of marketing data science, companies can provide content recommendations based on demography, location, and behavior patterns.

  • Upselling Based on Behavior Patterns

The role of predictive analytics in digital marketing is expected to increase as it enables companies to nurture leads and convert them into sales. Marketers analyze all the steps of a customer journey to find the touchpoints that require improvement. They use predictive analytics tools to categorize leads and target only the high-quality ones using the most suitable channels.

By making their efforts more targeted and analyzing the history of previous purchases, companies can improve their upselling and cross-selling rate.

  • Marketing Campaign Improvement

Using predictive analytics tools, companies can save money on advertising campaigns by making their efforts more targeted. The most successful campaigns rely on historical data and customer behavior stats.

  • Development of Efficient Advertising Strategies

By analyzing the way people interact with a site and what content they find interesting, companies can prioritize pages with the highest conversion rate. Customer behavior data helps businesses maximize their ROI.


6 Steps to Build Custom Marketing Analytics Dashboard

In the future, predictive analytics and digital marketing are expected to be closely intertwined. To add value to their businesses, professionals use custom marketing analytics dashboards. It allows them to keep all the insights in one place.

Using a marketing analytics dashboard, companies can see which campaigns deliver better results. It enables them to get data on the devices that customers use to access a website and features that have the highest engagement rate.

The most important trend in predictive analytics involves using a marketing dashboard for analyzing KPIs, organizing data from various sources, and evaluating ROI. Thanks to it, companies can make better decisions and promote their products more effectively.

Follow the steps described below to build an efficient custom marketing analytics dashboard.

  • Find Out Who Are Your Target Customers

    Predictive analytics dashboards and AI-based data visualization tools allow you to learn more about a specific group of clients and use this information to improve the KPIs of your campaigns. Companies should use different dashboards for different target audiences.

    For B2B marketing, such dashboards are crucial as well since they allow businesses to get access to all performance metrics. Digital marketing specialists who specialize in social media marketing can use analytics dashboards to see relevant metrics for different channels.

  • Set Objectives for Each Dashboard

    Companies should set clear short-term and long-term goals. Top-level managers might need to use a dashboard that summarizes information about a budget and ROI. Marketing professionals will benefit from using a dashboard with insights that can help them improve their campaigns.

    The data available in a dashboard should make it clear what actions should be taken immediately. It should also demonstrate which areas require improvement and how to make planning more efficient.

  • Determine the KPIs of Your Strategy

    When developing a marketing strategy, it’s crucial to select the most relevant metrics, such as likes, clicks, traffic, conversions, etc. Additionally, companies can analyze the date when the information was received and the sources of data. By using different performance indicators, companies can make each marketing campaign more successful.

  • Use Information About Data Sources

    To improve their campaigns, companies use multiple data sources, including calls, emails, or website data. Each of them has specific metrics that marketing professionals should analyze.

  • Perform Data Visualization

    Don’t underestimate the power of proper visualization tools: graphs, charts, and maps. They provide an accessible way to discover trends, patterns, and outliers. By visualizing data, marketers can get more insights for improving their campaigns.

  • Consolidate Data

    As marketers have to deal with large sets of data, it is important to find a way to consolidate it and combine information from different sources. It will allow you to predict the results of your campaigns and ROI.


Consider Integrio Your Trusted Partner

Integrio Systems has been working in the software development industry for 20 years. In particular, it provides AI-based solutions for digital marketing to help companies scale up their businesses. Our company has teams in Canada, Poland, and Ukraine.

BioNimbus

From 2014 to 2015, the company worked together with Cascade Strategies to improve the accuracy of an AI-driven solution called BioNimbus. It was built for conducting consumer behavior analysis at an advanced level. The project's goal was to make the VR experience more immersive by using data obtained from neural activity scans.

The project relied on the analysis of biometric data and the way it drives consumers to make a decision. What makes BioNimbus one of the best examples of predictive analytics is that it collects eye-tracking, GPS, and EEG data to track emotional excitement and brain activity. It allows companies to see what interests customers the most.

Thanks to BioNimbus, many top brands, including Nike and Disney, made their marketing strategies more effective and increased their profits.

Mobiry

Another project that demonstrated the powerful impact of predictive analytics on digital marketing was a solution called Mobiry. It relies on ML algorithms, AI-driven A/B testing, and a segmentation engine to make predictions about purchases. Mobiry will come in handy to companies that specialize in omnichannel sales. It is used by CPGs and restaurants to increase their profits and ROI.

Integrio Systems developed this solution from scratch. Mobiry consolidates data from multiple sources and provides companies with recommendations based on customer behavior patterns. It accurately predicts purchase frequency and allows businesses to minimize dropout risks. This SaaS solution comes with innovative features that allow large retail companies to increase their revenue.

Get in touch with Integrio Systems if you need to create an advanced solution making predictions based on customer data!

Integrio Systems

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How Predictive Analytics Will Change Digital Marketing in Coming Years What is Predictive Analytics? Role of Predictive Analytics in Digital Marketing Benefits of Predictive Analytics in Digital Marketing 6 Steps to Build Custom Marketing Analytics Dashboard Consider Integrio Systems as Your Trusted Partner FAQ

FAQ

Predictive analytics in digital marketing makes it easier for businesses to foresee the results of their marketing campaigns and use customer behavior data to quickly improve their ads. It allows them to make their message more targeted. By creating personalized offers, companies can boost customer engagement rates.

Marketing campaigns will become more personalized due to the increased usage of AI-driven tools for analyzing large bulks of data and predictive marketing analytics dashboards. The usage of social media platforms as promotion channels is going to increase as well.

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