With an estimated market size of approximately $12 billion in 2022 and expected to reach a phenomenal $27 billion in 2026, predictive analytics plays an immense role in digital marketing and offers invaluable insights into customers’ behavior.
From helping marketers analyze insights from historical trends and patterns to personalizing marketing campaigns, predictive modeling can be instrumental in strengthening a marketer's personalized marketing efforts and enabling them to foresee potential outcomes.
In this post, we will explore predictive analytics in more detail and discuss its role in defining the success of personalized marketing efforts.
What Is Predictive Analytics?
Predictive analytics refers to a method of processing massive data sets using a range of modeling techniques to be able to make accurate predictions.
Artificial intelligence technologies used in predictive analytics allow data professionals to make predictions about aspects such as customer behavior and accordingly optimize their marketing strategies for better success rates in their respective campaigns.
Put simply, predictive analytics is the process of leveraging information or raw data to forecast future outcomes accurately. This detailed process uses a range of different techniques, including machine learning, data analysis, artificial intelligence, and various statistical models, to find patterns that help predict future behavior.
Different Ways Predictive Analytics Help in Personalized Marketing
Here are some of the ways predictive analytics can help marketers make their campaigns more personalized:
1. Better Understanding of Consumer Behavior
Predictive analytics can be a valuable tool for marketers to gain valuable insights from customer preferences and behavior.
Marketers can analyze browsing data, purchase history, and other similar data points to segregate/segment customers into various groups and identify specific customer segments. This allows them to target the right set of audiences for personalized marketing campaigns.
2. Personalizing Content
By accurately predicting customer behavior and designing useful statistical models based on that data, marketers can tailor their content to target specific audiences.
This kind of predictive analytics in marketing helps them understand exactly which type of content works better for a certain set of customers so that they can target the right audience at the right time for optimal results.
3. Building Targeted Promotional Campaigns
After customer segmentation, marketers can design tailored marketing campaigns for specific target audiences to cater to that set of customers only. Marketers can also use predictive analytics techniques to predict a customer's likelihood of making the purchase of personalized products based on aspects such as past browsing history and individual product preferences.
Real-World Examples of How Personalization Is Changing Trends
There are several predictive analytics examples in the real world in various applications and insights.
Some of these are discussed below:
1. Amazon
Amazon is a global brand that uses predictive analytics techniques for product recommendations.
Whether a customer puts a product in the cart or simply browses through it, the brand uses that data to learn customer likes and preferences and recommend similar products to them in the future. This is how the company earns over 35% of its annual sales.
2. Netflix
Netflix is one of the biggest online platforms for streaming the latest movies and TV shows and a big part of its success goes to big data and predictive analytics.
Since the company knows its users, its retention rate is over 93%, which is a huge number compared to other players. The company is also growing rapidly because of its original movies and TV shows, which just show that it listens to its consumers.
3. Starbucks
Starbucks is another global brand that is using big data to create a better customer experience.
The company collects data by offering its customers Starbucks rewards programs and mobile apps, which help them learn and understand more about each customer's purchasing habits. The brand then uses this kind of data-driven marketing to recommend products to its loyal customer base, thus helping it create better marketing campaigns.
To Wrap Up
In today's business world full of data at every touchpoint, the ability to harness data appropriately and personalize customer experiences using techniques like predictive analytics is what sets businesses apart.
If you are looking to strengthen your personalized marketing efforts using predictive analytics, Contact us to know more!