You collaborate with your team, strategize your goals, develop your message, and launch that stellar new campaign – and it flops. Lead generation is inconsistent, the sales funnel isn’t converting, but you can’t find the missing link. That is, until you incorporate the crystal ball known as predictive marketing into your design.
What Is Predictive Analytics in Marketing?
Predictive analytics in marketing is an advanced method of inferring what might happen next in a customer journey or ad campaign based on dating mining and machine learning. This growing field – which is expanding at a rate of 23.2% year over year – uses vast amounts of data and massive computing power to make predictions about future outcomes.
Many people confuse predictive analytics and machine learning, but machine learning is actually a tool used within the process of predictive analytics. Simply put, predictive analytics is a type of data-driven marketing that analyzes vast amounts of historical data to make predictions about future outcomes and answer the hypothetical question, “What might happen next?”
Sounds like a marketing home run, right? Who wouldn’t want a glimpse into the future performance and problems your brand might face? The tools exist, machine learning and AI in marketing are up for the challenge, but many brands still aren’t convinced that predictive analytics could enhance their marketing. Why? Because they’ve been let down by inaccurate results in the past.
The Importance of an Accurate Predictive Analytics Solution
A predictive analytics model is only as good as the data it collects, so if a brand can’t access, organize, and analyze a large enough quantity of high-quality data, its insights are worthless. What’s more, inaccurate predictive marketing could lead to giant advertising missteps and cost a brand thousands of dollars in ineffective campaigns.
The trick is to find and implement a robust predictive marketing analytics platform that offers massive computing power, utilizes new developments in machine learning marketing, and harnesses machine learning and artificial intelligence to generate accurate insights. When a predictive marketing solution works, the benefits are enormous and the results are undeniable. Let’s take a closer look.
The Benefits of Predictive Analytics in Marketing
Many of us have received a call or text from our bank asking us to verify a recent transaction. We take these interactions for granted, but banks are only able to offer such a streamlined process because their marketing analytics model is working properly: The model noticed an abnormality in our purchasing patterns, flagged the transaction for potential fraud, and notified us to double check. We simply reply yes or no, and our funds are secured. The day moves on, our trust in our bank grows, and everyone is happy.
Nearly every industry now relies on predictive analytics to forecast trends and behaviors with a high level of precision. For example, the hospitality sector uses predictive marketing to determine future staffing needs, and manufacturers depend on the “what might happen?” nature of the model to prevent malfunctions in the production process. Marketers are using predictive analytics to gain richer insights about their audience and how to effectively target them in an increasingly competitive global market.
How Marketers Use Predictive Analytics
In a highly competitive global market, predictive analytics can give brands a significant advantage in understanding consumers, making future decisions, and recognizing patterns:
- Decision Trees – A predictive analytics model can assist your brand in developing decision trees, or maps of every potential customer choice and the impact of those choices on your company.
- Regression Analysis – Predictive analytics insights can help your business identify correlations between variables, like how a product price increase might affect sales.
- Neural Networks – Machine learning in predictive analytics can create neural networks for your brand. Neural networks identify patterns within complex data sets and can be used to validate the accuracy of regression analytics and decision trees.
Create Your Own Predictive Analytics Workflow
Wondering how to put predictive analytics in marketing to work for your brand? Follow these four steps to start the process:
01.
Identify Your Needs:
Like most marketing strategies, good predictive analytics begin with identifying your goals and needs. Does your business need increased fraud detection, better quality control insights, or something else? Knowing what types of problems you’d like to solve with your predictive analytics model will help you choose the best solution.
02.
Gather & Organize Your Data:
As we mentioned above, predictive analytics in marketing only works if your data set is large enough and gathered from high-quality sources. Recognize the data flows your brand has access to, organize that data into workable sets, and find a reliable storage location to house this massive collection of information.Like most marketing strategies, good predictive analytics begin with identifying your goals and needs. Does your business need increased fraud detection, better quality control insights, or something else? Knowing what types of problems you’d like to solve with your predictive analytics model will help you choose the best solution.
03.
Choose Your Predictive Analytics Model:
Whether you partner with a marketing agency like Leap Group or incorporate an analytics model on your own, you’ll still need to make a decision about which predictive analytics solution will meet your needs and give you the most accurate, data-driven results. Choosing a robust solution like humanView (discussed below) is the best way to ensure top performance.
04.
Validate Your Results:
Determine the accuracy of your model’s results through data splitting, cross-validation, and select evaluation metrics. If any errors are found, adjust your model accordingly and retest until acceptable results are achieved.
Leap Group’s Predictive Analytics Solution: humanView
Does your company need predictive analytics to better target audience segments, optimize campaigns, and effectively prioritize leads? To give our clients a competitive advantage in this world of data-driven marketing, Leap Group developed humanView, our proprietary predictive modeling solution. humanView can clean and enrich first-person data, gather and analyze online consumer reviews, and give you greater insights into lead lists. More specifically, humanView can be used to:
- Clean & enrich Data: humanView can scrub massive amounts of first-party data and add up to 1,000 different demographic and psychographic variables, giving brands a comprehensive knowledge about their customers.
- Review Data: humanView can read through thousands of consumer reviews on the web to gather, organize, and summarize what other consumers are saying about your brand, product, or service.
- Lead Insights: humanView can synthesize information about your lead list to give valuable insights on how to effectively engage with them.
Without a doubt, a comprehensive predictive analytics solution like humanView could revolutionize your company’s efficiency, growth, and revenue. If you’re ready to learn how Leap Group’s signature predictive analytics model can give your brand the edge it deserves, contact our team to schedule a demo today.
