Predictive analytics has matured into a must-have tool that helps companies leverage their data to focus marketing efforts.
It has an impressive effect on performance.
Predictive marketers exceed organizational goals twice as often as their less data-driven peers.
On a larger scale, their companies are three times more likely to experience revenue growth at rates higher than the industry average.
What’s behind results like these?
The incorporation of machine learning technology into the analytics cycle gives marketers the ability to focus their predictive analytics marketing strategy like never before.
Read on for some of the leading reasons marketers are turning to modern predictive analytics.
Demographics don’t tell the whole story.
Sometimes they’re actively misleading.
Cluster modelling groups customers by more accurate and useful factors than bare demographics, such as psychometric characteristics.
When better segmentation is combined with intelligent customer profiles, marketers have a clearer picture of who their users are and what motivates them.
Better lead scoring
Past customer performance offers direction as to which leads will bear fruit, but the reasons aren’t always obvious.
Predictive analytics sifts through available sales data to find commonalities among the highest performing customers, then creates a data-based scoring system to identify the most valuable leads.
The process can operate in reverse to decide whether a particular client merits extra sales attention.
Probability-based customer behavior mapping
Understanding customer behavior highlights the places where marketing and sales executives can influence their clients’ decisions.
Historical data on advertising response rates, purchasing patterns, social media engagement, online cart activity, and more can be run through machine learning algorithms to create a map of the typical buying journey.
These maps answer a lot of questions for marketers:
- What are the most common routes to purchase? (This is especially helpful for identifying the best channels for advertising campaigns.)
- How likely is any given customer to recommend the product on social media?
- How much time usually passes between purchases?
What is a customer’s potential lifetime value? What causes them to churn before realizing that value?
Predictive analytics reduces churn by both identifying the areas where customers fall out of the buying journey and suggesting ways to resolve those pain points before the customer leaves.
More impactful campaigns
Knowing who the best customers are and what motivates them is a major asset.
One target audience might respond well to a series of humorous Twitter ads while another prefers coupon-rich emails.
Knowing this, marketers can create tailored campaigns to reach each buyer persona through the most relevant channels.
Personalization is not the only way predictive analytics guide market strategy.
The technique also tracks information such as transaction data, social media activity, and market conditions to measure the real-time demand for a product.
If the data indicates a potential new market (a competitor closing, population shifts, etc.), a company can position its assets to take advantage of the change.
When a customer drops something in their online cart that’s often bought with other items, those products can be suggested before checkout.
Predictive analytics reveal time-sensitive opportunities, too.
Simple examples include sending people who buy tickets to a concert in a distant city offers for nearby hotels, or suggesting celebratory drink specials after a local sports team wins a game.
These actions don’t need to be individually approved by a human; they’re triggered automatically when the predictive algorithm recognizes an opening.
Conventional marketing wisdom is that 80% of revenue comes from 20% of customers.
That leaves a company vulnerable to disruptions to that 20%.
With predictive analytics, the base of valuable customers expands to offer better profit and stability.
Are you ready to make make better, smarter decisions for your company? Contact Concepta to explore our business intelligence and data science offerings.