Predictive Analytics: Why should you use it?
We get asked quite frequently: Why should my company invest in predictive analytics? Why even bother? What can it do for us?
Great questions. Predictive Analytics, or predictive analysis, used to be a competitive advantage. All through the first part of the 2010s, companies used data science, predictive analytics, and machine learning to take their business intelligence (knowing what is happening inside the company right now) and turning it into what is going to happen in the future so we can plan for it before it happens. We call this moving up the data hierarchy. But somewhere in the middle of 2019, we saw a switch. As CAN took companies through our process to get them data-driven decision making, we realized companies weren’t using it for their competitive advantage anymore, they are using it to stay relevant.
Companies now are required to do more with less. They are required to stay relevant to their customers. They are required to know who their customers are and what they want-all before the customer does. Data intelligence is now so common in our lives, companies have to implement predictive analytics to even stay with (not ahead) of their customers.
Example: With technology developing so quickly, new ways to implement marketing strategies and more effectively reach consumers are popping up all the time. Predictive analytics is one such technique. Praised for its ability to inform companies of future trends and reveal important information, predictive analytics is growing in popularity, with 87 percent of B2B marketing leaders saying they had already implemented or were planning to implement predictive analytics in the coming 12 months.
So what is it? What is predictive analytics and how do you use it.
What Is Predictive Analytics?
Before fleshing out its benefits, it’s probably best to first explain what predictive analytics is. Predictive analytics is a process for collecting and analyzing current data using Business Intelligence, Machine Learning, and potentially AI.
How Can Predictive analytics Benefit Marketing and Sales?
- More Efficient Customer Acquisition
By providing your sales team with specific data, predictive analytics can allow them to acquire new customers and keep old ones more efficiently and with less cost. What journey do they take to purchase a product? What advertising do they respond to? What is it about your product/service that they enjoy the most? All these questions can be answered by analyzing previous data and drawing conclusions about future activity. This information can then be used to determine which customers to reach out and how best to appeal to them, saving time and money.
- Determine Up-sell Opportunities
Predictive analytics also assists in drawing conclusions about other aspects of your customers’ buying behavior. Through analytics, brands can better understand what their customers’ needs are and what exactly they’re looking for. This can then be used to tailor the sales and marketing strategy to specific customers.
For example, if you are a fashion brand and have customers who are in need of shoes, it would be inefficient and wasteful to send them an advertisement for a new shoe promotion. Instead, it would be better to send this to customers in need of footwear to maximize on profit.
- Optimize Marketing Strategy
Not only can predictive analytics benefit brands by helping to find information on customers, it can also help in regards to the market environment. You can learn what time of the year spending peaks, how much people are spending and what they’re spending their money on. This information can assist in the successful execution of marketing strategies by ensuring you are targeting the right people at the right time.
Or you can figure out where to score the most candy on Halloween as we did back in 2013 when we invented a dashboard to help trick-or-treaters. See, predictive analytics can be fun too.
Predictive analytics is an increasingly popular method for brands to more effectively initiate sales and marketing strategies. By providing detailed information about market trends and buying behavior, brands can cut costs, boost profit and increase overall efficiency.
