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What is Machine Learning and How to Leverage it for Marketing

Today, marketing tools such as marketing automation completely saturate the business world. A different platform seems to advertise the latest gadgets and gizmos full of data-driven solutions every day. One potential link between automation and results is machine learning.

 

The Problem

 

Take this example. One use of marketing automation is audience segmentation. Marketing automation systems can take CRM data and place consumers into various categories based on characteristics such as demographics, taste preferences and online behavioral patterns.

 

However, the segmentation categories are predetermined by the marketer. If the marketer selects geographic location as a focal point, the CRM system will respond by segmenting the data based on this characteristic. Audience segmentation is based on human assumptions of what’s important. This leaves room for poor assumptions to be made, assumptions that can often omit an important component of the bigger picture.

 

Machine learning could very well be the solution to this problem.

 

The Solution

 

So what is machine learning? Machine learning “can look at a full set of a customer datapoints, identify patterns and organize it into ‘clusters’ of similar data,” according to ClickZ. Machine learning is valuable in that it disregards what a human marketer predetermines as important. It takes the whole data set into account and determines categories based on its analysis, rather than picking a category and seeking out the data that would support it.

 

Another benefit to machine learning is real time responses. Machine learning can help predict the best time to engage with a buyer based on behavioral patterns. For example, machine learning may determine that someone who has visited your site and has added specific items to their cart is three times as likely to purchase. Marketing automation could then be used to send this customer a promotional email in order to encourage them to complete the purchase.

 

A third example is churn prediction. This is a model that’s based on an algorithm that analyzes new customers in comparison to those already existing. In essence, this algorithm predicts that if an existing customer similar to the new has “churned” in the past, the new customer is likely to churn as well. Once again, the entire data set is taken into consideration, so categories that a human marketer may have disregarded will be considered.

 

Lastly, machine learning allows for a more tailored approach to outreach. Customers today interact with a business across various channels. It’s crucial that a customer’s experience is personally tailored throughout every step of the purchasing process. Machine learning enables this by recognizing patterns that a human marketer may not extract from a data set, and better yet at faster speeds. Machine learning identifies segments within larger segments that a marketer may never recognize or even have time to care about if they did.

 

Increased creativity

 

Ultimately, only marketers can create effective content that’s tailored to a consumer, but certain insights from machine learning can deliver added value. Machine learning can help with the nitty gritty work, freeing up time for more creative thinking on the part of marketers. Machine learning can open doors to categories you never knew existed, serving as the first step to a brilliant, new creative marketing campaign. When evaluating marketing software, the presence of machine learning should be taken into account in order to effectively evaluate all capabilities.

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