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Pattern Mining: Increase Conversions by Predicting Your Consumer Behaviour

Mohammad Farooq | Jul 17, 2017 93 views No Comments

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Thanks to smartphones, tablets and other portable devices, mobile commerce, also referred to as m-commerce, is transforming the e-commerce industry as we know it.  And as these mobile devices become more and more powerful, consumers will increasingly rely on them to make their purchases.   This spells tremendous opportunity for advertisers and marketers since new technologies can track these types of transactions and subsequently provide valuable insight into consumer behavior and buying patterns if the data is utilized properly.

The Buyer Process

There are five steps consumers follow – mostly unconsciously – when making a purchase:

  • Problem recognition

  • Information search

  • Evaluation of alternatives

  • Purchase

  • Post purchase evaluation

Savvy marketers know that they can impact decisions at each stage of this buying process, simply by understanding patterns in consumer behavior. This insightful piece on

how to serve customers better using social metrics

shares details on how marketers are doing just that.  The key is to know exactly what impacts changes in purchase behavior.  

Understanding Pattern Mining

Pattern mining is the process of gathering information that can help businesses identify and monitor useful consumer patterns.  Two types of consumer patterns that every m-commerce business should care about are customer moving patterns and purchase patterns.

  • Moving patterns are the steps a consumer takes to get to a particular website or store. For example, a consumer talks to their friend about a great new product, and then look online to find it. The progression of steps is the moving pattern.

  • Purchase patterns are common actions taken each time a person makes a purchase. For example, researching a product, searching for lower prices, and then buying the item.

By tracking both, companies gain insight as to what makes people purchase a specific product or service.

For example, by using pattern mining, a business may identify that when people receive a coupon or discount on their mobile devices, they are more likely to make a purchase right then and there, as opposed to saving items in their shopping cart and purchasing at a later date. Tracking and storing this information is the key component of the m-commerce pattern mining process.  

Understanding Data Prediction

Data prediction, also known as

predictive analysis, utilizes the information collected by pattern mining

to help marketers understand what a consumer’s next move will be during each stage of the buyer’s process.  Having access to this type of information can help marketers fine tune messaging, possible incentives, and even color choices.

How Pattern Mining and Data Prediction Work Hand-in-Hand

Pattern mining and data prediction are best understood when you fully grasp how they work together. Let’s think about a person who wants to purchase a specific product.  When this person is ready to buy, what is the motivation behind the purchase?  Determining a buyer’s psychological mindset and then converting this information into a statistical format can reveal things like:

  • How someone feels, reasons, thinks and chooses between options

  • How environment influences decisions

  • Consumer behavior while shopping

For example, was there a specific word, button, ad or other factor that led to a consumer choosing one product over another?  Once that question has been answered, this information can then be used in the future to direct customer purchases in a more effective manner. Analyzing information itself requires an able set of eyes who can get that insight and a

comprehensive data scientist training

is helpful.

Applying Consumer Behavior to Advertising Campaigns and Marketing Strategies

Pattern mining and data prediction provide businesses with a more in-depth look at consumer behavior. With this information, more laser-targeted advertising and marketing campaigns can be created.

For example, knowing that children are more receptive to food advertising when they are hungry, a snack company may tweak advertisements so that they only run during afterschool hours. A beer company may choose to only run their advertisements during evening hours and weekends when their target demographic is least likely to be working. Pattern mining helps build a clear strategy that helps in conversion and retention.

The Bottom Line

In the past, businesses were stuck simply trying to guess consumer buying patterns based on the limited information that was available.  But now, thanks to the power of pattern mining and data prediction, marketers and advertisers alike can truly “get into the minds” of their target audience and strategically launch campaigns that deliver ROI’s like we’ve never seen before.  As the old saying goes, “knowledge is power,” and nowhere is this phrase more relevant than in the world of m-commerce.

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