How Behavioral Analytics Powers the Shopper Experience.

June 11, 2020

Have you ever wondered how Youtube consistently recommends videos that you love? Or how Spotify puts up playlists with songs you have never heard before but instantly become your new favorites? Or how Google keeps curating news feeds that are absolutely relevant to you? Or how Amazon keeps presenting you with products you can’t resist? Or …

The list goes on and on. This “on-point” recommendation phenomenon is powered by behavioral analytics.

What is Behavioral analytics ?

Behavioral analytics is a type of new analytics that reveals the behavior of users on eCommerce platforms.

Think of the millions and even billions of event data streams collected on your site – each click, download, or purchase – as steps in a powerful customer story that is waiting to be told.

Your job as a growing eCommerce or digital marketing business is to connect the different data points in your goal to understand customer behavior.

Why is Behavioral analytics important ?

Netflix the online movie platform is able to achieve lower cancellation by presenting its users a list of movies they are likely to enjoy this in turn saves the company billions of dollars.

Amazon on the other hand had its revenue exponentially increase by being able to recommend products that are likely to be bought by its users.

Both companies are able to provide a better user experience that saves time and delivers using behavioral analytics.

Behavioral analytics helps you analyze raw data collected over a specific time period, focusing on the entire customer journey rather than specific events frozen in time, as with traditional analytics. This helps you listen more carefully to the story your customer is telling you.

  • How can you turn first-time shoppers into loyal customers?
  • Do you know why shoppers purchased?
  • Is it because a business offers competitive prices, an attractive presentation of the right number of relevant items, or was it the targeted offers personalized to each shopper?

Answering these types of questions in the eCommerce arena can be done with the help of behavioral analytics.

As the marketing industry becomes more metrics-driven by the day, the need for advanced and fine-tuned web analytics and BI methods coupled with technologies to analyze the shopper experience is also increasing.

Specifically, behavioral analytics technology with insight and engagement engines gives businesses the ability to not only answer vital questions for business growth but to act on them, so you can engage with your shoppers in a deeper and more personal way than your competition.

Next let’s look into how engagement-engine methods such as NBOs ( Next Best Offers), and data-driven insights such as behavioral segmentation power the shopper experience in real-time.

Engagement Engines and Next Best Offers

Online shoppers are a fickle bunch – any combination of experiences can easily push them away from your site onto the site of your competitors.

How do you know when you’ve succeeded in engaging your shoppers with dynamic, personalized experience in real-time?

The real moment of truth is when a shopper adds a product to their cart, purchases, and then returns later to purchase on your site.

Turning these shoppers into loyal customers is what will make or break your eCommerce business.

One of the most popular and proven methods of engagement engines is a form of predictive analytics called “Next-Best-Offers,” or NBOs.

One example of an NBO that is probably quite familiar to you are called product affinity insights.

For example, Netflix presents customers with suggestions after purchasing a movie, offering additional movies they might be interested in watching.

Amazons’ recommendation engine also uses these types of behavioral insights to suggest matching items to shoppers in real-time.

Here’s a less familiar but powerful example of behavioral path analysis. A well-known eCommerce site found that many of the visitors to the men’s department also shopped in the sports department, added products to their cart, and then continued to the hardware department.

Behavioral Analytics – Data-Driven Insights

Other valuable insights that drive engagement engines are those gathered by behavioral path analysis.

For example, a leading media publication used behavioral path analysis to learn that of readers who browsed political content, 13% of them continued to read entertainment, then sports, and finally the technology sections.

Engagement systems that guide a shopper through the customer journey must be powered by data-driven insights, and they must be delivered at the exact point that matters to the customer.

Today, these insight systems are able to provide quicker and more advanced insights than before.

Behavioral segmentation, for example, examines user actions over time to reveal patterns that provide insight into the present.

Real-time counters allow quick insights without having to wait for analysis.

Changes in Shopper Motivation

Customer engagement is also linked to the changes in shopper motivation: According to McKinsey’s research, while purchases are still driven by loyalty, they are driven even more by shopping.

McKinsey looked further into their findings to understand that even when shoppers switched brands, the brands in the initial consideration stage were more than twice as likely to be purchased as brands considered later in the shopper’s journey.

That means brands are still a consideration for shoppers, and it also means that first impressions are still important.

Businesses that deliver engaging shopper experiences will be more successful in becoming part of the shopper’s initial consideration.

Closing Thoughts

As we’ve mentioned, businesses need to collect the entire spectrum of customer data points in order to understand the complete story of their customer’s journey.

Additionally, as brand loyalty is weakening, it’s more important than ever to analyze that journey and be able to deliver an engaging experience to shoppers.

Behavioral analytics, specifically engagement and insight engines using methods like NBOs, are ways to power the shopper’s journey forward, personalize their experience in real-time, and go one step further in delivering customer engagement, an increasing challenge in the eCommerce world today.



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