The Relation Between eCommerce and Consumer Behavior

The internet has transformed how we lead our lives, including how we socialize, spend our time, and shop. But as technology evolves, online shopping experiences also change. Sellers now use several metrics to determine consumer behavior to positively contribute to shopping experiences and customer retention.

By analyzing consumer behavior, sellers can improve shopping experiences to become competitive in eCommerce. A great consumer behavior analysis example is how eCommerce sites now use AI to suggest related products.

The importance of consumer behavior in eCommerce

Technologies like algorithms and AI that help determine consumer behavior benefit buyers and sellers. Consumer behavior data analysis means the buyer gets recommended products they are likely to add to their cart. On the other hand, this strategy can help the seller increase the average cart value and get a loyal customer base because of a smoother shopping experience. Your brand is able to gather which products or services are driving the most success when performing an analysis.

The next sections explore how a consumer buying behavior analysis has revolutionized eCommerce. In this article, you also learn how online sellers can conduct a customer behavior analysis to become more competitive in this already cut-throat world.

Consumer behavior eCommerce metrics

With today’s technologies, buyers have a range of tools at their disposal for the analysis of consumer behavior.

Metrics like click-through rates and open rates are old-school, but still in use. Now along with these simple metrics, advanced metrics also help track consumer behavior through simple platforms like Google Analytics. On the other hand, advanced SAAS platforms like Shopify also offer amazing consumer behavior analysis tools. Their automated consumer behavior reports for eCommerce websites also help improve seller analysis and in turn, their profitability.

Here are some metrics that you can track to assess your customer’s behavior:

• Average order value.
• Customer acquisition costs.
• Shopping cart abandonment rate.
• Returning customer rate.
• Bounce rate.
• Impressions.

Consumer’s behavior on eCommerce marketplace

Amazon is one of the biggest online marketplaces in the world. It uses the A9 algorithm to rank products in its search results based on product performance and keyword relevance. Because Amazon uses this algorithm, online retailers are bound to create product descriptions relevant to the audience’s search queries.

But Amazon is not just an engine that gives search results for products. Amazon records every stroke and scroll to predict the consumer’s behavior for a better shopping experience. It analyzes large amounts of data including the customer’s search history, browsing behavior, and purchase history to make product recommendations while the consumer is shopping. Customers interact with what they are most interested in and this is valuable data to have when trying to appeal to them. It is critical to understanding customer behavior.

But consumer behavior analysis is not just limited to product searches and recommendations. It also extends to modern marketing which in turn, impacts the eCommerce world. For instance, modern research finds that a customer makes a purchase decision after viewing an ad at least 7 to 8 times. This means that to be effective, digital marketing strategies like retargeting ads are important to appeal to customers who have previously interacted with the brand.

Consumer behavior can help sellers strategize regarding pricing, branding, and products. These strategies help brands become more profitable.

How has eCommerce changed by predicting consumer behavior?

Although consumer behavior is not a new marketing concept, the way it has made its way into eCommerce has revolutionized the industry. In turn, consumer behavior analysis and prediction metrics have impacted both the seller’s approach and the overall shopping experience. Here are some ways consumer behavior predictions have impacted the eCommerce sector:

Targeted marketing strategies

With new technologies, eCommerce platforms can now gather and process large amounts of data related to consumer behavior trends. Through this data processing, software services now analyze past purchases, browsing history, and even search queries to recommend products likely to interest the customer.

This increases the chance of a conversion (turning a visitor into a buyer) by showing relevant items and keeping them engaged for longer.

Personalized experience

With insights into consumer preferences, businesses tailor their marketing strategies. Many businesses also leverage AI for dynamic text replacement to target customers in specific locations. However, personalized experience also means that the customer gets shown targeted social media ads, personalized email campaigns, or special offers based on their purchase history.

Dynamic pricing

Perhaps the most effective use of consumer behavior predictions is optimizing pricing strategies. Businesses can now adjust their prices based on factors like demand, competitor pricing, and even a customer’s perceived willingness to pay. Similarly, targeted promotions and discounts can be offered to incentivize purchasing decisions.

How to use consumer behavior on eCommerce platforms to strategize

Consumer behavior analysis offers an insight into consumer habits. These habits, like demographics, define the audience which helps sellers to formulate strategies. Even habits like the social media platforms that the target audience uses to the personalities that influence the consumer help sellers gain a better understanding of what will sell and how it will sell.

So, these habits can help sellers design products that appeal to the audience, use platforms where the audience is present, and hire influencers that convince the audience to make the purchase. When it comes to marketing on eCommerce platforms, consumer behavior habits can be determined by A/B testing and AI tools to improve conversions.

A summary of consumer behavior analysis on eCommerce

The online shopping experience has changed a lot since the advent of new tools and software services. Now, analytics tools are a must for sellers to succeed in the world of eCommerce. AI has further improved how sellers collect and analyze data related to consumer behavior. For sellers, this improvement means keeping up to date to get a better chance of securing customers and making a profit.

Bottom line

If you’ve shopped online, it is easy to discern that – compared to the past – the experience now is a much smoother one. You get products recommended to you as if the eCommerce platform is reading your mind. Mobile commerce has further improved the consumer behavior analysis process. Although many people feel that mobile commerce has transcended the boundaries of privacy, it has rewarded us with a better internet and shopping experience.

Visit us at Pimberly to see how else you can improve the customer experience using your product data.