Enhance E-commerce Revenue: Boost Average Order Size with Data-driven Strategies

Maximizing Average Order Size in E-commerce: A Data-Driven Approach

• Working in e-commerce poses the question of how to boost customers' average order size. Look no further as here's a data-driven strategy to enhance customer value. This strategy, implemented with Amplitude, begins with the Funnel Analysis chart. The chart illustrates the typical e-commerce conversion funnel, tracking customers from viewing items to adding them to the cart, and eventually making a purchase. There's a noticeable drop-off between the initial stages of viewing an item and adding it to the cart, presenting a prime opportunity for enhancement.

Maximizing Average Order Size in E-commerce: A Data-Driven Approach

Unlocking the Secrets of Customer Behavior

• Delving into customer behavior reveals fascinating insights into their decision-making process. While the solid blue portion represents those who took the first step, the grayed out section signifies individuals who dropped off. Understanding the behavior of these converted customers unveils the motivations behind their actions. By clicking on the solid blue portion, I initiate the exploration of conversion drivers, which leads me to a panel showcasing the events correlated with successful conversions. This feature provides a detailed view of customers who completed step two, highlighting their interactions between the initial and subsequent steps, such as viewing an item before adding it to their cart.

Unlocking the Secrets of Customer Behavior

Unveiling Customer Insights with Amplitude

• In other words, amplitude is saying, 'Hey, I looked at the behavior of more than a hundred thousand customers who have successfully converted, and this is something they tend to share in common.' Here, I see that the action most correlated with driving conversion is this event called 'selecting a recommended item.' That's a huge insight. My customers may be more inclined to add an item to their cart if they see and then select an item that's been recommended to them. Now, I could stop here. We've already found one way to increase sales. And that means that if we recommend more items, more customers will purchase them. But with something like Amplitude, I can always keep asking questions of my own data.

Unveiling Customer Insights with Amplitude

Unlocking the Power of Data: Understanding Consumer Behavior Through Recommended Items

• As we delve deeper into the realm of data analysis, there is always more to uncover. In our quest to understand consumer behavior, we are presented with a valuable tool: recommended items. By analyzing which recommended items have the highest impact on user conversions, we gain valuable insights into consumer preferences and habits. Clicking on 'expand by property' reveals a plethora of options, but for now, let's focus on the brand. This reveals to us the brands that are most correlated with successful conversions when listed as recommended items. It appears that users have a strong affinity for brands such as Michael Kors, Levi's, Nike, and Coach, as these brands drive the highest conversion rates. Armed with this powerful information, we now have a deeper understanding of the brands that resonate most with our audience and drive conversions. This knowledge empowers us to tailor our strategies, run targeted promotions, and leverage these brands more effectively. However, our exploration into consumer behavior doesn't end here; we still have more insights to uncover with just two clicks remaining.

Unlocking the Power of Data: Understanding Consumer Behavior Through Recommended Items

Uncovering Customer Preferences Through Data Analysis

• Upon further exploration, I decided to delve deeper into the data. By selecting the 'department' filter, I was able to analyze which brands were driving conversion across different categories - men, women, and kids. Surprisingly, Michael Kors emerged as a favorite among our customers. In just six clicks, I gained valuable insights into user behaviors that lead to increased average cart values. Moving forward, I plan to highlight these specific recommendations more prominently for our customers. Additionally, I am considering launching a strategic marketing campaign targeting users who didn't convert, showcasing the recommended brands and departments. Stay tuned for more details in an upcoming video. I trust you found this informative. For more strategies, feel free to explore amplitude.com/6clicks.

Uncovering Customer Preferences Through Data Analysis

Conclusion:

Implementing data-driven strategies to enhance the average order size in e-commerce can lead to increased revenue and improved customer satisfaction. Stay ahead in the competitive market with these insightful approaches.

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