AI-Powered Customer Journeys: Boosting E-Commerce Conversion:CatalystConversations, Ep.5, SessionStack

Venture into the ever-evolving world of e-commerce with CatalystPay's new interview series. Join us as we delve deep into the entrepreneurial journeys of leading figures in the e-commerce realm in Central and Eastern Europe, uncovering insights on revenue growth, sustainable business models, and international scaling. Whether you're a budding e-commerce entrepreneur or a seasoned pro, these conversations are bound to ignite fresh perspectives and actionable wisdom.

What would you say are the biggest challenges in eCommerce customer journeys merchants in CEE face right now and how do you address them?

Firstly, the rapid expansion of the digital economy in CEE, outpacing that of Western Europe, highlights the region's growing significance in the global e-commerce landscape. The CEE e-commerce market was estimated to reach €93.84 billion in 2022, indicating a robust compound annual growth rate (CAGR) that far exceeds the Western European average. This growth trajectory suggests a dynamic market ripe for exploration by e-commerce businesses. However, it also underscores the escalating need for businesses to navigate the complexities of cross-border e-commerce efficiently to tap into this expanding market​​.

The truth is that busy e-commerce teams don’t have time to digest reports and stare at session replays and this is why it’s sometimes so challenging for them to find the customer journey hiccups that need to be addressed.

Further complicating the issue, as noted by G2, is the reality that a staggering 99.5% of all collected data in the digital realm is never analyzed or used​​. This statistic underscores a significant missed opportunity for e-commerce businesses to harness the insights buried within their data to drive growth and improve customer satisfaction.

Buried deep inside all of ecommerce merchants data are ‘golden nuggets’ - high-impact UX/UI, technical, and other issues that stand in the way of a smooth purchase flow and cost dearly in the long run.

This is the challenge we took head-on. We extract the golden nuggets and deliver them in the form of handy insights that the whole team can use. We’ve found that CEOs, e-comm managers, marketers, designers, and developers are equally likely to find value in these insights and use them as a conversion rate optimization starting point.

Fraudulent activities are often on the top of the list for potential revenue loss. Could you go through the process that you’re using to help e-commerce businesses identify and prevent them?

Customer journey analysis often focuses only on the common ways customers interact with the shop. But certain uncommon behaviors can be counted as fraudulent - attempting to ‘game’ the system with old coupon codes, or ordering and never retrieving an unpaid order, for example. These behaviors often follow a pattern and machine learning models can be taught to ‘catch’ these customers before their actions result in revenue loss.

Through detailed analytics, e-commerce businesses can start to recognize patterns of behavior that deviate from the norm. These patterns may include rapid changes in the volume of transactions, unusual transaction sizes, or patterns in the return and dispute rates. By identifying these patterns, businesses can flag potentially fraudulent activity for further investigation.

A good payment flow and checkout experience have become essential in eCommerce. What can be done for the optimization of these processes?

Each online shop is different and even if there is a certain set of optimizations that can be applied universally, finding the best combination of optimizations takes a lot of work. This is where machine learning and AI come into play - as checkout and payment are two critical parts of the customer journey, finding the best optimizations for them can result in the highest conversion uplift.

These can be as simple as removing an unused mandatory form field or adding a new payment method. Or a more complex combination of measures involving a more informative approach to shipping costs throughout the journey, not only on the checkout page.

As you prepare for expansion, what role will AI and analytics play in shaping the future of e-commerce in the CEE region?

Broadly speaking, the integration of AI in e-commerce within CEE is set to provide great opportunities to merchants in the sector by enabling unparalleled levels of personalization and efficiency. By using AI to analyze vast datasets, e-commerce platforms can predict consumer behavior, tailor recommendations, and optimize logistics, ensuring that inventory meets demand without surplus. This not only enhances the shopping experience through customized interactions but also streamlines the supply chain, reducing costs and delivery times.

With the projected growth rate, e-commerce is set to play an even greater role in the upcoming years. With that expansion comes great responsibility towards the consumer - every online retailer will bear the responsibility to provide the best customer experience possible. The fighting ground will expand around who is more prepared to offer the smoothest journey from advertising to payment and beyond. SessionStack AI can be a powerful ally, providing a constant stream of actionable insights to help keep e-commerce business owners ahead of their competition.

Can you tell us more about how you use it to improve the conversion rate for high-traffic e-commerce sites?

SessionStack has been working with a variety of businesses over the years and, no matter the type of business, we noticed one thing: the vast amount of data that the platform recorded was always underutilized. This was due to a complex set of reasons ranging from a lack of direction as to what to use the data for to a lack of trained analysts on the team.

So, when AI started to make waves, we thought about ways to incorporate the technology into our product offering and the solution was rather straightforward - machine learning and generative AI were part of the answer to the problem of underutilization, with a logical focus on e-commerce where every user interaction counts.

We started building SessionStackAI, our industry-first set of proprietary machine learning models and generative AI, to help online retailers extract valuable conversion optimization insights from their data.

Looking forward, what product developments do you have in mind, considering the versatile needs of eCommerce businesses?

When it comes to conversion optimization, e-commerce businesses think in terms of finding the issues that need to be fixed (diagnostic), finding the best way to fix them (recommendations), and actually implementing the fixes themselves (implementation). We are currently focused on the first stage of this process, but our ultimate goal is to be able to provide an all-in-one approach to conversion rate optimization. While the ‘diagnostic’ stage is being put to the test by our pilot clients, we’re already working hard to polish the ‘recommendations’ part.