Retail brokers and exchanges face a familiar problem: attracting new traders is expensive, while keeping them engaged is harder still. With high acquisition costs and a steep learning curve for first-time traders, onboarding has become a make-or-break moment for trading platforms seeking sustainable growth.
Devexperts, a developer of software for capital markets firms, recently delved into bridging the engagement gap in online trading.
Trading venues typically cast a wide net, pushing marketing campaigns designed to drive registrations at scale. But many firms accept that a significant share of signups will never become active traders, while churn remains stubbornly high among beginners who struggle to build confidence and routine.
To reduce early drop-off, brokers have leaned on a set of well-established tactics. These often include educational courses and explainers, simplified “lite” trading interfaces that remove advanced functionality, and retention teams that proactively check in with new clients to keep them on track.
However, Devexperts argues that many of these approaches fail to scale effectively because they are not consistently anchored in actionable customer data and automation. The company says the missing link is a system that can translate behavioural signals into timely interventions, helping businesses run retention and growth initiatives without relying on manual, one-to-one effort.
Devexperts says it has been working to address this gap by helping clients make better use of the information generated by traders. In the company’s view, the challenge is not that brokers lack data or ideas, but that valuable signals are spread across disconnected systems and therefore fail to inform engagement at the right time.
The firm points to two products it has developed as part of this work: Devexa, an AI client engagement agent, and Acomotrade, an AI-powered personalisation solution for the DXtrade platform. Devexperts positions the tools as complementary, with each focusing on a different category of user behaviour.
The company broadly divides brokerage client data into two sources: user inputs and trading data. User inputs can include questions, preferences and engagement touchpoints. Trading data can include platform telemetry and account behaviour. Devexperts says both can be used to support engagement strategies such as low-activation fixes, earlier churn detection and more targeted communication that improves long-term value.
Devexperts describes Devexa as a first line for client enquiries that can answer questions quickly, reduce pressure on customer service teams and support satisfaction scores. The company says the agent goes beyond basic chat functions by acting as an always-on trading assistant that learns from each interaction to build a richer picture of the user.
Devexperts says Devexa’s conversation-led insights can be used to trigger relevant alerts, suggestions and content at key moments in a trader’s development. The goal, it says, is to keep outreach timely and tailored so that users receive information that matches their interests and experience level, improving engagement and reducing the likelihood of early disengagement.
The firm adds that Devexa integrates with channels such as Discord, Telegram, Messenger and WhatsApp, aiming to meet clients where they already communicate. It also says the agent can be trained by in-house teams through an administrative interface without coding.
Acomotrade, meanwhile, is positioned as a behavioural insight engine that uses trading activity and account management decisions to support personalisation at scale. Devexperts says it can provide users with relevant information and instrument recommendations, shaping the platform experience over time through prompts such as targeted education, contextual suggestions and alerts around significant market events.
The company argues that content and marketing teams often have no shortage of communication ideas, but struggle to target and execute them using real user data without adding manual workload. Devexperts says Acomotrade is designed to close that gap using machine learning models trained on trading data and telemetry, helping brokerage teams identify what is happening with clients and prioritise interventions.
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