How Much Does The Conversation In Conversational Commerce Matter?

As retail continues its shift from physical storefronts to digital channels, conversation has become a central component of brand strategy. Live chat, email, and omnichannel messaging now replace many in-person interactions, creating a powerful opportunity: every customer conversation generates data that can be measured, analyzed, and improved.

In this context, conversational commerce is growing rapidly. While overall retail growth has remained modest, e-commerce has expanded at a far faster rate, making online engagement—especially live chat—an increasingly critical driver of revenue. Research shows that customers are significantly more likely to return to an online retailer that offers live chat, reinforcing its importance as a sales and retention channel.

The key question is whether how live chat agents communicate actually influences outcomes. To answer this, the authors analyzed data from an anonymous e-commerce company with over 200,000 customer visits, $25 million in annual revenue, and more than 2.8 million live chat messages.

The researchers built a detailed model of agent–customer conversations, incorporating both contextual variables (such as time of day, location, and demographics) and the subtleties of human dialogue, including word choice, grammar, pacing, conversational style, and emotional signaling.

These factors were divided into two categories: controllables driven by agent behavior, and non-controllables outside the agent’s direct influence. This distinction allowed the researchers to isolate what agents can realistically change—and how much those changes matter.

Four controllable dimensions of agent behavior emerged as especially important: Effort (grammar, spelling, capitalization), Emotion (use of emoticons, exclamation points, positive language), Friendliness (expressions of empathy and human connection such as “I” and “we”), and Responsiveness (speed and rhythm of replies).

Using a statistical technique known as Variance Decomposition, the authors measured how much each factor contributed to outcomes across four key performance indicators: customer satisfaction, sales conversion, total order size, and repeat purchases.

The results were striking. Agent-controlled behaviors accounted for the majority of explainable outcomes across all metrics—driving 57.7% of chat scores, 60% of sales conversions, 58.2% of total order size, and 74.9% of customer retention. In every case, controllables outweighed non-controllables.

These findings demonstrate that in conversational commerce, agent behavior matters more than context. How a conversation unfolds—tone, responsiveness, emotional cues—has a greater impact on outcomes than the topic of the message or the customer’s background.

The implication is clear: before replacing human agents with chatbots, organizations should invest in improving human conversations. With the right training, analytics, and AI-driven guidance, live chat agents can significantly increase satisfaction, conversions, repeat purchases, and overall revenue.

While human conversation is complex, this research shows it is not unmeasurable. Rapport-building behaviors can be identified, optimized, and scaled—turning live chat into a powerful, data-driven engine for growth.