For much of the past decade, digital commerce competed on speed.

Faster websites. Shorter checkout flows. Reduced response times. Each optimisation aimed to remove friction from customer journeys that were assumed to be linear, self-directed, and transactional.

That strategy worked. But it is no longer sufficient.

As commerce increasingly unfolds inside conversations, the constraint is shifting. The next competitive advantage is not how quickly a brand responds, but how well it understands what a customer is trying to do.

Speed Was the First Phase

Speed mattered most when customers navigated digital experiences independently. They searched, browsed, compared, and converted with minimal interaction. When friction appeared, abandonment followed.

Optimisation therefore focused on efficiency:

• Page load times
• Funnel compression
• Faster issue resolution
  

In this environment, latency correlated strongly with conversion. Shaving seconds off an experience often produced measurable gains.

Speed remains a baseline requirement. But it is no longer the primary differentiator.

Commerce Is Shifting From Transactions to Decisions

Buying decisions today are increasingly made inside conversations.

Customers ask questions, compare alternatives, seek reassurance, and refine preferences across multiple interactions. These journeys are iterative rather than linear and often span time, channels, and departments.

This shift is reflected clearly in customer expectation data.

Salesforce’s State of the Connected Customer report finds that:

• 78% of customers expect consistent interactions across departments
• 65% expect companies to respond to their needs in real time
  

These expectations are not limited to speed at a single touchpoint. They reflect a demand for coherence across the entire experience. Customers expect brands to remember prior interactions, align responses across teams, and adapt in context.

Zendesk’s Customer Experience Trends Report reinforces this cumulative view of experience quality:

• 73% of customers say they will switch to a competitor after multiple bad experiences
• Customers report that standards for customer service are higher now than they were three years ago
  

Customers increasingly evaluate brands not by isolated moments, but by how well each interaction builds on the last.

Why Speed Alone No Longer Converts

In conversational contexts, speed without understanding feels shallow.

A fast response that fails to address the customer’s underlying intent does not meaningfully advance a decision. It simply accelerates the customer through another unhelpful interaction.

This helps explain a growing paradox in commerce teams: organisations continue to optimise response times and automation rates, yet still struggle to convert high-intent customers.

They are optimising throughput, not decision support.

AI Is Not the Destination. It Is the Material.

Most early applications of AI in commerce have focused on automation:

• Handling higher volumes of interactions
• Replacing templates with generated responses
• Reducing time-to-first-reply
  

These improvements deliver efficiency. But efficiency alone does not guarantee better experiences.

Gartner’s Customer Service and Support Predictions warn that by 2026, organisations that deploy AI without redesigning underlying service processes risk declining customer satisfaction, even as automation increases.

The reason is straightforward: if the structure of the experience does not change, AI simply accelerates existing friction.

AI becomes strategically valuable when it helps brands recognise why a customer is interacting, not just that they are interacting.

Context and Memory as Design Requirements

A core limitation of many conversational systems is their lack of memory. Conversations begin, end, and reset, with little persistent context.

Customers do not experience brands this way.

In channels such as WhatsApp or in-app messaging, continuity is assumed. A customer who discussed product fit yesterday should not have to repeat themselves today.

McKinsey’s research on generative AI adoption notes that many implementations fail to deliver value because they are not designed with contextual continuity in mind. AI’s advantage lies not in speed alone, but in supporting coherent decision-making over time.

This is particularly relevant in commerce scenarios where customers:

• Compare options across multiple interactions
• Revisit questions after external research
• Follow up as new information becomes available
  

These behaviours cannot be supported by one-off responses or static campaign logic. They require memory as infrastructure.

Conversational Channels Change the Stakes

Conversational channels are not simply support surfaces. They are decision environments.

Meta’s research on business messaging shows that customers are significantly more likely to make a purchase when they can message a business directly, compared with traditional outbound channels. At the same time, tolerance for poor or irrelevant responses is lower than in email or static web experiences.

Messaging feels personal and immediate. When brands meet that expectation with understanding, trust compounds. When they do not, trust erodes quickly.

How Some Brands Are Responding

Leading organisations are beginning to shift how they approach AI and conversational commerce.

Merx is one example of this approach in practice. It treats conversations as ongoing journeys rather than isolated events, structuring conversational signals into persistent context that informs future interactions.

Across Merx Customers:

• Conversations that extend beyond four messages convert at over 20%
• Single-message interactions convert between 8–13%
• Ads that lead directly into conversation consistently outperform ads that route to static landing pages
  

These outcomes are not driven by persuasion alone. They reflect reduced uncertainty and better-aligned decision support.

Understanding Requires Trust

Understanding is not purely technical. It is also ethical.

Customers share information in private channels, often with an expectation of discretion. For conversational intelligence to work at scale, it must operate within clear boundaries.

This includes:

• Filtering sensitive data at input
• Avoiding unapproved use of personal data for training
• Escalating complex or ambiguous cases to human teams
• Enforcing brand-defined guardrails
  

Without trust, contextual understanding is fragile and short-lived.

The Advantage Ahead

Speed remains essential. But it is no longer enough.

The brands that win the next phase of commerce will be those that:

• Recognise intent early
• Preserve context across interactions
• Reduce uncertainty at critical moments
• Guide decisions rather than accelerate transactions
  

AI is not the destination. It is the material from which better understanding is built.

Speed was yesterday’s advantage.

Understanding is tomorrow’s.