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Conversational commerce: making your data work harder

Conversational commerce allows retailers to deliver a convenient and personalised shopping experience for consumers who are often on the go, or multi-tasking.

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Conversation has always been a critical part of commerce. From the early Phoenician textile markets to the department stores of today, transactions have hinged on a dialogue between seller and buyer. The online model, with marketplaces cutting out human interaction, has disrupted this in the past decade. However, it’s clear that consumers still long for interaction when browsing and buying goods. This is showcased by the growing use of voice technology and chatbots, which are allowing conversational commerce to thrive.

The data from these conversations is a goldmine of feedback and insight, as retailers can gain direct insight into not just what consumers want but also how they want it.

However, retailers are failing to fully leverage the sheer amount of data produced by these customer interactions. As a result they are missing out on actionable customer feedback which could improve the way they deliver services and ultimately their business.

Lost in translation

A major issue is that customers have a tendency to not explicitly state what they want or need. They often use imprecise language or fail to adequately communicate what it is they’re looking for. As a result of these conversations and interactions, retailers are left with massive amounts of unstructured data. And data alone is meaningless unless businesses can leverage it for decision-making.

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AI and machine learning offers retailers a means to uncover the value of unstructured data. By Forrester’s reckoning, around 70 per cent of enterprises will implement AI in 2018, up from 40 per cent in 2016 and 51 per cent in 2017. Companies that adopt AI now will be on the front lines of increasingly important enterprise technology.

AI tools easily address the daunting volume of unstructured data generated day to day, providing insights into the conduct of agents and supervisors and the overall customer experience. This provides retailers with the opportunity to adapt their offering to suit their customers’ needs.

AI-driven semantic engines can assess factors such as customer satisfaction, personality and education for every customer — information retailers can use for anything from segmentation to more effective targeting and messaging.

According to a study from San Francisco-based Opus Research, 72 per cent of companies believe speech analytics can lead to improved customer experience, 68 per cent say it can reduce costs and 52 per cent think deploying speech analytics can lead to higher revenues.

Putting the data to work

Excellent customer experience is a business imperative. It provides a strategic differentiator that clears the way for retailers to stand out from their competitors.

To improve customer experience, Deloitte has found that more companies are factoring customer feedback into their business decisions. More than 80 per cent of people surveyed at 450 contact centres worldwide reported feedback is ‘core to their DNA’ or a ‘core input to business decisions’ — up from 45 per cent in 2013.

In today’s market, there are tools, available that can assess more than 50 unique conversational behaviours including pauses, silences, over-talk, interruptions, jargon and words spoken per minute by both the customer and the call centre agent. All of these measures provide different dimensions of insight about the construction of the conversation.

In this way, AI can power conversational commerce, helping businesses to hear, understand and appreciate their customers more competently and completely. Conversational commerce prioritises conversations — the most natural, convenient means to communicate and supports better customer experiences.

The goal of conversational commerce technology is to accurately recognise what people want — and to consistently and correctly provide answers or recommendations at scale. AI tools will enable retailers to stay relevant in an era of increasingly elevated customer expectations. The insights gained from data analysis will allow retailers to anticipate the next best thing and strategically adopt their approach to drive their desired outcomes.

Every customer conversation has the potential to help or hinder a retailer’s performance. The more intently a business listens to its customers, the better it understands their wants and needs. By using AI to encourage conversational commerce and then effectively analyse and understand the conversations taking place, retailers can stay on top of their game.

By Marc Giretto, Product Lead, Daisee