Conversational AI: Ecommerce websites need smart talkers

conversational ai

Conversational AI is set to change the way British buyers interact with brands and it couldn’t come soon enough according to Rachel Tonner, VP Global Marketing at Klevu

Globally, the social-commerce market is expected to grow to more than $2 trillion by 2025. It’s now too big for UK brands to ignore. Given their massive reach and potential for monetisation, platforms like Facebook, Instagram and TikTok are now integral to the marketing mix. 

But for British brands to win in the social space, they must do more than switch channels, they also need to change how they engage with traffic from social platforms. That means innovating on the website, especially when it comes to discovery and search. 

To extend the smooth, hyper-targeted, highly humanised and fun social shopping experiences that the UK’s 15 million social buyers crave, brands must switch the emphasis from information retrieval to intelligent dialogue.  

How to make the leap from dumb bots to smart socialisers  

When ecommerce brands fail to deliver on social marketing KPIs, it’s not always content, or product appeal that is to blame. Interactive friction or lack of context in recommended links, underperforming search boxes and basic chatbots can also undermine engagement, conversion and performance.

This is because many chatbots and search functions are based on outdated technologies that simply match keywords in user queries with content on websites/indexes. It’s a hit-and-miss approach that can lock users into a never-ending battle to be understood or to get the relevant results they need. 

Rapidly evolving Conversational AI is ready to come to the rescue, enabling digital marketers to build smarter, more personal, two-way social exchanges and to move away from the keyword-tied dumb bots of the past.

What makes it better at communicating? 

Combining natural language understanding (NLU), natural language processing (NLP), and machine-learning models, Conversational AI can emulate human cognition – so it can initiate and respond to conversations, as quickly and intuitively as a human brain – making it perfect for social platforms.  

It also uses semantic platforms to instantly assimilate and analyse contextual data and intent so it can understand what’s being asked of it and can provide more accurate responses based on its wider and continuously expanding knowledge base.   

This is vital for digital brands that want to recreate the value-rich, two-way conversations typically associated with building a positive presence on social platforms. 

How can marketers exploit conversational AI in the social space?

Organisations are relying more on social platforms to initiate product discovery, for customer support and service. In all these cases, Conversational AI can up the stakes, helping to produce more positive outcomes across a variety of use cases. 

Put simply, it’s about making dreams come true. By knowing what customers want before they want it and providing the right curated content or highly relevant and personalised recommendations at the exact moment of highest intent. It solves customer issues faster. With service and support chatbots that won’t leave them stuck in continuous query loops, asking the same question in a different way or being presented with a limited menu choice. Ultimately, it’s also about delivering the frictionless and authentic social interactions that make brands stand out from competitors by ensuring a fast, highly personalised and responsive service.

By ensuring discovery and query tools on social platforms have the intelligence and insight to understand, interact and communicate with customers and prospects, marketing can start to drive the returns their business and stakeholders demand.

Three ways smart bots can transform social marketing and deliver ROI 

  1. Collecting context and intent data for brands to be more authentic
    Brands can record, analyse and share more meaningful, accurate and deeper customer intent insight from higher levels of interaction and more detailed ‘conversation-based’ searches to deliver greater authenticity in their social interactions.   
  2. Driving conversion through digital channels with hyper-relevant recommendations
    Website and app chatbots can predict and deliver more accurate recommendations based on what customers really want – not what an algorithm thinks they want.
  3. Building deeper long-term community relationships
    Unlike people, smart bots can remember past conversations and initiate new ones.
    Conversational AI applications can automatically track previous searches and queries and connect these with back office and CRM functions to drive value and sales

Taking the heavy lifting out of social engagement at scale

With Conversational AI, smart bots can do all this and more using automated functions and a myriad of data sources. This leaves marketing teams free to focus on content, promotions and creatives and less time on tech. And allows tech teams to spend more time creating truly seamless, smooth social engagement that keeps conversion high and customer churn low.

Within the Conversational AI depository, there are already thousands of models available, each of them is doing something different, and many are ready to disrupt social platforms with “as-authentic-as-human” interactions, suggestions and insights.  

In the future, these models will come together to transform social interactions

Imagine automated functions which not only have the power of ChatGPT but can also understand the complex nuances of sound, images and abstract thoughts, and be able to analyse and combine that knowledge with textual interpretation. 

For marketers, brands and consumers this brings massive opportunity. But it also brings new concerns around ethics and AI security. We can expect lots of discussion and investment in this area in the years to come.  

However, one thing is clear, as AI advances, we are entering the era of adapt or die. Soon there will be only two types of companies – ones which embrace and adapt hyper-intelligent technologies and the others that no longer exist because they didn’t.  

In the meantime, we must continue to explore tools, learn to improve prompt engineering, and ask the right questions, to make AI as human and as social as we are.