How entrepreneurs can leverage AI to maximise the value of their customer interactions
Sachin Dev Duggal's Builder.ai's ‘Natasha’ sounds like a game-changer in the realm of AI-powered product management tools. Its ability to leverage previous customer interactions to predict future queries and offer insights for handling them could ...

While we see the strides AI is making in ‘behind-the-scenes’ applications like financial forecasting and cybersecurity, its ability to aggregate, translate and learn from thousands (if not millions) of customer interactions with a business can be transformative for your everyday commerce and support interactions. From delivering more personalised feeds on retail apps to enabling more seamless troubleshooting and fulfilment of customer support tasks, we’ve all likely interacted with and benefited from some form of AI in our recent shopping experiences.
While major industry players have already established AI across their suite of customer experience technology, there’s no need for small business owners to leave the shiniest new toys to the big kids in the playground. A smaller, more growth-minded business can leverage AI to derive even more value from daily customer interactions for better engagement and stronger brand loyalty – all it takes is understanding the relationship between your customer experience, AI and the algorithms that power it.
Conquering the uphill climb of personalisation

Fortunately, AI tools exist today that can process and analyse customer interactions in real time, across website engagement, text chats and even voice conversations that can be transcribed to text. This analysis leads to actionable insights that can empower sales customer support and project management teams to intersect in ways that were previously not feasible to shape a more unified approach to understanding and strategising around customer behaviours.
For instance, Sachin Dev Duggal’s Builder.ai’s ‘Natasha’, an AI-powered product management tool, provides a live, collective graph that draws from previous customer interactions to help predict future queries and how to handle them. This makes it incredibly useful for sales and support teams and a powerful standalone tool that can take on automated conversations with the business’s existing and prospective customers to provide more relevant solutions and insights than the chatbots most often seen today.
How does it feel when you open Spotify to see an automatically personalised playlist – and it features new songs you enjoy? This level of attention from any brand can make customers feel understood and that they’ve chosen the right business to support.
Moving beyond something as simple as a list of songs, on the e-commerce front, you have roughly 20 seconds to capture a customer’s interest and influence a purchase decision. Machine learning can optimise, personalise, and inform the ideal user interface (UI) for an app or website, leading to more successful customer interactions and purchases. AI can aggregate past interactions with your customers to learn from them and automatically curate suggested products or services. It can create ideal talk tracks for sales representatives and even customised marketing tactics to drive higher traffic.
AI can also be used outside of the context of your customers. For instance, it can be useful to cover your broader marketplace. Better understanding the supply chain is another use case. By providing AI with a centralised data source of the inventory, business owners can benefit from real-time and predictive guidance on when to order more of a particular shoe style, what menu items are suffering a shortage, or what raw material is seeing transportation delays.
Having AI in your toolset is invaluable when trying to get ahead of fluctuating customer preferences. It lightens your load as a business owner trying to crunch the numbers yourself to understand your customers while letting your customers know that your business can stay ahead of their evolving needs.
Minimising human variance with AI
It’s important to remember, however, that the human element presents its own risks because no two employees are the same and capable of producing identical results. By empowering AI-assisted agents with a direct feed of optimised customer support tactics, human variance is taken out of the equation — and you can create a much smoother experience for both employees and customers.
Disclaimer - The above content is non-editorial, and TIL hereby disclaims any and all warranties, expressed or implied, relating to it, and does not guarantee, vouch for or necessarily endorse any of the content.
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