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In today’s world, customer service agents and inside sales representatives are armed with considerably more tools to improve efficiencies when dealing with customers and prospects.
Over the last decade sales strategies have changed considerably, and the inside sales model has overtaken the field sales model that once dominated larger organizations.
One of the biggest challenges for the modern business is learning to utilize all of the data available to them in a way that is both meaningful and actionable. However, the potential for using data generated by a website is often left unexplored, and as a result, the intentions and reactions of individual digital customers can be overlooked.Read More >
Building resilient distributed systems that enable large scale data processing in real-time is hard.
The system was designed to serve some of the following use cases in a reliable and highly scalable manner:Read More >
The key to successful selling is identifying what your customers need and engaging them at the right moments in their journey. Understanding why, how, what, and when your prospects want to buy takes time. To do this, you need the right data – and a lot of it. You can try to meet with every single customer, or… you can use customer journey analytics and machine learning to understand:Read More >
A primary pain point when dealing with technical support queries over the phone – for both the customer and the customer service agent – is the quality of communication. A customer experiencing a problem on your website or app has to recount all the steps they have taken to get to the point where they are stuck, and the agent has to make sense of this information in order to identify where the problem lies. This isn't always a smooth transaction.Read More >