If you haven’t been asleep for the past few years, you’re aware that there is a real and growing buzz around Customer Experience (CX). Every company wants to tackle CX but precious few know where to start. Understanding the thoughts, needs and problems of a customer base is a great place to begin. To do that, companies have turned to the various analytics options available in their current CX technology stack, but those existing technologies have been – in a word – underwhelming. Why?
For years, voice and text analysis has been a “feature” of platforms offering customer communication channels. Call recording, chat, email, social media monitoring, surveys, and other platforms have provided some form of analytics on the data generated by the use of that platform. Never the primary focus of the companies behind them, these bolt-on analytics packages have been relegated to the status of second-class citizen: line items on a list of features that come along with the platform’s primary objective. In fact, platform providers have been known to throw in their analytics offerings free of charge, as a “value add” on the contract for some clients. That alone gives an idea how much emphasis is placed on the value of analytics by those vendors.
Another issue with these bolt-on analytics packages is they only tap into the channel they come with. The unstructured, conversational data generated by these platforms is incredibly useful, but – and here’s the catch – only when analyzed in aggregate across all channels. Nearly every B2C company offers at least 5 channels of communication with customers, many having more than 10. Your customer’s experience of your company or brand isn’t channel-specific. It spans the channels they choose to use to interact with you, and so must your analysis of that experience.
To analyze all this disparate data together though, it must be normalized and have a common classification model applied across all of it. Here’s the good news – there is new technology available from companies like Topbox, sometimes referred to as agnostic aggregators. These are pure-play, “BYOD” CX Analytics providers who ingest unstructured interaction data from every channel (along with its accompanying, structured metadata), normalize it, classify it, and provide deep analytic capabilities to identify friction points and quantify the customer experience.
Topbox is built on analytics, machine learning, and AI. It’s not a side gig. The technology doesn’t generate the data, but helps businesses make sense of it. If you’re interested in learning more, you can request a demo of Topbox’s Customer Experience Platform, here.