• Part 2: Why You Need AI Machine Learning To Improve Your Telecom Sales

    In Part 1 of this blog series on using big data to improve your telecom sales strategies, we looked at predictive analytics as a means to increase efficiency, improve customer retention and unearth more viable sales opportunities.

    AI machine learning is another buzz term that’s ripe for the future of big data and telecom sales.

    To set the stage for how powerful AI machine learning can be, NASA has recently written about how astronomers are enlisting the help of these machines to discover and sort through thousands of stars in our galaxy and learn their sizes, compositions and other basic traits.

    While humans alone can’t easily make sense of all the data telescopes around the world produce, AI machine learning (along with specialized algorithms) can help out. Likewise, much of the data your telecom produces in a given day, week or month is hidden to the human eye.

    Where predictive analytics (in terms of sales strategy) is based on big data analysis, AI machine learning is software that’s capable of asking certain questions and finding correlations in big data that are virtually blind to the human eye. It runs calculations and looks for patterns that an analyst may have never thought to look for. It looks at every change in the data over the course of time and recognizes the small but critical details.

    Correlations found from AI machine learning and predictive analytics identify opportunities for new business, getting you closer to the magic of the one-call close, which is the ultimate goal of telecom sales.

    Last year, McKinsey Quarterly published an executive’s guide to machine learning, which included these snippets:

    • “Machine learning is nothing like learning in the human sense (yet). But what it already does extraordinarily well – and will get better at – is relentlessly chewing through any amount of data and every combination of variables.”
    • “It is, after all, not enough just to predict what customers are going to do; only by understanding why they are going to do it can companies encourage or deter that behavior in the future. Technically, today’s machine-learning algorithms, aided by human translators, can already do this.”

    Predictive analytics is the next data revolution that’s already finding acceptance from the C-suite of telecoms and beyond. It’s an exciting and powerful way to put a ton of data to good use, informing your telecom sales strategies in a granular way and supporting your pursuit of gaining a competitive advantage.

    Ready to learn more about how to decipher your telecom sales data and identify new business opportunities?

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