Improve Your Telecom Sales

With Predictive Analytics For Sales And Marketing

In telecom sales, your reps are in a unique position. The transactional nature of telecom means more dials made to find the right people who need your products or services now.

While you don’t often see the benefits of relationship building that other industries see during a longer sales cycle, you are at one particular advantage: Due to the sheer number of people you contact on a monthly basis, you are collecting a ton of data.

This data is incredibly important, because it’s ripe for predictive analytics to help drive your telecom sales strategies.

Why Predictive Analytics?

You’re likely already monitoring some metrics of your telecom sales statistics, and looking for patterns and some type of through line to sales-ready prospects. Predictive analytics takes your data sets and goes deeper, because it’s capable of building statistical models to solve business problems. Because the data sets are so large, it’s easier to identify patterns to reasonably and statistically rule out outliers.

Instead of making educated guesses based on high-level metrics, predictive analytics technology is reliable enough to unearth trends and patterns that simply can’t be accomplished with human analysis.

The 3 Big Benefits Of Predictive Analytics In Telecom Sales

  1. Increased Efficiency
    Instead of your sales reps wasting time calling prospects who aren’t going to convert, through predictive analytics you’re able to classify customers according to their likelihood to buy a product or service. Targeting sets of customers with better purchasing potential helps to yield a higher ROI.
  2. Improved Retention
    Through predictive analytics, you can find out when customers are at risk and then develop specific campaigns around that particular risk. The data empowers you to make educated at-risk predictions so you can take appropriate action to retain customers.
  3. More Viable Sales Opportunities
    Predictive analytics is also beneficial for customer segmentation, which helps eliminate meaningless segments and elevate those prospects with higher predicted conversion rates. For example, you can leverage predictive analytics to build campaigns around identifying prospects geographically or firmographically.

Big data is a term businesses of all stripes are going to hear more and more about, because technologies like predictive analytics are now truly starting to come into their own. The sheer volume of data involved in telecom is perfect for reaping the benefits of predictive analytics to boost your telecom sales.

The Power Of Predictive Analytics For Marketing And Sales

To set the stage for how powerful predictive analytics can be, NASA recently wrote about how astronomers are enlisting the help of machine learning 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, machine learning (and predictive analytics) can help out. Likewise, much of the data your telecom produces in a given day, week or month is hidden to the human eye.

Predictive analytics (in terms of telecom sales strategies) is based on big data analysis through software that’s capable of asking certain questions and finding correlations. The software runs calculations and looks for patterns that an analyst may have never thought to look for. It’s capable of identifying every little change in the data over the course of time, recognizing small but critical details.

Correlations found from 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 leverage your telecom sales data to develop new strategies to drive revenue?

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