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Big Data has been a buzzword in sales and marketing for quite a while now. Thought leaders often mention how Big Data can transform businesses and empower teams. But that’s only true when the data is used correctly.

It’s easy to forget that all that data is worthless without analytics to put it to use. That’s why, when it comes to sales, predictive analytics — using data on past events to predict future outcomes — is particularly valuable. Here’s a closer look at predictive analytics applications and what they can do for your sales team.

What is predictive analytics?

Predictive analytics is pretty simple on the surface. It’s the practice of analyzing data from past events to try to make predictions about the outcomes of future events. Of course, things are a little more complicated than that. Analyzing Big Data to generate predictions about future events requires powerful software and lots of data. However, the impact it can have for a business — especially a sales-centered one — is huge.

A key benefit of predictive analytics is parsing specific learnings from enormous quantities of information. “Big Data has meant there are many data points we can consider and many we can use effectively,” says Michael Ferranti, founder of BuyerGenomics.

Take care not to get lost in all that information, though. “Brands would be wise to pick a discrete focus for an opportunity and ensure that the data they need for that specific opportunity is both readily accessible and reliable,” Ferranti notes.

Here are some ideas for implementing predictive analytics into your business to boost your bottom line:

  1. Find the hottest leads for your sales team

As your analytics system evaluates data on closed sales, you can use those findings to generate personas for your buyers, and then add prospects to these personas based on demographics and other information. This can help your sales team target the prospects most likely to buy from the get-go, rather than having to initiate contact and discovering that the prospect isn’t interested after time, energy and resources have been invested.

  1. Predict buyer behavior

Big Data analytics really shine when used to predict future behavior. Past customer purchasing behaviors can be analyzed rapidly to predict how your company’s customers might respond to future offerings. Analytics can also be used to compare and predict outcomes of different promotions and marketing campaigns.

  1. Generate accurate buyer personas for targeted marketing

Effective marketing requires accurate, detailed buyer personas for your ideal customers. Data analytics offers a powerful way to generate personas for current customers based on past behavior. These personas can then be used to selectively target your marketing.

“Specific target marketing, the kind that’s attainable through predictive analytics applications, is a great way to reduce inefficiencies,” says Harrison Brady of Frontier Communications. “Buyer personas really help narrow your focus so you can get more out of your investment and avoid spinning your wheels with strategies that won’t resonate with a specific group. And that wouldn’t be possible without the data and analytics backing up those buyer categories.”

  1. Segment and target email campaigns

For an even more automated approach, use your analytics to segment your email marketing. Using data from past campaigns, along with buyer personas, you can use analytics software to explore which email strategy will work best for different types of customers. From there, you can assign your customers to persona lists or segments based on their history, ensuring they get the appropriate email messaging.

This approach can also be used to great effect with small details like subject lines. Certain personas may respond better to different subject types, so you can really maximize your open rates by honing your message to specific groups.

Possible roadblocks

For predictive analytics to be effective, the software needs quality data, and lots of it. The more testing and data points you can provide, the better-quality predictions you’ll get. This is why companies like Google and Facebook collect so much data on their users: quantity matters when it comes to data analytics.

As a result, very small businesses with only a handful of clients at once may not be able to get as much out of predictive analytics as larger organizations with hundreds or thousands of data points. This is probably the single largest hurdle a business will encounter when getting started with analytics — getting the volume of data needed to make the analytics effective. It can take time and a healthy investment, but it’s worth it.

Predictive analytics can be a powerful tool for sales teams looking to maximize their efforts and close more prospects. If you’re not using analytics in your organization, it might be time to rethink your strategy.

To explore the advantages from, and avenues for, shortening sales cycles in both marketing and sales operations, download this comprehensive report: Secrets to Shortening Sales Cycles and Growing Marketing and Sales Effectiveness.

 

Alec Sears graduated from Brigham Young University in public relations and business management. He is a digital journalist with a focus on the latest trends in business marketing.

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