Predictive analytics is a statistical technique that makes use of existing information—or, more specifically, historical data—to predict future events. It’s a pretty handy technique in many ways, regardless of what kind of organization you’re operating.
For example, when an individual asks for a loan from a bank, apart from asking for collateral, they also look at that person’s historical information, including their credit history, past transactions, and more, to predict whether they can pay for their loans. This statistical technique has many other applications across different industries, and that includes marketing.
Unfortunately, since predictive analytics isn’t exactly a common technique in marketing, not many people are aware of any strategies for it. Hence, it typically takes a great deal of trial and error to make it work with your marketing strategy. So why should you take the time and effort? Is it worth it at all? In this post, you’ll learn why predictive marketing analytics should also be used in marketing.
Utilizing trends is one of the basic techniques in marketing. It signifies that you understand what’s relevant and you’re ahead of the curve. Oftentimes, when marketers finally have sufficient data to utilize trends, they may no longer be relevant. It’s a common problem marketers face nowadays, but predictive analytics fixes that.
By predicting a trend before its popularity, marketers can get ahead of everyone else in terms of relevance. When that happens, companies can stand out from the rest of the noise in the industry. Of course, you shouldn’t expect it to be easy, even with predictive analytics.
On that note, if you want to maximize the potential of this technique, it’s best to use a B2B marketing analytics platform. This type of software often consists of functionalities that allow you to speed up the predictive ability of your technique. Furthermore, you can integrate the platform with your marketing software, allowing you to immediately apply your analytics results to your marketing strategy.
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If you didn’t know, lead scoring is a process where you rank prospects or leads according to their value to your company. It involves several factors such as the likelihood of a lead to convert into a customer or their purchasing power.
Regardless, prospects would receive attention from marketers corresponding to their rank or, as they like to say, lead score. It’s an essential part of marketing and advertising, as it allows marketing teams to spend their time where it truly counts—high-value leads.
On the other hand, lead scoring is a bit tricky, as it not only requires you to analyze the behavior of each prospect; you must also collect their information beforehand.
These may include information such as:
Although collecting data is straightforward, using these pieces of information to calculate the value—or score—of a prospect is difficult. Marketing teams often take it subjectively instead of objectively, which results in a bias in the overall ranking of leads. That’s where predictive analytics comes in.
Since predictive marketing analytics follows and analyzes information objectively, it eliminates the bias in lead scoring, solving one of the issues with this methodology. Furthermore, predictive analytics can also pull out data from third-party sources such as the internet, social media platforms, and more—all of which are relatively helpful when deciding the value of a lead to your company.
Market segmentation is a methodology that aims to divide the business market into sub-groups based on characteristics that they share. For example, suppose you operate a law firm. Naturally, your target audience would be those who require legal assistance.
If you plan to market your services to a specific group of individuals, you can segment your prospects into the following sub-groups:
Market segmentation and lead scoring are similar in one way—they both aim to help marketers focus their money, time, and other resources on things that matter. In this case, if you’re not receiving as many inquiries on slip-and-fall accidents, you can focus on creating ads and tailoring to prospects that belong in this category.
It also allows you to better understand the different types of prospects in your business market, which can go a long way in personalizing your marketing campaigns.
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Personalization is an extremely vital part of marketing. For one, it allows you to improve customer experience by tailoring to their specific needs. It also shows your concern for their individual needs, thereby enhancing brand loyalty.
But most importantly, your competitors are likely sending out the same old emails, text messages, and advertisements to the market, following the same pattern. Prospects would’ve already grown tired of these monotonous attempts to convert them into customers.
This would mean that if they encounter a unique and personalized marketing campaign, it’ll be a breath of fresh air, and they’d have more motivation to click on these campaigns as a result.
Apart from predictive analytics, other methodologies might be more efficient, which begs the question, why, out of all the techniques out there, should you focus on this technique?
As stated earlier, only a few people truly understand the value of predictive analytics in marketing, and even fewer are experienced in its arts. For that reason, if you were to adopt predictive analytics now, you can immediately gain an edge over your competitors. Moreover, this technique is slowly growing in popularity, so there’s no better time to adopt predictive analytics than now.
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Predictive analytics has always been around in the marketing world, but it never really got the chance to shine due to its complexity. However, with the advent of big data, this methodology has become more manageable, even for those who aren’t exactly tech experts.
Not only did it become more convenient and straightforward, but it has also become a lot more accurate than before. On that note, now is the best time to adopt predictive analytics, especially since it’d be difficult to catch up since the trend isn’t showing any signs of slowing down.
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