An Introduction to Predictive Modeling

Concerned that you aren’t properly anticipating the needs of your target market?

Feeling like you’re falling behind your competitors? Predictive data modeling will likely be able to help you.

In this post, we’ll help you to understand what predictive modeling is, as well as how it can seriously benefit your brand.

Then, we’ll also let you know the steps you can take to learn how to build a predictive model. We’ll finish up by telling you where you can find professional predictive modeling services that you can rely on.

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What is Predictive Modeling?

Before we go any further in this article, let’s tackle the most important question of all.

What is predictive modeling?

You may also have heard it referred to as “predictive analytics,” or “trend forecasting.”

In the simplest possible terms, predictive modeling is the process of using past consumer data and information to predict how they’ll behave/interact with your brand in the future.

In short, it helps you to not only anticipate the needs and buying patterns of your market. It also works to help you understand buying trends, identify potential pitfalls and risks, and estimate things like revenue, product success, and much more.

Notice that we used the word “estimate” here.

That’s because, as much as we’d like for it to be, predictive modeling is not a foolproof method. Instead, think of it as making the most “educated guess” possible.

The Benefits of Predictive Modeling

Now that you have a better understanding of what predictive modeling actually is, let’s take a look at how using it can seriously benefit your company.

First of all, it’s an incredibly effective way to approach risk management.

You can use the data that you’ve collected to not only identify potential risks but to actively prepare for several “what if” courses of action.

Predictive modeling can also help you increase your overall customer satisfaction. This is because you’ll be able to better understand exactly what your customer is looking for and identify gaps in your own business model as a result.

You can even get a better feel for what customers will likely expect in the future based on the data you’ve collected. This isn’t just a way to anticipate the needs of your market.

It also allows you to get out in front of your competitors.

Plus, you can gain a much deeper understanding of why you lost certain customers in the first place. Once you’re aware of this, you can prevent others from leaving for the same reasons.

You can actively create plans to strengthen your overall customer retention rate — and perhaps even win back those who left.

Predictive analytics can also help you to tap into new markets, as well as to understand when the best time to offer a sale or debut a new item might be.

This is because you’ll be able to better understand the general buying patterns of your target market so that you can plan accordingly.

Above all, you’ll just be able to provide a higher level of customer service than ever before. You can understand the needs and pain points of your market, and much more.

How to Build a Predictive Model

So, you now have a much better understanding of not just what predictive modeling is, but also the kinds of benefits it can offer to your company.

Now, you’re curious about the process of building your own predictive model.

While of course, your model will largely depend on your market, your industry, and what you’re trying to accomplish?

There are a few specific rules that you can still follow.

First, you need to clearly define the project itself. Understand which types of data you’ll need to use, how broad of a project you’d like to take on, and your deliverables.

Next up, it’s time to start actually collecting that data.

Of course, you should never get your data from just one place alone.

You’ll need to look at things like your past customer buying cycles, your number of email subscribers, your website analytics, the success rates of your past campaigns, and much more.

In addition to hard data, you might also consider sending out question and answer surveys to your customers. This way, alongside the numbers, you can gain an even deeper understanding of why your customers behave in a certain way.

Now, you’ll be ready to actually analyze all of the data that you’ve worked so hard to collect.

You’ll need to check for errors, figure out which pieces of data are the most relevant/useful to the project at hand, and create models based on the data.

You should then create several statistically-informed hypothetical situations and data models. This way, you can actually test out the data that you’ve gathered, and determine the overall likelihood of your outcomes.

Then, it’s time to put what you’ve learned into practice. Use it to forecast trends, make pitches to your clients, and much more.

Consider Professional Predictive Modeling

So far in this post, we’ve been able to quickly cover the predictive modeling basics.

Even if you understand everything that we’ve spoken about so far, you need to be honest with yourself.

Does your company truly have both the time and the technical mastery to handle predictive analytics on its own?

Especially if you’re a smaller business or even just a younger company, then the answer is very likely “no.”

You don’t want to run the risk of making costly mistakes that could easily damage your entire brand’s reputation because you incorrectly analyzed your data.

You also don’t want to make errors that could have easily been avoided thanks to proper predictive analytic techniques.

Plus, professional predictive modeling services also have some of the most effective tools for quickly and accurately monitoring your data.

Even better?

Often, they’re able to take a look at this data and your customer buying trends in real time.

This is an excellent way to stay ahead of your competition, as well as to better anticipate the future needs of your target market.

Professional services can also help you to mine unstructured data — which is packed full of insights that the majority of companies miss.

Finally, professional predictive modeling can develop a specific technique that’s relevant to both your industry at large as well as the individual needs of your business.

They can help with things like classification models, which will help you to segment your market and the actions that they’re likely to take.

They can also harness the power of regression modeling. This will help you to get a much better estimate of how much money a customer is likely to spend with your company in the next few months.

Predictive Data Modeling: Wrapping Up

We hope that this post has helped you to better understand not only what predictive modeling is, but also why it’s so important to your company.

Remember that it can improve your overall marketing strategies, help you to attract and retain more customers, and work to allow you to better manage your risk.

In short, it’s something that businesses within a wide variety of industries shouldn’t be going without.

Ready to take your predictive modeling to the next level? If so, get in touch with us to find out how we can help you.

We can’t wait to get started on making your company the best it can be.