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How to Develop Predictive Analytics Models for Marketing

How to Develop Predictive Analytics Models for Marketing

Here’s something you might have figured out about ABM by now: success might look different from what it looked like in your company’s pre-ABM era. Maybe you don’t know what it looks like at all — which wouldn’t be surprising, considering research shows that 82% of ABM programs fail to achieve measurable success. If you’ve invested some of your budget into predictive analytics marketing technologies, you probably want to know what success should look like, and that’s what we’ll try to unpack: what do the predictive models of the other 18% look like? And what are the benefits of having a streamlined campaign?

What is Predictive Analytics and why should you be using it?

Predictive Analytics is an important piece of modern Account Based Marketing campaigns and allows you to more accurately discover information about your target accounts. When using predictive analytics you are able to discover research and buying habits for each account. Predictive analytics allows you to tailor your marketing messaging and target an individual account when they are most active.

You need to define your goal.

Here’s the thing: your predictive model is going to vary based on your desired end result. Success doesn’t necessarily mean higher ROI…but it might. On the other hand, success to you could look like reach or breaking into a new vertical (or any other number and/or combination of goals). The very first step in determining what a successful predictive model looks like to you is determining what you’re after.

Let’s say your main goal is ROI.

In a blog post following Predictive Analytics World 2014, Sri Srikanth, a member of the Advanced Data Analytics and Strategy team at Cisco, wrote:

“This is spoken of very often, but frequently in an attempt to develop the “right” or “perfect” model, the focus on ROI sometimes begins to waver. Being driven by ROI implies understanding which variables are controllable by the business, which data observations are of real interest and sometimes making adjustments to accomplish that. This may mean considering variables that are otherwise not significant, or oversampling certain data observations and so forth. But a relentless focus on ROI will yield the desired results.”

In other words, if your end goal is ROI, you need to really focus on ROI – understand what variables are in your control and harness them, but also understand that some variables aren’t. This also means that achieving better ROI involves some trial and error. You may be surprised by the predictive datasets that can really work for you, so it’s important not to discount any potential assets in the beginning stages. You can always trim the fat later.

But maybe your goal is more specific.

Everybody wants ROI, but some prefer to recognize that ROI is a long-term goal and that there are more niche ways to achieve it in the long-term. Naturally, if you have a more specific goal than just “increasing ROI,” your model is going to look slightly different. A predictive analytics model that wants to break into a certain vertical, for example, will include tracking keywords that pertain to that vertical, researching decision-makers in big-name companies within that industry, and some carefully crafted messaging.

Knowing your goal = knowing your success.

Once you know what you were hoping to achieve with your predictive model, you can determine the metrics that reflect your success and where you want to be at each stage of the campaign. To quote the Predictive Analytics Times, “We, as analysts, need to understand the intent of the model and match the metric we use to that intent.” Assessing those metrics at least weekly will leave you with a lot of benefits that will help to contribute to the long-term success of your efforts:

  • The ability to quickly change tactics that aren’t working, which leads to more confidence in your campaign
  • The ability to learn to make better data-based decisions
  • Campaigns that are more focused on your end goal
  • The ability to have a less bulky, more streamlined campaign with metrics that matter

Stay tuned for a post about how we at MRP track, specifically, the success of our own Prelytix campaigns using AI technology!

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