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How to Budget for Predictive Analytics in 2018 (Even If Your Budget is Set)

If this year played a numbers game with your heart, you’re not alone. Data was the watchword in 2017, contributing to the documented rise of AI, ABM and Machine Learning in the B2B space. Chances are you’ve been charged with implementing one or more of these tools in 2018. Maybe you’ve already trimmed your list of products and people, now it’s time to write and file the darn thing.


And if you haven’t made room, never fear. Investing in predictive analytics doesn’t have to be a lump sum that mucks up your earlier work. This is a tool you can use for all your marketing campaigns, or just a few to complement your existing tests. Though the choice is yours, the only bad option is doing nothing at all.


Where 2017 was experimentation, 2018 will be implementation—there’s never been a better time to learn from the successes of others. Maximize your predictive budget by segmenting your spend, leveraging your database, and distributing across channels. Below, we’ll go into each of these in detail. With a small commitment to each of your campaigns, you can increase ROI and take the guesswork out of lead generation.

1) Segmenting Your Spend
In March, Alexander Leeds wrote about the optimization of marketing channels at Squarespace, where he works as Strategy and Data Science Lead. Whether it’s “TV, online radio (like Pandora and Spotify), podcasts, and Internet display ads. The more we spend, the less efficient most channels become.” Apply this idea to your predictive spend. Embracing ABM fully on a Q1 promotion, for example, and not at all on your mid-year product launch isn’t going to teach you much about the performance of either. Instead, devote some time and dollars to following up on last year’s campaign—who was the receptive audience? What did they buy, and how much? Now how can you get them to buy again?

2) Leveraging Your Database
Onboarding any new products in 2018 means it’s essential to take stock of any tech you’ve employed in the past. Otherwise, one or more ingredients to the perfect model could slip down the drain. Luckily, Salesforce, Mailchimp, and Hubspot integrate with almost anything, making it easy to craft new insights from prior work. Stakeholders, after all, are most attracted to the ideas that will drive a return. Convince your superiors you’ll be using what you already have.

3) Distributing Across Channels
While the principles of predictive analytics are the same in e-mail and social media, different approaches will work for your audiences on those platforms. Since, for example, customer-facing campaigns occur alongside prospecting from sales, marketers should keep sales in the loop when scoring the outcome. That’s why you need to diversify, measuring each of your model’s results separately.

It’s clear that predictive analytics is essential to a successful marketing budget, but implementing it does not have to break the bank. In fact, it could be the easiest addition to your 2018 budget. By leaving room for discretionary spends on each campaign your team can capitalize on this trending technology, then scale it to match your future efforts.

This post originally appeared on MarTechAdvisor, December 21 2017

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