Predictive Analytics: When to Use It and How

When to use predictive analytics is the question leaders ask before they invest in new campaigns, tools, or growth bets. In 2025, as AI tools and marketing automation platforms become standard, predictive models help marketers and fundraisers anticipate customer behavior with more precision — and accountability — than ever before.
I’ve written before about predictive analytics, which allow us to use the data we have on purchase histories, location and psychological profiles to predict customer purchasing habits. (Plus, check out our new infographic on the right – click to enlarge!)

The most effective teams now combine traditional regression models with AI-assisted forecasting to spot shifts in buyer or donor sentiment early — turning uncertainty into advantage.

In today’s crowded, ever-more-niche market, it’s not just smart to use predictive analytics to reach our customers and leads; it’s absolutely vital! As marketers spend more on social platforms that allow us to target down to the zip code with specific purchasing habits, it’s more important than ever that we use our data to pick the right audiences and reach them at the right time. This is why we use Predictive Analytics: to spend less money on marketing and make more money on sales! As Forbes recently noted, predictive analytics is being supercharged by AI, making it more accessible and effective for organizations of every size.

When to Use Predictive Analytics (and When Not To)?

Predictive analytics helps when you’re making data-driven decisions in uncertain conditions—here are five common situations where it pays off:

1. Are you unable to group your customer database into meaningful segments that you can target with tailored messages and offers? By starting with your customer data, and not your assumptions, you can successfully segment your customers and determine which segments to spend marketing dollars on and what messaging or offer will be most effective with those segments.
2. Are you only using monetary value to determine your most loyal customers? Combine recency, frequency and monetary value from your transactional data to complete a full RFM analysis and find your most loyal customers.
3. Are you testing campaigns and determining the highest response rate is the winner without statistical validation? Run the numbers to use science, not your gut or the loudest voice in the room, to drive your success.
4. Are you unable to discern which customer ‘segments’ within your low-responding campaigns have the characteristics of the high responders? By drilling down in your data, you can find commonalities to help you maximize revenue – or cut your losses with dead leads.
5. Are you unable to determine the attributes shared by those most likely to purchase, so you cannot score a customer accordingly? With a cross-section of all of your customers’ data, you can pinpoint behaviors to predict purchases across segments.

With predictive analytics, you can reach your customers with the strategies that are effective and at the time they’re most impactful. As a result, you can:

• Cross-sell and up-sell more effectively to your current customers
• Choose the best lists to more easily acquire new customers
• Select the best offer for each customer segment
• Test your campaigns and choose the best one
• Increase response rates for all of your campaigns

The best part is that predictive analytics works for all types of businesses. More often than not, you can leverage the data you already have in place to start better marketing, and add in more info-captures along the way as you fine tune your funnels and targets. It does require the purchase of specialized software and someone with a knowledge of how to build predictive models.

What Predictive Analytics Delivers in Practice

Predictive analytics isn’t just a model — it’s a decision-making tool.
It helps teams project likely outcomes before they spend, shift budgets with confidence, and understand which audiences deserve attention now versus later.

In practice, predictive analytics helps organizations:

• Forecast likely responders before launching campaigns
• Prioritize segments that are most likely to generate revenue
• Reduce wasted spend by identifying low-propensity audiences
• Strengthen retention by predicting churn before it happens
• Build more confident plans for boards, CFOs, and leadership teams

Here are a couple common questions I hear as organizations begin putting predictive insights to work:

Q: When should a small team use predictive analytics?
A: When you need to forecast outcomes before spending—like campaign response, donor propensity, or churn risk. It clarifies where to invest and what to avoid.

Q: What data do I need for predictive analytics?
A: Recent, representative customer or donor data with basic fields (ID, transactions, dates, attributes). Better data improves accuracy; a quick data audit reveals gaps to fix first.

Ready to see whether predictive analytics is the right move now? We’ll review your goals and data, then outline the decisions you can forecast before you invest — no obligation. At Massa & Company, this work comes together in what we call Predictive Insights — our process for helping clients turn analytics into confident decisions. Visit Predictive Insights to start.

Massa & Co. can take you from whatever state your data is in today through to creating and testing a predictive model, all to help you spend less on marketing and make more in sales! Contact us today at BDMassa@MassaInc.com or (312) 463-1050.

Food for Thought: Crock Pot Chicken Soup

Speaking of needing help with something that seems hard at the moment: Food is obviously a passion of mine, and given that you’re reading this section of a post on predictive analytics, you must love it, too. So imagine the absolute agony of being laid up all winter with an ankle injury that left me unable to walk or spend time in the kitchen for weeks! Talk about devastation.

Thankfully, I discovered this tasty dump recipe for crock pot chicken soup, and I practically lived on it for two months through the slow process of healing. Using the modern luxuries of online grocery shopping, I got everything I needed, dumped it into my slow cooker and climbed back into bed. In these final cold weeks in Chicago, I can’t recommend it more highly. Image and recipe via Damn Delicious.

 

Contact us to get started on your predictive insights project today: BDMassa@MassaInc.com or (312) 463-1050.