It’s nearly impossible to know how well a marketing campaign will perform before you hit the launch button. You could have the most amazing idea backed by your creative editorial, social, and design teams. You could be pushing the campaign out on numerous platforms, targeting your core demographic. However, even the most well-designed, articulate campaigns can be a miss without leveraging real data tied to audience behavior.
There’s nothing new about looking at data to make sound decisions. Relying on gut instinct will only get you so far, after all. And a few rounds of trial and error will become expensive mishaps for your company. Making data-driven decisions, on the other hand, can lead to improved ROI, ensuring you’re getting the most out of your marketing campaigns. The key here is to lean into predictive marketing.
Predictive Marketing 101: What it is and How Can it Help You?
Predictive marketing is an umbrella term for any tactic that is utilized based on data stemming from how future customers will act. By looking back at how consumers have behaved, you’re more likely to know how they will behave in the future.
Predictive marketing makes use of predictive analytics — prior and current data examined for the purpose of helping predict these future behaviors. Nearly every business sector can make use of this data. Entertainment channels such as Hulu and Netflix can use this type of data to know which types of shows and movies to invest in. By analyzing patterns of watching behavior, they can know whether you’re a fan of reality television or prefer sci-fi. New content will be served to you based on how you liked similar (or dissimilar) shows and movies.
A newer development in predictive analytics is predictive audiences, or an audience built on at least one analytic metric. The overall goal of these audiences is to anticipate the needs of your consumers’ current and future needs. An example of a predictive audience is building a segment of users who are more likely to make a purchase in the next month. You’ve identified these users by how often they’ve returned to your site, visited your social media channels, and perhaps signed up for your newsletter, too.
Predictive audiences are arguably the wave of the future, mainly because they rely on AI learnings and first-party data. With third-party cookie deprivation, it’s going to be harder and harder to learn more about your audiences through data owned by others. Because marketing teams have relied on third-party data, shifting to predictive audiences can feel like diving into uncharted territory. However, it’s better to make the shift now than be left behind.
If you’re unconvinced that this is the direction your team needs to go, read on. Here are three ways to leverage predictive audiences that will lead to marketing wins for your team:
1. Find New Audiences
One of the greatest challenges for any business is identifying and reaching new audiences. Your business will remain stagnant if you are only reaching the same customer base. This marketing challenge can be helped through the use of predictive audiences. With this method, you can look at past data to identify the preferences of potential new audiences. By tailoring your marketing tactics to align with these new audiences, you’re able to better reach and engage them.
This is a more proactive approach to finding new audiences, one that helps shape future market research. It will also help diversify your current customer base. Rather than reaching the same type of customer, you will be tested to market to similarly-minded audiences. A gardening store, for instance, may find that in addition to targeting contractors for gardening needs, they can also target new homebuyers.
It’s important to note that predictive audiences are not the same as lookalike audiences. Although both rely on data for audience segmentation, lookalike models assume that past consumer behaviors will be the same as future consumer behaviors. They also have heavily relied on third-party cookies, making their extinction forthcoming. Predictive audiences provide a more adaptable view of options, relying instead on AI and first-party data.
2. Deploy Targeted Recommendations
With predictive audiences, you know what your current customers are interested in. Back to the entertainment example, you know whether they like reality television or sci-fi. Having this data in hand, you’re able to send out targeted recommendations that are more likely to suit their interests. Personalization is key in marketing, so customers will appreciate a brand that sends them recommendations that are tailored to them.
You can provide these recommendations directly on your site, like Amazon does on each member’s homepage. Or, you could have a product roundup on the bottom of the page before a customer checks out. Seeing what others have purchased or what can go along with a product can entice users to add this new item to their cart as well.
Another option is to send out personalized email newsletters that will lure them back to your site. This is a minimal-cost solution that is fairly easy to personalize based on a user’s prior shopping behavior. There are various ways to send these types of recommendations, such as including them on an order confirmation summary page or after a user has browsed your site. Adding in a coupon code or discount never hurts, either!
3. Improve Customer Retention
Lastly, by knowing what your audiences like, you are more likely to retain them as customers. Customer retention is a metric taking how often consumers return to your brand as a way of measuring loyalty and success. If someone receives poor customer service, such as a damaged product or unanswered questions, they are probably not going to be repeat customers. On the other hand, a customer who has a great experience from start to finish is more likely to return when they need the product or service again.
Unfortunately, many companies don’t realize they are going to lose a customer until it is too late. And getting them to come back to prove yourself again is an uphill battle. With predictive audiences, however, you’re able to analyze indicators that may signal someone is unhappy sooner. For example, recognizing that customers buying one particular product on your site are less likely to make a second purchase is something to look into. Upon further investigation, you may realize that the product is not holding up as advertised and needs to be fixed.
Feedback surveys are another way to help improve your overall customer experience and boost loyalty. A survey shows that you care about your customer’s thoughts and want to ensure they have the best purchasing experience possible. Surveys can also shape future product development and build a sense of trust with your audience.
Takeaways
By using predictive marketing, including predictive audiences, you’re able to be more proactive in your marketing efforts. Instead of wasting time and money on tactics that don’t perform, you’ll be able to refer back to the data and make more informed decisions. As AI continues to develop, your predictive audience models will only improve and get smarter over time.
