Only a short time ago, marketers were relegated to using third-party and historical data to inform their strategies. Now, they have the closest thing to a crystal ball: AI.
By using AI software embedded with machine learning capabilities, marketers remove a lot of guesswork from their lives. After all, guessing at what someone will do based on past behaviors doesn’t always pan out. People change — and their purchasing habits change, too. AI can keep up with (and even get ahead of) those changes. This enables marketing teams to cultivate stronger customer relationships (and better results) by constructing predictive audiences.
If you’re unfamiliar with predictive audiences, you’re not alone. They’re a relatively new capability — and one you’ll want to learn more about.
As explained by AI-driven prediction software provider Nativo, predictive audiences are customer cohorts built around granular factors such as an individual’s interest in specific products or their affinity toward getting discounts. While historic data is taken into consideration, it’s not the only data that’s used to build predictive audiences. Consequently, predictive audiences’ future behaviors are far easier to anticipate.
Taking advantage of predictive audiences
Since predictive audiences are based on numerous data points, they offer plenty of benefits. The first is their ability to help marketers snag higher ROIs on their advertising spending. Remember: Predictive audiences are extraordinarily targeted, and this can translate into higher conversion rates and less budget waste.
Another benefit that comes from having a cadre of predictive audiences is the ability to be proactive instead of reactive. Marketers frequently construct customer journeys based on reactive measures, but sometimes their reactions are too late to be effective.
For instance, marketers might send an email to all customers who haven’t made a purchase in 90 days. However, this type of engagement may result in lower conversions since not all customers who wait 90 days are “at risk”. Some may simply have longer individual buying cycles than others. Predictive systems can analyze the habits of each customer rather than clumping them all together, making it simpler to send personalized, preemptive messages to encourage momentum at the right moment..
This leads to a third benefit, which is the ability to get truly personal with customers. As a brand, it can be hard to give people the personalization that McKinsey says 71% of consumers are demanding. By moving buyers into AI-fueled predictive audiences, marketers have a better chance of individualizing their experience.
Can marketing teams still automate the steps along the customer sales funnel or with the customer lifecycle? Of course. But those steps can be deployed at unique points for each customer based on multiple data points derived from first-party data.
Getting close to your customers with predictive audiences
If you like the idea of making fewer “guesstimates” about customers and fostering customized interactions between them and your brand, adopt a few new practices. First, invest in a predictive audience tool. Then, start implementing these strategies to help you enhance your customer insights and grow tighter bonds between you and your buyers.
1. Collect more first-party data
The more first-party data (which Daasity explains is data gathered from visitor behavior on your owned sites,) the more valuable your predictive audiences will be. And as you increase the reliability of your predictive audience information, you can start to understand customers on a much deeper level. For instance, you may find that some customers operate outside customary buying patterns. AI can reveal insights into why those customers act differently, prompting you to revise your marketing approaches.
Are you seeking more ways to increase the volume of first-party data coming into your company? First, make sure you’re tracking visitor movement on all the sites you manage. Next, consider gathering feedback whenever possible through surveys and forms. Finally, generate value-added content and offer it to customers in exchange for their information. The richer your first-party data, the better your “crystal ball” powers.
2. Stay on the lookout for emerging trends
As you become more accustomed to using predictive audiences, you may begin to see some trends. Take note of those anomalies. They can often be precursors to what’s going to happen later.
For example, let’s say you notice a shift in the buying frequency among customers within a certain predictive audience. The shift may tell you something more about the audience, as well as the demographic they represent. Or, it may be indicative of an opportunity to serve the audience in some significant way. Staying at the leading edge of trends helps you compete in a way that wasn’t possible before. At the same time, it allows you to anticipate what your customers are going to need in the near future, as well as introduces you to untapped customer sources.
3. Let your predictive audiences drive your decisions
The world is evolving quickly. But thanks to the dynamic and real-time nature of predictive audiences, you can make more confident decisions. At the same time, you can spot gaps and friction points sooner, enabling you to keep providing your customers with the best possible offerings, support, and overall experiences.
Case in point, you may be wondering how to engage customers who are in the mid-funnel stage and researching their options. You could solve this issue by constructing a predictive audience of qualified mid-funnel buyers. Afterward, you could deliver proactive content to the audience in an effort to encourage them to go to your site. (Bonus points: You’ll get traffic and first-party data from their visits to further enrich your predictive audience data pool.)
Practically every marketer on the planet is using some type of AI, but only forward-leaning professionals have fully embraced predictive audiences. By becoming an early adopter, you can lead your team to more wins — and make lasting, positive, and individualized connections with your customers in the process.