What is predictive marketing?
Marketers are embracing predictive marketing as a sophisticated means of anticipating consumer needs and actions. Predictive technologies use advanced analytical techniques, such as data modeling, statistical algorithms, and machine learning, to learn from past consumer behaviors to predict future needs.
The science behind predictive marketing: predictive analytics
Predictive analytics can help brands determine customer responses or purchases, as well as identify cross-sell opportunities. Predictive models help businesses attract, retain, and grow their most profitable customers. The benefits from Artificial Intelligence (AI)-powered analytics is significant; McKinsey and Co. reported deep learning techniques could enable the creation of between $3.5 trillion and $5.8 trillion in value each year.1
What are the benefits of predictive marketing?
Predictive marketing leads to improved marketing outcomes and increased ROI. Companies can identify which customers will leave and when, what products/services a customer will want, or which prospects are likely to become high-value new customers and more.
How are companies using it?
Savvy companies are using predictive technologies to change the world: from self-driving cars to smart home devices – like thermostats, TVs, refrigerators – to constantly learning virtual assistants. In today’s predictive world, consumers are demanding more from their devices and services; and they expect brands to deliver.
Become a predictive organization by investing in predictive analytics tools
In 2021, brands need to have a platform or technology that is fueled by real-time data so that they can predict and manage the ever-changing needs of the consumer. This means focusing on predictive marketing to anticipate the consumer’s interest, intent, and need.
Advertisers have spent most of 2020 in the thick of all of this, as we adjust marketing strategies to pandemic behaviors and the new normal. Especially for our retail and travel clients, we really need to help them navigate and service their customers during these times. The travel industry has taken a hit – business is down by 70-80%. Marriott’s business is not; because we are helping them identify those people who are ready to travel safely and market to them.
Brand example: Marriott Bonvoy
Marriott has used consumer data to tailor their messaging and mitigate losses stemming from travel restrictions during the pandemic. Marriott’s 2020 Memorial Day email used dynamic content and personalized messaging based on consumers’ locales, providing fun ideas for places within driving distance that were safe, outdoors, and near a Marriott hotel. The email generated above-average unique open and click rates, with an open rate of 16% and a click-through rate of 9%. The campaign generated the highest conversion rate that month.
Marriott also encouraged a positive attitude with their messaging. During the pandemic, they decided to offer a sweepstakes titled “Dreaming of Brighter Days” to encourage their customers to be hopeful about what’s to come and give them a taste of the hotel amenities they’ve been missing while staying at home.
1. Invest in data: When it comes to advanced analytics, companies need to ensure they have the right data to generate predictive insights. Predictive analytics draws on a clean set of datapoints to deliver accurate insights – usually requiring both the company’s own data on their clients and prospects as well as third-party data to create comprehensive profiles. In addition, with COVID causing rapid changes to consumer needs, brands need real-time, accurate data to understand the needs of consumers and businesses alike.
2. Identify your best prospects: Every marketer knows that it’s much more expensive to acquire new customers than it is to keep them, particularly in industries with high customer acquisition costs (CAC), like finance and insurance. Predictive marketing can help companies reduce CAC by identifying the best prospects to target – accurately predicting the consumers or businesses that are most likely to be in market for their services, as well as helping prioritize targets based on intent or past purchasing behaviors.
3. Increase customer engagement and retention rates: Predictive marketing can be used to generate greater value from existing accounts and improve customer loyalty by increasing a company’s ability to predict the individual needs of their customers and personalize offers based on those needs. For example, a company can identify a correlation between specific customer attributes and the products they use to predict which customer segments are likely to need a certain product or service.
4. Personalize messaging: Companies can use predictive marketing to understand which messages resonate with various prospect and customer segments and offer the right content to help them make decisions. Strong customer segmentation is always the foundation for accurate personalized messaging. Using predictive marketing and machine learning to improve their segmentation strategies and inform their content, companies can more accurately deliver the right message to different customer segments.
Conclusion: Companies need to learn how to leverage predictive marketing to stay competitive in a changing marketing. By understanding what predictive marketing is, how it can help and the tools needed to apply it, companies can take their marketing strategy to the next level.
As Content Marketing Manager, Natasia is responsible for helping strategize, produce and execute Data Axle's content. With a passion for writing and an enthusiasm for data management and technology, Natasia creates content that is designed to deliver nuggets of wisdom to help brands and individuals elevate their data governance policies. A native New Yorker, when Natasia is not at work she can be found enjoying New York’s food scene, at one of NYC’s many museums, or at one of the city’s many parks with her two teacup yorkies.