Activating customer data for AI marketing: From aspirations to reality
Today’s B2C marketers are increasingly tapping the power of AI marketing to drive greater revenue. According to a recent study conducted by Blueshift in collaboration with TechValidate that has been featured in Forbes, 43 percent of marketers are already using forms of AI, including machine learning, to expand their audiences. And enterprises that apply artificial intelligence to their business strategy in this way are enjoying impressive results: marketers who have real-time access to data and regularly use it for segmenting customers are 1.7 times more likely to exceed their revenue goals.
Here’s how leading B2C companies are using customer data and AI to succeed in a competitive environment.
Smart B2C strategies for AI marketing success
Beyond the 43 percent of B2C companies already using AI to expand their audiences, 39 percent are pursuing audience targeting. Meanwhile, 28 percent are tapping AI to enhance their product recommendations and 26 percent are weaving it into their campaign optimization. The clear majority of them — 64 percent — anticipate leaning on AI more heavily in the next 12 months. And as they do, they will primarily rely on their own first-party customer data.
B2C companies that excel with AI marketing have a markedly different strategy from their peers. Namely, marketers who unlock advanced access to their data are two to three times more likely to deploy leading-edge AI use cases such as using predictive affinities for segmentation, employing collaborative filtering or leveraging predictive models for personalization. Enabling nontechnical business users to independently access data without the help of an IT or data-science professional is a key factor in making these AI deployments viable.
Marketers who are empowered to use data directly, without IT involvement or the need for complex manual SQL queries, activate 1.6 times more customer data for use in their campaigns than their peers who lack such agency. In fact, 56 percent of the organizations that free their marketers’ hands in this way are able to access more than 50 percent of their customer data. Successful data activation correlates to revenue success — 70 percent of the organizations that used 75 percent or more of their data exceeded their revenue goals.
Common challenges with customer-data activation
While leading B2C companies are enjoying the fruits of their early AI initiatives, most marketers are still struggling with their customer data. When asked what top challenges they faced in deriving greater business benefit from their data, 54 percent of respondents said analysis was their chief barrier. Forty-six percent named access as their primary obstacle, while 43 percent cited the ability to quickly segment their data as a stumbling block. Unifying customer data was also a tricky prospect for 41 percent of the organizations surveyed. A whopping 92 percent of respondents identified analysis, access, unification or a combination of the three as a major impediment to their progress.
Given the prevalence of these challenges, it should be no surprise that most B2C companies are still early in their maturity curve when it comes to adopting modern marketing strategies. Only 6 percent of marketers are making use of advanced AI capabilities including personalizing campaigns with collaborative filtering and predictive models. So far, marketers appear to be able to leverage AI against their third-party data sources more nimbly than they can with their own first-party customer data, so there’s certainly room for future innovation when it comes to the deployment of customer analytics with AI.
Keys to B2C success with AI marketing
Not all B2C companies are prepared to take full advantage of AI’s benefits for marketing. How can they best position themselves to activate customer data and apply advanced AI marketing techniques to it? According to the study, there are four keys to becoming an AI-ready enterprise. First and foremost, the company will need a data strategy that prioritizes access to the real-time data being generated by customers. This includes engagement and transaction data that arise from multiple touch points and channels. Such data is already considered crucial for enhancing and personalizing the mobile experience, among other things.
Secondly, to adapt Philip Kotler’s famous four P’s of the marketing mix, there are four P’s essential to successfully deploying AI for marketing: people, process, platform and performance. Key members of the marketing team should understand AI’s potential and embrace it, and marketers should be empowered to independently access and use data in their campaigns. Enterprises require a platform that provides data flexibility, transparent and readily understandable AI and the ability to deploy campaigns across multiple channels. B2C companies must also use AI to continuously optimize engagement and revenue performance.
In addition to pursuing the above strategies, B2Cs should also invest in customer-data solutions that provide a single, unified view of the customer in a way that empowers marketers to access the most salient insights without leaning on help from their IT or data-science colleagues. And as they select an AI marketing platform to power their future initiatives, they should opt for a solution that neatly integrates with other enterprise systems and puts advanced capabilities directly in the hands of the marketing professionals themselves. It’s the quickest path toward realizing AI’s most powerful capabilities.
Marketers can dramatically grow the business by getting ahead of the AI curve now. As Forbes noted in another recent article, AI will help marketing teams look at their initiatives with a broader lens, focusing more closely on big-picture decisions and strategies than they could have before. As a result, they’ll be better able to identify favorable opportunities for driving increased revenue. The path to doing so lies in activating as much customer data as possible and enabling marketers to engage more meaningfully with it.