Are you considering the addition of personalization to your digital marketing, using AI technology? Would you like to know what characterizes the best AI engines for relationship marketing? Then you’ve come to the right place. This blog post covers the main considerations and latest stats on the rapid rise of artificial intelligence in the marketing segment.
The rise of AI has been rapid, indeed. And working at Selligent Marketing Cloud, I’ve been able to witness this evolution firsthand.
The technology was still cutting edge when Selligent introduced its own marketing-specific AI engine, Selligent Cortex, a few years ago. Now it’s become the status quo: While only 29% of marketers used AI in 2018, the number has increased to 84% over the course of 2020. And looking into the future, 36% of marketers expect AI to have a significant impact on marketing performance.
Marketing with AI transforms insights into CX
The impact on performance is broad. Implementing AI has the power to not only change your marketing, but change your entire business by extracting significance and meaning from massive amounts of data.
Here lies the main value proposition behind enhancing digital marketing with AI: The technology allows for delivering ultra-personalized, highly relevant customer experiences across channels and devices. And to do so at scale, with personalized engagement and journeys for every individual customer.
Since Selligent Marketing Cloud began offering Selligent Cortex as an out-of-the-box feature, its clients have achieved up to 20% uplift in conversion rates, among other benefits.
Then again, AI is not for everyone. It’s not to be taken as a fleeting trend, but requires serious investment in aligning your tech stack and data structure to function properly.
So before getting serious about choosing a vendor or platform for marketing with AI, here are 5 key considerations to keep in mind:
1. Not all marketing AI is built the same
The market for AI engines is booming, and global spending on AI is poised to double from $50.1 billion in 2020 to over $110 billion in 2024. But relationship marketers need to read the fine print carefully: Not all AI marketing applications deliver actionable intelligence or have the power to fine-tune their capabilities over time.
For example, at Selligent, we built a self-learning system that can adapt its behaviors based on insights gained as it processes information. Instead of adapting an AI from another segment, we trained our system, Selligent Cortex, to ‘think’ like a marketer and improve its mathematical model independently. With that said, Selligent Cortex has expanded its set of features (see 3.) and continues to train its own algorithms.
Takeaway: Just because it says ‘marketing AI’ is no guarantee it’s actually AI, or marketing related.
2. Successful marketing with AI requires structured data
Basically, even the most marketing-savvy AI engine is only as ‘intelligent’ as the data it feeds on. That’s why a good marketing AI vendor will help you prepare your data structure before implementing AI capabilities, like our team did for German carmakers Opel.
Preparing your customer intelligence for AI marketing requires a close look at your company’s data landscape, data mart, and all data processes with their KPIs. It requires breaking down silos and synchronization lags, with the ultimate goal of having crucial interaction data available in real time. I see many of our customers at Selligent who achieve this level of alignment by using our AI engine and plugging it into the platform’s Universal Consumer Profiles for a “super view” of every customer.
Takeaway: Artificial Intelligence is only as ‘intelligent’ as your data.
3. Invest in technology that evolves over time
Any good marketing AI engine will get better over time, as it churns more and more customer data into personalized marketing. Over time, the algorithms naturally improve at selecting the right data sets and creating more and more efficient customer engagement. The number of functions and applications also increases, which maximizes the ROI from your AI technology investment.
The evolution of marketing-specific AI engines has already been significant. At first, the algorithms helped by automatically identifying customer segments, creating customized journeys, and delivering personalized product recommendations and ads. Since then, it’s literally been strength in numbers as more capabilities emerged.
Using deep learning technology, today’s marketing AI engines can identify optimal message opening times and the times of day when each customer is most engaged with communications. As a result, marketers stand to benefit from automatic Send Time Optimization to send relevant messages at the perfect time.
Looking ahead, the evolution continues as “natural language processing” (NLP) technology helps engines understand the meaning of textual messages. This will add new functionality to AI platforms, like creating the most impactful subject lines for marketing emails.
Takeaway: Investment in marketing AI delivers more than a static platform, but an evolving neural network.
4. You’re already marketing in an AI world
Here’s the kicker: Whether or not you decide to add personalization to your marketing with AI, you’re already marketing in an AI-powered world! That’s because every single campaign, web page, and initiative you post online is crawled, filtered, and evaluated by AI engines that decide how you rank in searches and, ultimately, how many potential customers you will reach.
So while deciding on an AI platform is important, pay attention to the ‘pull’ side of the AI marketing equation. Your inbound marketing also needs to be optimized for AI and machine learning; for instance, by providing answers to frequent questions surrounding your products and services on your FAQ page.
With any luck, these answers will make it to the ‘featured’ search results and get millions of hits, especially when you optimize your website’s meta descriptions, structured data, and indexability for Search Engine Results Pages (SERPs).
Takeaway: It’s already an AI-powered world, we just live (and market) in it.
5. Harmonize AI with your tech stack
It’s a dream come true when an AI engine evaluates consumer preference and intent to suggest the perfect product with clairvoyant precision. But it’s all in vain when the customer has already purchased said product the day before. At worst, receiving the AI-generated message is perceived as intrusive and annoying, like all those abandoned cart messages still triggered by your Black Friday shopping spree.
Here’s where integration with real-time consumer interaction data, stored in Selligent’s Universal Consumer Profiles (see 2.), makes all the difference. Live data allows marketing AI engines to stop messaging around certain products or conversion goals, and seamlessly shift gears to post-purchase care or loyalty programs.
It’s all part of a bigger picture: A harmonized tech stack, firmly connecting data backbone, AI capabilities, and omnichannel engagement to deliver personalized customer experiences at scale.
Takeaway: Marketing with AI is no solo performance, but part of a symphony.
Conclusion
The power of AI-generated personalization comes from the ability to continuously analyze and learn from customers' reactions and behaviors in real-time, in order to deliver messages specifically to meet an individual consumer’s needs. From there, future messages are informed and brands are able to influence the next best action they desire the consumer to take. If you’re not part of the world of AI-powered marketing personalization yet, it’s time to get started!
Author
Lasse Foltmar
Partner Manager, Nordics
Selligent Marketing Cloud
Connect with me: Linked In
Lasse Foltmar is Partner Manager for the Nordic countries at Selligent Marketing Cloud, building strong partnerships with consulting and technical agencies to help brands make marketing more personal. Previously, he worked as Retail Manager for HighCo, setting up and managing loyalty programs for the retail industry in Benelux. After nearly 10 years in marketing, Lasse made a career switch, moving to Creditsafe, where he initially worked in sales and then created strategic partnerships with international and local solution providers in his role as Partner and Integrations Manager.