When mass media was invented, increasing its levels of personalization always seemed like an enormous task.
How can you speak more directly to an audience of millions when they have no apparent similarities other than the fact that they decided to see or listen to the same show? In this context, it comes as no surprise that AI and machine learning have captured the attention of the marketing industry as a whole… since they’re able to predict behaviors and give personalized recommendations.
AI-powered apps can be integrated into any brand’s strategy and help personalize its consumer interaction by learning from experience and adjusting to new inputs. This makes it easier for businesses to communicate with their target markets and personalize their experiences. Whether they do so by using behavioral data gathered through algorithms or predictive analytics, these applications allow them to create closely related audiences and deliver personalization at scale.
Customers now expect these tailored experiences, and the companies that provide them can see a clear difference. A study from Researchscape International found that around 54% of marketers have experienced a 10% increase in their sales, and 13% of them experimented a lift of more than 30%, just by implementing personalization in their process. This ends up in 97% of them assuring that they’ll continue to invest in personalized marketing efforts.
AI can give any brand a competitive advantage, causing e-commerce platforms to integrate with many third-party apps that use artificial intelligence. They benefit from AI without having to spend a lot of time or money on creating their own.
These applications, the ones that analyze voice, recognize images and assess behavior, could help businesses learn more about their prospects’ and customers’ needs and expectations. This would then allow them to better target their campaigns and deliver the right products to the right people.
This platform has an email solution that uses behavioral data (email clicks, purchase history, and other online activities) to personalize emails. One of its greatest features is its ability to create dynamic email templates. First, marketers specify the parameters that will make the application send an email, like when a visitor decides to leave its shopping cart.
Then, the tool uses machine learning algorithms to decide which message it will send to a particular customer based on the individual attributes it has collected. Eventually, it learns to predict preferences and, in the long run, potentially maximizes revenue.
This recommendation engine uses machine learning algorithms at its core. It can deliver over 500 recommendations in a couple of seconds after any user action. It uses a combination of collaborative filtering algorithms that analyze human behavior (like views and purchases), as well as content-based algorithms for titles and descriptions. These also continue to be refined while the visitor uses the site.
Recombee says that its AI is capable of deciding which algorithm it will use according to the data available. A person who continually visits the site has profile of interactions that helps the platform make better recommendations.
This AI design assistant builds websites by predicting which sections, elements, images, and design styles are truly relevant to specific industries. It scans the web to find and learn more about its clients and the type of businesses they run. Then, its algorithms gather information from its own and its customers’ social channels to determine which elements would be more relevant for that specific website.
This ai-powered app uses the company’s online texts, colors, and brand information to create branded website themes with the same color palette and a similar style, but that can be customized.
Instead of singlehandedly testing out audiences by yourself, Adext AI uses artificial intelligence and machine learning to find the best possible audience for all of your ads by automatically managing and optimizing your budget on different platforms. This, in turn, can help you get better copy content and art for your campaigns to connect your target audiences with more personalized content.
The tool may be the easiest way to start taking advantage of AI since it finds potential audiences that may never have crossed your mind. It does this by performing up to 480 budget updates across 20 audience segments for every single ad. It can be up and running after a 5-minutes set up process and allows its customers to actually see what it does on their own ad accounts.
This machine learning-based service builds natural language understanding. It creates custom models that continuously improve through a cloud-based API service which analyzes users’ conversations to predict overall meaning.
The tool extracts any detailed information that may be relevant to develop its natural language capabilities to complete a task. Unlike other “chatbot” like software, this application can be deployed to social media apps, website chatbots, and even speech-enabled desktop applications.
There are undoubtedly a lot of options for marketers to start incorporating AI and personalization into their businesses, so selecting the best possible partners for this quest is crucial. They must be serious about using machine learning and AI on their platforms.
The AI technology mentioned above will help you dig a little deeper into the unique preferences of every single one of your customers as it keeps on learning more and becoming better at predicting outcomes.
Today, with the help of AI, marketers are able to collect and analyze data that helps them personalize and contextualize their advertising messages and overall customer experiences. They do this by tailoring the messages to their customers’ needs, which (in time) focuses on prompting regular purchases.
So, even though AI technology has enabled the automation of the most repetitive aspects of the marketing process, humans continue to develop more strategies and perform more problem-solving oriented tasks. And yes, AI helps with personalization through its insights, but marketers are still the ones who (at the end of the day) define the message and the voice. They’re the ones who make the final and unique touches.
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