How AI Can Shape the Future of Personalized Marketing


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AI is integral to delivering personalized customer journeys and the platforms and tools that enable them.

AI has enormous potential to help brands deliver the individualized customer experiences that customers are coming to expect. Few brands have achieved the holy grail: an end-to-end, omnichannel, orchestrated, and personalized customer journey.

Many brands have begun their journey with personalized customer journeys. Cloud-based platforms and AI solutions have enabled a new class of customer experience. They provide real-time CX tailored to the requirements of each customer.

The possibilities are endless. From chatbots that use AI to customize helpful conversations to personalized fashion recommendations based on individual style preferences- AI takes many forms. It is integral to delivering personalized customer journeys through their platforms and tools.

Furthermore, personalization use cases and techniques have evolved significantly in recent years.

The Contribution of AI

AI can improve the customer experience and journey in a few distinct areas.

  • AI Helps analyze data at scale

People now have access to immense data, whether from devices, networks, home automation systems, or automobiles.

Automation makes it easier to distribute and store this vast amount of data. Models that were previously impossible to run can now execute against many variables, using AI tools. Undoubtedly, personalization at scale results from insights derived from data’s variety, velocity, and volume.

  • AI can power improved Contextual analytics

Personalization is effective when it is pertinent and based on specific analytics and data.

Models like neural networks or decision trees fit machine learning data better than conventional generalized linear models. They deliver better results and better context.

Certain tools help to create relevant structured data from unstructured sources, such as:

  1. Natural language processing
  2. cognitive computing
  3. sentiment analysis extraction

They can add information to customer profiles not previously used for context and offer insights into customer sentiment, allowing brands to respond appropriately.

  • AI-based insight increases customer engagement

Boosted customer engagement drives customer activation. The more personal information it may have about a customer, the more a brand is capable of better activation and greater engagement. Machine-learning-based techniques like natural language processing and sentiment analysis extract crucial customer data. This allows brands to gain relevant insights,

This data includes phrases from voice chats, requests for an AI assistant, or discussions on social media platforms.

Value creation through AI-powered personalization

Personalized customer journeys are a strong area to consider for using artificial intelligence. They hold much more potential for present and future market expansion. The process needs data sharing and platform coordination.

With AI, creating a seamless, personalized customer journey needs great teamwork, but the benefits for the customer are huge.

Personalized customer journeys require more than just marketing automation. The customer experience is customized to offer the “next best action” for the specific person based on their behaviors and propensities.

The objective is to use/purchase particular goods and services. These platforms and techniques put the customer at the center of the action by utilizing AI and machine learning.

Platforms of the following types frequently allow for customized customer journeys:

1. CJO: Platforms for customer journey orchestration (CJO) allow for the mapping, automating, and measuring of the customer journey.

It works across various channels with a customer-centric approach, letting the customer’s actions drive the journeys offered.

2. RTIM: While real-time interaction management (RTIM) platforms and CJO have many similarities, RTIM platforms are typically more driven by the business’s immediate need to communicate a specific message.

Platforms that use AI-driven propensity models to recommend the next best action or offer to a customer based on their preferences and other factors, such as past purchases and other behavior.

Personalized images and video create an immersive experience. Brands can produce a truly engaging purchasing experience by combining generative AI applications with personalizing the customer journey. Many platforms are using this strategy, and many more will undoubtedly follow.

But these platforms rarely operate in a vacuum.  They also require integrated channels that can be orchestrated and automated, as well as customer data. They deliver actionable market insights using a customer data platform or CDP, a CRM, and a purchase history.

This will be a full set of tools that link customer data to the communication channels the customer will likely use. These channels can include email, websites, mobile apps, SMS, social media, and more. A brand must engage with customers across all these channels for omnichannel marketing.

Why marketing personalization with AI is valuable?

AI aids personalization, which increases audience engagement and boosts marketing campaigns. It enables improved customer targeting. An understanding of multi-channel interactions can optimize the omnichannel customer journey. With each attempt, AI helps to achieve better user engagement, conversions, and sales.

Additionally, businesses can meet customer needs and cut costs of human resources by using conversational AI, such as chatbots and virtual assistants.

It is crucial to ensure that AI-generated suggestions for customer chats, sales emails, and other prompts are based on factual data. The data used in AI applications is extremely accurate, reliable and trustworthy.

AI-driven personalized marketing has huge potential. With the constant evolution of marketing tools, companies can stay on top of trends and gain a competitive edge in the digital environment.

The Future Impact of AI 

Many brands may need help creating omnichannel, personalized customer journeys that will soon span the entire buying (and post-purchase) experience.

They can still advance this area significantly by using AI-based and non-AI-based tools.

Let’s look at a few initial or follow-up steps that brands can take. Remember that personalized journeys are more successful when they target more channels. Their reach is broader and more successful when they include the entire customer experience.

Here are some activities for brands to cut a sure path to successful personalized customer journeys:

  • Think before beginning orchestration. Start by developing more automated drip campaigns based on behavior or interest if your brand needs more time to prepare for CJO or the next best action.
  • Increase the level of personalization. Even without cross-channel coordination, a good first step is increasing personalized messaging displayed in regular communications.
  • Boost the number of automated customer interactions. To expedite customer interactions and deliver a customized experience, you can also use chatbot/ conversational  AI.
  • Limit your use of CJO to one or two channels. Customer Journey Orchestration can still be very beneficial, even in small portions of the customer experience, even if you are still getting ready for the full omnichannel experience.

Also Read: Limitations of Artificial Intelligence that Marketers Should Know

By approaching the development of personalized journeys in this manner, brands can use AI to enhance the customer experience in an incremental yet meaningful way. As programs grow, it enables teams to learn quickly and apply those learnings better.

As new trends like predictive analytics, conversational interfaces, and deep learning advancements change how businesses conduct marketing, the use of AI for personalization in marketing has a bright future.

Companies can deliver targeted and timely marketing campaigns using predictive analytics. This increases their ability to predict customer needs and preferences accurately.

Businesses will be able to gain deeper insights from data thanks to developments in deep learning, which will lead to more efficient decision-making and individualized experiences.

Together, these trends represent a fundamental shift in marketing tactics that will enable companies to succeed in the fiercely competitive digital environment.

Personalization is transformational, and AI helps businesses build strong customer relationships, become more resilient, and respond quickly to changing consumer needs. Companies that use the wealth of data to tailor their offerings digitally have an advantage over rivals.

Swapnil Mishra
Swapnil Mishra
Swapnil Mishra is a global news correspondent at OnDot media, with over six years of experience in the field. Specializing in technology journalism encompassing enterprise tech, marketig automation, and marketing technologies, Swapnil has established herself as a trusted voice in the industry. Having collaborated with various media outlets, she has honed her skills in content strategy, executive leadership, business strategy, industry insights, best practices, and thought leadership. As a journalism graduate, Swapnil possesses a keen eye for editorial detail and a mastery of language, enabling her to deliver compelling and informative news stories. She has a keen eye for detail and a knack for breaking down complex technical concepts into easy-to-understand language.


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