Maximizing Omnichannel Customer Experience with AI


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Are brands struggling to deliver a seamless omnichannel customer experience (CX)? Are they able to provide the same message across every touchpoint? With so many touchpoints on many different channels, offering a consistent and cohesive experience is challenging.

To boost omnichannel CX, brands must have real-time access to customer data and a deep understanding of their needs. They will need a solid tech base, collaboration across all departments, and commitment.

As per a recent report by CX Network, “The Global State of CX 2023,”


The Global State

Fortunately, brands can boost omnichannel CX using the power of AI. It is a game changer in creating seamless, personalized, and effective omnichannel customer interactions.

Here’s how AI will help brands maximize omnichannel CX. 

1. Personalization

One of the ways AI is revolutionizing omnichannel CX is via personalization. The algorithms can process vast amounts of data to understand customer preferences, behaviors, and purchase histories. This allows brands to personalize their interactions and recommendations for each customer.

For instance, the AI system can check customers’ past purchases, products in their cart, and browsing history to suggest the products they are interested in. This enhances the CX and also increases the chances of making a sale.

2. Better Customer Support

CX Network’s report also states investment priorities for the year ahead in

states investment priorities

AI-based chatbots and virtual assistants are becoming key factors of customer support in omnichannel environments.

These systems handle routine inquiries, address complex issues, and respond instantly. They are available 24/7, offering customers the support they need at their convenience.

For instance-

If a customer wants to know more about the product while browsing a brand’s website, they can initiate a chat with a virtual assistant rather than wait for business hours to make a call or send an email.

These chatbots can offer immediate answers, track order statuses, and even facilitate returns or exchanges efficiently.

3. Predictive Analytics

CX Network’s report states that

CX Network's report

AI helps predict customer behavior and track historical data and current trends to anticipate customer preferences and market shifts. These insights will help brands to refine their omnichannel strategies to meet changing customer demands.

4. Maintaining Context

AI efficiently tracks conversations across channels and maintains context so clients do not have to repeat information.

For instance-

When a customer contacts a call center with an issue, the agent uses an AI-based knowledge solution to understand the problem. Due to some error, if the call gets dropped, the chatbot can access the details from the previous call. This minimizes customer frustration.

5. Smart Routing

AI can smartly direct customers to a suitable resource or channel per their needs and preferences.

For instance-

If customers contact brands via social media, AI will route them to an automated bot. If the query requires human attention, it can direct them to the right call center or chat queue.

6. Automation

With AI, brands can automate repetitive tasks and queries across channels. Chatbots and voice bots can handle basic questions and requests via chat, SMS, and voice calls. This reduces wait times and takes the load off human agents.

Automation also cuts costs by reducing human involvement in basic interactions. According to CX Network’s report,

42% of brands agreed that automation

7. Human Sentiment Analysis

Natural Language Processing (NLP), a subset of AI, enables machines to understand human language. This is ideal for social media channels where customers express their thoughts and concerns using natural language.

AI-based sentiment analysis can measure customer sentiment, enabling brands to respond appropriately.

8. Consistency

As per CX Network’s report,

65% of brands agree or strongly agree that customers

Maintaining consistency across different channels is a challenge. AI helps ensure a unified brand experience by syncing customer data and interactions across all touchpoints.

For instance-

  • AI can help combine data online and offline interactions, giving brands a holistic view of each customer.
  • AI-based content management systems can tailor website content, mobile app interfaces, and email campaigns. This way, brands can stay aligned with customers’ preferences and behaviors.

Also Read: Customer Experience (CX) Tools: Why Do They Fail and What Marketers Must Do


AI is a transformative force that can streamline operations, drive efficiency, and, most importantly, enhance omnichannel CXs. AI helps brands personalize interactions, provide efficient support, offer predictive insights, and maintain consistency.

The tech also understands natural language, further maximizing omnichannel CXs. With AI’s power, brands can meet and exceed customer expectations, increasing customer satisfaction and loyalty.

Moreover, the potential ROI from implementing AI in omnichannel strategies is significant. According to CX Network’s report,

45% said revenue was the most popular gauge for CX's success.

While AI in omnichannel strategy benefits brands, it also has some data privacy and regulatory compliance challenges. Brands must clearly understand the data they collect, how it is stored, and who can access it. They must implement strong security measures to protect against unauthorized access and data breaches.

Following this, define clear policies and procedures for data handling and retention within the AI tech. Regulations such as the EU’s General Data Protection Regulation (GDPR) or California Consumer Privacy Act (CCPA) define how data can be gathered and used. This includes obtaining user consent before collecting data and providing transparency in data handling practices.

Apoorva Kasam
Apoorva Kasam
Apoorva Kasam is a Global News Correspondent with OnDot Media. She has done her master's in Bioinformatics and has 18 months of experience in clinical and preclinical data management. She is a content-writing enthusiast, and this is her first stint writing articles on business technology. She specializes in marketing technology. Her ideal and digestible writing style displays the current trends, efficiencies, challenges, and relevant mitigation strategies businesses can look forward to. She is looking forward to exploring more technology insights in-depth.


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