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Can AI Customer Journey Transform the Customer Experience?

Here’s how AI customer journey transforms customer experiences across online and offline channels, giving marketers a more holistic view of their audience.
14 Min Read
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Table Of Contents

    There’s been a great hubbub around AI, and rightly so – it’s simplifying marketing in a way never seen before. A report by Salesforce indicates that 51% of small and medium businesses or SMBs are using artificial intelligence in their day-to-day activities, while an additional 27% plan to adopt it in the next two years.

    AI and machine learning technologies can now process customer data and automate repetitive marketing tasks, offering real-time insights and product recommendations.

    Marketing technology is not the only thing changing; your customers are also evolving. Their expectations are growing, and ensuring customer satisfaction at all touchpoints is getting harder. Users don’t ask but demand personalization at all levels – they’ll jump ship if they don’t get it.

    So what do you do in such a situation?

    It’s simple: start leveraging AI and advanced analytics systems to build AI customer journeys. Incorporating AI into customer journeys will transform customer experiences and automate customer support processes via AI-powered chatbots and virtual assistants.

    What is customer journey?

    A customer journey is the path people follow to get to your products or services, including all their direct or indirect actions and interactions with your brand, sales, and customer service teams. This path is not straight – it doesn't go from point A to B – but rather a unique zigzag of customer touchpoints that come together to form their buyer’s journey.

    No two individuals share the same customer journey. For instance, one person might visit your ecommerce website directly while the other might find you through a social media forum.

    And it’s never two platforms either; it can be three to seven. Customer journey mapping is critical for brands that want personalized customer interactions. According to Gartner, 50% of organizations already have customer journey analytics (CJA) in place, with 45% planning to start investing in it within the next 12 to 18 months.

    When it comes to customer experience, marketers must map a prospect’s journey to identify their goals, motivations, and preferences, along with the purchase barriers.

    A person wants to listen to good music – that’s his goal. Because he is sad and wants to feel happy – that’s his motivation. So, he wants to find a feel-good music playlist – that’s his preference. But, he cannot find a music streaming service with a mood-boosting feature. This is the barrier that companies need to overcome.

    There are two ways to address this problem:

    1. A digital music service can develop a mood board if they don’t have one.
    2. If they do, the marketers must highlight and promote it using ads, emails, social posts, and PR promotions.

    Once the listener finds what he is looking for, he will listen to and share the playlists with his friends on WhatsApp or Instagram.

    Spotify does a good job with this.

    It uses AI and machine learning algorithms to analyze a user's listening habits, song preferences, and play history. It then creates a playlist tailored to their interests. The app also sends notifications and makes it easy for the user to share a song.

    Like Spotify, brands can overcome friction points after they identify it; what it is, why it is, and where it is. Once done, they can eliminate them and influence the rest of the buyer’s journey, peppering it with personalized content, imagery, messaging, and advertisements. Elements that leave a memorable impression, foster brand familiarity, and build customer loyalty.

    7 stages of the customer journey

    A customer journey map is the pole star to navigating the highs and lows of customer experiences.

    It not only helps you understand your business from the perspective of your buyers but also helps you spot the barriers that customers encounter in the quest for the perfect solution to their problems – that is, your products or services.

    Usually, a customer’s journey includes seven stages:

    • awareness stage
    • consideration stage
    • purchase stage
    • onboarding stage
    • usage stage
    • retention stage
    • advocacy stage

    Let's look at how users navigate each stage and turn from prospects into paying customers.

    1. Awareness

    The point where things are put in motion. Customers learn that they have a problem, which needs to be solved. They come across your solution – your product or service – via Google, social media, search ads, or referrals. Then, they start conducting initial research about your brand, visiting your product websites, and checking out customer feedback.

    2. Consideration

    Prospects have found you and want to make a purchase decision. They are actively comparing and rating different options against each other by evaluating pricing, features, reviews, and customer testimonials. Everyone wants to be as thorough as possible, and they might even join online communities and forums for better advice.

    3. Purchase

    After carefully scrutinizing all options, customers decide to buy your product. They add it to the cart, select a payment method, and finalize the transaction. Once they receive the order confirmation via in-app notifications, email, or SMS, the purchase is complete.

    Remember, a purchase for a physical product is only complete after the order has been delivered to the customer.

    4. Onboarding

    Buyers familiarize themselves with the product and learn to use it. Most companies send a welcome email with setup instructions and tips, while others might reach out to agents from company contact centers. Users onboard the service by following set-up instructions and connecting to relevant platforms.

    5. Usage

    Once onboarded, customers start using your product and explore its features, functionalities, and benefits. To reduce customer churn and build loyalty, the brand must resolve queries and complaints using customer helplines and chatbots.

    6. Retention

    Users continue to use your solution and derive real value from it. They appreciate customer service that quickly solves their issues and enjoy receiving offers and product recommendations that nurture their relationship with the brand.

    7. Advocacy

    If customers are satisfied with your services, they will likely become advocates for the brand and recommend it to others, like their friends, family, or acquaintances. They might also create user-generated content (UGC) in the form of positive testimonials, social media posts, reviews, and videos.

    Businesses should leverage this data to improve customer experiences and incentivize users to spread the word about the brand.

    So, what is AI customer journey?

    AI customer journey is like your regular customer journey but infused with artificial intelligence and machine learning systems. It aids and enhances every customer touchpoint, from awareness to post-purchase consumer interactions.

    We're talking about dynamic ads, interactive content, and humanized customer support chatbots made not for cohorts but for individual people. At scale.

    “Competitive advantage will be based on the ability to capture, analyze, and utilize personalized customer data at scale… and use AI to understand, shape, customize, and optimize the customer journey,” authors David Edelman and Mark Abraham write in "Customer Experience in the Age of AI" in Harvard Business Review.

    Proper use of customer data is the key issue today.

    As with everything AI, you need large amounts of data to make AI customer journeys possible. This can include all qualitative and quantitative data forms, like web analytics, CRMs, social media data, competitor intelligence, surveys, feedback, reviews, and ratings.

    The problem is that it’s tough to get actionable consumer data.

    It’s not that people don’t want to use it. Although 60% of marketers utilize data to inform their marketing decisions, they lack confidence regarding data quality and accuracy.

    data quality statistics

    You can get over this problem by putting advanced analytics platforms and people to work. AI can also help out by collecting, cleaning, and processing said data, saving time and resources for more fruitful endeavors.

    Once you've solved your data problems, you can create a customer journey map.

    AI systems will analyze your user data and map a virtual buyer journey that reflects the original one. You can use predictive analytics and sentiment analysis models to understand customer behavior in everything they do, studying millions of possibilities and data points. Additionally, AI recommendations allow you to change a negative customer experience into a positive one.

    AI customer journeys can track a user throughout the customer lifecycle and spot upsell and cross-sell opportunities for more revenue.

    Combined with autonomous marketing systems, they can quickly respond to changes in the market; it doesn’t matter if the change is macro (at the industry level) or micro (at the user interest level). You can find instances where frictions are arising and get the best solutions to mitigate them.

    AI customer journey vs traditional customer journey

    As we move on to the future, traditional customer journeys aren’t going to cut it out anymore. This is the age of artificial intelligence and machine learning – advanced technologies that do the work of ten (thousand?) people at once and in less time.

    It only makes sense to leverage AI in customer journey mapping to efficiently predict future customer interests and preferences.

    And why not? AI customer journeys do a lot more (and then some) than traditional pen-and-paper journeys. Compared to the one-size-fits-all approach, AI algorithms can analyze user intent for millions of individuals, creating a customized journey for every one of them. Brands get unprecedented control over the whole process, using predictive analysis and real-time data to anticipate customer needs and improve their customer experience strategy.

    AI customer journey vs traditional customer journey

    Traditional customer journeys follow a linear path, with users moving through a series of organized and predetermined steps. We know that buyers aren’t this simple. They’ll comb through a bunch of platforms and websites before they end up at ours.

    The following are some more points you need to keep in mind:

    • The level of personalization available is limited and unachievable through traditional customer journeys.
    • AI systems can respond to user activities and problems immediately with chatbots and virtual assistants (VAs), which doesn’t happen in traditional journeys.
    • The traditional method is incapable of predictive analytics and cannot forecast changes in behavior or customer emotions.
    • Regardless of the marketing channel or network, AI can integrate user interactions across all touchpoints, giving buyers a smooth and consistent shopping experience. Traditional user journey maps don’t support this feature.

    Note: AI-enhanced journeys are constantly optimized. After all, continuous learning and improvement is a key trait of AI and ML technologies. These systems spot errors, learn from them, and then resolve them, ensuring that such problems don’t happen again.

    Intelligent Customer Experiences (ICXs)

    Intelligent customer experiences use high-quality audience data and AI to design end-to-end interactions between brands and consumers.

    Organizations listen to their users and respond to consumer needs with contextualized content. Contextualization is not just at the segment level but at the individual level. With access to real time data, brands can identify user intent and match it with the right products and services.

    ICX enhances omnichannel content placements, automates company responses, and minimizes friction across the buyer journey.

    Industry 4.0 technologies like AI, ML, Internet of Things (IoT), and automated martech tools supplement the whole process and help connect people with channels that simplify transactions. Of course, it’s critical to have a 360-degree view of the customer with systems that can capture different buyer signals in place.

    For example, clickstream data can track browsing behavior, which in turn can improve ad placements.

    You can combine online and offline behavioral data to launch new marketing campaigns and cross-sell or upsell products or features, influencing consumers wherever they may be. If you sell popsicles and your buyer prefers outdoor activities, you can market to them with billboards placed in popular parks and beaches.

    Give the right experience to the right people in the right place.

    Content is of prime importance when it comes to guiding prospects down the sales or marketing funnel. Intelligent customer experience systems collect sample content and bring it to buyers in the desired language, tones, formats, and views.

    One can make use of conversational AI tools like ChatGPT to develop humanized chatbots that assist users in their research, consideration, and post-purchase stage.

    It goes without saying that you need to test all your customer workflows relentlessly – measure KPIs, make changes where required, and monitor both positive and negative impacts. Build a tech stack that automates experiences across multiple platforms and devices, and facilitates long-term customer journeys with minimal human intervention.

    How AI customer journey can boost customer experiences

    AI customer journey maps are not just about collecting data points – they are about treating customers as real people, not entities behind a computer screen. They eliminate errors and negative customer experiences by focusing on the correct users.

    AI customer journeys boost customer experiences

    However, you should clarify some points before using AI customer journeys in your workflow:

    • Do you have a data collection and implementation strategy in place?
    • Is data available readily on one platform or is it still siloed?
    • Does your company know about the cybersecurity risks and privacy concerns that come with centralizing data in one place?
    • Are your employees sufficiently trained to use customer data and AI to make decisions?
    • Do you have a strategy in place to ensure cross-department collaboration in your organization?
    • Most importantly, does your company possess up-to-date user data and technology?

    If the answer to these questions is in the affirmative, then you're set to leverage AI customer journey maps. Yet, if the answer is no, you'd be going around like a headless chicken. So, take a breath and cross these items off your checklist before moving forward.

    In the awareness stage

    Prospects are curious about your products in the awareness stage of the customer journey. They do a lot of random things that don’t necessarily mean anything. AI journeys can play a role here by identifying positive customer behavior, intents, and actions.

    You can reaffirm positive actions with customized promotions and engage users with interactive videos and conversational virtual agents.

    Live chatbots can offer informative content tailored to that user and create a good first impression. This can be followed by product recommendations that suit their interests and preferences.

    A site like Airbnb could employ AI customer journeys to provide travel suggestions based on users' past bookings, searches, and travel history.

    In the consideration stage

    Buyers look at past customer inquiries, reviews, and feedback to make purchase decisions. They continuously hit up Google and visit your website's product pages for more information. AI models can analyze these transactional keywords and search volumes to make suggestions for paid search advertising.

    You can use generative AI tools for content, copy, and videos.

    Dynamically optimize ad content and copy based on user intent to fill any gaps in your marketing strategy. You can even tailor product descriptions and features based on buyer attributes, values, and browsing behavior. So, if you sell electronic items and a major segment of your audience is environmentally conscious, make it a point to highlight the sustainability of your products.

    In the decision-making stage

    Browsers are ready to become your customers. They want an easy checkout experience and user-friendly transaction options.

    As such, you need to simplify the decision-making process. This will consequently lead to increased customer satisfaction and retention. Provide thorough product details and transparent pricing plans. Make sure to respond to their queries as soon as possible – they only need a few minutes to switch to a competitor with faster support service.

    AI bots and virtual assistants make this easy for you.

    Automated marketing systems can send follow-up emails to customers who have abandoned their shopping carts, with relevant deals and promotions. They can also run retargeting ads with impactful copy, images, and discounted prices on the right platforms. Once the transaction is complete, they provide 24/7 support and show order status updates.

    In the post-purchase stage

    Selling a product should not be your only goal. You need to ensure a fantastic post-purchase experience so that your customers keep coming back for more.

    AI journeys facilitate a seamless onboarding experience with interactive videos and how-to guides, so users know how to use your products properly. Offer complementary services and do everything possible to prevent customer churn and increase product usage.

    Once users are satisfied, explore upselling and cross-selling opportunities like Amazon.

    Automated customer support can further address post-sale queries and solicit feedback from users. Since they have access to the company's knowledge base, AI support agents can resolve simple issues and escalate complex ones to their human counterparts. Agents retain chat history and get insights and suggestions during their chat with the user.

    Businesses can use chats and call recordings to measure customer satisfaction levels via sentiment analysis and find areas for improvement.

    A Way Forward

    Whether you like it or not, AI customer journeys are here to stay. They are one of the best ways to track marketing shifts and ensure a positive customer experience. Every company needs to map customer journeys and align them with organizational goals to personalize interactions and build deeper, long-lasting brand connections.

    AI technology combined with business acumen meets customer expectations in innovative ways.

    It doesn't matter whether you’re using marketing automation, predictive analytics, intelligent customer experience engines, or AI customer support agents; it’s important to adopt a fast-learning mentality to keep up with changes in consumer behavior.

    Take a sneak peek at how Delve AI can help you map a customer journey and achieve a 360-degree view of the customer with AI.

    Frequently Asked Questions (FAQs)

    How is AI used in the customer journey?

    AI helps automate and track the customer journey across multiple channels, enabling businesses to adapt to changing consumer behaviors. With predictive analytics, they can spot trends and forecast shifts in user preferences and interests. AI-generated insights can also inform marketing decisions, operations, and customer support at different stages of the customer journey.

    How is AI used in customer service?

    AI in customer service helps resolve simple queries, escalates complex ones to human agents, and provides a consistent support experience. It analyzes sentiment, speech patterns, and tone to address customer frustrations, eliminating repetition and providing contextual interactions.

    Extract and analyze customer journeys with Delve AI
    Track visitors' journeys and refine customer experiences

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