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How to Improve Customer Experience Using AI

AI can improve customer experience (CX), reduce employee workload, and save costs; it produces a significant ROI and enhances a company’s digital advantage over competitors.

Not a bad start.

If you’re a business owner, we guarantee you’ll have wondered recently how to improve customer experience using AI. Using AI technology to serve people and enhance CX and EX (employee experience) is critical as your human capital provides vital expertise and insight into issues buyers experience.

The core components of improving customer experience using AI revolve around creating customer personas and an end-to-end buyer’s journey.

What Is AI?

Artificial intelligence uses advanced algorithms to mimic some of the abilities of human brains while excelling in areas where humans often stumble, such as cleaning up data or analyzing giant data sets. AI also does not need sleep, vacations, or sick leave.

You’re probably aware of the buzz around generative AI, such as ChatGPT, but AI for improving CX is based on machine learning (algorithmic analysis of massive data sets) and deep learning (multiple layers of machine learning algorithms that can identify objects, such as letters and faces).

Unlike traditional data analysis software, AI learns from the data it analyzes to improve its future predictive ability, allowing it to anticipate customer behavior.

Natural language processing is another useful AI tool. The system uses computation to extract meaning from natural human language (written or spoken) to extract the sense a person has encoded. This ability also allows AI to synthesize increasingly realistic text and speech.

AI text responses imitate human responses so well that most users cannot distinguish between them.

AI helps you improve both CDM and CRM – here’s how.

How AI Improves CDM

AI can improve your customer data platform (CDM) software by unifying customer data collected via different channels and systems and potentially siloed. While you must protect customers’ data security and privacy, the free flow of data helps your AI-infused CDM enhance CX.

The CDM can execute real-time decisioning and analysis to assist your marketing team in understanding what consumers feel, desire, and are likely to do.

Clean Data

AI can capture data more accurately than humans and identify mistakes such as typos.

It can clean dirty data, such as phone numbers being formatted differently (unspaced numbers, spaces, periods, hyphens, or dashes separating groups of numbers or brackets around area codes), ensuring customer data uniformity and eliminating duplicate customer records.

Improve Customer Retention

Natural language processing (NLP) can analyze unstructured data, such as buyer comments, identify keywords and other signals of sentiment, and alert you to unhappy customers and those about to leave.

Identifying these at-risk customers and engaging with them reduces churn, i.e.,  it improves retention. Tracking interactions with your app, including uninstalls, lets your AI learn how to predict people who are about to disengage.

A few uninstalls and lost customers become valuable data to learn from and retain more customers or win them back.

Radically Segment Your Customer Base

AI algorithms can track data such as purchasing behavior, past customer communications and behavior, interactions with your website, psychographic and demographic factors, location-based data, preferences, and referral sources to create customer personas (granular segmentation).

Improve Informational Articles

Machine learning can determine which knowledge base/help center articles are high-performing vs. underperforming, allowing you to improve the latter by increasing their relevance to customers, adding content, or updating them.

How AI Improves CRM

You can also improve customer relationship management (CRM) with AI, using it to execute predictive analysis, real-time decisioning, conversational chatbots, and other sales and support-oriented functionality.

Personalize Offerings

Data-backed customer personas allow you to display the most relevant content, recommend products and services that fit their needs and interests, and customize chatbot interaction with appealing messages.

Data gathering/data mining, statistical analysis, and modeling allow AI to engage in predictive analytics, deciding what to offer customers, when to contact them, and which channel to use. This can be done in real-time and is often known as predictive engagement.

Personalize Communications

Email is often used to engage consumers and market brands. Traditionally, it has been necessary to spend hours each week writing and scheduling emails. Segmenting one’s email list has been relatively crude (an onboarding drip sequence versus thank-you emails for buyers).

AI can analyze data points such as previously-read blog posts, the currently most popular blog post, interactions with your initial branded emails, interactions with your site, and time spent on your site. AI tools can then craft dynamic, individually-customized emails for each customer!

Eight out of ten consumers value brands automatically customizing content from context to increase its relevance to their lives and are more likely to buy from such brands.

AI also makes your brand’s messages via your site, social media, support service, app, and other channels seamless and cohesive, creating an “omnichannel” customer experience.

AI can track the frequency of customer orders, remind them to place an order and recognize their IP address when they visit so that it pulls up the details of their last order, making reordering effortless.

Expand Customers’ Horizons

Not everyone wants the same thing every time. Whether they want to try a new blend of coffee, find a new series to watch, discover better accounting software, or experience an innovative exercise program, your business can benefit from predictive personalization.

AI analyzes past behaviors and purchases (either by that person or buyers as a whole) to recommend products a customer might like. Amazon’s “Also Bought” feature is a famous example of how to improve customer experience using AI.

This is where some “friction” in the sales journey is desirable. Both B2B and B2C sales nearly double when customers encounter brand interactions during the buying journey that cause them to reflect on their needs and goals to understand them better.

AI chatbots can interact with customers to learn what they need and use real-time decisioning to tailor suggestions with near-zero latency, offer advice and insight, and use customer data and answers to chatbots to show promos, pricing tiers, or upgrades they might like.

The AI can also alert human sales agents to follow up with customers and upsell or cross-sell in a helpful, genuine way.

Improved Customer Service

Six out of ten customers will ditch a company after a single poor support experience.

The key regarding how to improve customer experience using AI is to automate basic support with chatbots and use human agents plus AI digital assistants for complex problems.

Machine learning and predictive analysis can pick out common complaints from consumer data and use this information to inform AI chatbot responses to customer queries, allowing people to find answers to FAQs and resolve simple issues quickly themselves.

Chatbots can double the speed of handling account management, invoice management, and order tracking queries.

Modern chatbots can handle changes in topic and channel and know when to refer users to a knowledge base (help center) article or transfer them to a human agent.

AI gathers customer information such as names, order numbers, dates of purchase, contact details, and their problem and feeds it to human agents, enabling them to help consumers faster and better.

If you want to zero in on the single best means of how to improve customer experience using AI, this is it. People who have a problem don’t want to repeat everything repeatedly, and this frustration often leads to churn.

Seamless, sympathetic support may be the key differentiator between brands in the coming years, with AI adoption being shown to increase customer satisfaction.

Interactive voice response (IVR) technology can be used in parallel with chatbots for people who prefer to interact with you by phone.

AI can assign customer tickets to human support agents based on factors such as the agent’s expertise regarding the issue, consumer language preferences (e.g.,  assign Spanish-speaking customers to Spanish-speaking agents), and time zone.

The Bottom Line

Improved customer experience. Greater brand loyalty. Higher sales drive by brand retention. Sound good?

Can using AI for customer service guarantee this? Well… not quite. You still have to do some work. You have to be smart in how you implement it.

Intelligent customer service is a group effort – it’s time to welcome the newest member of your team!

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