AI Self-Service: A Definitive Guide for 2023-24

Bhavna Gupta

November 22, 20235 min read

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Smart brands are using AI in self-service in innovative ways. Starbucks allows coffee lovers to place orders via Amazon’s voice assistant – Alexa. No drive-ins or checkout queues, simply voice your order, and your hazelnut brew is on its way. Likewise, Google Workspace allows brands to craft smart replies 24/7 to customer inquiries on Gmail without lifting a human finger!

The examples and use cases of artificial intelligence (AI) in self-service are plentiful. AI-based self-service options like chatbots, voice bots and even knowledge portals empower customers to find quick, contextual answers to their questions. Efficient and timely self-service leads to improved customer satisfaction, retention and loyalty for brands and contact centers.

What’s more?

Our roundup of customer experience statistics indicates that customers manage 85% of interactions without human intervention, with the help of AI-powered tools. If you are behind the AI self-service trend or aspire to lead the pack with innovative tips and use cases, this post is meant for you. It details AI-powered customer self-service - definition, benefits, KPIs, features and use cases.

Learn more: A Comprehensive Guide to Customer Self-Service

Table of Contents

What is AI self-service?

AI self-service refers to using AI tools and capabilities to empower customers to resolve their issues, access information, and perform tasks independently with zero or negligible direct human assistance. AI-based customer self-service tools are designed to:

  • Understand text and voice queries

  • Detect the underlying intent and sentiment

  • Locate requisite information using algorithms and keyword spotting

  • Craft personalized responses using traditional or generative AI models

  • Answer follow-up questions or route complex queries to best-matched agents (as needed)

The main AI self-service tools include chatbots and virtual agents, voice bots and voice recognition technology, knowledge base systems and online communities. With a solid self-service strategy, these tools can work together to enhance your customer experience and deliver omnichannel customer service while controlling your support costs with automation.

Read more: AI in Customer Service

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Benefits of AI self-service

AI self-service drives efficiency and scalability for brands while contributing to a satisfying user experience. Let’s talk about these benefits in detail.

  1. Efficiency and speed
    Self-service tools like chatbots serve multiple customers parallelly with no downtime or temper tantrums prone to humankind. They are able to switch from channel to channel and from customer to customer, fetching information in seconds, which is vital in customer touchpoints where speed is essential, such as online transactions.

    Recommended read:
    5 Ways to improve your response time with AI

  2. Round-the-clock availability
    AI self-service tools are your best bet when you want to cater to customers outside of business hours. Knowledge portals with AI search are always live, providing quick troubleshooting information on a scale human agents can’t possibly reach.  Multilingual chatbots and voice bots can deliver service that transcends geographical and regional borders seamlessly.

  3. Response consistency
    Brands can avoid subjectivity and bias in human service by using conversational AI. Response quality and brand voice are uniform, which goes a long way in fostering user trust and brand recall in a competitive ecosystem.

  4. Resource and cost efficiency
    AI and automation can handle traffic spikes and contact fluctuations without adding to your contact center headcount. Your agents are reserved for cognitive, complex tasks, while AI tools handle the routine, repetitive ones that make up a majority of incoming contact volume.

    Finance and insurance brand tackles a 110% surge in messages with the power of AI


  5. Deep insights and data-driven decision-making
    AI can analyze conversations to decipher trends and patterns in customer behavior, enabling response personalization and strategic decision-making. It indicates customer satisfaction (CSAT) and sentiment in real-time, plus gives recommendations to improve response quality and overall customer experience.

    💡Pro tip:
    Cutting-edge platforms like Sprinklr AI+ offer generative AI-powered bots that can scour conversations, revealing your top contact drivers and intents for each channel. Use these insights to expedite bot creation and testing, risk-proofing your investment in a big way.

    Editor’s Pick: Working Together for the Greater Good: Humans, AI and Customers

Top applications of AI in customer self-service

While there are multiple ways to yield AI in self-service, here are some surefire ways you must try before moving on to more complex and domain-bound use cases.

Knowledge base with AI search

During the product/brand discovery stage of the customer journey, there are times when a customer has questions about products, shipping, pricing, support and other aspects. That’s where a knowledge base with intelligent search can become a game-changer for your customer self-service.

How so?

As of now, 37% of customers find branded knowledge portals hard to navigate, they’d rather pick up the phone and talk to an agent than attempt information hunting on a knowledge base (KB). AI can accurately read customer cues and intent and serve the right information on a platter.

Moreover, intelligent search or natural language search has a self-learning mechanism (automatic tuning) that improves its algorithm over time. For e.g., if most searchers click on the third entry for a particular keyword, AI understands that the third result is the most relevant and automatically adjusts its ranking algorithm.

Lastly, AI uses natural language processing (NLP) to surface antonyms, synonyms and other related keywords to produce comprehensive search results for every query. With tools like AI-backed knowledge management systems, the AI self-service paradigm is redefined and refined to meet customer expectations and control agent case queues consistently.

Dig deeper: How to leverage AI search in help portals

The AI advantage in knowledge portals

Legacy knowledge bases use keyword spotting and mapping to surface search results. Such results are distorted owing to typos/special characters in queries and a lack of personalization.

AI-led search can overcome these pain points by:

  • Reading the searcher’s intent accurately the first time

  • Smart handling of typos and special characters in queries

  • Showing brand-approved content at the top

  • Locating relevant content in multiple sources (knowledge base, social platforms, online community, etc.)

  • Individualizing search results basis the user’s historical behavior

 Explore: Sprinklr’s AI-powered knowledge base

Conversational AI chatbots 

Traditionally, chatbots were rule-based and linear. They presented users with a menu of routine tasks like setting appointments, checking order status, sharing feedback or talking to an agent/sales. Anything out of this set agenda was beyond the bot’s scope. It would start throwing off-mark responses or simply hang.

Today, AI-powered conversational platforms engineer bots that can interpret open-ended conversations and give context-rick responses. They don’t get thrown off when the user switches intent and can tie together separate threads of conversations within the same session.

Conversational AI chatbots in Sprinklr for self service

The user need not repeat their case history or contact details to the bot, which saves a lot of time and frustration and translates into a great user experience.

Do it like a pro: Best Practices for Building Conversational AI Chatbots

Voice-led AI

As customer expectations from brands evolve, voice bots and voice-activated assistants are proliferating. These self-service tools follow a sequential process that covers:

  • Voice input from users

  • Conversion of voice to text via automatic speech recognition (ASR)

  • Extraction of meaning from text using NLP

  • Understanding the user’s intent or the action they want to perform

  • Information retrieval

  • Response delivery via text-to-speech or TTS

  • Feedback gathering using customer surveys in voice or text modes

💡 Pro tip: Sophisticated AI platforms like Sprinklr allow brands to customize the voice of bots to reflect their brand personality and differentiate themselves from the crowd. Apply your mascot’s voice or that of your favorite Hollywood star and lend a human touch to your bot.

Voice customization in Sprinklr's voice bots

 Dive deeper: Best Practices for Voice Bot Implementation

Measure AI Self-Service with 3 key metrics

Out of all the customer service metrics, here are three that can be used to quantify the effectiveness of AI self-service objectively:

  1. Self-service success rate: It refers to the percentage of self-service tasks completed successfully without agent intervention. It can be computed by using this formula:

    Self-service success rate (%) = [No. of successful self-service interactions / Total no. of self-service interactions] X 100

    If the rate is below the industry average, optimize it by refreshing your KB, providing clear guidance on the usage of self-serve channels and soliciting improvement suggestions regularly.

  2. Call deflection rate: It is the percentage of customer queries successfully resolved through self-serve channels without the need for phone calls. Its formula is:

    Call deflection rate (%) = [No. of successfully resolved deflected calls / Total no. of incoming calls]  X 100

    To boost your call deflection rate, ensure your interactive voice response (IVR) system is user-friendly and guides callers to no-voice channels painlessly.

  3. CSAT: This metric indicates how satisfied users are with your brand, products/services or interactions. It is measured using a customer survey where users are asked to indicate their satisfaction level on a scale of 0 to 10. Thereafter, overall CSAT is computed by:

    CSAT (%) = [No. of positive responses / Total no. of responses] X 100

    To increase customer satisfaction scores, include open-ended questions asking for improvement suggestions in your product, processes and people. Use AI and automation to scale your customer self-service and reduce response time.

Leverage Sprinklr to exceed your self-service goals by 150%

AI-led self-service is becoming a mainstay for the service industry, especially contact centers constantly striving for speed, efficiency and cost savings. With AI tools as the first line of support, incoming call volume and agent workload come down. As a result, the burning problems of agent burnout and overall attrition stay in check, which is good news for the support industry.

Impressive, isn’t it?

Indeed. However, AI customer support has a long way to go in terms of building customer trust and adoption. Customers, especially from technologically challenged groups, are wary of AI as a support touchpoint.

Enter Sprinklr Service – a unified contact center as a service software with a best-in-class AI engine trusted by 9 out of 10 enterprise brands. With AI in its DNA, Sprinklr delivers self-service with 90% accuracy and relevance, exceeding customer expectations every time.

Take Sprinklr Service for a free spin and witness the results firsthand.

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