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Artificial Intelligence (AI) Powered Customer Service

June 23, 2021 1 Comment

Top 5 Topics Covered

  1. Current trends in the adoption of AI as applied to customer service.
  2. The business case for AI adoption in customer service.
  3. Common use cases for AI powered customer service delivery.
  4. Real companies that have implemented AI driven customer service.
  5. How to get started implementing AI applications for customer service.

The application of AI for customer service has been traditionally viewed with skepticism and believed to be somewhat bleeding edge as a non-matured and risky investment prior to 2018. While this has been true up to that point in time, this reality is quickly changing for the following major reasons:

  1. AI software applications now have proven the business case for implementation in that the business value delivered vastly exceeds the initial implementation investment costs.
  2. AI application functionality has stabilized to the point of being highly reliable and mainstream.
  3. There are now several common and proven use cases for the application of AI for customer service.
  4. There are now numerous best-of-breed & enterprise-level AI customer service applications to choose from vs. just a very few.

Companies have now caught onto the fact that AI can help improve the delivery of customer service and exceptional customer experiences while simultaneously accomplishing the following wins (Quadruple win!):

  1. Decreasing the overall cost to serve customers.
  2. Decreasing the reliance on expensive human capital to deliver customer service.
  3. Increasing the levels of customer insights and customer intimacy.
  4. Changing the company’s customer service from a reactive model (i.e., upon customer request) to a predictive and proactive model (i.e., upon automation detection of latent customer need).

Accordingly, recent studies and statistics have pointed to the trend of AI adoption by companies accelerating per the following credible studies:
• “Eight out of ten companies have already implemented or are planning to adopt AI as a customer service solution by 2020.” Source, Oracle: https://www.oracle.com/webfolder/s/delivery_production/docs/FY16h1/doc35/CXResearchVirtualExperiences.pdf
• “AI chat and other bots will power 85% of customer service-related interactions by 2025.” Source, Gartner: https://research.aimultiple.com/ai-stats/#customer-service
• “AI will power 95% of all customer interactions by 2025, including live telephone and online conversations.” Source: https://servion.com/blog/what-emerging-technologies-future-customer-experience/

Here are some of (small sample) the more common use cases for the adoption of AI powered customer service:

  1. AI Powered Social Listening to detect customer issues, trends, brand mentions, etc. and with proactive workflows to help the internal team resolve these issues.
    This capability allows AI to perform real times scans of 1,000’s of social media posts and media channels including mobile application data to spot social mentions, potential customer service issues, potential product/service defects, brand and/or company mentions, etc. that are trending. The more powerful tools also search and respond to specific customer service inquiries from a multitude of channel sources. Here is an example of a social brand listening dashboard from Brandwatch:

Brandwatch Social-Brand Listening Dashboard

Source: https://martech.org/6-of-the-best-social-listening-tools-for-2019

Several durable goods product/manufacturing companies use this function for listening to track trending potential product defect issues like “my front loading xyz brand washing machine keeps growing mold” or “my air bag caused extensive injuries during my crash”, etc. to get ahead of potential disastrous crisis’s and then manage them proactively.
Here are a few good articles that point to some of the leading social listening tools for the purpose of providing improved and more proactive customer experiences.

https://www.aitrends.com/ecommerce/social-listening-tools-powered-by-ai-going-for-deep-personalization/
https://martech.org/6-of-the-best-social-listening-tools-for-2019

2. AI powered customer account authentication & access via advanced number/voice recognition and biometrics. Instead of having to remember your password for each account, wouldn’t it be great to use your own unique physical identity to securely access your accounts? These physical identity attributes include your unique voice, eye attributes, and fingerprint to name a few. Many banks are quickly adopting this new capability by allowing people to access their accounts simply by speaking their voice into their phone. I first encountered this on my personal funds account and have since seen this at several banks. Here is a great example from HSBC bank as to how AI voice recognition is powering bank account authentication and access. Source: https://ciiom.hsbc.com/ways-to-bank/phone-banking/voice-id/#tab-2

HSBC Customer Voice Account Authentication and Access

3. AI powered customer personalization. There is a growing need to better develop and understand customer profiles and to develop personalized content based on this specific profile. With the help of AI, a deeper understanding of customer’s specific needs and unique profiles is now possible. Here is a great graphic depicting this capability from Unfold Labs:

Unfold Labs AI Driven Customer Personalization Solution

Source: https://unfoldlabs.medium.com/ai-driven-personalization-6dc9c47c1418

4. AI powered agent matching via AI call classification and intelligent call routing. Based on triaging the reason for the customer to contact the company in #3 above, AI then matches the customer-need to the best available customer service agent (i.e., those who specialize in resolving those specific customer needs). The call is then routed to the best CS agent with a pre-brief on why the customer is contacting them, their interaction and purchase history, any previous known attempts to resolve this or any other issue, etc. Here is a great pictorial of how Genesis Predictive routing accomplishes this along with a high-level explanation of how it works.

Genesis AI Predictive Routing Solution

Source: https://genesys.miratechgroup.com/genesys-predictive-routing-the-perfect-customer-agent-match/

Below is another great example of this from Affinity Intelligent AI Interactive Voice Response (IVR) system.

Affinity Intelligent AI Interactive Voice Response (IVR) system.

Source and details on the above graphic: https://www.nojitter.com/afiniti-taps-ai-optimize-customer-agent-pairing

  1. AI powered customer service agent interaction response improvement suggestions.
    Bots will scan customer service agent’s sessions (calls, chat, text, etc.) and then suggest in real-time optimal answers to improve customer satisfaction and to standardize the customer experience. Here is an example of how Digital genius suggests who will respond (agent or Bot) and what the content of the reply should be:

Digital Genius AI Automated Customer Response Engine

Here is a great video from Digital Genius explaining how it works, what is does, etc. https://www.youtube.com/watch?v=NkvJ21aje84

6. AI powered customer service and ecommerce chatbots with advanced analytics. Chatbot are being used in increasing numbers by companies due to the simultaneous increase in chatbot customer service capabilities as well as decreased cost of these solutions. Here is a great example of Dom, the Dominos pizza chatbot located on messenger, Facebook, website, etc.

Dom, Domino’s Pizza AI Driven Automated Chatbot

Source: https://www.chatbotguide.org/dominospizza-bot

Chatbots are also increasingly being used to automate the ecommerce process for ordering, re-ordering, resupply, etc. Here is a great example from Hewlett Packard being used to service customers ordering or reordering toner cartridges, using the leading Netomi solution for their AI chatbot solution.

HP Netomi ecommerce Solution for Ink Reordering

Source: https://www.netomi.com/ecommerce-chatbot
Read other use cases in the above article on Sephora, Tommy Hilfiger, Harry Rosen, eBay, etc.

  1. AI powered call mining & analysis with systemic improvement recommendations & workflows. These applications are designed to be the powerful engine that analyzes and recommends systemic improvements for agent customer interaction. Think of these applications as the 24×7 call center director’s expert analysis assistant that never sleeps and has the ability to monitor the equivalent of the combined workload of 100+ top expert analysts. Specifically, here is what these solutions like Call Miner from Eureka can accomplish:
    A) Analyze: Better understand conversations with root-cause analysis. Discover what matters most with omnichannel customer journey mapping that scores performance, tags transcriptions with sentiment and emotion, and delivers customer insights that drive business growth.
    B) Coach: Create cultures of improvement and persistent optimization. Improve customer experience and agent performance with automated scoring, data-based feedback, and progress monitoring.
    C) Alert: Real-time guidance. Gain immediate awareness of next-best actions to turn around a negative customer experience and reduce risk for fines or legal action – all driven by powerful AI and ML capabilities.
    D) Capture: Gather speaker-separated audio. Collect high-fidelity, dual-channel audio for the most accurate conversation analysis, with encryption to ensure the security and an always-open API to integrate easily across platforms.
    E) Visualize: Compel action with data. See and share the story your data tells with an interactive, easy-to-use interface that makes it easier to drill down into the detail of a single agent or customer, and visually connects the dots between insight and action.
    F) Redact: Accurately identify and remove sensitive numeric data. Extract the value of conversation analytics without exposing private customer information.

Eureka AI Call Miner Call Analysis and Recommendation Engine

Source: https://callminer.com/products/eureka

8. AI powered Intelligent Document Processing (IDP). Leveraging Natural Language Analysis and OCR of customer documents like surveys, invoices, orders, reviews, questionnaires, etc. AI is being adapted to analyze text fields in documents to uncover customer insights and trends in order to improve systemically and increase customer satisfaction (CSAT) and service efficiency while reducing costs. There are several tools available in the market as shown on the Intelligent Document Processing (IDP) chart for Infrrd.ai which is one of the leading IDP Software vendors. View this chart here: https://www.infrrd.ai/. Other IDP leaders include Workfusion, Automation Anywhere, IBM, etc. IDP tools enable the automatic scanning of millions of documents and hundreds of millions of lines of document text, characters, numbers, symbols to extract and record key information from these documents and then aggregates and reports on the important customer facts, figures, issues, etc.

Infrrd Intelligent Document Processing (IDP) Solution

Source: https://www.infrrd.ai/product/intelligent-data-processing-platform

If your organization is seeking experienced assistance in lowering your overall cost to serve and increasing CSAT with automated and AI powered customer service, then give me a call or e-mail me at 518-339-5857 or stevenjeffes@gmail.com.


Lastly, this is just one article of over 50 articles I have written on customer strategy, customer experience, CRM, sales excellence, marketing, product management, competitive intelligence, corporate innovation, change management – all of which I have significant experience in delivering for numerous Fortune 500 companies. In fact, my blog is now followed by nearly 107,000 world-wide and was just named one of the top 100 CRM blogs on the planet by Feedspot, alongside Salesforce.com, Infor, Microsoft, SAS, etc. – Reference this informative site here: https://blog.feedspot.com/crm_blogs/.

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