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How to Efficiently Transform Your Customer Service Through AI
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- 5. How to Efficiently Transform Your Customer Service Through AI Rana Gujral, CEO @ Behavioral Signals May, 2022
- 6. OUR TALK TODAY ... - Customer Service Problems - Why AI? - Voice Insights - AI by Behavioral Signals - Technology details - Who is the decision maker when it comes to AI integration? - Benefits - Case Studies 6
- 7. CUSTOMER SERVICE Customer Service is everywhere but we’re going to focus on the most challenging types: Revenue recovery, Financial services, Sales, and Customer Service over a call. 7
- 8. THE HURDLES THAT NEED TO BE OVERCOME IN CUSTOMER SERVICE ● Call center efforts are largely reactive. Someone calls in, they might be upset and humans respond accordingly, not always in the most effective way ● There’s a need to balance the goal of maximizing the outcome and customer satisfaction ● Revenue recovery organizations want to deliver a seamless process but also increase the dollars collected ● Data like voice is often not analyzed in depth, and not for 100% of calls ● There is no easy way to quantify emotional distress or any other emotion ● Staff attrition is a huge challenge ● A hastiness to move to automated services, like bots, without having solved “How do you use AI to communicate like a human” 8
- 9. WHY AI? Algorithms can be used to rapidly evaluate and identify the behavioral patterns of customers – based on previous calls and observed emotional data during a call. >> This could enable call pairing to the best-suited customer service agent to more effectively address the customer’s needs. Predictive models can be built for individual customers based on already established demographics such as their age, the type of work they do, their job title and salary, and a detailed history of their recent interactions with the company. >> This allows for a predictive approach to debt collection – identifying high-risk debtors for restructuring and deprioritizing those who are considered lower risk. AI can not only monitor 100% of calls and suggest a suitable course of action ‘during the interaction’, but also monitor for potential issues such as threat of litigation, emotional distress, compliance, predict propensity to buy or pay. It can do this while working in the background with minimum disruption to the business processes. 9
- 10. HOW BIG IS THE AI OPPORTUNITY? According to Autonomous Next Research and Business Insider Intelligence the aggregate potential cost savings for businesses from AI applications is estimated at $447 billion by 2023, where the front and middle office account for $416 billion of that total. Where will the biggest AI impact be? - A change in how financial institutions generate and utilize insights from data - It will help personalize interactions based on individual goals and create a reimagined customer experience - Drive business model innovation and create opportunities for new revenue streams such as optimizing the outcome of the collection 10
- 11. VOICE AI INSIGHTS Banks and large companies are marching towards digitization. Today, every sector, whether it’s banking, customer service, utilities, sales, must understand that using technology to convert their data into insights is the only way to stay competitive. Voice is part of that data! Voice is rich not only in content but also emotions and predicting factors such as propensity to buy. Voice data, like that collected at a customer service center, needs AI to analyze it and capture the small nuances. The Conversation AI systems are important for any company which wants to optimize its interactions with their customers and in the process drive better relations, higher customer satisfaction, improved first call resolution and cost saving among other things. 11
- 12. WHAT KIND OF VOICE AI INSIGHTS ARE WE TALKING ABOUT? Companies need to start utilizing their most powerful asset…their voice data. NOT just the spoken word, converting the audio into text and running basic analytics, but capturing subtle cues like emotions and behavioral signals unique to the customer. Behavioral signals that can help predict intent: Who’s close to buying or paying? Who’s distressed or ready to change vendor? Are companies using voice to improve their revenues, CSAT, or their employee’s performance and job satisfaction? Voice is not text. It’s a deeply rich experience that can give away a ton of information on the state of a customer’s mind and how she perceives a brand. To give you an example, our AI can search and quantify over 75 traits in any single voice file. 12
- 13. AI, BEHAVIORAL SIGNALS and CUSTOMER SERVICE 13 Our flagship product, ‘AI Mediated Conversations’ or AI-MC is a Conversational AI for Revenue Recovery, Sales, and Workforce Optimization. AI-MC uses the power of our patented tonality engine to build rich behavioral profiles (conversational bioprints) for all parties involved in the conversation These profiles are then fed to a use case specific predictive model (collections or a sales call) which creates a Pairing Index (PI) for every agent-client pair. A high PI indicates that the corresponding agent has a higher probability to ‘click’ with the client and achieve a positive outcome Good Matches => Great Conversations => Successful Outcomes
- 14. Customer id A54225 Speaker diarization Emotion and Behavior Analysis Customer id A54225 Profile confident polite aggressive 50 100 politeness detection model AI White Box: Oliver Engine 14 CONVERSATIONAL AI FOR AGENT-CLIENT PAIRING
- 15. Customers Agents Pairing Model increasing probability of success Behavioral Profiles Who is the best to talk to this customer? AI White Box: AIMC Engine 15
- 16. 16 Revenue Recovery * 17% avg increase in Revenue for Collections Sales Conversion * 8% increase in Positive Sales Outcomes (up-sell / cross-sell) * 20% increase in Agent Productivity (better matches translates into faster conversions for outbound campaigns) Customer Support + Agent Performance (CSAT) * 8% improvement in Average Handle Times (e.g. 5-minute call to 4.5-minute on average) * 7% improvement in First Call Resolutions * 10% reduction in Repeat Calls * Equal Agent Call Load (reducing agent idle time) * Agent Optimization & Schedule Forecasting (leverage AIMC data to schedule high performing agents to other business units) IMPACT
- 17. 17 Impacts and Creates Revenue AI-MC directly impacts revenue by improving positive call outcomes. ROI in weeks. Language Agnostic No ‘Spoken Word’ processing. Most languages supported out of box. Exceptional Privacy Client privacy is intact by analyzing only “how it’s said”. GDPR Ready. Measureable Scientific measuring techniques using MetaData. EXCEPTIONAL ROI
- 18. 18 BEHAVIORAL SIGNALS’ AI ENGINE Some of the 75 metrics produced: Emotions/Behaviors Arousal/Strength, Positivity/Emotional Valence Politeness Emotions (Anger, Happiness, Sadness, Frustration, ..) Engagement Empathy Agent Alerts Key Performance Indicators Propensity to Buy/Pay /Customer Satisfaction/Compliance Call Success Agent Performance Score Agent/Cust. Matching Score Behavioral Profiles Customer Engagement Operational Optimization Campaign Management
- 19. WHY DOES AI-MC IMPROVE CUSTOMER SERVICE? 19
- 20. CASE STUDIES 20 Redefining Bank’s Revenues Through its Call Center Client: EU Bank (Bank, Southern Europe) Campaign: Restructuring of Non-performing Loans Results: – 20.1% increase on Active Debt Restructuring Applications. – 7.6% Fewer Calls – $7.5M USD of additional restructured debt for the Bank Projected Yearly Upside: – $1.5 M per agent/year – $300 M Total Restructure Debt Boosting Sales Call Success Client: BPO (PagSeguro, Brazil) Campaign: Outbound, Inbound, Winback, Targeted Marketing Results: – 19.4% Increase in Sales – 5.8% AHT Boosting Agent Call Success in Utilities Revenue Rec. Client: Energy Power Corp (Utilities Corp, Southern Europe) Campaign: Optimize Collections Process Results: – 11.6% Increase on positive revenue recovery payments – Calls evenly distributed among agents – 95% Improvement in Call Success, across all agents Russian Bank Increases Revenue Recovery Client: Credit Bank (Credit Europe Bank, Russia) Campaign: Loan Revenue Recovery Results: – 13.1% increase on Active Debt Restructuring Applications Car Loans Revenue Recovery Client: Credit Bank (LocalCred, Brazil) Campaign: Car Loan Revenue Recovery Results: – 9.4% increase on payments
- 21. 21 WHERE IT SITS
- 22. DEPLOYMENT 22 Data Driven strategy Use of live and historical unstructured data Additional use of metadata Model improvement with new data Applied Intelligence Natural Language Processing Deep Learning Behavioral Signal Processing Continuous model training Economy of Scale Deployed on the Cloud Deployed on premises Hybrid solution Automation Solution runs behind the scenes with minimal need for human intervention Fully automated Monitor and analyze 100% of calls Scalable No need for special training Partnership Distribution through global experienced providers, with established presence, and open to AI innovation Maximum 3 months to full deployment
- 23. 23 AI-MC INTEGRATION ● Available integrations for: ○ Genesys Cloud ○ Aspect ○ Cisco ● Hosted on Behavioral Signals’ or Virtual Private Cloud ● The software is updated twice per year ○ The matching models are updated once every quarters ● Custom integrations to or from other sources of customer information can also be developed as needed
- 24. WHO IN ‘CUSTOMER SERVICE’ IS RESPONSIBLE FOR INTEGRATING AI SOLUTIONS? 24 > The executive decision makers need to be onboard and understand how such AI technology impacts the bottom line. > The people that are responsible for the technology stack, are also responsible for compliance and the tech coexistence and often influence decisions in a significant way.
- 25. Tech leadership team has 50+ years of cumulative experience in engineering, computer science, linguistics and psychology Research collaboration with Signal Analysis & Interpretation Lab of University of California Best-in-Breed PhDs and PhD candidates on the team Significant Machine Learning/AI, Speech/NLP and conversational system expertise Sustained research leadership and award-winning accomplishments 25 OUR TEAM
- 26. IP, RECOGNITION & AWARDS 26 Exclusive patent license “Emotion Recognition System” Winner: Gold-standard Emotion Sub-challenge at the 2018 ACM Audio-Visual Emotion Challenge Full patent filed “Deep Actionable Behavioral Profiling and Shaping” (provisional June 2018 - full June 2019) Two patents filed on “Deep Fusion for Emotion Recognition” and “Data Augmentation for Emotion/ Behavioral Profiling” Numerous award winning papers 6 time winner of the INTERSPEECH quality of human interactions & computational paralinguistics challenge Winner: Sentiment analysis twitter challenge SemEval/NAACL 2016 Led by the Signal Analysis & Interpretation Lab (SAIL) at USC
- 27. Use-Case Leader in Maverick* Research Report 27
- 28. Validated by Gartner, Omdia & Forrester The deployment was showcased by Gartner in their 3 Best Practices for Product Managers to Drive Adoption of Emotion AI Technology study, highlighting the: + Use of acoustic analysis vs text transcription for superior accuracy & outcomes + Safeguarding of debtor data privacy facilitating solution adoption and in the OMDIA report: Artificial Intelligence Applications for Financial Services 28
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Editor's Notes
- Customer service is present in every industry but we’ll be talking about the specific industries we work with, finance, banks, sales, and call centers. The global contact center market size amounted to 339.4 billion U.S. dollars in 2020. This industry is expected to grow steadily in the next years and reach a value of 496 billion U.S. dollars by 2027. https://www.statista.com/statistics/880975/global-contact-center-market-size/ https://www.statista.com/statistics/881114/contact-center-employees-united-states/
- The possibilities are endless with AI but we will mention just a few here, mostly relevant to what we do.
- Our flagship product, ‘AI Mediated Conversations’ is a Conversational AI for Workforce Optimization. AI-MC uses the power of our patented tonality engine to build rich behavioral profiles for all parties involved in the conversation These profiles are then fed to a use case specific predictive model which creates a Pairing Index (PI) for every agent-client pair A high PI indicates that the corresponding agent has a higher probability to ‘click’ with the client and achieve a positive outcome The premise here is simple. Good Matches lead to Great Conversations which in turn drives Successful Outcomes
- Our conversational AI capabilities are centered around real-time speech processing. Our AI gets behind the spoken word and focuses on the tonal attributes of a conversation such as intonations, prosidy etc. We ignore the actual words and focus on how those words are spoken. We extracts a variety of signals that can be bucketed as follows: emotions such as anger, happiness, sadness; behaviors such as engagement, empathy, politeness and intent such as propensity to pay or propensity to buy These intelligent insights can then be applied to a variety of cross industry use cases ranging from monitoring agent engagement, customer satisfaction, detecting duress etc. For this use-case, our AI white box: Oliver Engine creates behavioral profiles for all parties (agents and clients) using 75 behavioral attributes that identifies an individual’s unique conversational style.
- Our second AI White Box: AIMC Engine then constructs optimal behavioral matching of customers and agents by creating a pairing index that maximises the probability of a successful outcome. Customers are paired with their top match, or if not available, second-best match, and so on. Agent-customer profiles are matched in relation to the desired outcome. Different matches are created for different use cases.
- AI-MC positively impacts a variety of key metrics that are important to our clients, such as: 17% avg increase in Revenue Recovery 8% increase in Positive Sales Outcomes 20% increase in Agent Productivity 8% improvement in Average Handle Times And many more …
- The product not only directly impacts revenue, but this impact is accurately measurable, creating a great ROI story. Since we do not process the spoken word, the solution is language agnostic. Another nice side effect of ‘not being dependent on processing the spoken word’ is exceptional client privacy. There is no redaction necessary since there is no text to redact. We are GDPR ready and PII and Soc2 compliant.
- In a professional setting, we’re constantly meeting and interacting with new people. While our personal relationships are naturally curated – either by decades of familiarity or through personal preference in who we engage with – professional relationships are often hoisted upon us. We don’t choose who we work with or, to some extent, who we work for. To be successful, we must make these relationships work. There is always an optimal setting that allows both sides to achieve the desired outcome in a business environment. And that comes down to the natural rapport that develops between two people. That rapport can be influenced by the right conversations and the right responses at the right times. Whether it’s a sales call with a prospect, a support conversation with a customer, or a difficult conversation in collections, business turns on the interactions of real humans. The affinity between any two humans is rarely ideal – most of us will get along better with some people than others, and it can influence the efficacy of business interaction. So yes, better communication can influence a sale, resolve a complaint or even help with employee attrition.
- We have deployed our solution on a diverse set of debt portfolios which include late-stage debt such as mortgage loans and early stage debt such as credit cards. We have scientifically measured the outcomes at each deployment and delivered consistent results. The detailed analysis of these case studies are available upon request. One of our early deployments at a leading public sector bank in the EU where we delivered upto 20% improvement in loan restructurings was audited by Gartner, which led us to being named the Cool Vendor in 2020.
- A fully working solution employing AI-MC has 1) the client’s audio recording system, 2) their CRM, and 3) their call distribution system all connected to the AI-MC engine. These are the three points of integration essentially. The engine works in the background getting all necessary information from the CRM and the recorder to build the profiles and then updates the distribution system with the recommended matches dynamically on a day-to-day basis.
- This is from the Genpact CXO-2 deck. You might wanna skip
- Again this goes more deep into how the technology is set up but might be useful to get an idea…
- AIMC is not intrusive. Unlike a typical core business process AI offerings this solution can be integrated over any telephony solution that’s in place, and this can be achieved in a very short period of time. It works in the background routing each call to the best suited agent, without requiring a dedicated support team or any managed oversight. The results can be observed by comparing the improved outcome data, between business as usual and with AIMC.
- We hold an exclusive patent license on “Emotion Recognition System” We have a provisional patent on “Deep Actionable Behavioral Profiling” and two pending on “Deep Fusion for Emotion Recognition” and “Data Augmentation for Emotion/ Behavioral Profiling” We actively publish research papers and have won several awards and recognitions. Notable among these is the Gold-standard Emotion Sub-challenge and Sentiment Analysis challenge. And gold 6 times at INTERSPEECH, the biggest international research conference on speech technologies.
- We are proud to be the Use-Case leader in the coveted Maverick Research report from Gartner that profiles bleeding edge technologies.
- We made it to Gartner Cool Vendor list in 2020. It’s exceptionally rare for a company to share this stage with industry titans in early or pre-revenue stage. We have also been extensively profiled in Omdia and Forrester research papers.