HOW CONVERSATION ANALYTICS CONTRIBUTES TO A SUCCESSFUL CUSTOMER

HOW CONVERSATION ANALYTICS CONTRIBUTES TO A SUCCESSFUL CUSTOMER JOURNEY Prepared by: Call Journey April 2020 GOVERNMENT

The Customer Journey GOVERNMENT

Joe started a new business and is looking forward to hire new employees. However, being a proprietor himself for a long time, he is not familiar with having employees around and is anxious about employee taxes. The following events shows Joe’s customer experience journey and missed opportunities without Conversation Analytics. In the absence of Conversation Analytics, these interactions go unanalyzed and do not contribute to customer experience journey data for Customer Insights. “JOE” New business owner 1 NEED Joe is excited on his new venture for starting a new business but is very anxious about hiring new employees due to tax implications. 2 4 RESEARCH To look for answers, Joe searches the internet to help him gather basic information about filing taxes for employees. • Hoping to get information in one search. Joe found the first link on the search list which is the “tax. gov”. He went to the website and clicked on “Help and Support” and found a phone number he can call. • Spoke to a CSR Agent and discussed about new business and hiring new employees. • Told the CSR Agent that his main concern is to get more information about employee tax. 3 INQUIRY POST-CALL SURVEY Joe is happy with how the conversation went and is expected to be directed to a Tax Specialist to help him more informed about his concern. • The CSR Agent hold Joe for 15 minutes and returned asking Joe to answer a post-call survey before proceeding. • Joe is still feeling positive despite the long wait and submitted a positive review.

5 ENGAGEMENT After being in the phone call for more than 30 minutes talking to the CSR Agent and waiting time, Joe finally speaks to a Tax Specialist. • Joe again discussed his new business and the challenge of lack of tax information in hiring new employees. • The Tax Specialist does not quite understand how the conversation is going and kept on asking unrelated questions to Joe. • Joe irritably discuss his concerns for a few times again. 6 8 POST-CALL EXPERIENCE Still feeling positive that Joe is getting more follow-up information from the Tax Specialist, he went to the agency’s social media to check on other customers reviews about their experience. There are some positive reviews, so Joe decided to proceed with the agency’s help for information. FIRST EDM Joe received the first email from the agency hoping it is the full information he needs. Unfortunately… • The EDM is information about processing personal taxes and how to go about them when you’re a first timer. Joe is disappointed with the EDM content as this is not the right information he needs. He’s already set-up his own personal tax and this is useless for him. 9 Joe called the Tax Specialist again and complains about the EDM received. • Negative reaction to EDM • Joe explained that this is not the information he needs. • Discussed again his concerns about the tax information about hiring new employees. 10 7 EDM REACTION 11 BAD REVIEWS SEEKS HELP AGAIN SECOND EDM Joe received another EDM from the agency hoping this is right information he seeks. But very angry to received that this is a follow-up EDM from the first one he received. • Angry about how things turned out and by slow processing, wasting time for nothing. Due to slow and poor customer service, Joe decided to leave a negative review in agency’s social media accounts and encouraged other customers who experienced the same service to leave their reviews as well. This is a bad PR for the agency which resulted to decrease of agency’s credibility and loses future customers.

The Executives are not happy with how the Customer Journey Experience turned out: Meanwhile inside the company’s Management Team: 1. 2. 3. Customer Retention Project Team MARCOMMS PRODUCT MANAGER LEAD DATA ANALYST CONTACT CENTER MANAGER ACTUARY REVIEWING LAPSED CUSTOMERS ONLY VIA STRUCTURED DATA – NO CONVERSATION INSIGHTS! Future customer / revenue Loss Bad reviews, decreased agency’s credibility Long AHT SALES DIRECTOR MARKETING DIRECTOR GENERAL COUNSEL

With VOICE DATA now being added to MICROSOFT ecosystem, this is now Joe’s new customer journey experience with Conversation Analytics environment. 1 NEED Joe is excited on his new venture for starting a new business but is very anxious about hiring new employees due to tax implications. 2 RESEARCH To look for answers, Joe searches the internet to help him gather basic information about filing taxes for employees. • Hoping to get information in one search. “JOE” New business owner 4 Joe found the first link on the search list which is the “tax. gov”. He went to the website and clicked on “Help and Support” and found a phone number he can call. • Spoke to a CSR Agent and discussed about new business and hiring new employees. • Told the CSR Agent that his main concern is to get more information about employee tax. 3 INQUIRY ANALYTICS Adding VOICE DATA to Microsoft’s Customer Insights tool, the data analytics team pick up the fact that Joe mentioned a couple of times that he needs more and accurate information about filing taxes for new employees. • Triggered outbound calls and EDMs around information and procedures on filing taxes for employees. • A specific Tax Specialist will be assigned to him to further assist him.

5 ENGAGEMENT After a few moments, from Joe was transferred to a Tax Specialist to further assist him. • Joe again discussed his new business and the challenge of lack of tax information in hiring new employees. • With the Customer data and insights recorded, the Tax Specialist was able to quickly action on Joe’s concerns and is now processing his request. 6 POSTEXPERIENCE Joe is very pleased with how the whole conversation and process went with the agency. OUTBOUND PROACTIVE CALL Joe is very satisfied with the conversation with the Tax Specialist and promised him that he will be receiving an email from the agency regarding his concerns. • The Tax Specialist told him that he can call again if he have further questions. • Joe was given a reference number that he can use the next time he will call again so they can attend to him quickly and easily. 7 8 FIRST EDM Joe received the first email from the agency with all the information about filing taxes for hiring employees. • Aside from the initial information he requested, the EDM also includes a customized process he can follow since he’s a first-time business owner with employees, a different set-up when he was still only a proprietor of his business. 9 POSITIVE REVIEWS Joe left positive reviews to all the agency’s social media accounts and encourage other people to seek their help with regard to their taxes. • Positive customer experience • Encouraged positive word-ofmouth 10 INCREASE AGENCY CREDIBILITY With the positive reviews in their social media accounts, more people are encouraged to try their services and became a “top-of-mind” tax agencies for people who are looking for more information especially for people like Joe who are first timers on their new ventures. • High credibility, more positive reviews, more customers to come!

ADDING VOICE DATA FROM POSITIVE CUSTOMER EXPERIENCES, THE RETENTION TEAM GET BETTER INSIGHTS Meanwhile inside the company’s Management Team: Customer Retention Project Team MARCOMMS PRODUCT MANAGER LEAD DATA ANALYST CONTACT CENTER MANAGER STRACTURED DATA – INCLUDING CONVERSATION INSIGHTS Happy Customer – I’m happy! More Customers – I’m happy! No Complaints – I’m happy! ACTUARY SALES DIRECTOR MARKETING DIRECTOR GENERAL COUNSEL

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Microsoft Assets For Customer Journey

Conversation transcription Data hits the Azure database and is added to Customer Insights. With augmented data, this now hits the Azure Machine Learning environment. Conversation insights around customer engagement are created in the Customer Insights tool and pushed into downstream Insights packages. Meta data and conversation Insights arrive in Dynamics 365 Marketing and a Tax Information filing-based EDM is created. Predictive churn and NPS measures are added based on the interaction aligned to the customer mentioning he is worried about tax implications in hiring new employees for his business. Conversation Insights arrive in Dynamics 365 CRM adding to the single customer view, noting a Tax Information filing-based EDM is created Campaign was created and that an EDM was sent. Predictive churn and NPS measures are added based on the interaction into the single customer CRM view. Conversation Insights arrive in Customer Service insights measuring employee performance soft skills and compliance and customer experience. Predictive churn/lapse and NPS measures are added based on the interaction as are key Conversation insights – for example where COVD 19 was mentioned and the context. Conversation Insights arrive in Sales Insights measuring employee performance soft skills and compliance and customer experience. Next best offer campaign is added, and a new revenue opportunity created for a new Life Insurance product. Key sales drivers and triggers are noted in Sales Insights. 1

Post call survey data and conversation transcription Data is added to Customer Insights and with augmented data hits the Azure Machine Learning environment. Insights around customer engagement are created and pushed into downstream Insights packages. In this case – data summarizing a positive NPS score was allocated. Meta data and conversation Insights arrive in Dynamics 365 Marketing and a Life Insurance EDM is created. Predictive churn and NPS measures are added based on the interaction. Conversation Insights arrive in Dynamics 365 CRM adding to the single customer view, noting a Tax Information filing-based EDM is created Campaign was created and that an EDM was sent. Predictive churn and NPS measures are added based on the interaction into the single customer CRM view. Conversation Insights arrive in Customer Service insights measuring employee performance soft skills and compliance and customer experience. Predictive churn/lapse and NPS measures are added based on the interaction as are key Conversation insights – for example where COVD 19 was mentioned and the context. 2

Social Media data is added to Customer Insights and with augmented data, hits the Azure Machine Learning environment Insights around customer engagement are created and pushed into downstream Insights packages. In this case – data summarising a positive NPS score was allocated and key social media comments added. Social media interaction data arrives in Dynamics 365 Marketing. Predictive churn and NPS measures are added based on the interaction Social Media data arrives in Dynamics 365 CRM adding to the single customer view, noting customer commentary. Predictive churn and NPS measures are added based on the interaction into the single customer CRM view. Social media data arrives in Customer Service insights. Predictive churn/lapse and NPS measures are added based on the social media interaction. 3

Conversation transcription Data hits the Azure database and is added to Customer Insights. With augmented data, this now hits the Azure Machine Learning environment. Conversation insights around customer engagement are created and pushed into downstream Insights packages. Meta data and conversation Insights arrive in Dynamics 365 Marketing and a positive response to the Tax Information filing-based EDM is assessed. Predictive churn and NPS measures are added based on the interaction as are key points of positive reaction to product elements. Conversation Insights arrive in Dynamics 365 CRM adding to the single customer view, noting a Tax Information filing-based EDM was presented and received positively. Predictive churn and NPS measures added based on the interaction into the single customer CRM view. Conversation Insights arrive in Customer Service insights measuring employee performance soft skills and compliance and customer experience. Predictive churn/lapse and NPS measures are added based on the interaction as are key Conversation insights – for example where COVD 19 was mentioned and the context. 4

Conversation transcription Data hits the Azure database and is added to Customer Insights. With augmented data, this now hits the Azure Machine Learning environment. Conversation insights around customer engagement are created and pushed into downstream Insights packages. Meta data and conversation Insights arrive in Dynamics 365 Marketing showing a customer purchase outcome and drivers of purchase summary. Confirmation EDM triggered as the tax information hits the administration system. Customer management campaign triggered across new and existing policies. Conversation Insights arrive in Dynamics 365 CRM adding to the single customer view, noting a Tax Filing Information. Purchase and key point conversation summary. Predictive churn and NPS measures added based on the interaction into the single customer CRM view. Conversation Insights arrive in Customer Service Insights measuring employee performance soft skills and compliance and customer experience. Predictive churn/lapse and NPS measures added based on the interaction 5