Subject: Thread-Index: AQHa1A/WGW4PGGV9tEmkbJakdHfGKQ== Date: Fri, 12 Jul 2024 03:59:05 +0000 Message-ID: Content-Language: en-US X-MS-Has-Attach: X-MS-TNEF-Correlator: X-MS-Exchange-Organization-RecordReviewCfmType: 0 Content-Type: multipart/alternative; boundary="_000_MA0PR01MB9877609EF47FA3B38006CC73A0A62MA0PR01MB9877INDP_" MIME-Version: 1.0 --_000_MA0PR01MB9877609EF47FA3B38006CC73A0A62MA0PR01MB9877INDP_ Content-Type: text/plain; charset="Windows-1252" Content-Transfer-Encoding: quoted-printable Thanks for reaching out regarding the need for Smart Call Branding. This e= mail explains the context of how our solution works, what to expect. It al= so has a few business and technical discovery questions, so we understand t= heir business and expectations. It will be great if we can get on a call wi= th the account team / customer to understand more. Context: 1. It is assumed that the customer has a mobile application. 2. Assertion will supply an Android and IOS SDK that the customer will b= e expected to integrate with their existing mobile application. 3. The system operates in 2 logical parts =96 Consent flow (that sends a= pre-call message to the end-user and collects their consent) and Smart Cal= l branding flow (that launches the branded call). 4. Consent flow: * Assertion Identity Assurance integrates with the dialer (Avaya POM= / Avaya AXP / Genesys etc.) to pull the contact list ahead of the campaign= start. * It sends a consent message to each contact approx.. 30 minutes bef= ore the call launch time. The consent message is sent as an app notificati= on. * If end-user interacts with the app and provides consent and prefer= red time to call, the system will reschedule the call with the dialer. If = end-user does not provide consent or does not interact with the notificatio= n, the call will be scheduled for dialing immediately. 5. Smart call branding flow: * Assertion will supply the software that will screen all outgoing a= nd incoming calls to/from the enterprise, use that hook to inform the mobil= e app that a call is expected to arrive from the enterprise. * Assertion will determine based on end-user=92s network and other c= onditions, whether to launch the call as an App-branded call or fallback to= a Telco branded call (fallback option is only in the US). * End-user will receive the call as a branded call with full screen = graphics and a personalized message 1. The flow for dialer launched calls will be Consent flow + Smart call = branding flow. 2. The flow for manually dialed calls will be Smart call branding flow (= no Consent flow). 3. NOTE: To support live call verification, Assertion needs to screen in= coming calls as well. Discovery questions: 1. Which lines of businesses make outgoing calls? 2. Which dialing modes do you use? * Predictive * Preview * Progressive 3. Do you also do manual dials to customers? * Do employees call from their enterprise phones / mobile app or dir= ectly from their mobile phone? (Note: In this version, this solution does n= ot brand calls made from employee=92s mobile phone directly. ) 1. Do you outsource the =93out calling=94 process? * If you outsource, do all calls flow through your system or directl= y from the outsourcer to the Telco and to the customer? 1. What is the Connect rate on the outbound calls? * Percentage of calls answered * Average duration of connected calls 1. Do you measure outcomes of the outbound call (e.g., sales closure etc= .), If so, how? 2. What are your top 2 challenges in the outbound calling universe? 3. Are customers getting scammed by impersonators using your brand to ca= ll them? 4. How many customers have your mobile app? * As an absolute number and as a percentage relative to your retail = customer base * IOS Vs Android * Used your mobile app in the last 30 days 1. What dialer do you have? 2. What SBCs do you have? 3. Do you have 100% SIP trunks? * If not, what percentage of outbound calls flow on SIP trunks? 1. Can we get a complete voice network architecture, so we understand th= e components and their interactions? 2. What is the user experience you seek? 3. What are the outcomes you expect? Thanks --_000_MA0PR01MB9877609EF47FA3B38006CC73A0A62MA0PR01MB9877INDP_ Content-Type: text/html; charset="Windows-1252" Content-Transfer-Encoding: quoted-printable

Thanks for reaching out regarding= the need for Smart Call Branding.  This email explains the context of how our solution works, what to expect.  It a= lso has a few business and technical discovery questions, so we understand = their business and expectations. It will be great if we can get on a call w= ith the account team / customer to understand more.

 

Context:

  1. It is assumed that the customer has a mobile application.  = ;
  2. Assertion will supply an Android and IOS SDK that the customer will = be expected to integrate with their existing mobile application.
  3. The system operates in 2 logical parts =96 Consent flow (that sends = a pre-call message to the end-user and collects their consent) and Smart Call branding flow (that launches the branded cal= l).
  4. Consent flow: 
    1. Assertion Identity Assurance integrates with the dialer (Avaya POM /= Avaya AXP / Genesys etc.) to pull the contact list ahead = of the campaign start.  
    2. It sends a consent message to each contact approx.. 30 minutes befor= e the call launch time.  The consent message is sent as an app notification.  
    3. If end-user interacts with the app and provides consent and preferre= d time to call, the system will reschedule the call with the dialer.  If end-user does not provide consent or does n= ot interact with the notification, the call will be scheduled for dialing i= mmediately.  
  5. Smart call branding flow:
    1. Assertion will supply the software that will screen all outgoing and= incoming calls to/from the enterprise, use that hook to inform the mobile app that a call is expected to arrive from = the enterprise. 
    2. Assertion will determine based on end-user=92s network and other con= ditions, whether to launch the call as an App-branded call or fallback to a Telco branded call (fallback option is only in the U= S).  
    3. End-user will receive the call as a branded call with full screen gr= aphics and a personalized message
  1. The flow for dialer launched calls will be Consent flow + Smart call= branding flow.
  2. The flow for manually dialed calls will be Smart call branding flow = (no Consent flow).
  3. NOTE: To support live call verification, Assertion needs to screen i= ncoming calls as well.

 

Discovery questions:=

  1. Which lines of businesses make outgoing calls?
  2. Which dialing modes do you use? 
    1. Predictive
    2. Preview
    3. Progressive
  3. Do you also do manual dials to customers?
      1. Do employees call from their enterprise phones / mobile app or direc= tly from their mobile phone? (Note: In this version, this sol= ution does not brand calls made from employee=92s mobile phone directly. )
    1. Do you outsource the =93out calling=94 process?
      1. If you outsource, do all calls flow through your system or directly = from the outsourcer to the Telco and to the customer?
    1. What is the Connect rate on the outbound calls?
      1. Percentage of calls answered
      2. Average duration of connected calls
    1. Do you measure outcomes of the outbound call (e.g., sales closure et= c.),  If so, how? 
    2. What are your top 2 challenges in the outbound calling universe?
    3. Are customers getting scammed by impersonators using your brand to c= all them?
    4. How many customers have your mobile app?
      1. As an absolute number and as a percentage relative to your retail cu= stomer base
      2. IOS Vs Android
      3. Used your mobile app in the last 30 days
    1. What dialer do you have? 
    2. What SBCs do you have? 
    3. Do you have 100% SIP trunks?
      1. If not, what percentage of outbound calls flow on SIP trunks?
    1. Can we get a complete voice network architecture, so we understand t= he components and their interactions?
    2. What is the user experience you seek? 
      3. What are the outcomes you expect?

     

    Thanks

     

     

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