{"id":4866,"date":"2020-07-03T14:05:34","date_gmt":"2020-07-03T14:05:34","guid":{"rendered":"https:\/\/staging.txtbox.in\/docs\/salesforce\/?post_type=lsvr_kba&p=4866"},"modified":"2020-07-06T10:53:50","modified_gmt":"2020-07-06T10:53:50","slug":"opt-out-analysis","status":"publish","type":"lsvr_kba","link":"https:\/\/staging.txtbox.in\/docs\/salesforce\/knowledge-base\/opt-out-analysis\/","title":{"rendered":"Opt-Out Analysis"},"content":{"rendered":"\n

This dashboard will show you the analysis for opted out numbers based on different dimensions. Such as numbers opting out from different types of content, messaging sources etc.<\/p>\n\n\n\n

\"\"\/<\/figure>\n\n\n\n

a. Filter<\/strong><\/h3>\n\n\n\n
\"\"\/<\/figure>\n\n\n\n

 It is a top-level filter to handle the analysis date range. The filter is on \u2018date opted out\u2019. i.e. all the further analysis is done on the records where opted out date is within the filter date range.<\/p>\n\n\n\n

The current version supports two filters <\/p>\n\n\n\n

  1. last 7 days<\/li>
  2. last 30 days<\/li><\/ol>\n\n\n\n

    b. Content Type<\/strong><\/h3>\n\n\n\n
    \"\"\/<\/figure>\n\n\n\n

    It is a graphical representation for the percentage of contacts opted out for each of the content types. <\/p>\n\n\n\n

    The percentage of the contacts opted out is calculated as follows:<\/p>\n\n\n\n

    Contacts opted out = [Count of phone numbers opted out during the date range]\/[Count of phone numbers opted in till the date range]*100<\/p>\n\n\n\n

    E.g Filter range selected 30 days(1st June-30th June).  During this date range<\/p>\n\n\n\n

    for Sales type of content 150 contacts opted-out.And as on the 1st of June, 1000 were numbers opted-in. Based on the above formula,<\/p>\n\n\n\n

    Contacts opted out = [ 150\/1000]*100= 15%<\/p>\n\n\n\n

    C. Message Source<\/strong><\/h3>\n\n\n\n
    \"\"\/<\/figure>\n\n\n\n

    It is a graphical representation for the percentage of contacts opted out for each of the message sources. (The percentage of the contacts opted out is calculated same as above in 2.b.)<\/p>\n\n\n\n

    d. Last Message Sent<\/strong><\/h3>\n\n\n\n

    It is a graphical representation for the percentage of contacts opted out and the time slots for the last sent messages. These time slots are important to understand the preferred time slots by your customers.Typically people don\u2019t like to receive the messages during late evenings to early mornings.(The percentage of the contacts opted out is calculated same as above in 2.b.)<\/p>\n\n\n\n

    e. Message Volume<\/strong><\/h3>\n\n\n\n

    It is a graphical representation for the percentage of contacts opted out and the number of messages sent.These time slots are important to understand the number of messages sent to your customers.Typically people don\u2019t like to receive frequent messages.(The percentage of the contacts opted out is calculated same as above in 2.b)<\/p>\n\n\n\n

    f. Conversation Engagement<\/strong><\/h3>\n\n\n\n
    \"\"\/<\/figure>\n\n\n\n

    It is a graphical representation for the percentage of contacts opted out and the number of messages.Grouping is done based on the conversation ratio bucket.<\/p>\n\n\n\n

    In to Out Ratio =  number of incoming messages\/ Number of outgoing messages<\/p>\n\n\n\n

    (The percentage of the contacts opted out is calculated same as above in 2.b)<\/p>\n","protected":false},"excerpt":{"rendered":"

    This dashboard will show you the analysis for opted out numbers based on different dimensions. Such as numbers opting out from different types of content, messaging sources etc. a. Filter  It is a top-level filter to handle the analysis date range. The filter is on \u2018date opted out\u2019. i.e. all the further analysis is done […]<\/p>\n","protected":false},"author":8,"featured_media":0,"comment_status":"closed","ping_status":"closed","template":"","format":"standard","meta":{"footnotes":""},"lsvr_kba_cat":[557],"lsvr_kba_tag":[],"class_list":["post-4866","lsvr_kba","type-lsvr_kba","status-publish","format-standard","hentry","lsvr_kba_cat-dashboards"],"_links":{"self":[{"href":"https:\/\/staging.txtbox.in\/docs\/salesforce\/wp-json\/wp\/v2\/lsvr_kba\/4866","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/staging.txtbox.in\/docs\/salesforce\/wp-json\/wp\/v2\/lsvr_kba"}],"about":[{"href":"https:\/\/staging.txtbox.in\/docs\/salesforce\/wp-json\/wp\/v2\/types\/lsvr_kba"}],"author":[{"embeddable":true,"href":"https:\/\/staging.txtbox.in\/docs\/salesforce\/wp-json\/wp\/v2\/users\/8"}],"replies":[{"embeddable":true,"href":"https:\/\/staging.txtbox.in\/docs\/salesforce\/wp-json\/wp\/v2\/comments?post=4866"}],"version-history":[{"count":2,"href":"https:\/\/staging.txtbox.in\/docs\/salesforce\/wp-json\/wp\/v2\/lsvr_kba\/4866\/revisions"}],"predecessor-version":[{"id":4963,"href":"https:\/\/staging.txtbox.in\/docs\/salesforce\/wp-json\/wp\/v2\/lsvr_kba\/4866\/revisions\/4963"}],"wp:attachment":[{"href":"https:\/\/staging.txtbox.in\/docs\/salesforce\/wp-json\/wp\/v2\/media?parent=4866"}],"wp:term":[{"taxonomy":"lsvr_kba_cat","embeddable":true,"href":"https:\/\/staging.txtbox.in\/docs\/salesforce\/wp-json\/wp\/v2\/lsvr_kba_cat?post=4866"},{"taxonomy":"lsvr_kba_tag","embeddable":true,"href":"https:\/\/staging.txtbox.in\/docs\/salesforce\/wp-json\/wp\/v2\/lsvr_kba_tag?post=4866"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}