[Mintigo Webinar] Mining For Gold In Your Email House List

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To watch the entire webinar recording, please visit:
http://www.mintigo.com/mining-for-gold-in-your-email-house-list/

Title: "Mining For Gold In Your Email House List"

Description:

Email marketing is still the workhorse of modern B2B demand gen. But can you find the gold in your house list before time runs out?

On one hand, you’ve got to move fast, since contacts degrade at a rate of 30% per year. On the other hand, if you mail too aggressively, contacts will tune-out and opt-out. You only get limited at-bats, so make each one count!

In this webinar, we’ll learn the secrets from Jeanne Hopkins, CMO of SmartBear Software, author of mobile marketing book Go Mobile, and Mintigo customer. She’ll explain:

SmartBear’s proven strategy for nurturing over 1 million leads
How to segment a contact database quickly
How SmartBear uses analytics to increase response rate
If you’re investing in a marketing automation solution like Eloqua, HubSpot, or Marketo, you need to know how to use it right. Mintigo is proud to host this special presentation by an accomplished industry insider.

About The Guest Speaker:
Jeanne Hopkins, Chief Marketing Officer at SmartBear Software
Prior to her role as CMO at SmartBear, Jeanne was vice president of marketing at HubSpot, a marketing software leader and pioneer in inbound marketing. Her leadership helped HubSpot become the second-fastest growing software company in the Inc. 500 by generating 45,000 new leads each month. Hopkins previously was CMO of MEC Labs, owner of MarketingSherpa, MarketingExperiments, and InTouch, and senior marketing director at Symmetricon.

Jeanne, a firm believer in the top-of-the-funnel lead-generation capabilities of inbound marketing, is coauthor of the book Go Mobile, a step-by-step introductory look at starting mobile marketing efforts that has been the #1 best-selling mobile marketing book on Amazon.com. She is also one of the top 10 Sales Lead Management professionals for 2011.

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  • Open rate not always a determinant but this is directional.
  • Jason
  • Create custom fields for each theme, and tag anyone in your system who has downloaded content related to each theme.Use your assets for each theme to break out separate tracks in a drip/nurture programAdd the leads that have expressed interest in a certain theme to the appropriate track, so that they will be sent the rest of the content that you have related to that theme that they have not already receivedWhen you create new content, keep adding to your tracks, and when leads download content related to one of the themes moving forward, make sure they are added to the appropriate track so that you continue to nurture that interest.
  • [Mintigo Webinar] Mining For Gold In Your Email House List

    1. 1. Mining  For  Gold  In     Your  Email  House  List   Host:   Jason  Garou*e   CMO,  Min1go   @jgarou*e   Guest  Presenter:   Jeanne  Hopkins   CMO,  Con1nuum.net   @jeannehopkins  
    2. 2. We  Work  with  Great  Marketers  
    3. 3. About  Min?go  
    4. 4. Jeanne  Hopkins   CMO  at  Con1nuum.net   •  Previously  CMO  at  SmartBear  SoBware   •  Previously  VP  of  Marke1ng  at  HubSpot   •  Co-­‐author  of  #1  best  selling  mobile   marke1ng  book  “Go  Mobile”  on  Amazon  
    5. 5. Mining for Gold in Your Email House List 5
    6. 6. 6  
    7. 7. 7  
    8. 8. 8  
    9. 9. 9  
    10. 10. 10  
    11. 11. 11  
    12. 12. SmartBear Email Facts 12 •  In Q2 2013, SmartBear sent one marketing email every 2.3 seconds •  On a typical Tuesday, individual email campaigns will go out to as many as 20-35 different segments in the database •  Average number of SmartBear emails leads receive per week: 1 •  Average unsubscribe rate: 0.1% •  Average % delivered: 94.3%
    13. 13. SmartBear Marketing Ninjas 13
    14. 14. Team Achievments 14 Since Q3 of 2012… •  Grown marketing automation/email marketing “Ninja” team from 3-9 members (3 core users, 6 “agile” users/ contributors, 3 Marketo Champions) •  Winner of 2013 Marketo Revvie Award for Most Dramatic Business Impact with Marketing Automation for a Small/ Medium-Sized Company •  Winner of 2012 Forrester Groundswell Award for Excellence in Social Media •  Honorable Mention in 2013 WhichTestWon Email Marketing Awards
    15. 15. 15 Gary DeAsi – Mintigo Ninja
    16. 16. Database Segmentation: Behavioral Tagging & Custom Fields 16 SmartBear  Database   as  of  September  2012   SmartBear  Database   as  of  November  2012  
    17. 17. Relevance of a Targeted Email Campaign to a (Non-Segmented) Mass Audience 17 Fit  OR  Interest  (16%)     NO  Fit,  NO  Interest  (80%)     Fit  AND   Interest   (4%)   Fit  (Explicit):  Lead  possesses  key   demographic  or  firmographic  traits   relevant  to  campaign       Interest  (Implicit):  Lead  has   (historically)  demonstrated   behavior  linked  with  (inferred)   relevance  of  campaign  
    18. 18. 18 Fit  OR  Interest   (16%)   No  Fit,  No  Interest   Emails  Delivered:  80,000   Average  CTR:  0.5%   Responses:    400   Fit  OR  Interest   Emails  Delivered:  16,000   Average  CTR:  2.0%   Responses:    320   Fit  AND  Interest   Emails  Delivered:  4,000   Average  CTR:  6.0%   Responses:    240   Total   Emails  Delivered:  100,000   Average  CTR:  0.9%   Responses:  960   +   +   =   Results of a Targeted Email Campaign to a (Non-Segmented) Mass Audience Fit  AND   Interest   (4%)   NO  Fit,  NO  Interest     (80%)    
    19. 19. Without segmentation, you are guessing. Which audiences should we send our new eBooks to this week? 19 New  eBooks   this  Week   Product  A   Product  B   Product  C   Non-­‐Segmented   Database   ?  
    20. 20. Results of Targeted Email Campaigns Segmented by Relevance 20 Product  A   Segment  1   Fit  OR  Interest   List  Size:  16K   Fit  AND   Interest   4K   Segment  1     Responses:  560   +   =  Total  Responses:  1,880   Fit  OR  Interest   List  Size:  16K   Fit  AND   Interest   4K   Fit  OR  Interest     List  Size:  16K   Fit  AND   Interest     4K   Segment  2   Responses:  560   Segment  3     Responses:  560   Segment  4     Responses:  200   +   +   No  Fit,  No  Interest   List  Size:  40K   Product  B   Segment  2   Product  C   Segment  3   Proudcts  A/B/C   Segment  4  
    21. 21. Non-Segmented vs. Segmented 21 Non-­‐Segmented   Email  Responses/Send:  960   Segmented     Email  Responses/Send:  1,880   X  4weeks  =  3,840   X  4weeks  =  7,520  
    22. 22. Growing Your Optimal Audiences 22 Interest   Fit   Time   •  Over  1me,  your  op1mal  segments  (in  terms  of   relevance  and  engagement)  will  grow  the  more   you  generate  leads,  and  email  and  nurture  them  
    23. 23. Segmentation gives you options & grows your potential relevant audience(s) for each campaign. Which audiences should we send our new eBooks to this week? 23 Persona  1   Persona  2   Persona  3   Persona  4   Persona  5   Persona  6   New  eBooks   this  Week   Product  A   Product  B   Product  C   Poten1al  Segment   to  Send  Content  
    24. 24. Which products need the most love (this week)? 24 Persona  1   Persona  2   Persona  3   Persona  4   Persona  5   Persona  6   New  eBooks   this  Week   Product  A   Product  B   Product  C   Poten1al  Segment   Chosen  Segment   to  Send  Content  
    25. 25. 25 Persona  1   Persona  2   Persona  3   Persona  4   Persona  5   Persona  6   New  eBooks   this  Week   Product  A   Product  B   Product  C   Poten1al  Segment   Sent  Week  1   Who can we send these eBooks to (next week)? Sent  Week  2  
    26. 26. Segmentation: Getting Granular 26 Tes?ng   Development   API   Performance   Monitoring   Persona   (Demographic)   Behavioral   Interest   Min?go  DNA   Match  
    27. 27. Q2 Mintigo Analysis: Job Titles 60% of trials came from 27% of leads! 27%   60%  
    28. 28. Segmentation = Engagement 7.6%   8.5%   9.5%   10.0%   11.3%   14.1%   0.0%   2.0%   4.0%   6.0%   8.0%   10.0%   12.0%   14.0%   16.0%   ABYSS  1   ABYSS  2   Tes1ng   Min1go  Scored   (INT)   Min1go  Scored   (NA)   Cross-­‐PG  (Tes1ng   Title)   %  Opened  
    29. 29. Segmentation = Engagement 0.6%   1.0%   1.7%   1.9%   3.1%   4.7%   0.0%   0.5%   1.0%   1.5%   2.0%   2.5%   3.0%   3.5%   4.0%   4.5%   5.0%   ABYSS  1   ABYSS  2   Tes1ng   Min1go  Scored   (NA)   Min1go  Scored   (INT)   Cross-­‐PG  (Tes1ng   Title)   %  Clicked  
    30. 30. TestComplete DNA Matches 67.6% of TestComplete DNA Matches Not Being Marketed TestComplete! AlertSite_Customers   AlertSite_Prospects_Trial   Net  New   LoadComplete_Customers   LoadUI_Customers   AlertSite_Prospects_NOTrial   AQ1me_Customers   TestComplete_Prospects_Trial   TestComplete_Customers   Collaborator_Prospects_Trial   Performance_Prospects.csv   SoapUI_Customers   Collaborator_Customers   Collaborator_Prospects_NOTrial   SoapUI_Prospects_Trial   TestComplete_Prospects_NOTrial   Total  DNA  Matches  from  SmartBear  House  List  Source   32.4%   67.60%   Marketed  TC   Not  Marketed  TC  
    31. 31. Segment your database! Segment by: •  Job title •  Lead region (geographic) •  Industry •  Company size •  Lead score •  Behavioral interests •  Viability (Email-ability) •  Lead type (prospects, customers, partners etc.) •  Funnel stage •  Engagement levels •  Technology usage •  Create custom data fields that are most important for your business! 31
    32. 32. It’s easier to find gold once you sort through the garbage 32 How many members of your database… •  Are unsubscribed? •  Have empty, invalid, or bounced email addresses? •  Have been rejected as non-workable leads by Sales? •  Are customers? Partners? Employees? •  Have not visited your site or opened a single email in the past 3-6 months? •  Do you have almost no demographic data for? •  Were acquired via list purchase vs. created organically? •  Have public domain email addresses? •  Are from geographic locations that you do not sell to? •  Are more than six months old? More than a year? More than 3 years?
    33. 33. Persona  1   Persona  2   T   I   P   S   Drip  A   Drip  B   Drip  C   R   E   S  P   Persona-­‐Based  House  Lists  –  Outbound   Email   TOFU  Persona-­‐Based  Drips  (Pre-­‐Trial)   MOFU  Tips  and  Reps  (During  Trial)   BOFU  Reps  (Post-­‐Trial)   Nurturing, Optimizing the Funnel, Recycling
    34. 34. Persona  1   Persona  2   T   I   P   S   TOFU  A   TOFU  B   TOFU  C   R   E   S  P   TOFU  Drips  (Pre-­‐Trial)   TRACKS  (Inside  Drip)   1   2   3   4   5   6   •  Persona   •  Business  Need   •  Funnel  Stage  (TOFU/MOFU)   •  Product  Interest   •  Lead  Region  (NA  vs  INT)   •  Themes/Topic   Nurturing & Optimizing the Funnel: Tracks
    35. 35. Persona  1   Persona  2   Persona  3   Persona  4   Persona  5   Persona  6   T   I   P   S   A   N   D   R   E   S  P   TF  A   TF  B   TF  C   TF  D   TF  E   TF  F   TF  G   TF  H   SmartBear Database/Nurturing “Ecosystem” as of Q3 2013
    36. 36. Custom Segmentation and Nurturing: Hypothetical Example 36 Use  Case  or   Theme  1   Use  Case  or   Theme  2   Use  Case  or   Theme  3   Track  1   Track  2   Track  3   Use  Case  or   Theme  1   List  1    9,000  Leads   List  2   12,000  Leads   List  3   6,500  Leads   TOFU     Drip   Use  Case  or   Theme  2   Use  Case  or   Theme  3  
    37. 37. 37 Track  1   Using  (Compe1tor)   automated  tes1ng   solu1on     Manual  tester,   no  auto-­‐tes1ng   solu1on   Has  automated   tes1ng  experience,   no  solu1on   Track  2   Track  3   Track  1   Tes1ng  Desktop   Applica1ons   Tes1ng  Mobile   Applica1ons   Tes1ng  Web   Applica1ons   Track  2   Track  3   Track  1   QA  Tester  or   Engineer   Other  QA  Manager   Track  2   Track  3   Use  Case   Need   Job  Title   Nurture  Tracks  Example:  TestComplete  (Automated  Tes?ng)   TRACK  1   TRACK  2   TRACK  3  
    38. 38. 38 Track  1   Using  (Compe1tor)   automated  tes1ng   solu1on     Manual  tester,   no  auto-­‐tes1ng   solu1on   Has  automated   tes1ng  experience,   no  solu1on   Track  2   Track  3   Track  1   Tes1ng  Desktop   Applica1ons   Tes1ng  Mobile   Applica1ons   Tes1ng  Web   Applica1ons   Track  2   Track  3   Track  1   QA  Tester  or   Engineer   Other  QA  Manager   Track  2   Track  3   Use  Case   Need   Job  Title   TRACK  1   TRACK  2   TRACK  3  
    39. 39. 39 Track  1   Using  (Compe1tor)   automated  tes1ng   solu1on     Manual  tester,   no  auto-­‐tes1ng   solu1on   Has  automated   tes1ng  experience,   no  solu1on   Track  2   Track  3   Track  1   Tes1ng  Desktop   Applica1ons   Tes1ng  Web   Applica1ons   Track  2   Track  3   Track  1   QA  Tester  or   Engineer   Other   QA  Manager   Track  2   Track  3   Use  Case   Need   Job  Title   TRACK  1   TRACK  2   TRACK  3   Tes1ng  Mobile   Applica1ons  
    40. 40. Get the most out of our leads Trial  Product  A   House  List/   POFU  Drip   Product  A   TOFU  DRIP   Product  B   TOFU  DRIP   Product  C   TOFU  DRIP   Product  D   Route    by:   •  Demographics  (Job  Title)   •  Behavior   •  Min1go  DNA  Match  
    41. 41. 41 Outbound   Email   Paid   Media   PPC   Website   Social   Media   Blog   MQIs   TOFU  Drip   MQLs   Use Your Channels to Feed Your Nurture Paths
    42. 42. 42
    43. 43. Q&A  and  Next  Steps   Request  a  Live  Demo  of   Min1go   Get  the  ebook  on  “Crea1ng   Personas  For  B2B  Marke1ng”   Interested?         jason@min1go.com  

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