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PeerIndex Twi,er Ads Tes/ng Using PiQ data and audiences to op/mise Twi,er campaigns

Optimising Twitter Ads with PiQ Audience Targeting

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Using PiQ influence and audience analytics and data to optimise Twitter Ad targeting. 3x Engagement Rate 3x Click-through Rate 8.5x Retweet Rate 12.8x Average Reach per Retweet

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Page 1: Optimising Twitter Ads with PiQ Audience Targeting

PeerIndex  Twi,er  Ads  Tes/ng  

Using  PiQ  data  and  audiences  to  op/mise  Twi,er  campaigns  

Page 2: Optimising Twitter Ads with PiQ Audience Targeting

Brief  

•  PeerIndex  were  asked  by  to  provide  audiences  for  a  promoted  tweet  campaign  targe/ng  Africans  interested  in  filmmaking.  

•  Main  objec/ves  were:  –  Increase  site  visits  from  campaigns  –  Increase  sign-­‐ups  –  Increase  engagement  on  Twi,er  aGer  campaigns  have  reached  ini/al  audience  

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Page 3: Optimising Twitter Ads with PiQ Audience Targeting

Results  Overview  •  The  targe/ng  was  run  alongside  campaigns  using  the  same  crea/ves  using  Twi,er’s  built-­‐in  topic  and  user  targe/ng.  

•  Ads  using  PiQ  custom  audiences  showed  an  increase  in  all  key  metrics:  

–   3x  click-­‐through  rate  –   3x  engagement  rate  –   8.5x  retweet  rate  –   13x  average  poten/al  reach  of  people  retwee/ng  

             

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Page 4: Optimising Twitter Ads with PiQ Audience Targeting

Results  Overview  Metric   PiQ  Audiences  Overall  

Performance  Twi8er  Ads  Overall  

Performance  Improvement  

Click Rate 1.33% 0.44% 3.05x

Engagement Rate 3.82% 1.29% 2.96x

Retweet Rate 0.44% 0.05% 8.5x

Retweet Reach (avg) 5380 418 12.8x

Impressions 24543 128679

Clicks 327 563 Interactions (clicks

on tweet) 742 1518

Retweets 108 67

Replies 4 10

Followers 84 64

Cost per Click 0.92 0.74 4  

Page 5: Optimising Twitter Ads with PiQ Audience Targeting

PiQ  Audiences  •  Peerindex  created  5  custom  audiences  to  target  Africans  between  18-­‐30  working  or  interested  in  the  film  industry:  

•  5  were  chosen  to  test  the  effec/veness  of  PeerIndex’  various  methods  for  genera/ng  audiences.  

•  A  –  Core  PiQ  Search    •  B  –  Followers/Influencees  of  Key  Accounts  •  C  –  Top  1000  lookalikes  of  Core  Search  •  D  –  Next  5000  lookalikes  of  Core  Search  •  E  –  Outside  Influencers  of  Core  Search  

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Page 6: Optimising Twitter Ads with PiQ Audience Targeting

PiQ  Audiences  

•  A  –  Core  PiQ  Search  -­‐  Size:  1,500  –  Using  PiQ’s  built-­‐in  search  feature  only.  –  Used  keywords  such  as  ‘filmmaker’,  ‘cinematographer’,  ‘producer’,  ‘director’  to  find  relevant  individuals  

–  Limited  results  to  countries  in  Africa  •  B  –  Followers  and  Influencees  Size:  3,240  

–  Took  25  key  Twi,er  accounts  of  film  magazines,  organisa/ons  and  schools  in  Africa  

–  Created  a  list  of  users  who  follow  at  least  3  of  these  –  Added  people  who  men/oned  or  retweeted  two  or  more  of  the  accounts  from  Audience  A  

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Page 7: Optimising Twitter Ads with PiQ Audience Targeting

PiQ  Audiences  •  C  –  Lookalikes  Top  1000  

– Using  the  Core  PiQ  Search  Audience,  created  a  list  of  handles  with  similar  keywords  in  their  Bios,  ranked  by  similarity.  

–  The  top  1000  were  added  to  this  audience  •  D  –  Lookalikes  Next  5000  

– As  above,  taking  the  next  5000  •  E  –  Outsiders  –  Size:  1000  

–  The  users  most  influencing  (but  not  in)  Audience  A,  measured  from  men/ons  and  retweets  using  PeerIndex  influence  algorithm  

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Page 8: Optimising Twitter Ads with PiQ Audience Targeting

PiQ  Audience  Performance  (Round  1)  

Metric   Overall   A   B   C   D   E  

Click  Rate   1.28% 1.54% 1.34% 2.15% 1.30% 0.94%

Eng  Rate   3.98% 4.62% 4.04% 6.09% 3.96% 2.59%

Impressions   16,057 3,575 10,059 2,840 10,649 4,671

Clicks   205 55 135 61 138 44

Interac/ons   496 130 321 145 325 96

Retweets   75 21 49 13 50 19

Replies   3 1 2 2 2 1

Followers   65 13 34 13 45 5

Cost  Per  Click  

0.76 1.05 0.83 1.05 0.86 0.89

PiQ  Audiences  (see  slide  5  for  more  info)  

Best   Worst  8  

Page 9: Optimising Twitter Ads with PiQ Audience Targeting

PiQ  Audience  Performance  (Round  2)  

Metric   Overall   A   B   C   D   E  

Click  Rate   1.44% 1.87% 1.50% 1.63% 1.35% 0.76%

Eng  Rate   3.52% 4.68% 3.68% 4.71% 3.39% 2.18%

Impressions   8,486 3,267 4,672 2,081 6,880 1,192

Clicks   122 55 135 61 138 44

Interac/ons   246 126 141 81 189 22

Retweets   33 18 23 11 25 3

Replies   1 0 0 0 1 0

Followers   19 9 8 6 18 1

Cost  Per  Click  

1.18 1.03 0.92 0.83 1.12 1.81

Best   Worst  

PiQ  Audiences  (see  slide  5  for  more  info)  

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Page 10: Optimising Twitter Ads with PiQ Audience Targeting

Twi,er  Ads  Targe/ng  Control  campaigns  were  set  up  using  Twi,er’s  regular  built-­‐in  topic  targe/ng  and  user/follower  targe/ng.  

 

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8  Topics:    Independent  Film  Business  and  News  Documentary  Movie  News  Ac/on  and  Adventure  Drama  SciFi  Anima/on        

23  Users  (targets  their  followers):    @Nollywood  @FilmAfrica  @AfriWomenCinema  @IFCAfrica  @ScreenAfrica  @MTVBaseAfrica  @JumiaNigeria  and  other  similar  users…  

Page 11: Optimising Twitter Ads with PiQ Audience Targeting

Control  (Twi,er  Targe/ng)  1  Metric   Best  click  rate   Best  engagement  rate  

 

Click Rate 0.19% Independent Film 0.40% Independent Film 1.43% Engagement

Rate 0.97% Drama 0.23% Documentary 1.08%

Impressions 61,352 Documentary 0.21% Drama 1.03%

Clicks 118 Action / Adventure 0.21% SciFi 1.01% Interactions

(clicks) 541 Business and News 0.20% Animation 0.99%

Retweets 21

Replies 1

Followers 32

Cost per click 1.02

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Page 12: Optimising Twitter Ads with PiQ Audience Targeting

Control  (Twi,er  Targe/ng)  2  Metric   Best  click  rate   Best  engagement  rate  

 

Click Rate 0.66% Independent 1.12% Independent 2.33% Engagement

Rate 1.58% Business and News 0.72% Documentary 1.70%

Impressions 67,327 Documentary 0.71% Business and News 1.66%

Clicks 445 Movie News 0.66% Movie News 1.58% Interactions

(clicks) 977 Action and Adventure 0.61% Action and Adventure 1.53%

Retweets 46

Replies 9

Followers 32

Cost per click 0.67

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Page 13: Optimising Twitter Ads with PiQ Audience Targeting

Post-­‐ad  engagement  •  The  con/nued  engagement  with  tweets  aGer  the  ads  have  reached  their  

targets  can  spread  messaging  further  afield.  •  The  higher  rate  of  retweets  per  impression  suggests  that  the  PiQ  targe/ng  

reached  more  relevant  people  who  felt  the  messaging  would  be  interes/ng  to  their  followers.  

•  Ads  using  PiQ  targe/ng  were  retweeted  by  more  influen/al  users  with  a  further  secondary  reach.  

4.5  0.5  

Retweets  per  thousand  impressions:  

PiQ  

Control  

5,384  418  

Followers  per  retweeter:  

PiQ  

Control  13  

Page 14: Optimising Twitter Ads with PiQ Audience Targeting

Crea/ng  Advocates  

@HlubiMboya    PI  Score:  73  Followers:  70,900  

@mandyldewaal    PI  Score:  68  Followers:  21,800  

@Moni_R    PI  Score:  48  Followers:  3,538      

Important  users  based  in  Africa  retweeted  the  ads,  extending  the  reach  of  the  campaigns.    The  adver/sing  brand  also  collected  several  relevant  new  followers  from  Africa.      This  will  give  all  their  future  organic  ac/vity  added  focus  and  reach  as  well.  

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Page 15: Optimising Twitter Ads with PiQ Audience Targeting

PeerIndex  Audiences  for  your  next  campaign  

•  We’re  currently  looking  for  people  using  Twi,er  ads  (min  £1,000  /  $2000  budget)  to  test  PeerIndex  Audience  targe/ng  FOR  FREE!  

•  If  you’d  like  to  learn  more  about  what  we’re  up  to  get  in  touch  today:  

Nick  Taylor  –  [email protected]  

Page 16: Optimising Twitter Ads with PiQ Audience Targeting

Thank you Nick Taylor | [email protected]

Visit peerindex.com to start using PiQ today