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Airbnb Case Study: Marketing Automation

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The presentation is an example of how to apply the marketing automation tools with Airbnb products.

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Airbnb Case Study: Marketing Automation

  1. 1. Emarsys: Airbnb Case Study By Jitsupa Piyadit (31.01.2018)
  2. 2. Contents • Background: Airbnb - Products • Challenges • Strategy • Tactics • Evaluation
  3. 3. Background • Airbnb is launching in a new market SEA • Needs Emarsys to help them to define an omni-channel customer experience and marketing strategy to help gain market share and build a community • Currently using email and web scripts to capture customer behaviour
  4. 4. Airbnb • “An online marketplace and hospitality service, for people to lease or rent short-term lodging including vacation rentals, apartment rentals, homestays, hostel beds, or hotel rooms.” Source: Airbnb - Wikipedia Products • Home • Experience • Restaurant
  5. 5. Challenges • Airbnb is launching in a new market SEA requires relevant target audience • New products launch: Experiences and Restaurants • Only email and web scripts to capture customer behaviour will not be able to maximise reach
  6. 6. Strategy • Airbnb is launching in a new market SEA requires relevant target audience • New products launch: Experiences and Restaurants • Only email and web scripts to capture customer behaviour will not be able to maximise reach • CRM Ads: Reach relevant target audience and customer Retention • Predict: Increase sell by product recommendations (cross-sell) • Omnichannel Marketing Automation: Maximise reach
  7. 7. Tactics CRM Ads: Reach relevant target audience and customer Retention Retention: retention focused ad campaign targeting existing customer • Automate center audience (collecting new audience data, match and fill the user profile once reached CRM ads ) • Segment audience (synchronisation) Acquisition: Facebook lookalike audience Lookalike: existing travellers, competitors (homeaway, local guesthouse booking websites, etc.) 1% 5% 5% 10% New audience Segment A Segment B
  8. 8. Tactics Predict: Increase sell by product recommendations (cross-sell) Web: Enhanced browsing experience Personal widget: First display popular listing/unique listing/low price listing etc. then personalise as the web user is browsing through Email: Personalised recommendation in newsletters Recently booked CatA: San Francisco Recommend CatA ProductA,B: Experience and Restaurant in San Francisco Mobile App: Abandoned cart campaigns Display related listing to abandoned listing via mobile app: use CART web logic Display personal widget Email: Personalised recommendation in newsletters
  9. 9. Tactics Omnichannel Marketing Automation: Maximise reach Making Decision Purchase Touch points Check price/Find listing Inquiry: send message to hosts Saw Facebook Ads, liked friend’s newsfeed at Airbnb listing Discuss with friends browsing listing/share wish list Received host message confirmation of listing Chat with friends on Facebook chat to confirm the listing and booking Make a reservation Devices Airbnb Website (Web) Airbnb Facebook Ads (Social Media) Airbnb mobile app (Mobile App) Email/SMS/Push Facebook chat Airbnb mobile app (Mobile App)
  10. 10. Evaluation CRM Ads: Reach relevant target audience and customer Retention Revenue vs Cost ROAS CRM Ads Funnel CPM/CPC/CPA Impressions Clicks Conversions Predict: Increase sell by product recommendations (cross-sell) Performance overview Revenue from Web recommender Revenue from Email recommender Discovery (open - click - revenue) Omnichannel Marketing Automation: Maximise reach Increased number of conversions from one-o purchases. Increased click-through rates on email campaigns.
  11. 11. Q&A
  12. 12. Thanks a million! Jitsupa Piyadit

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