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Case study: Square Meal - How to use Intelligent Data to Implement Successful Recommendation Campaigns

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Case study: Square Meal - How to use Intelligent Data to Implement Successful Recommendation Campaigns

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This slide share presents the benefits of using intelligent data to implement successful recommendation campaigns. Looking specifically at email and web recommendations highlighting the benefits personalisation can provide when delivering the right message to the right person at the right time.

This slide share presents the benefits of using intelligent data to implement successful recommendation campaigns. Looking specifically at email and web recommendations highlighting the benefits personalisation can provide when delivering the right message to the right person at the right time.

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Case study: Square Meal - How to use Intelligent Data to Implement Successful Recommendation Campaigns

  1. 1. VIENNA • LONDON • MUNICH • ZURICH • BERLIN • PARIS • HONG KONG • MOSCOW • ISTANBUL • BEIJING • SINGAPORE • DUBAI How to use Intelligent Data to Implement Succesful Recommendation Campaigns, a Square Meal Case Study Daniel Hagos – Client Solutions Manager, Emarsys Ed Butcher – Head of Online, Square Meal
  2. 2. Talk with us @Emarsys @SquareMeal #totallyengaged Before we begin…
  3. 3. About Emarsys
  4. 4. About Emarsys Email Service Provider The Customer Engagement Company
  5. 5. 4 key questions for successful customer engagement
  6. 6. How to choose the right Product?
  7. 7. Marketers aims Personalized and Targeted Communication ” 88% of business leaders said being closer to their customers was the top priority for realizing their strategy over the next five years IBM 29% 34% 38% 37% Social media engagement Conversion rate optimisation Content marketing Targeting and personalisation 2013 2012 44% 41% 66% 37% 39% 56% 44% 31% Improving email deliverability Quantifying email marketing ROI Targeting recipients with highly relevant content Both channels (32B2C) Consumer channel (B2C) Business channel (BB) Which three digital-related areas are the top priorities for your organisation in 2013? Most significant challenges to email mar-keting effectiveness, by primary channel “ 39% 39% 39% 68%
  8. 8. The reality Are targeted emails being sent? 20% 20% 20% 19% 19% 25% 25% 24% 18% 18% 15% 9% Content viewed on site Up-sell Abandoned baskded Subscription due for renewal Selling comple- mentary products Lapsed customers Win-back/reengagement Shopping cart abandonment Upsell/Cross promotional Date triggered Event countdown Post purchase Activation Triggered based on website behaviour Do you send out automated emails based on any of the following triggers or behavior? Do you use targeted email for the following occasions? In spite of consumer affinity for personalization, few companies other than Amazon.com and Netflix execute it in a turnkey, efficient, and effective way. Forrester “ ” 64% of CMOs have either an informal or no process to manage their marketing automation. The Annuitas Group “ ” 25% 26%
  9. 9. Why Is There A Gap? Many delegates focused on... the barriers they face before implementing a marketing automation platform, with the vast majority saying that they don’t know where to start (especially in a very large organisation) Econsultancy, 2013 “ ” Lack of know-how …on the barriers they face before implementing a marketing automation platform, ……or that internal challenges prevent them from making any notable progress Econsultancy, 2013 “ ” Internal challenges (e.g. IT support, no resources) Decision Tree Labs, 2013 “ ” Lack of integration IBM, 2013 “ ” Budget & ROI The two biggest barriers are cost and lack of certainty about ROI — both issues that are becoming increasingly important in the marketing domain 46 percent believe one of the top challenge of data- driven marketing today is the inability to connect data across multiple sources
  10. 10. Currently, what data do most marketers use to send segmented campaigns? What data is being used? Purchase behaviour Gender Preference centre Email behaviour Merchandising Teams knowledge
  11. 11. How do you know what a customer is interested in now?
  12. 12. The Website tells us what a customer is interested in now The most meaningful interaction with the customers is on the website 10x more user data generated on the website compared to email alone The website is always the most up-to-date point of expressing interest Challenge: How can the website data be utilised to automatically create unique and personalised content across various marketing channels?
  13. 13. Recommendations : How do they work? Captures: • everything visitors do on the website Capture Analyse Act Applies: • recommendation and prediction algorithms to the data Provides: • personalised content in web, email and display advertising
  14. 14. Multi-channel recommendations Dynamic recommendation widgets in real-time. Boost website conversions and sales. Automatically personalise every email you send. Recommend products to people. DisplayAd Retargetng Website Recommender Email Recommender Retargeting keeps track of your website visitors and displays your ad to them as they visit other sites.
  15. 15. Recommendations… only for the big boys??? Who’s using recommendations effectively?
  16. 16. Now available to SMBs.. Who’s using recommendations effectively? and many more… electronics real estate job listings toys grocery books dating
  17. 17. Why do they work? ROI Revenue Brandloyalty Engagement Engagement CTR Enabling personalised, highly relevant 1-to-1 product & content recommendations
  18. 18. Why do they work? “Up to 20% of retailers revenue could be attributed to product recommendations” “15% of consumers explicitly admitted that they purchased when they saw recommendations on a page”. (Forrester, 2010) What percentage of revenue can be attributed to product recommendations??
  19. 19. Browsing Cart Purchase Multi-Channel Recommendations across the Buyer Cycle 2 Predict Website Predict Email Personal • 8% CTR • 2.5% revenue Similar Items • 10% CTR • 4-10% revenue Matching Items • 2-3% CTR • 1% revenue Abandoned Browse • retarget aban- doned browse In Cart • 4% CTR • ~3% revenue Abandoned Cart • retarget aban- doned items Re-Purchase • Increase retention & ROI Personal • 1.5-2x CTR • 2-6x revenue
  20. 20. About Square Meal • UK’s leading guide to restaurants & bars • 2 print titles • Big website, mobile site & apps • 11,000 restaurants, 8,000 venues • Active database of 250,000 users • 2 trade shows • 25 years Square Meal Background
  21. 21. Square Meal Results from Predict 43% higher click through rate when Square Meal’s emails have recommendations More customers can discover new restaurants and fewer leave without booking 4 times more likely to convert.
  22. 22. Before recommendations • Open Rate: ~31.29% (max 48%) • Click Through Rate: ~13% (max 22%) • Click To Open: 40% • Loyalty (LTV): increased 30%
  23. 23. Similar/Related Items ALSO VIEWED widget offers alternative products • “Other products you may be interested in” • Generates 4%-10% of total revenue • Increases engagement, average CTR 10% • Square Meal: 4% of all website bookings revenue is generated by Emarsys Predict
  24. 24. Learn the 3 key benefits of using a single platform over disparate technologies 3:30 – 5.30pm
  25. 25. VIENNA • LONDON • MUNICH • ZURICH • BERLIN • PARIS • HONG KONG • MOSCOW • ISTANBUL • BEIJING • SINGAPORE • DUBAI Thank You Any Questions?

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