Apptus provides intelligent search, recommendations, and content targeting technology to help e-commerce sites boost profits and streamline operations. Their relevance engine analyzes multiple dimensions like what, where, when, who, and channel to provide the most relevant results. It uses techniques like auto-complete, spelling corrections, implicit synonyms, and dynamic navigation personalized for each user. Reference customers like CDON, a Nordic Amazon, saw increased sales and reliability using Apptus's technologies to show more relevant products to buyers.

1. Intelligent Search ScandinaivaneBusiness Camp, 26th of May

2. Introducing Apptus Pioneering relevance engine technology Search, recommendations & content targeting for e-Commerce Boosts site profits; streamlines marketing & merchandising back-office Founded in 2000, profitable and VC backed HQ & development in Lund - Sweden Sales offices & partner network in Europe and North America

3. Apptus clients

4. 15% of the buyers know exactly what they are looking for 70%have a clue, but they are open to guidance

5. Is it possible to guide & influence without being relevant?

6. Relevant interactions lead to more and better transactions

7. When Channel What Where Who

9. Nearest location where the buyer can fetch or return the goods

11. Trends(site-specific and general)

13. Search, Navigation and click track

14. Preferences (revisits to specific information entities)

15. Segment orientation and persona

16. Membership in any VIP or loyalty programs

17. Purchase history(duration, average order size, context)

18. Social network and influence

20. Ever met a great salesman who suffered amnesia?

21. We need to recall: * What we have shown* To Who, when and why* In what context* The outcome

22. Learning from the crowd: automating the personalisation process Book Michael Jackson Behaviouraldatabase”Collectiveconsciousness” New user Fingerprints from pastusers –clicks, searches, purchases

23. Intelligent Search Personalized Search & Navigation Multiple languages Multiple channels Combines multiple inputs • Product catalogue search • Browsing history • Learning from the crowd • Purchase history to achieve the most relevant result Search Incremental search Spelling corrections Auto- complete Did you mean? Implicit synonyms

24. Auto-complete Search chosen fields in catalogue Top of list: match to most popular products

25. Filtering auto-complete Pick the most popular matches for ‘bruc...’ Show how many hits for each Only show most important of the total matches

26. Implicit synonyms Implicit synonyms: look at what users did after searching

27. Spell-tolerant recommendations Recommendations allow for common spelling mistakes

29. Highlight factors influencing buying decisions

33. …optimises use of page real estate eSales search finds best match to what user is looking for in each category… Product Product Product Search, navigation and layout optimised for maximum conversions based on relevance & crowd learning Faceted search personalised

34. Category-based recommendations Customers who bought things in this category bought...

35. User-driven recommendations People who bought this bought that...

36. Attribute-based recommendations Other products with similar attributes....

37. Recommendations & selects and positions most effective Product Product Product Product Product Product eSales creates recommendations using pre-build & custom merchandising tactics Product Product Product

38. ContentTargeting Image Image Image Image Image Image eSales automatically tests and chooses content to maximise sales outcome

41. Boosting relevancy from 20% to 80% Combined Behavioral Sales Text Match

42. Avoiding cold starts by combining technologies Combined Behavioral Sales Text Match

44. 15% admit to purchasing when they see recommendations

45. “Retailers told us … that between 2% and 20% of their revenue could be attributed to recommendations”By year-end 2013 over 30% of the 100 most popular websites will use search technology or content analytics to target content at users. Börge Olsen, Sales Manager Personalised promotions double retention rates to 16%

47. 4.2 million searches/day; peak 2,000 searches/sec