Intelligent SearchScandinaivan eBusiness Camp, 26th of May

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

Apptus clients

15% of the buyers

know exactly what they are looking for

70% have a clue,

but they are open to

guidance

Is it possible to guide & influence without being

relevant?

Relevant

interactions lead to more and better

transactions

Where Who

When ChannelWh

at

The many dimensions of relevancy

WHAT

• Only 10% of the users know the exact name, article id or specifics of what they are looking for

• 80% of searches address 20% of the database• The margin of the long tail is between 50-400%

higher than the top list

WHO

• Visit history(duration, time, length, outcome)• Search, Navigation and click track• Preferences (revisits to specific information entities)• Segment orientation and persona• Membership in any VIP or loyalty programs• Purchase history(duration, average order size, context)• Social network and influence• Contract specific terms for Business-2-Business

WHERE

• Nearest store where the buyer can explore the product

• Nearest location where the buyer can fetch or return the goods

• Location specific purchase/delivery terms

WHEN

• Seasonal influences • Trends(site-specific and general) • Ongoing marketing activities

Channel

• Web, Mobile, eMail, MMS, Store tillsLogged in

Anonym

ous

Ever met a great salesman who suffered amnesia?

* What we have shown* To Who, when and why* In what context* The outcome

We need to recall:

Learning from the crowd:automating the personalisation process

Behavioural database”Collective consciousness”

Fingerprints from past users –clicks, searches, purchases

New user

Michael Jackson

Book

Personalized Search & Navigation

Intelligent Search

Incremental search

Search Spellingcorrections

Auto-complete

Did you mean?

Implicitsynonyms

Combines multiple inputs• Product catalogue search• Browsing history• Learning from the crowd• Purchase history

to achieve the most relevant result

Multiple languagesMultiple channels

Auto-complete

Top of list: match to most

popular products

Search chosen fields in catalogue

Filtering auto-complete

Show how many hits for

eachOnly show

most important of

the total matches

Pick the most popular

matches for ‘bruc...’

Implicit synonyms

Implicit synonyms: look at what users did after searching

Spell-tolerant recommendations

Recommendations allow for common spelling

mistakes

Dynamic Navigation

Personalised, dynamic navigation simplifies product selection

Refines search results• Help shoppers zero in on what they want• Highlight factors influencing buying decisions• Shoppers will never see ‘no results found’

More ways to browse • Encourage shoppers to linger• Opportunity for up-sell and cross-sell

Personalize by relevance for higher conversion • Rank relevant attributes higher• Include user ratings

Dynamic Navigation

Navigation on brand landing page

Context-sensitive filtering

Product

Product

Product

eSales search finds best match to what user is looking for in each category…

…optimises use of page real estate

Faceted search personalised

Search, navigation and layout optimised for maximum conversions based on relevance & crowd learning

Category-based recommendations

Customers who bought things in

this category bought...

User-driven recommendations

People who bought this bought that...

Attribute-based recommendations

Other products with similar attributes....

Recommendations

Product

Product

Product

& selects and positions most effective

Product

Product

Product

Product

Product

Product

eSales creates recommendations using pre-build & custom merchandising tactics

Content Targeting

eSales automatically tests and chooses content to maximise sales outcome

Image

Image

Image

Image

Image

Image

Controlling merchandising

• Drag and drop deployment merchandising panels simplifies change

• Easily guides personalisation – e.g. boost products based on stock level

Displays

51150Inspects

27997Commissions

10233Commissions / Displays

19%Inspects / Displays

67%Commissions / Inspects

37%

Displays

32156Inspects

18356Commissions

5467Commissions / Displays

17%Inspects / Displays

57%Commissions / Inspects

30%

• Continuous feedback on performance guides improvements

Understanding performance

CombinedBehavioralSales

Text Match

Boosting relevancy from 20% to 80%

CombinedBehavioralSales

Text Match

Avoiding cold starts by combining technologies

Proven approach

By year-end 2013 over 30% of the 100 most popular websites will use search technology or content analytics to target content at users.

• 62% consumers find recommendations useful

• 15% admit to purchasing when they see recommendations

• “Retailers told us … that between 2% and 20% of their revenue could be attributed to recommendations”

Börge Olsen, Sales Manager

Personalised promotions double retention rates to 16%

CDON – the Amazon of the nordics

Challenges:• Slow search response times• Unstable IT environment and service

outages @ peak load• Irrelevant products shown to buyers

Results with Apptus eSales:• Lightening fast response time regardless of

load • 99.97% uptime and excellent reliability

during peak hours• Record sales in 2010 thanks to relevant

products exposed to the buyers in different contexts

• 10 million products

• 4.2 million searches/day; peak 2,000 searches/sec

• 5 million attribute updates/day

Reference case: CDON

Mikael Olander, CEO

Thank you

Michael.Mokhberi@apptus.com +46 701 66 41 02