Fusion was implemented at Foot Locker to improve the speed and scalability of their search capabilities. It helped reduce indexing times from 1 hour to 5 minutes, enabled A/B testing and experiments, and provided more dynamic faceting and keyword handling. Customers experienced a 0.25-1% increase in conversion, 1-2% increase in revenue per visit, and 4% decrease in null search rates. Future goals include enabling dynamic relevancy using analytics, geospatial search, multi-lingual support, and expanding to Europe and Asia-Pacific markets.

2. Speed At Scale
Fusion at Foot Locker
PAVA N B A R U R I
Director, Core Services
Agenda
• Need for speed at scale
• Foot Locker search problem statements.
• Foot Locker customer reaction.
• Future goals of Fusion at Foot Locker

3. Need for speed at scale

4. Multi branding support
LOGO LOGO LOGO
LOGO

5. Complex retail calendar
Ja
n
Feb Mar Apr May Jun
Ju
l
Aug Sep Oct Nov Dec
Shoe
Launches

6. Speed to market

7. Mobile savvy customers
Augmented
Intelligence
Data
Science

8. What did we do?
• Evaluated multiple solutions and choose
Fusion
• Migrated Foot Locker search from Hybris
Solr.
• Leverage plug and play components of
Fusion.
• Scaled the installation to support all Foot
Locker customer facing sites.

9. Foot Locker search problem
statements

10. Relevancy Tuning
Search and relevancy strategy for different brands at Foot Locker
• Fusion abstracts relevancy and search tuning at an App level.
• Create an App for each brand to maintain different relevance algorithm, field
weightages, boosts and signal rules.
• Weaved stages within relevancy strategy through the query pipeline.
• Share common query pipeline components across Apps to cover some
common aspects between the brands.

11. Indexing Times
Long indexing times and no capability to update index in real time
• Use of Fusion’s prebuild connectors for various data sources with minimal
customization.
• Use Fusion’s prebuilt API’s to perform index updates in real time.
• Build stages within index cycle using index pipeline.
• Index times reduced from 1 hour in Hybris Solr to 5 mins in Fusion.

12. Synonyms and keywords
Synonyms and keywords used to solve relevancy problems
• Use of Fusion’s rules editor to configure required promotional keyword
redirects.
• Rules editor also used to boost and bury products for specific keywords.
• Keyword redirect configurations were reduced by 70%.

13. Experiments and A/B tests
No capability to run experiments and A/B tests to test relevancy tuning changes
• Use of Fusions experiments feature built into the platform.
• Leverage Fusion’s provides analytics engine to ease measurement of your A/B
tests.
• Goal to run more than 10 experiments per month.

14. Facets
No dynamic facet and multi select facet capability.
• Use Fusions field facet stage in the query pipeline to create dynamic facets.
• Dynamically change the facets based on the facets selected by the users.
• Apply rules using the rules editor to apply facets on certain keyword triggers.

15. Monolith vs Microservice
Traffic on search impacting other commerce functions.
• Fusion allowed to completely decouple from our main commerce system.
• Single installation of multi cluster Fusion supporting all the traffic from different
sites.
• Allowed to separate Fusion components to different VM’s allowing more
optimized scaling of each component.

16. Foot Locker customer reaction.

17. Conversion
0 . 2 5 T O 1 % I N C R E A S E

18. Revenue Per Visit
1 % - 2 % I N C R E A S E

19. Null Search Rate
4 % D E C R E A S E

20. Future goals of Fusion at FL

21. E N A B L E D Y N A M I C R E L E VA N C Y C O N S U M I N G
S I T E A N A LY T I C S S I G N A L S
E N A B L E G E O S PAT I A L S E A R C H T O A L L O W
U S E R L O C AT I O N B A S E D R E S U LT S .
G O G L O B A L I N T O E U R O P E A N D A PA C
S U P P O R T I N G M U LT I L I N G U A L S E A R C H
C A PA B I L I T Y
4%
MOREC O N V E R S I O N
$$$R E V E N U E P E R V I S I T

22. THANK YOU