Machine Learning & Ecommerce - by David Jones - PAPIs Connect
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Transcript of Machine Learning & Ecommerce - by David Jones - PAPIs Connect
Machine Learning&
Ecommerceby David Jones - Technical Director - Resolve Digital
Machine learning & Ecommerce
better. together.
Predictive APIsmake it feel like you have your own
team of ML experts
Personalised recommendations
Abandoned cart emails
Customised content
Lead scoring
Email marketing
Benefits of ML in EcommerceMore visitors with longer session duration
Improved retentionHigher conversion rates
Larger order sizeBottom line, more revenue.
machine learning in ecommercedeeply enhances customer experiences
Customers expect ML featuresEven if they don’t know what ML is
Real world example:United Cellars
Goal: Increase revenueSolution: Product recommendationsImplementation: Predictive APIs
16k product views60k orders
3k product ratings
79000 rowsSmall data
Any data that linkscustomers to products
Optimise data collectionInitially had no data for logged out users
PredictionIO
Open source machine learning server
Ecommerce templatesUses established implementation of algorithms
Evaluation metricsProduction ready
Storefront <-> Processing Queue <-> PredictionIO
PAPI Production TipsMonitor performance
Cache where realtime is not neededDerived data is low risk
Bricks & mortar retailinspires an ecommerce experience with ML
With winetaste preferences are diversepeople usually prefer red or white
A/B TESTwith Google Analytics
Filter PredictionsAvoid anything that lessens relevanceDon’t show out of stock products
A/B Test Results45% longer average session22% increase in conversion rate37% increase in average order size
71%More Revenue
Where to next?Predictive features in more channelsIntroduce new predictive features
Conclusion
1Small data can be enough
Quality is key
2Predictive APIs
are awesome
3Machine Learning
is highly effective withEcommerce
Business LeadersStart a project
Use Predictive APIsThe timing is perfect