Ecommerce&

Machine Learningby David Jones - Technical Director - Resolve Digital

Google Search - NetflixGmail Spam Filter - SiriFraud Detection - Amazon

Machine learning is not just for the

big guysanymore.

Machine Learning in EcommerceEmail marketing

Cross-sellingPersonalised recommendations

Abandoned Cart EmailsLead Scoring

—1. Collect Data2. Train Model

3. Make Predictions—

Collect Data:Purchases

Product ViewsLikes & Ratings

Wishlists

Any data that linkscustomers to products

2. Train Model

—

—

prediction.ioOpen Source Machine Learning Server

Ecommerce TemplatesAPI for DevelopersProduction ready

3. Make predictions

Real world example:United Cellars

16k product views60k orders

3k product ratings

79000 rowssmall data (by bay area standards)

With winetaste preferences are

diverse

1. Personalised Product Recommendations2. Similar Products

A/B TEST

Filter PredictionsAvoid anything that lessens relevanceDon’t show out of stock products

How do your customers’ shop?

With Winepeople usually prefer red or white

A/B Test Results45% longer average session22% increase in conversion rate37% increase in average order size

71%More Revenue

Machine LearningGenerates revenue

But alsoImproves customers’ experience

3ThingsLearned

1The human touch

is still important

2prediction.io

is awesome

3Small data

can be enough

Thank You~

David Jones, @d_jonesresolve.digital/ml