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IxD ∩ DS

IxDA Helsinki 23.4.2015

Jouni Kallunki, Data Scientist @ReaktorNow @jouni9

What is Data Science?(Almost) Synonyms:

Machine learning, statistical modelling, analytics

A field between coding and statistics

Mathematical and/or statistical modelling of user behaviour and events

How is it related to IxDProvide means to improve services through:

Search, sort, personalisation, prediction

Assist design process through:

Analysis of user behaviour, finding patterns, related things, user paths

Testing

IxD tells how the analysis results and predictive components are built into the actual products and services

Where’s the $$$Two main goals:

Directly increase revenue from each session, better conversion and up-sell

Relevant especially for services used only once

=> Always Be Closing

=> Sell more! Sell expensive!

Make the service better, keep users coming back

Crucial for often used services

=> beat the competition.

Quick moneyAlways be closing

Increase probability of buying

Increase purchase size

Predict what add-ons you can sell or how expensive

Methods

Typically a prediction of how likely user is to buy each product

Finding optimum between likely small purchase and seldom large one

Remove unnecessary elementsShow only the relevant stuff, but what is relevant?

Predict what user is looking for based on:

her usage history, what she has done in this session and context

What should be done with the predictions?

How to balance reduction and choosing from all possibilities?

Search should be extensive, but return only relevant results and sorted meaningfully

Again: what is relevant?

Algorithms to sort found matches

Can also suggest similar items not matching exactly

Make searching easy

Assist browsingLarge catalogs make it impossible to find anything.

Search is good, but maybe don’t know exactly what I’m looking for.

Or maybe detailed description is lengthy.

Find thing through “something like this” browsing.

To help this:

Find similarities between items, automatically either through item’s properties or user behaviour

AutomateDon’t make people do machines work.

Repeatable simple tasks belong to computers.

Such tasks are most often found in professional tools.

Accounting, inventorying, etc.

How much can be automated? Maybe just suggest?

Usage analysisHow services are actually used can help designing it better.

Recognise:

Different types of users

Motives behind shopping baskets

Trends and other variations in time

Items, actions, persons that are related or similar

TestingTest to find out reality:

Even more important than what users do is how changes in service alter their behaviour. There is no other way to find out.

Good test result analysis:

Statistically valid results, acknowledges uncertainty

Includes variation of users

Not only webMost cases are in web applications and services

Mobile apps provide even more information about location & context

Also, assistance is always in users pocket.

IoT is coming…

IoT =? Interplay of things

What can my refrigerator tell to my oven? Or to grocery shop?

How much we can automate? Or suggest?