Quantifying Knowledge

with :CRUX

James Webb

Group Product Manager, FT.com

About :CRUX

A technology company dedicated to Quantifying Knowledge.

:CRUX measures how much users know based on what they read,

and recommends the best content to increase their knowledge.

:CRUX’s mission is to quantify knowledge everywhere,

for everyone.

“Stay abreast of global

business, political and

economic developments

to formulate a ‘big

picture’ view.”

“Understand

the context of a

specific issue

that is relevant

to my client.”

“Be confident that I

haven’t missed out on

interesting things my

colleagues might

know about.”

Our users #JTBD

“Be updated

about news

relevant to

my industry”

“Research a

topic or company

to become an

expert in it.”

Reading the FT

supports

work needs

People often

know what they

need to know.

But when do

they know

enough?

The plan

We’ll provide users with a live

knowledge score and

recommendations to show

them how much they might

know based on what they’ve

read, with a more compelling

onward journey.

Scenario 1:First Contact

Article Journey

KQ:The

Quantified

Knowledge

Box

First Contact,Article journey

The KQ box appears

on all relevant article

pages.

Live knowledge score

displays how much the

user knows about a

Topic, based on articles

read.

Recommendations

appear for further

knowledge-rich articles

about the topic. The

expected contribution to

the user’s KQ score is

displayed next to the

articles.

On reading this story

about quantum

computing, their KQ

score gained 10%...

First Contact,Article journey

...and a further 8% by

moving onto this story

about China’s robotics

industry...

First Contact,Article journey

...and so on.

With three article reads,

this user has moved their

KQ score to 52%.

First Contact,Article journey

Scenario 2:User returns to a previously read topic

KQ:The

Quantified

Knowledge

Box

Scenario 2:Users return to a previously read topic

...the system quantifies

and displays the

negative knowledge

impact of what they

have missed out on

since their last visit...

...and recommends a

maximum knowledge

reading list covering

new developments

since their last visit

When users return to a

topic on which they have

previously built up

knowledge...

Scenario 3User reviews topic progress over time

KQ Dashboard

Users can choose

knowledge topics to

follow in myFT, and can

track their progress

history in a central

dashboard.

KQ Dashboard

...and see the expected

benefit of reading the

recommended articles. They

also see the predicted

negative impact if they

ignore this topic further.

Users can track how

they gained and lost

knowledge in a topic

over time...

Users will receive periodic

Knowledge summary emails

analysing their progress with

a cross-topic view.

Here they can compare their

knowledge progress in

different topics directly within

the email.

And see individual

achievement highlights, as

well as comparisons to other

readers.

Scenario 4: Periodic Knowledge update Email

Exploring multiple engagement prospects

KQ: Dashboard

Ways to maintain

engagement over

time

KQ: Articles

Innovative hook

from an article

page journey

KQ: Email & Alerts

Helping users understand

their time and effort

investment while offsite

How will we measure success?

RFV: The metric that matters

Recency

How recently the subscriber visited

Frequency

How many times they visited

Volume

How many articles they read

This metric galvanises many areas of the business because it correlates

with FT subscription revenue.

Becoming engaged

leads to 10% reduction

in cancellation rates

There are two ways to increase Engagement

Recency Frequency Volume

How can we

encourage

people to make

another visit?

How can we

encourage

people to read

another article?

Revenue prospects

If we can get disengaged users to visit

one extra time every 90 days, and read

one article extra per topic they already

engage on - we believe this to be worth

up to £1.5m per year.

At the end of the project we hope to have:

● A working Knowledge Score algorithm from :CRUX

● A KQ presence on articles, a topic progress dashboard and some

experiments with alerting

● Insights into which subscriber types find the ‘knowledge’ treatment

most appealing

● An indication of in-demand knowledge topics among subscribers

Outcomes

Thank you

@jameswebb