The Client
We created the system for a marketing company that caters to
some of the biggest names in American publishing. Thanks to our
reputation, we were approached to build a system that addresses
some of the key challenges faced by publishers as they digitize
their operations.
Business challenge
As publishers digitize they must find new ways of reaching out to readers,
and focus on building a revenue model based on subscriptions in a media
marketplace that has never been more crowded and competitive.
Revenue model
Publishers are shifting back to a model powered by their readers,
rejecting the advertising-based model of the early digital years.
This requires a new approach to readers and to acquiring and
keeping subscriptions.
Converting subscribers
Converting casual readers to subscribers in the digital world
is both more necessary and more difficult than signing up
regular newspaper readers. Publishers must source the
tech and skills to convert and retain a new generation
of consumers.
Consumer expectations
Customer expectations have been conditioned by other
digital media platforms such as Netflix. Readers now
expect personalization as standard, and are no longer
satisfied with a one-size-fits-all approach.
Content responsiveness
Publishers need to know which content is successful with which
readers, in order to plan future content creation and distribution
strategies. Without attribution and analysis, they cannot build
the publication their most profitable readers want.
When they attempt to address these concerns, publishers typically encounter technical issues including:
Persistent user identification
Identifying anonymous, non-logged in users on the site across sessions.
These are conversion targets, but while they remain anonymous there can be no
data-driven conversion rate optimization (CRO) aimed at them.
Support for different clients and structures
When building tools for publishers, agencies encounter difficulties
in creating a tool that supports
multiple website structures and client backend logic flows.
Data acquisition granularity and volume
To be effective, the system must collect and analyse massive tranches
of granular pageview data for large numbers
of users, including anonymous users and subscribers.
Inbound sales
Integration across the stack is a vital component of integration
across departments; in particular, inbound sales needs a responsive,
real-time window into the insights generated by the system.
The goal was to create a system that addressed
these concerns, equipping publishers for digital success.
In particular, it was necessary to deliver:
- Increased sales efficiency
- Transparency of data and decision-making facilitation based on analysis
- Automated suggestions to readers and campaign running
- Calculation of likelihood to subscribe
- Personalized content consumption patterns
Personalizing publishing CRO at scale with machine learning
Lightpoint created a ML-based tool that matches users with
content based on analysis of their previous behavior, and creates proposals designed
to appeal to individual users, programmatically and at scale.
1. A reader visits the publisher’s site.
2. The backend matches that reader with a persistent
identity inside the tool and an analysis of their previous onsite behavior.
3. Based on this, the system offers that
reader content with a higher probability to encourage conversion.
4. The system also generates tailored calls to action
and personalized proposals emphasizing
the content most likely to generate conversions.
5. Post-subscription, the process continues, with relevant
offers displayed to segmented subscribers to encourage retention and upgrade, and
sales involved in upselling and cross-selling where appropriate.
Key features of the system
Single user identity
Even anonymous users have a single, persistent identity
across sessions, which survives cache
clearance and enables long-term data collection.
Rapid sales response
The system is built to help increase the speed of sales
reps to warm customers, as well as putting customer
information at their disposal to improve closure rate.
Marketing campaign automation
Offers and analysis are built into marketing campaign design,
allowing automated launch and monitoring.
Report generation and dashboarding
The system converts analysis into reports delivered via a dashboard,
providing the insights necessary for data-driven strategy.
Lightpoint built the system with:
2 Front -end Developers, 1 Back-end Golang Developers,
1 Data Scientist / Python developer, 1 Manual QA
Tech stack:
Database:
Google bigquery, Mongo, Postgres
Back-end:
Go (REST WebAPI), Python, NodeJs
UI:
TypeScript
Other:
GCP, GA, Google Data studio
Results
The product has become one of the most popular in the
US media market, and continues to develop and expand its
functionality. Our customers became the largest players in
the American media market with a combined market share of
around 60%. Customers of all sizes, not just enterprise clients,
saw sharp increases in revenue and subscriber numbers.
Ready to talk about a similar solution for your business?
Get in touch with us at: