Competitive Intelligence

I designed an advanced SaaS platform product for C-level execs of top-tier mobile operators.

Despite facing numerous challenges with limited research possibilities and a congested project pipeline, I delivered a viable MVP with easy-to-understand architecture and relevant vizualizations for complex data, within a tight timeframe.

My high-fidelity prototype impressed clients so much that we sealed deals prior to implementation.

Competitive Intelligence, an advanced Software-as-a-Service (SaaS) Platform Product, is specifically designed for the C-level executives of top-tier mobile operators such as Vodafone and Free. By providing these key decision-makers with timely and accurate information, Competitive Intelligence empowers them to gain a clear understanding of their market with early warnings ahead of public disclosures.

This executive dashboard is a part of the Opensignal* Products portfolio, alongside the Public Reporting and Brand Endorsement offerings.

*Opensignal is an authority in measuring and reporting on mobile network experience and quality worldwide.

The challenges

I led the development of use cases and user flows, culminating in the design of a sophisticated interface that presents clients with relevant insights into our complex metrics.

However, the complexity of the Opensignal methodology, which captures the real mobile experience of consumers, resulted in persistent confusion around our metrics even within the organization, necessitating regular consultations with subject matter experts.

It became clear that if we faced these challenges internally, presenting the metrics to clients in a way that they could comprehend without drawing erroneous conclusions would be a significant hurdle.

Our metrics, including Speed, Latency, Voice, Games, and Video Experience, are designed to accurately reflect the real-world experiences of consumers, but translating them to a user-friendly format remains a formidable challenge.

A couple of competitive products

Studying cases with our internal experts served me in learning the mental models in analysis.

In the example below, two main factors affected Rakuten’s low speeds:
Only 1 frequency available for 4G (Band 3: 1825-1845MHz) + some regions limited to 5 Mhz
Average national speed was dragged down by low-performing regions such as Kyushu, Chugoku and Tohoku, potentially due to domestic roaming with KDDI where users are limited to 2Mbps.

Competitive Intelligence was the first SaaS product Opensignal planned to offer, which was the consequence of directional change company took at that time.

We faced challenges with limited research possibilities due to the scarcity of C-level executives in our focus markets and their busy schedules. The complex structure of our metrics and sub-metrics, limited access to comparable products offered by our competitors, and a congested project pipeline created time constraints for delivering a feasible MVP.

First generation of the MVP

The design process involved creating multiple low and high-fidelity versions of the project, while learning from stakeholders and a data science team. The team experimented, failed, and iterated to reconstruct the audience’s way of thinking. Objecting and iterating took several weeks.

Design solution has been adapted to a quite limiting technology known as Qlik Sense.

How to determine the quality of this product design?

My focus was on the most important aspects of the project while working solo under tight deadlines. As a designer who tried to explain metrics, I had to know them by heart, so I could organize them in an easy-to-understand product architecture and provide relevant visualizations for complex data

I achieved a rewarding sense of accomplishment when we sealed deals with clients prior to implementation, thanks to the high-fidelity prototype. The Sales team was impressed that they could sell a non-existent product.

Well done, Malgo!