NetBase
Enterprise
A high-precision engine for trained analysts. My job was making its power legible and shareable.
The platform had power to spare. It didn’t have reach.
Enterprise could process billions of posts and slice sentiment a hundred ways, but all of that lived with the trained analysts who ran it. A spike on a chart means nothing without context. A curated view means nothing if only the analyst can build it. A crisis means nothing if no one catches it in time. My feature work kept answering the same question in different shapes.
Giving the data context, right on top of the data.
Analysts sat on valuable data that was useless to anyone without the story behind it. Annotations let them mark a launch, a campaign, an event, so a spike could be read correctly by anyone with access. My first concept was a side panel of notes. It didn’t hold up. The stronger, riskier idea was annotating in-chart, something we weren’t sure Highcharts could even support.
Design for the best idea to pull engineering forward, keep fallbacks, don’t pre-compromise.
The full story, the rejected side panel, the in-chart bet, and pushing Highcharts past its defaults:
Read more about AnnotationsCarrying the data to people who’ll never open the platform.
A major global retailer needed social data in front of managers and C-level execs without giving them the raw Enterprise platform. It started as a simple emailed snapshot and grew, through ongoing work with the client, into a live dashboard of analyst-curated data. I made the call for live over a static report because it fit the real use case.
A one-customer feature that had to serve many, de-risked by pulling other clients’ feedback in early.
The full story, snapshot-to-dashboard, the live-vs-static call, and designing one-for-many:
Read more about the Executive DashboardSpotlighting the spikes that matter, good or bad.
Crisis management is a headline selling point for an enterprise social platform. Analysts needed to catch large fluctuations fast and drill straight into the cause. The hard question was the whole feature: what even counts as a fluctuation?, because the honest answer is it depends on who’s looking.
“Simple, sufficient, complete”, ship a threshold-based MVP now, hand users control later.
The full story, defining the undefinable, and scoping an MVP that could actually ship:
Read more about Fluctuation AnalysisThree features, all in production.
All three shipped. Annotationswent in-chart, over an initial doubt that Highcharts could support it, the dev team stretched past the platform’s defaults and made it work. The Executive Dashboard shipped as a live dashboard, built with one retail client but validated with others during development, so analysts could stop hand-building exec reports. Fluctuation Analysis shipped as a threshold-based MVP, with a defined path toward user-set thresholds.
How I kept shipping on questions with no perfect answer.
Our CTO’s scoping frame: simple is the MVP, sufficient is enough to launch with most functionality, complete is fully realized. It let me scope an honest MVP when a question, “what counts as a fluctuation?”, had no perfect answer, instead of stalling.
Rather than pre-compromise a design to the platform’s current limits, I designed for the best idea and let it pull engineering forward, fallbacks in my back pocket. In-chart annotation is exactly that: a bet that stretched the team past building only to the defaults.
On a dense platform, the design work is making the power usable and shareable.
These features shipped with KPIs framed as goals, more data shared between analysts and non-analysts, faster understanding of fluctuations. The dedicated feature screens are illustrative reconstructions of the design decisions, not the original production UI.