# Market signals: Helping traders see, and act on, indications of interest Designer: Phaneendra Sivangula Interactive version: https://hellophaneendra.com/#/work/trading Role: UX Researcher & UX Designer (solo) Timeline: 30 days Team: Worked directly with FactSet stakeholders Summary: Indications of interest (IOIs) tell traders who wants to buy or sell, but they were scattered and hard to read. In 30 days, I designed a FactSet IOI platform that captures, analyzes and presents them inside the trader's workflow. Problem: Traders had no easy way to capture, compare and act on IOIs inside their order workflow. Approach: Contextual interviews with 8 traders, affinity mapping, 6-up ideation, two concepts, then moderated usability tests with 5 users. Outcome: An IOI app with live market data, buy and sell side by side, custom filters and one-click routing from linked apps. --- FINTECH / TRADING / FACTSET ## Helping traders see, and act on, indications of interest Indications of interest (IOIs) tell traders who wants to buy or sell, but they were scattered and hard to read. In 30 days, I designed a FactSet IOI platform that captures, analyzes and presents them inside the trader's workflow. ROLE UX Researcher & UX Designer (solo) TIMELINE 30 days TEAM Worked directly with FactSet stakeholders SCOPE 6 experiences, 20 screens 40% faster IOI bulk trading 15K+ asset managers and traders 6 experiences, 20 screens in 30 days PROBLEM Traders had no easy way to capture, compare and act on IOIs inside their order workflow. APPROACH Contextual interviews with 8 traders, affinity mapping, 6-up ideation, two concepts, then moderated usability tests with 5 users. OUTCOME An IOI app with live market data, buy and sell side by side, custom filters and one-click routing from linked apps. 01 The brief BACKGROUND ### Signals of who wants to trade Indications of interest (IOIs) are messages from market participants saying they intend to buy or sell a financial instrument. They help other traders judge liquidity and interest before they place an order. IOIs come in many forms, from block trades and dark pool orders to conditional orders, after-hours trading and algorithmic strategies. Read well, they show market sentiment and point to real opportunities. How might we build a user-friendly platform that captures, analyzes and presents IOIs, so traders can make informed decisions and act on market opportunities? MY PART ### One designer, end to end I worked independently with FactSet stakeholders as both the UX researcher and the UX designer, from the first interview to the tested prototype. 1 Research: contextual interviews and synthesis 2 Ideation: workflows, 6-ups and two concepts 3 Design: wireframes, visuals and prototype 4 Validation: moderated usability testing 02 Research UNDERSTANDING THE PROBLEM ### Eight traders, in their own setup I started with contextual inquiry interviews with 8 traders, chosen to cover a range of perspectives, and followed their journey from spotting interest to executing an order. An affinity map turned the notes into four clear needs: - Essential data points to choose the right broker - IOIs inside the order workflow, not in a separate tool - Real-time market data to read sentiment - Control over what's displayed 03 Strategy IDEATING ### Workflows first, then two big ideas Each scenario became a workflow: the actions a trader needs, assigned to screens and ordered into a clear information architecture. Two opportunities stood out: #### Suggest the best IOI - Recommend the strongest available IOI - Cut the manual analysis - Lower the cognitive load #### Show IOI trends - Visualize historical IOIs - Pair them with market trends - Read liquidity quickly 04 Design PROTOTYPING ### 6-ups, two concepts, many rounds I ran 6-up brainstorms around key scenarios: viewing available IOIs, connecting to different blotters, filtering, and customizing the view. That led to two concepts, an IOI Deal Pad from the Orders panel and a discretionary approach. I iterated on both with client feedback across workflows, IA, sketches, wireframes and prototypes. FINAL DESIGNS ### Designing around real constraints Technical constraints meant trading off some features. I kept the focus on the user problems and product requirements, so the product would drive adoption and retention. Here is the final flow, from a ticker to a routed order. Live data gives each IOI context, buys and sells sit side by side, the grid is easy to customize, and linked apps route in one click. 01Search a security 02See every IOI for it 03Read the live quote Price, spread and volume give each IOI context. 04Compare buys and sells Both sides together help with price discovery and liquidity. 05Make the grid yours Filters and columns for each desk. 06Route in one click Linked apps trigger the order right from the IOI. 05 Outcome USABILITY TESTING ### Less data by default, more control I ran moderated usability tests with 5 FactSet users on their own desktops, testing efficiency, intuitiveness, learnability and findability. - Participants found the flows intuitive and finished tasks efficiently - Most users only needed some of the data, so I limited the default view - Users can still customize the display to match their needs What the new flow changed. Traders go from a ticker to a routed order without leaving their workflow: 40% faster IOI bulk trading 1 click to route an IOI from a linked app 2 letters to find a security 6 steps from ticker to routed order The final prototype. Use the arrows or swipe. Click a screen to see it full size. 01 / 03 Start with a search TAKEAWAYS ### What I'd bring to the next one 1 #### Go to the desk. Contextual interviews showed IOIs belong inside the order workflow. 2 #### Default to less. Show the few fields most traders use, and let the rest opt in. 3 #### Constraints shape the scope. Cut features, but never the core user problems.