Einstein Chatbot
We turned Salesforce's chatbot from a sales funnel in a costume into a product advisor with a personality: one that asks before answering, reads hesitation, and never forces a handoff.
Einstein wasn't a generative AI chatbot. It just looked like one.
When we started, Salesforce's chatbot could produce simple responses and push users to contact sales, and that was about it. No memory, no personality, no product discovery. Four failures kept showing up.
Endless scrolling with no way to revisit earlier parts of the conversation. Users lost their place and gave up.
After most responses, the chatbot pushed users to contact sales before they had enough information.
Generic, repetitive phrases made the experience feel robotic. No distinctive personality or human-like tone.
Product suggestions were vague and generic. No links, no comparisons, no way to make progress on a decision.
"How does a little window like a chatbot get people to be excited about this experience?"
SALESFORCE SPONSOR · THE BRIEF IN ONE QUESTIONOne study asked how it should talk. The other asked what it should actually do.
Personality research and context research ran in parallel: 16 interviews with three chatbot personas on one side, contextual inquiries across ChatGPT, Amazon Rufus, and Einstein on the other. Open either one for what it found.
The research collapsed into a dolphin named Fin.
The personality research told us how the chatbot should talk. The context research told us what it needed to do. They merged into Fin, a curious dolphin with a schedule for its tone, and three principles that settled every feature argument after.
Assist, don't redirect.
Connecting to sales is a feature, not a fallback. It appears only after repeated failed attempts.
Adapt the tone to the moment.
Product browsing gets opinions. Troubleshooting gets empathy and brevity.
Make the information findable.
Every response should be locatable, comparable, and saveable without scrolling the entire thread.
Every feature either finds the product or reads the room.
Half the system helps you find and judge the right product. The other half watches how the conversation is going and adapts. Together the four features make one discovery arc. Click through them.
The conversation gets a map
A timeline alongside the chatbox generates clickable headings for each section of the conversation: user needs, product suggestions, comparisons. Clicking a heading jumps directly to that part. We tested two designs: a dark tab (hard to find without onboarding) and a skeleton timeline with a clock icon. The skeleton won, but users clicked instead of hovered, so hover-to-expand became click-to-expand.
Nothing came out of testing unchanged.
We put the mid-fidelity wireframes in front of four business professionals: timeline, triggers, and comparison flow. Every finding below forced a change. Open one for what we did about it.