STEP 24: Consultative Robots
Objective: Engage with Recommendations Engine/Quiz Why This is an advanced module to enhance what we’ve built so far. Immediate implementation may or may not...
This is an advanced module to enhance what we’ve built so far. Immediate implementation may or may not be necessary.
A recommendations engine is an extremely effective and evolutionary tool to instantly generate outcomes based on user’s preferences.
The goal is to match users with a suitable product to start their exploration process.
It is a great tool to guide user’s product search without a sales agent.
This engagement also allows your company to collect personal information, which makes it a great alternative to traditional methods of data collection.
Recommendations engines are the start to a personal relationship without the human interaction.
Here are some of the benefits:
Easier to use than search and sorting
Fun, interactive and provides real results
Trustworthy lead generation tool
Gives actual value without a physical present
Personalizes the user experience
Creates immediate trust and is resourceful
Offers instant gratification with incentives
Think of some naturally engaging and interactive experiences for users that can assist users in product discovery.
We recommend that you work with someone who has experience with quiz-making software, form builders, and creating calculated outcomes.
Use the tool below to structure your quiz.
Brand the outcomes and incentivize users for taking immediate action.
Store client inputs securely and provide curated suggestions for the client to explore.
Spotify recommendations engine is truly the best in the music business.
It can accurately predict the style of music you like and recommend artists you never knew you liked. It is truly an algorithm of taste.
Spotify’s recommendation engine curates music using more narrowly segmented data than other platforms and matches your taste with similar profiles.
No one truly knows the magic that happens behind the scenes (even if they say they do), but this is a perfect example of why recommendations engines work so well. They help users passively discover more music on the platform based on their specific preferences.
Each answer is auto-linked to its color-coded outcome. Make sure to assign answer choices according to its outcome.
Potential Question Categories:
Aspirations, Income, Location, Interests, Career, Experience, Product, Past Purchases, Frequency, Daily Routine, etc.
Name(s) of Outcome Examples:
Analytical - The Brain
These entities use most of their logical thinking rather than their emotions when it comes to decision-making.
Amiable - The Heart
Expressive - The Face
Driver - The Soul
QUESTION | ANSWER CHOICES EXAMPLE
Which of the following would you rather have?
1 - ie. Books and Newspapers
Generate Product Interest