Onboarding project | ToggleAI

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Let's Begin!

Toggle AI is an advanced investment tool designed to empower both retail and institutional investors with AI-driven insights and analytics. The app offers features such as real-time pricing, market indicators, and scenario analysis, helping users make informed decisions across various asset classes, including stocks, cryptocurrencies, and global equities. Targeting a wide market, from individual investors looking to grow their portfolios to professional fund managers seeking comprehensive data analysis, Toggle AI caters to users who value accuracy, efficiency, and actionable intelligence in their investment strategies.

Define the ideal customer profile (ICP)?

Here are the 2 User's selected from the TAM, depending on the product and services offered by Toggle.

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B2C Table

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Define user goals and JTBD

Understand user goals and their JTBD on the platform. When looking at user goals, look at 4 themes, user goals will always be within one of the four.

1. Personal Goals
2. Social Goals
3. Functional Goals
4. Financial Goals

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​Core JTBD:​

• ICP 1: Retail Investor (Retail Investor):

• JTBD: Uses Toggle AI to simplify his investment process by providing quick, reliable insights that help him manage his portfolio efficiently and make informed decisions with minimal time investment.

• ICP 2: Institutional Investor (Institutional Investor):

• JTBD: Uses Toggle AI as an advanced analytical tool that integrates large financial datasets, enabling him to optimize portfolio management and achieve higher returns while effectively managing risk.

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Do user research to validate or invalidate these goals.

You want to talk to users and understand why they're signing up. What's the end goal for them and for what job are they "hiring" your product for.

User Conversations and Insights:​

1) Retail Investor (Michael Anderson):​

• Relevance: Michael mentioned that he struggles to find time for detailed investment research but values having quick, reliable insights. This confirms that the need for efficient portfolio management is highly relevant.

• Clarity: Michael clearly understands that Toggle AI is meant to simplify his investment process and provide the necessary insights to make informed decisions. He appreciates the ease of use and the straightforward information provided by the Copilot plan.

• Actionability: The insights and tools provided by Toggle AI allow Michael to take immediate action on his investments, such as adjusting his portfolio based on real-time data.

• Specificity: Michael’s tasks are specific—he needs to manage his stock and cryptocurrency investments with minimal time investment while aiming for steady growth.

• Prioritization: Michael considers quick access to insights and ease of use as his top priorities, making these aspects of Toggle AI critical to his satisfaction with the product.

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2) Institutional Investor (David Carter):​

• Relevance: David emphasized the importance of having a tool that can handle large datasets and provide advanced analytics. This aligns perfectly with the JTBD of using Toggle AI for portfolio optimization.

• Clarity: David is clear on how Toggle AI fits into his workflow, using it primarily for scenario analysis and making data-driven investment decisions. He particularly values the depth of analysis offered by the Pro plan.

• Actionability: The tools and indicators available in the Pro plan allow David to make strategic decisions quickly, especially during market hours, which is critical for his role.

• Specificity: David’s use case is very specific—he needs to optimize his portfolio performance while managing risk, which requires the advanced features provided by Toggle AI.

• Prioritization: For David, the ability to perform complex analyses and manage large portfolios is the highest priority, confirming that the advanced features of Toggle AI are essential for his needs.

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Based on the user conversations, the goals and JTBD we identified for both the retail and institutional investors are validated. Both Michael and David found Toggle AI to be a crucial tool for meeting their specific needs, whether it’s simplifying investment processes for a retail investor or providing advanced analytics for an institutional investor. These insights confirm that Toggle AI is effectively addressing the core needs of its users and can be further refined to enhance these aspects.

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Onboarding Teardown

Step 1 → Start right from your homepage or App listing page
Step 2 → Take screenshots of every single page and interaction throughout the onboarding right till activation.
Step 3 → Start by putting yourself in your customer's shoes. Have empathy for their pain points and then analyze the page/screen.

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Here’s a list of things we’d recommend you evaluate your onboarding on:

• Does this page/screen help get my job done?
• How am I feeling while being on boarded for this product?
• What part of the onboarding experience is giving me that aha moment?
• What screens would you change/add and why?

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(this is not the only way to go about with the teardown, feel free to experiment here!)

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Also, evaluate your onboarding on the cognitive biases.

Don't worry, you don't have to include biases but it's a good practice to start tagging things to their respective biases.
(We identify issues when we are able to tag/name them, yes another bias)​

The Teardown is done for 2 methods of onboarding:

• iOS Mobile App
• Web App (Browser)

IOS_App_Teardown.pdfWeb_App_Teardown.pdf

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iOS Mobile App:

​1. Introduction Screens:

• Screenshots:

• The initial onboarding screens introduce Toggle, explaining what it does and how it benefits the user.

• The design is clean with a dark theme, which is visually appealing and aligns with the app’s branding.

• Analysis:

• Good Points:

• The minimalist design with clear, concise text allows users to understand the app’s purpose quickly.

• The consistent use of icons and graphs gives a sense of data-centricity, which is crucial for an investment app.

• Areas for Improvement:

• The onboarding might benefit from a short interactive demo to engage users more actively. This could help reduce drop-off rates by giving users a hands-on experience early on.

• Impact:

• Currently, these screens are straightforward and informative but could lead to higher drop-off rates due to a lack of interactivity or personalization. Adding an interactive element could help retain users who prefer a more engaging introduction.

2. Account Creation and Setup:

• Screenshots:

• The sign-up screens are simple, asking for basic information like email, password, and user name.

• The process includes enabling Face ID and setting up notifications.

• Analysis:

• Good Points:

• The process is streamlined, making it easy for users to get started without overwhelming them with too many fields.

• Including Face ID setup enhances security, which is crucial for a finance-related app.

• Areas for Improvement:

• Consider offering a “Continue as Guest” option to allow users to explore the app before committing to creating an account. This can lower the initial barrier and potentially reduce drop-offs at this stage.

• Impact:

• The current setup is efficient but might deter users who are not ready to commit. A guest mode could improve user retention by allowing them to experience the app’s value before signing up.

3. Explore and Notifications:

• Screenshots:

• The app introduces the “Explore” feature and prompts users to set up their watchlist and notifications.

• Analysis:

• Good Points:

• Explaining the “Explore” feature helps users understand the value they can derive from the app.

• The prompt to set up notifications is crucial for maintaining user engagement through alerts.

• Areas for Improvement:

• Provide an example of a watchlist or a demo to guide users on how to set up and use this feature effectively. This can help users see immediate value and reduce confusion or hesitation.

• Impact:

• While the features are well-explained, the lack of hands-on guidance may lead to a higher drop-off rate. Demonstrations or examples could help mitigate this by showing users the app’s full potential early on.

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Web App:

1. Welcome and Initial Setup:

• Screenshots:

• The onboarding begins with a welcome message and a few questions to understand the user’s investment style.

• Analysis:

• Good Points:

• The personalized approach by asking about investment styles helps tailor the experience, which can increase user satisfaction and retention.

• Areas for Improvement:

• The welcome message could include a progress indicator to show how many steps are left in the onboarding process. This can reduce user anxiety and drop-offs by providing a clear path forward.

• Impact:

• The personalized questions are a strong point but could benefit from more guidance. A clearer, step-by-step indication of progress would likely improve user completion rates.

2. Asset Classes and Investment Style Selection:

• Screenshots:

• Users are asked to select the asset classes they trade in and define their investment style.

• Analysis:

• Good Points:

• This step allows Toggle to customize insights and suggestions, making the platform more relevant to the user.

• Areas for Improvement:

• Providing examples or definitions of each investment style might help users who are unsure about their approach. This guidance can make the selection process less intimidating for new users.

• Impact:

• The ability to customize based on asset classes and style is valuable, but without proper guidance, some users might drop off if they feel uncertain about their choices.

3. Subscription and Pricing:

• Screenshots:

• The app offers different subscription tiers with a clear breakdown of the features included in each.

• Analysis:

• Good Points:

• The pricing structure is straightforward, with clear value propositions for each tier.

• Including a free trial option (if available) helps users commit to trying out the app without immediate financial commitment.

• Areas for Improvement:

• Highlighting the benefits of upgrading directly in the app experience could entice users to move to a higher tier faster. For example, lock some advanced features and show them as a preview with a prompt to upgrade.

• Impact:

• The clear structure is beneficial, but emphasizing the value of premium features earlier in the journey could improve conversion rates to higher tiers.

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4. Dashboard and Insights:

• Screenshots:

• The dashboard provides a detailed overview of assets, market insights, and positions.

• Analysis:

• Good Points:

• The dashboard is comprehensive and data-rich, catering well to institutional investors who need in-depth insights.

• The inclusion of various tools like the “Scenario” feature allows for deep analysis and adds value for experienced traders.

• Areas for Improvement:

• Simplify or offer a more guided experience for less experienced users. The wealth of data and options can be overwhelming for new users, leading to potential drop-offs.

• Impact:

• The dashboard’s depth is a strength but also a potential weakness for new users. A simpler “lite” version or guided tours could help maintain engagement across different user segments.

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​Recommendations Summary:​

• iOS App Drop-Off Points: Users are likely to drop off during the initial sign-up due to a lack of guest access and during the setup of notifications due to the absence of clear guidance or examples.

• Web App Drop-Off Points: The potential for drop-offs is highest during the investment style and asset class selection due to a lack of guidance, and during the dashboard exploration if users feel overwhelmed by the data.

Customer Touchpoints and Discovery:​

• Customer Touchpoints:

• Initial Onboarding: First impressions via the welcome screens.

• Feature Exploration: Discovering “Explore,” “Notifications,” and the “Dashboard.”

• Subscription Decision: Deciding which pricing tier to select.

• Discovery Experience:

• The discovery process is well-structured but could benefit from more interactive and guided experiences to help users uncover the app’s full potential more easily.

Improvement Suggestions:​

• For iOS:

• Introduce interactive onboarding elements.

• Provide a guest mode for initial exploration.

• Offer guided examples during feature setups.

• For Web App:

• Include progress indicators during onboarding.

• Provide more guidance during investment style selection.

• Simplify the dashboard or offer a guided tour for new users.

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Defining your Activation Metric

Step 1 → Hypothesize at least 5 activation metrics that could be there for your product. (More the better)
Hypothesis 1: <Enter your one/two lines>
Reasoning: In about 5-6 lines explain why this could be an activation metric

Step 2 → After this, mention in detail all the metrics you'd be tracking and why are you tracking them?

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Step 1: Hypothesize Activation Metrics​

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Hypothesis 1:​

Metric: Number of assets added to the watchlist within the first session.

Reasoning: This metric could be an indicator of a user’s initial interest in using the product. Adding assets to the watchlist is likely one of the first actions a user takes after onboarding, showing their intent to engage with the product. This metric can demonstrate user commitment and indicate that the user sees value in the product by monitoring specific assets. Additionally, it could impact the retention curve as users who add assets might return more frequently to track them.

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Hypothesis 2:​

Metric: Completion of the onboarding flow.

Reasoning: Completing the onboarding flow is a crucial activation metric as it signifies that the user understands the core value proposition of the product. If users complete the onboarding, it likely means they’ve been exposed to the main features and are more likely to explore the product further. This metric impacts both conversion and retention, as it’s a gateway to deeper product engagement.

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Hypothesis 3:​

Metric: First use of the “Explore” feature.

Reasoning: The “Explore” feature is central to discovering insights within the product. The first use of this feature could demonstrate that the user is beginning to realize the product’s value. This metric is important for conversion as it likely leads to deeper engagement with the product’s offerings. It also affects the retention curve positively, as users who engage with this feature might find it valuable and return for more insights.

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Hypothesis 4:​

Metric: First interaction with personalized insights.

Reasoning: Personalized insights provide tailored value to the user, which can be a strong indicator of user commitment and perceived value. This metric directly affects conversion, as users who find these insights valuable are more likely to continue using the product. It also has a potential impact on LTV and word-of-mouth referrals if users find the insights particularly useful.

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Hypothesis 5:​

Metric: Number of sessions within the first week.

Reasoning: This metric tracks early engagement and indicates how quickly a user becomes an active participant in using the product. Frequent sessions within the first week can signify that the user is finding value in the product, which may lead to higher retention rates. This metric affects the retention curve and can also give insight into the product’s stickiness.

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Step 2: Tracking the Activation Metrics

Metrics to Track and Why:​

1. D1, D7, and D30 Retention:

• Why: These metrics provide insight into how well the product retains users over different timeframes. High retention rates at these intervals suggest that the product is delivering ongoing value to users.

2. DAU/MAU (Daily Active Users/Monthly Active Users):

• Why: This metric helps in understanding the stickiness of the product. A higher DAU/MAU ratio indicates that users are returning to the product regularly, which is a sign of strong engagement and value realization.

3. Subscription Rate vs Retention:

• Why: Tracking the subscription rate alongside retention can help understand whether users who subscribe stay with the product over time. It can also indicate whether the product is delivering enough value to justify a paid subscription.

4. Average Time to Load a Page (TAT):

• Why: Page load time directly impacts user experience. Slow load times can lead to frustration and drop-offs. Monitoring and optimizing TAT is crucial for maintaining a seamless user experience.

5. User Cohorts:

• Why: Analyzing users by cohorts (e.g., based on acquisition source or onboarding completion) helps to understand how different groups of users engage with the product. This analysis can identify which segments are most valuable and where there are opportunities for improvement.

6. Activation Rate:

• Why: Tracking the percentage of users who complete key activation steps (like adding assets to a watchlist) helps to measure how effectively the product is onboarding and engaging new users.

7. Feature Adoption Rate:

• Why: Monitoring how quickly and extensively new features are adopted can indicate whether these features are meeting user needs and delivering value. This metric can guide product development and prioritization.

8. Product Reviews:

• Why: User feedback through reviews provides qualitative insights into user satisfaction and areas for improvement. Positive reviews can also enhance word-of-mouth referrals, while negative reviews can highlight issues that need to be addressed.

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By hypothesizing these activation metrics and tracking the suggested quantitative and qualitative metrics, we can gain a comprehensive understanding of how users interact with our product, where they find value, and where they may drop off. This approach will allow us to optimize the onboarding process, improve retention, and ultimately drive higher engagement and conversions.

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we hope this helped you break the cold start problem!
Reminder: This is not the only format to follow, feel free to edit it as you wish!

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