Customer Development Plan for Scouta

Scouta aims to offer a personalized AI-driven shopping assistant that enhances the online shopping experience by leveraging social media trends and user behavior. This customer development plan specifically focuses on validating assumptions around customer needs, the problem Scouta aims to solve, and the willingness of customers to pay for the proposed solution.

1. Customer Discovery Plan

Key Assumptions/Hypotheses

1. We believe that tech-savvy millennials and Gen Z (18-45 years) have time-consuming and inefficient online shopping experiences.
2. We believe that online shoppers are frustrated with generic recommendations and desire more personalized suggestions tailored to their tastes and social engagement.
3. We believe that frequent online bargain hunters are actively looking for tools that can automate deal-finding while ensuring privacy and security for their data.

Specific Interview Questions

1. For the first assumption:

   • How much time do you spend looking for products when shopping online?
   • What do you typically find frustrating about your online shopping experience?
   • How often do you abandon a shopping session due to frustration?

2. For the second assumption:

   • How do you currently find personalized product recommendations?
   • Can you describe a time when you were disappointed by a product suggestion? Why?
   • What features do you wish existed in your current shopping assistant tools?

3. For the third assumption:

   • How do you usually hunt for deals online?
   • What tools or services do you currently use, if any? What do you like or dislike about them?
   • What concerns do you have regarding privacy when using shopping assistant tools?

Finding and Approaching Customer Segments

• Locations: Target university campuses, tech-savvy coworking spaces, and food festivals known to attract millennials and Gen Z.
• Online Communities: Engage in social media platforms like TikTok, Instagram, and Reddit (specifically subreddits like r/FrugalLiving, r/malefashionadvice, etc.).
• Approach: Utilize both direct outreach via social media (DMs or targeted ads) and in-person interactions during relevant events.

2. Problem Validation Strategy

Step-by-Step Process

1. Conduct 15-20 Interviews: Conduct user interviews following the preparation of the specific questions above.
2. Survey Creation: Create a survey based on qualitative insights gathered to quantify customer pain points.
3. Landing Page Development: Create a simple landing page to gauge interest in the Scouta concept. Use services like Carrd or WordPress.

Landing Page Copy Example

• Headline: “Meet Scouta: Your Personalized Shopping Assistant”
• Subheadline: “Experience shopping like never before — powered by AI and your unique preferences.”
• Key Features:
  • “Automated Deal Finding – Save time and money effortlessly!”
  • “Tailored Recommendations – Products chosen just for you based on your social media interactions.”
  • CTA: “Join our waitlist and be the first to know when we launch!”

Measuring Problem Validation

• Track user sign-ups on the landing page to measure interest. Aim for a goal of 100 sign-ups in the first month.
• Use Google Analytics to monitor traffic and heatmaps to assess user engagement and click patterns.

3. Solution Validation Approach

Minimum Viable Product (MVP)

• Start with a manual process where users can submit their shopping preferences (e.g., categories, styles) through a Google form or a simple Slack bot.
• Collect data on preferences and curate product suggestions manually for each user, sending them via email or DMs until an automated solution is developed.

Implementation Steps

1. Design the User Preference Form (1 week)
2. Manually Compile Recommendations based on user inputs, using data from existing e-commerce sites (1-2 weeks).
3. Engage Early Adopters for feedback triangulating their user experience (2 weeks).

4. Customer Validation Plan

Experiments to Test Willingness to Pay

1. Pricing Tests: Launch tiered pricing strategies for access to personalized recommendations (e.g., free basic version, $5/month for enhanced features).
2. Pre-sale Campaign: Leverage social media or your landing page to conduct a pre-sale for early supporter subscriptions.
3. Tracking Feedback via Surveys: After delivery of manual recommendations, send out user feedback surveys assessing value, pricing thresholds, and perceived benefits.

Framework for Analyzing Feedback and Iterating

• Metrics of Success: Analyze conversion rates from visitors to sign-ups, and feedback on pricing.
• Adjust Offerings Based on Feedback: Pivot functionality focus based on users’ interest in features and their willingness to convert into paying customers.

5. Get Out of the Building Action Plan

2-Week Validation Sprint Plan

• Week 1:

  • Day 1-3: Conduct interviews with 5-10 potential customers.
  • Day 4-5: Develop and launch landing page; promote on social platforms.

• Week 2:

  • Day 6-7: Engage with users who signed up via direct outreach to encourage participation in surveys; incentivize feedback with a chance to win a product.
  • Day 8-10: Begin manually curating recommendations from collected user preferences.
  • Day 11-14: Schedule follow-up sessions with initial users to discuss their experiences and any willingness to pay.

Specific Locations and Events

• Look for tech meetups, university campuses during open days, or popular e-commerce fairs.
• Utilize online communities like Facebook groups that center around online shopping and deals.

Outreach Scripts and Conversation Starters

• Cold Outreach Email:

  Subject: Be the First to Try Our New Shopping Assistant!
  
  Hi [Name],
  
  I hope this message finds you well! I’m developing an AI-driven shopping assistant called Scouta, designed to save you time and help you discover products tailored to your unique style preferences. 
   
  Would love to hear your thoughts and experiences with online shopping. Can we chat for 15 minutes this week?
   
  Best,
  [Your Name]

• Conversation Starter: “Hey! As an avid online shopper, what frustrations do you find in your current experience with e-commerce? I’m working on a solution that offers personalized recommendations—interested to share your thoughts?”

Conclusion

The customer development plan for Scouta focuses on direct engagement with the target audience to validate their assumptions about the problems and potential solutions. By employing a hands-on approach that prioritizes direct customer feedback over assumptions, Scouta can ensure that its unique value proposition resonates well with its intended market. Founders must continuously gather insights and iterate based on user feedback before fully launching to maximize their chances of success.