Product Case: Increasing revenue for GIVA, a D2C jewellery brand

You are the product manager for the GIVA App. Tell us one feature in each of the platforms that you would like to implement to improve revenue.

Setting Business Outcome

Let us begin by setting the outcome we are hoping to achieve, which is increasing revenue generated. So let us first break down revenue and see the factors that affect it.

Revenue = [Avg. Price per unit] x units sold

= [Avg. Price per unit] x #orders x [Avg. Qty per order]

So, if we have to increase revenue, we need to increase at least one of the three parameters.

Price -> Let us ignore pricing as a strategy for the scope of this case

Orders -> An increase in order count can come broadly from three areas:

a) Increased top line — Assuming a constant customer conversion rate, if more people come to our app/websites, the more orders we will get.

b) Increased conversion — For the same number of customers, if we can reduce purchase funnel drops, we can get more orders from a set of customers.

c) Retention/Increased purchase frequency — Even if customer conversion remains the same, increasing the frequency of purchase from our platform will result in more orders.

Avg. Qty per Order -> Bundling

Identify Persona

No customer base is perfectly homogeneous. There will always be a set of distinct clusters that are behaviourally different enough that it makes a case to solve while keeping one segment in mind. Each segment will have its own unique set of pain points, needs, and wants. Hence, solving for our chosen outcome might be tackled differently based on which segment we choose to prioritize.

Demographically, the majority of customers of GIVA will be female. They will also predominantly fall within the age group of 20 to 40. However, we need to look at other lenses to view the customers to segregate them behaviourally when making a purchase.

• First is whether the purchase is being made for themselves or is a gift for someone else. Assuming the cohort buying for themselves is bigger, let's solve for them.
• Next could be clarity of intention: Does the customer already have a good idea of what to buy? A customer is much more likely to explore different categories, and products and deliberate before committing to a purchase if they come to the platform unclear what to purchase. This is a segment with higher friction to purchase. So let's prioritize their needs.

Opportunities

The opportunity space is composed of the user's Needs/Pain Points and Wants. For our chosen segment of users who are purchasing for themselves and are unsure of exactly what to purchase, let's jot down their needs/pains/wants:

1. Too many choices lead to confusion
2. Difficult to compare one product with another
3. No way to try out a product before the purchase
4. Sizing concerns
5. Trust and authenticity
6. Customization/personalization
7. Limited info on materials

We now need to rank these opportunities based on their relative importance and prioritize the ones that when solved for can help us achieve our chosen outcome from the beginning.

Opportunity prioritization

Solution Space

Based on prioritization, our top opportunities are as follows. For each opportunity, let's look at a few ways how we may address it. Each solution has its set of assumptions that need to be identified and validated to be certain that solving it will indeed help our outcome. We can never be fully certain but rapid testing assumptions reduce the risk of failure and manage uncertainty.

Will the product look good on me?

1. Virtual try on (AR)
2. At Home Trials
3. Testimonial showcase

I am confused by too many choices

1. Product recommendation — Based on outfit/occasion/owned jewelry/inspiration?
2. Improved Search — LLM based?
3. Personality-based top picks

Prioritizing solutions

Assumption Tests

Rapid testing for assumptions is essential to quickly identify if we are on the right track. We have a variety of sources/tools at our disposal: user persona documents, experience maps, customer interviews, one-question surveys, historical purchase data, website user behavior data, backdoor MVPs, etc. Some

No way to try a product

• The proportion of customers returning/canceling orders. What is the reason?
• Customer interviews where customers mention similar pain point
• Product pictures checked per order
• Testimonial pictures checked/buyer vs non buyer
• Using a beta trial sign up for the Virtual try feature to check interest/CTR
• The proportion of users landing from Instagram (pics play an important role)

I am confused by too many choices

• Products viewed per session
• Products viewed per purchase
• Products viewed before the bounce
• Avg. #Sessions per purchase
• Avg. Session length per purchase
• Avg. Search queries per user
• Avg. search result failures
• Bounce reason (if capturing)

User Story, Success Metrics

Since Opportunity A has a higher score, let us prioritize it and from our solutions table, we can see that the chosen feature to be built is “Virtual Trial”

User Story

As a GIVA app user who is trying to buy jewelry, I want to try the jewelry virtually first so that I can better understand if I will look good wearing it before making the purchase.

North Star Metric

Increase in conversion rate: CVR of users

Success Metric

• Measure the percentage of users who use the virtual trial and complete a purchase within a defined timeframe
• From the users who are exposed to the feature, the proportion that use the VR Trial feature
• Collect user feedback through surveys to assess satisfaction with the virtual trial experience
• Compare the return rate for items purchased using the virtual trial compared to those purchased without it
• Count of Pictures taken/saved

Acceptance Criteria

1. User Interface:

• The virtual trial feature is accessible from the product page of eligible jewelry items.
• The user can activate the virtual trial using a clearly labeled button.

2. Jewelry Selection:

• Users can select different jewelry items to try on.
• Ensure a diverse range of jewelry types are supported.

3. Camera Integration:

• The feature integrates with the phone camera for a seamless virtual try-on experience.
• Users can adjust the camera view and capture images with the virtual jewelry.

4. Realistic Rendering:

• The virtual trial accurately renders the selected jewelry on the user, considering size, color, and style.
• The virtual jewelry should align with the user’s body proportions.

5. Share and Save:

• Users can save virtual trial images for future reference.
• Users can share virtual trial images on social media or with friends.

6. Performance:

• The feature should load quickly and perform efficiently to provide a smooth user experience.

Recommendation

Summarizing the problem statement: We started with the business outcome of increasing revenue. The product outcome to address the business outcome was reducing purchase funnel drops and increasing user conversion rate. We looked at different personas and wanted to solve for users who looking to purchase for themselves and didn't have a clear idea of what they were looking for. Among the different opportunities explored, we found that not being able to try on a product and see how one looks was an important pain point to be solved. Among the few solutions, we decided to build a feature that allows users to check how the jewelry would look on them using the mobile camera. The feature also allows users to save the pictures locally for reference later.

By implementing the virtual trial feature and measuring success against the outlined metrics, GIVA can enhance the user experience, increase conversion rates, and ultimately drive revenue growth.