Problem Statement:
Need to launch a Recommendations engine for the My Account section at Vistaprint

Product Description:

Vistaprint is an E-commerce website that specialises in personalised merchandise like pens, business cards, bags, and more. Within this platform, My Account is an essential feature on Vistaprint that allows users to manage their orders, update their personal details and track the status of their shipments.

Clarifications/Assumptions:

1: Even though our business might seem like B2B, it actually operates more like a B2C model because most of our customers are individuals who need things for themselves

2: We’ve already got a recommendation engine (looks like a content driven)in place at multiple spaces after checking UX, so we’ll use those same engines to make this work at My Account as well.

3: For now, we’ll treat the use cases and needs the same for all countries (since we deal in multiple locales), unless the data shows us something different, which isn’t the case at this early stage.

4: When I said “recent” in the “User needs/Solutions/Tradeoffs/Feature” column, I meant orders placed in the last 7 days. And when I said “past,” I meant orders placed more than 7 days ago.

5: I have considered 7 days as a period as having an understanding that delivery happens within 7 days after the order gets placed. This is based on the general delivery estimate of 2-3 days mentioned on the website. {{Assumption}

6: Assuming that it’s the initial stage of this feature, we’ll start by testing it with the most important use cases in the 1st iteration. Plus, we believe that most of the people who use My Account have ordered before because My account serves purpose for returning customers

Objective:

We’re categorizing users based on AAAERRR (Awareness, Acquisition, Activation, etc.).

In this case, I will take relevant objectives that come with product adoption an important key as we’re talking about launching the feature, and the product’s success is primarily determined by how many people become aware of it, decide to start using it, how they get activated or engaged with it, and make it all the way through the user journey.

Before committing to any specific objective within Product adoption, let’s go through the use case and will select later.

User Groups:

1. Small business owners (returning and new user)

2. Event planners (returning and new user)

3. Entities such as Digital Marketing/Brand Marketing agencies(Returning and new user)
4. Procurement Managers from large scale companies (Returning user)

To start, we’ll focus on Small Business owners who order for themselves (not other businesses). They bring in the most money and there are quite a few of them, based on what we’ve learned from the initial data and our understanding of the UX

Imp Use needs/Use case:

Here, I’ll begin by focusing on the user’s need to use My Account. Since our task is to introduce recommendations in My Account, it’s crucial to first understand what users want from My Account.

Returning user:

New user:

In summary, I’m giving the highest priority to customers who have ordered from us over a week ago and are coming back (P0)

Solutions:

Feature:

So, to sum it up, I’ll start with prioritising the Carousel/Progressive disclosure approach.

Tradeoff:

Thinking about the fact that some users can fit into both situations.For these users, we’ll see how many of their recent orders match the same category within the last 6 months.

If more than half (50%) of their orders are in the same category, we’ll focus on suggesting products related to their previous purchases (upsell). If less than 50% their orders match the same category, we’ll recommend different products that complement their previous purchases (cross sell)

Success Metrics:

I’ll be splitting the measurements into three: primary, partially primary & secondary: