This blog post will give you insight towards how I review startup products in their beta phase, including my step-by-step guide on how to conduct a proper beta/UX review.  

Time to read: 8 mins.

Today, I’m going to provide a real-time review of a startup in its beta phase. I’ll be reviewing Ziftit, a startup based here in San Diego. In disclosure, I got introduced to Ziftit from Jennifer Johnstone, a former eBoost Consulting team member who currently is the Performance Marketing Strategist at Piston. Ziftit’s VP of Product, Ricky Lopez is Jennifer’s longtime partner. Jennifer is a good friend of mine and suggested I provide an objective review of Ziftit. So here we go.

When reviewing products in their beta stage, I like to go from the macro to micro. For a step-by-step guide, this is what I do:

Step 1: Ascertain the dynamics of the industry the business is in
Step 2: Determine the business category and canvas the business model
Step 3: Identify the critical success factors that work in that category
Step 4: Identify the ‘honeymoon’ items in the user experience (UX). These are the items that you need to get right to get your users to fall in love with your product
Step 5: Demo the product in accordance to the critical success factors (Step 3) and the honeymoon items (Step 4)

Step 1: Ascertain the dynamics of the industry the business is in
Ziftit is a web and mobile gift registry that enables anyone with the ability to give the right gift to everyone, and get the right gift from everyone, every time. It plays in a social gifting space that’s leveling out in maturity with Facebook’s acquisition of Karma (mass market capture) and Wantful’s positioning (niche market capture) as it leverages its $5.5 million Series A raise led by Polaris Venture Partners last year. When the top-end and bottom-end of the market are captured, the squeeze is on to either (i) nichify further, or (ii) go value-based, mid-market.

Step 2: Determine the business category and canvas the business model
As a business category, Ziftit is a peer-to-peer marketplace with a potential (and interesting) data aggregation model. I’ve noted before that I like the marketplace business model very much. There are multiple options to develop liquidity in the platform such as transaction fees, payment fees, advertising, et al, and the peer network scales customer lifetime value very well.

To canvas the business model, I use the Business Model Canvas. Here’s a snapshot of the Business Model Canvas I sketched out for Ziftit:

Step 3: Identify the critical success factors in that category
The key metrics for Ziftit as a peer-to-peer marketplace are:

1. Take rate (keep it low as possible)
2. Activation rate (percentage of users who take a key platform action, such as purchase for someone or list their desired gifts)
3. CLTV (customer lifetime value). Customer’s frequency of use is important since the cost to acquire a customer (CAC) in marketplaces are typically high in comparison to the immediate revenue per user. Increasing frequency of use and incenting transacting members to keep coming back make marketplaces ‘smarter’ – i.e. they know more about you – and hence, much more useful. This increasing switching costs to the user which increases the value for the platform.

Step 4: Identify the ‘honeymoon’ items in the user experience (UX).
The honeymoon items in the UX are:

1. Landing page
2. Sign up process
3. First page post sign-up
4. First search for product

Step 5: Demo the product in accordance to the critical success factors (Step 3) and the honeymoon items (Step 4)
I don’t like to go into user experience haphazardly; ‘go and test it’ is a faulty instruction that leads to a lack of control variables and doesn’t inform iterative testing. I go into testing with a user scenario in mind. In this case, I am entering Ziftit after a word-of-mouth reference from a friend, get to the landing page and get to the process of buying a pair of shoes.

You can see my sketch of the user story here:

Now, let’s map it with my experience of Ziftit. This is my actual click-path (again, in accordance to the user-story).

The highlighted boxes are the honeymoon items that I identified in step 4. This was my impression.

• Landing page (#1) – I was met with a straightforward value proposition. Good use of color contrast to direct me to where I should look
• Sign-up process (#4) – I could not log-in with Facebook (Ziftit is in beta, so I expected this). User data collected seems useful for push marketing efforts (i.e. demographic information used can fuel retention and cross-sell strategies)
• First page post sign-up (#7) – Upon sign-up, the activation email was sent immediately and the click through was seamless. I’d like to see more of a ‘tell me what to do’ approach to this page. The dashboard seems useful but I don’t know where to start. Instead, I go to “About Us” looking for where to start. I see an adidas logo there (I love adidas) so I click on it but it sends me away to the adidas.com homepage. Not sure if there’s an affiliate code there that makes it suitable for the business model, but I typically recommend marketplaces keep the transactions on their own platform to build customer association with the marketplace, regardless of monetization opportunities.
• First search for product (#9) – I’d like to see this page use my demographic information (gender: male) to show me only male shoes and have me search from there. While the selection seems good, the user experience should support the data collected and only get smarter from there.

Which brings me to my final point (not directed towards Ziftit, but to marketplaces as a category): the most under-emphasized value of marketplace is intelligence. Users want their marketplaces to use the data (purchase, activation or otherwise) to stay a few steps ahead of them. For as much as paranoia about user privacy and ‘big brother’ is rampant in publications, the LTV of peer networks like Amazon, Facebook, and Etsy demonstrate that we want platforms that are as smart as they are useful. Or perhaps more aptly put, ‘smart’ IS ‘useful’ in marketplace platforms.

Overall, Ziftit provides a very good experience in its phase as a beta. Cleaning up its UX according to the points above should get it ready for full public release. The important thing is the data logic and data architecture behind the UX door; meaning, if the data collected and presented is tight, then the UX improvements will lead it to be market-ready in no time. Then, Ziftit’s plan would be to acquire users at a strong activation clip and work towards those key metrics rapidly and iteratively.

Thanks Ricky and Jennifer for giving me beta access and allowing me to walk through a beta/UX review.  Bright things on the horizon for Ziftit and the San Diego startup community!

Sign-up for Ziftit here: Ziftit