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The service helps a user to select available recipes for cooking and get the needed ingredients from local supermarkets. Users can customize their shopping cart in case they have some of the ingredients.
This startup was the only internal product of the agency where I worked as a UI/UX designer (the other projects were owned by external customers), and I was the only designer in the team, so I was responsible for the whole design process. I joined the project when the MVP version was planned to be launched, so we had plenty to work on.
In my everyday work, I communicated closely with my product manager/CEO, developers, and a marketing director.
Being able to be involved in the whole product process gave my product designer career a huge boost. Here I pointed out the key achievements:
"During our work together, I was impressed by Daria’s design skills and dedication to her craft. She has an outstanding ability to translate ideas into visually stunning creations, always delivering work of the highest quality..."
We assumed that the service would be a high value because the pandemic had changed the Russian market of essential goods, creating a bigger demand for home delivery. Users wanted to cook at home and save money and time. But there were already successful competitors on the market that made us come up with a unique value proposition.
During user research we defined our target audience as:
Young people («A» segment): a man or a woman 23-35 y.o., who has a job and hobbies.
People with a special diet or meal preferences (vegetarians or vegans, allergic, healthy lifestyle, health issues).
Hard to figure out what to cook every day.
Searching for and selecting groceries takes a long time for them.
They make spontaneous purchases in supermarkets, which lead to large unnecessary expenses.
They usually lack of time.
They throw away leftovers because they don't know how to use them.
They have a small variety of recipes and items to choose from.
They complained that such types of baskets (meal plans) are often more expensive than the usual ones.
As a part of our business model, we planned to expand the audience and involve nutritionists and food bloggers. So we also interviewed them and found out the following:
They still provided customers with a pre-defined list of recipes that didn’t include personal needs.
They had long-term communication with customers on the purchase of groceries.
They didn’t know about the opportunity to make money on suggesting recipes.
Their subscribers wanted specific recipes based on their meal preferences.
They didn’t know about an opportunity to make money selling food recipes.
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The personas.
We knew that our users valued their time, money, and the variety of recipes, so based on their needs we created job stories:
Young people who want to cook meal based on their needs want to cook simple but tasty food that would save their time and money.
During the first workshop, we defined 4 main hypotheses that we needed to prove.
“Ready-made recipe plans based on a user’s needs can save their time and increase the conversion into a purchase”
When users don't have enough time to decide what to cook, they could easily choose the meal plans that were made for everyone based on the most popular users' preferences. We offered 3 and 7 days meal plans with up to 5 meals each day.
“An option to remove or replace some of the items that users have at their home would save money and increase user loyalty and conversion into the next purchases”
It looked like one of the value proposition features we could suggest, because usually meal plans of our competitors were set and not available to adjust.
“An option to create their own plan with the recipes and ingredients will increase user loyalty to the product and conversion into the next purchases”
Many people wanted to customize their shopping cart with recipes.
“A choice from a large number of simple recipes will make the service more accessible and diverse, and therefore will increase loyalty and conversion”
We offered more than 500 recipes to choose from, including variety of recipes for people with special meal preferences.
I compared the product benchmarks existing on the market. Looked like our platform could offer everything from the list and have a competitive advantage by offering unique features like the possibility to exclude items from the shopping cart or offering big variety of recipes.
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Based on the data we gained and the hypotheses we formed, we came up with the following benefits of using our platform:
Saving up to 30% on groceries.
Individual meal plan for everyone.
500+ recipes for people with different meal preferences.
Possibility to exclude already existing items from the shopping cart.
Delivery from local supermarkets (which is fast and often more affordable).
Additional monetization source for influencers and nutritionists.
For the most personalized composition of the basket, we decided to compile the following algorithm.
I started with the low-fi flow of choosing recipes to order. Then I created:
Main page
Checkout page
Recipe card
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The wireframes.
I created 2 variations for the A/B test (the difference is in the card layout). The users chose the second option because it was clearer for them to figure out how to choose a recipe. The final design didn’t look much different from the one that I created for the testing, because we had time limitations before launching our MVP.
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The first variation.
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The second variation.
After the user testing, I polished the design and created an instruction for engineers, added different states, and collected components into a UI kit.
For the MVP we collected the orders and did menu planning manually, then purchased the groceries from a local supermarket, and after that we got them delivered by couriers. After the release of MVP, we got the following outcome in numbers:
‍- 650 sales
- Average bill was 4200â‚˝
- 36% of customers ordered more than once
Developed more than 500 recipes.
Users could make up an individual recipe plan suitable for them.
Created the recipe and menu management function in the admin panel.
Developed replacing an item with a similar one.
Developed the main page.
The team had plans on launching two more platforms:
Web platform for monetizing the work of nutritionists and food bloggers.
A mobile app that should’ve helped to track the expiration date of groceries and keep records of cooked meal and food leftovers.
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The first design conception of how it might've looked like.
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