-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathREADME.txt
81 lines (57 loc) · 4.49 KB
/
README.txt
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
This is a readme.
testing
READ ME
PROJECT NAME: DEALISH
DESCRIPTION
Problem
Meal planning is difficult and expensive because of how much time is wasted looking up recipes with out-of-season ingredients online which consequently makes the customer pay more.
Solution:
A web app would collect the prices of fresh food (including proteins & spices) from all the local grocers in the area. Not only would it be able to find the lowest costs for specific ingredients from each grocery location, but based on this information it would also know which ingredients are in season. (For example, vegetables are always cheaper when they are in season.)
Now that the app knows which ingredients are the most cost effective and the most tasty based on seasonality, the app can then compare them to different recipes online to find the ones that will be the most cost effective, (and likely delicious!)
When the user selects the recipe they’d like to use, the app can then optimize their grocery list by grocer location to maintain the lowest price! Never again will anyone go to the grocery store again after meal planning for the week and leave with a bunch of ingredients they paid too much for!
Methodology:
The user will enter the app and ask for postal code (or location).
With this location, the app will find the most popular grocery stores [with websites and prices] in the area and post their average $, $$, $$$, and google review stars. The user will select the grocers they’d be willing to shop at based on this information.
The webapp will use python to scrape prices from the grocers’ websites to be able to compare ingredients to different grocery brands. Coupons can be included. The webapp also scrapes for recipes online with popular recipe websites.
The webapp will recommend recipes that match combinations of the lowest price points that are available in the user’s area.
The customer can select recipes to add ingredients to their list, including checking off ingredients they already have. This could generate more recipes for the app to recommend.
The user can print a final list of groceries they wish to purchase at each location, and also applicable coupons all in one document. (Coupons cannot be digital.)
Ways of Monetization:
Sell advertising opportunity to grocery stores.
Commission based on link driven to each grocery store’s native site.
Advertising posted on site for user’s to click. We get paid per click.
Charging grocer for advertising select “premium” ingredients in high ranking.
Competitors & Similar Style Apps:
Spud.CA
Flyers
An app that presents catalogues for all the brands in the user’s area.
Flipp
An app that presents catalogues for all the brands in the user’s area. Key feature: can create one grocery list for everything the user wants to buy from all of the catalogues.
GasBuddy
An app that compares the prices of gas in the user’s local area.
Market Track / Numerator
This company provides metrics to enterprises for consumer insights, statistics, trends, etc. Exploring this company more may provide us insights on how we may be able to monetize at a corporate level.
Loblaws Grocer
This Loblaws website offers customers a way to shop for their groceries online for pick-up or delivery. We can use this to screen scrape information, but also gain inspiration on how to model our app’s website. Compare and contrast with Walmart site and other grocers for best practises.
Walmart Grocer
This Walmart website offers customers a way to shop for their groceries online for pick-up or delivery. We can use this to screen scrape information, but also gain inspiration on how to model our app’s website. Compare and contrast with Walmart site and other grocers for best practises.
Trivago
Trivago is a price comparison brand that finds the best price for quality at various destinations for hotels, flights, etc. How this website is models, and the backend including monetization, can help inspire us for how our app will be optimized.
Dexio.io
This company uses python to create web scraping & automation tools. This will be necessary to code ourselves or to outsource to a company like this.
Mustafa Tayyar SARIKAYA
Billy BOLTON
Hened SAADE
Quin MEIDINGER
Joseph ABONASARA
Github Organization/Repository Links
https://github.com/Dealish
https://dealish.github.io
GitHub Accounts for Each Team Member
Billy Bolton: BillyBolton
Hened Saade: henedsaade
Joseph Abonasara: josephabonasara
Mustafa Tayyar: MustafaSarikaya
Quin Meidinger: quinm2
GitHub Pages Link
Https://Dealish.github.io/README.txt