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Armed with a Trader Joe’s receipt, Fred goes to the DailyDigest website to record the groceries he just bought and to record the meals he ate last night and today. He lands on the homepage and clicks the login link.
He lands on the Food History tab, but sees the tabs to go to the Food Stock and Analytics tabs. He wants to record his groceries first, so he clicks on the Food Stock tab. He clicks on the Add Item button to add an item. A pop-up appears, so he enters the details and clicks Save. The item instantly appears in the list. He adds the rest of his items by clicking the Add Item button once for each item. After entering in “aspargus,” he sees his mistake in the list, so he clicks on the entry. A pop-up appears to allow him to edit the entry. He fixes the typo and clicks Save.
Food history After he finishes his phone call, he forgets that he hasn’t finished entering his receipt, but he does remember that he still needs to record the food that he ate for dinner last night and for breakfast and lunch today. He clicks on the Food History Tab and clicks the Add Meal button. A pop-up appears. He fills in the details for his dinner, ignoring the drop-down lists that contain ingredient suggestions pulled from his Food Stock. He moves onto breakfast, but this time he does not ignore the suggestion drop-down lists. He creates five ingredient fields and selects bread, peanut butter, egg, banana, and milk from the drop-down lists.
He remembers that he forgot to enter in the last item on his receipt into the Food Stock, so he clicks on the Food Stock tab to fix the error. He then returns to the Food History tab to fill in the details for today’s lunch. He remembers that he also got a snack from a multicultural exhibit, but doesn’t know the ingredients but can guess the number of calories it contained. The fields in the Add Meal pop-up are optional, so he only enters in the number of calories and a name to indicate that it was a snack from the exhibit.
Fred is curious about his eating habits so he remains on the Food History Tab. He clicks on the Week button since the Month button was initially toggled. This sets the time range to the current week. Glancing over it, he sees that he made a mistake recording yesterday’s dinner, so he clicks on it. A pop-up appears with the option to edit that entry. He clicks edit to fix the entry.
Analytics Next, he wants to see some statistics about his eating habits, so he clicks on the Analytics tab. He set a goal to eat more vegetables and spend less money on snack food, so he clicks on the food group image that’s shown on the Analytics tab.
Food group analytics He adjusts the time range and a bunch of graphs appear. He checks the vegetable graph and is satisfied, so he navigates back to the Analytics tab to click on the cost analytics image.
Cost analytics He adjusts the time range and clicks on the Criteria drop-down menu to select “Meal.” Four graphs show up, one for Breakfast, one for Lunch, one for Dinner, and one for Other (he categorizes snacks as Other). He looks at the Other graph to see how much money he has spent on snacks in the past month.
If he wanted statistics on where he gets his food, he could have clicked on the location analytics page.
He’s finally satisfied and closes his web browser window.
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Users like Fred eat their groceries (items in their Food Stock), so once the user has opened the meal entry form, he’ll want to pull ingredients from his Food Stock. This design increases efficiency by having a list of relevant Food Stock items drop down from the ingredient fields that he types in (same as the auto-complete suggestions in Google Search)As he types the name of an ingredient into a textbox, a dynamically-changing list will drop down from the textbox to provide suggestions from his Food Stock. He has the option of choosing one or none. This feature allows him to complete his task more quickly. Although we make it more efficient to enter ingredients, the whole notion of splitting a meal into its ingredients and classifying their food groups might actually decrease efficiency since it puts too much mental strain on the user. However, it would make the analytics more precise, thus increasing the application’s value.
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