A glimpse into how we might see applications for our phones and tablets evolve to make food shopping and preparing meals easier
Forrester for CIOs
By Forrester Research, CIO
George Colony nailed it when he wrote “the iPad signals the future of software”. So where do smart-device app’s go from here? Basically, any application that focuses on saving people time is likely to be a winner but the biggest game changer will come when consumers start to benefit from customized services that save time and money while increasing brand loyalty. For example, here’s a glimpse into how we might see applications for our phones and tablets evolve to make food shopping and preparing meals at home easier…
Let’s imagine the future of a typical suburban home. In our future world we’ll follow Mr. and Mrs. Smith, working parents with little time to spare.
While on the train home from work Mrs. Smith searches for a recipe online using her tablet internet device (think iPad). She has entered 30 minutes as the time she has to prepare dinner – the app, wirelessly connected to the internet, displays only recipes requiring 30 minutes or less prep time. For each recipe the app displays the anticipated taste rating for each family member (based upon historic ratings of similar foods), and Mrs. Smith can opt to filter recipes by projected food rating and genre. Having found the perfect recipe, the ingredients required are immediately checked against the real-time food inventory stored in her family’s shopping app. She sees she has most of the ingredients so she confirms the recipe. Step by step instructions are presented on her tablet for her along with video demonstrations of each step. She spends the rest of the journey planning meals for the rest of the week. Any needed ingredients are added to the family’s shopping list. Mrs. Smith IM’s her husband and asks him to pickup the grocery shopping on his way home from work.
Mr. Smith enters the supermarket and looks at the shopping app on his phone – it is already updated with everything on the family’s shopping list, including items needed for the week’s recipes just selected by his wife from her train. He responds “yes” to the question “would you like to receive special offers for this store?” (The application works in any major supermarket). The App now communicates with the store systems to notify the store of Smith’s preferred shopper number and the items on Smith’s shopping list. His phone app is automatically updated to present his shopping list in the correct sequence specific to this store’s aisle layout. At the same time every item in his cart is priced for the current price of items in the store, including his preferred shopper discounts which are highlighted. Anything not currently available in the store is highlighted along with a suggested alternative. He can see his shop is going to total $157.45 which is within his budget. He knows he will probably spend more – he loves special offers.
Smith looks at the first item on his list which is in the grocery section – bananas – alongside is an offer icon, so he clicks it to see that oranges are on promotion if he buys bananas and oranges together. He weighs the bananas and scans the printed bar code with his phone as he sticks it on the bag. He then picks up a bag of the oranges on promotion and scans the bar code with his phone. Each time he scans an item it is automatically checked off his shopping list. As he turns and enters the next aisle he sees an alert on his phone asking if he forgot apples (since the app knows the apples are in the aisle he just left). He has decided not to get apples today so he clicks to ignore the message.
As he proceeds around the store the total shopping cart value is continuously updated on his phone and updated back to the store systems. As he nears the end of his shopping list, the shopping cart total is $175 and the total value of the shopping list items remaining to be purchased is $15 based upon prices in the store – he receives a new message advising his that if he spends over $200 he will receive a bonus on his next shopping trip worth up to $5. Beneath the message is a list of suggested items based upon his past shopping experiences and what’s left in front of his in terms of aisles not yet shopped.
When he is finished his cart shows a value of $212 (he just couldn’t resist the extra offers from the ice-cream aisle – the children will love the treat). As he approaches the checkout he receives a message on his phone asking if he would like to auto-checkout. He confirms and the phone displays the total along with his usual method of payment. He confirms the purchase by entering his authorization code into his phone and his app is updated with an electronic receipt of his shopping trip. His bank account is charged with the transaction value. The shopping app now updates the family’s home grocery inventory with all the items purchased.
As the Smiths prepare dinner, Mrs. Smith takes out of the freezer the last four chicken breasts, using her phone she scans the bar code on the freezer’s perishables list – “chicken breasts”. She continues preparing their food, scanning any items as they are used up. The app’ builds a list of all the items consumed and adds them to the shopping list for the next time they go shopping.
After dinner each member of the family will get to rate the meal for their own preferences and the ratings are stored alongside the recipe for future reference.
How far are we from this being a reality? Well the technology is already in place today and there are plenty of iPhone Apps that perform some of these functions (see below). The challenge with this kind of application is that it requires considerable cooperation between multiple vendors (manufacturers, retailers, publishers and banking). Right now applications are mostly developed by individual companies hoping to boost their own bottom line or by software companies providing utility applications for consumers; there are very few applications that tie together shopper utility and retailer marketing. It’s easy to see the potential of this type of App. It saves the consumer time and money, and helps retailers to increase the size of the average shopping cart through highly personalized offers tied to manufacturer’s promotions.
The biggest challenges in making this a reality are likely lie in the complexity of having standardized product information across multiple retailers. Staples such as ketchup are relatively easy, but perishables vary by retailer and even in a single retailer something as simple as chicken is available in multiple varieties and packages, each with unique bar codes.
While some pretty advanced shopping list apps exist already, the ability to automatically sort the shopping list into the correct sequence for any store requires access to detailed store layouts. For big retailers with standardized shelf planning this may be possible. Accelerometers built into devices, coupled with location sensing technology should be able to detect when the shopper has entered a new aisle. Stores such as my local Stop and Shop are already using scanning technology from Modiv Media to help customers self-scan items and checkout instantly (see video below). It’s not a huge leap to seeing this type of application in a phone.
Then there is the ability to maintain inventory levels in a household. This was once the promise of RFID. Frankly it might be a stretch to expect every item consumed to be scanned. What may be more likely would be predictive analytics that suggests what should be purchased based on average consumption over time – which would be based upon purchase frequency – Grocery IQ comes close to this already. This would use similar logic to car dealers who predict when your car is going to be due for service based upon the average mileage per month.
The recipe component might require a significant investment from publishers in standardizing contents and establishing a global standard of products – clearly that’s a long way off. What may be more realistic is software that scans recipes for ingredients and matches them to items in the retailer’s product master. This would still leave plenty of room for ambiguity but it could prove accurate enough to deliver significant value in time savings.
We already see the ability to rate things we like and have that influence what’s recommended from retailers such as Amazon and Netflix. Having family preferences tied to recipes and using predictive technology to predict what we’ll like doesn’t seem a huge leap and it certainly would make selecting meals much less of a chore for many busy families.
Understanding how these interwoven mobile consumer applciations can be developed and deployed is likely to be one of the ways CIOs in the retail industry will be helping their organizations grow business in the next decade.
Personally I don’t think we are too far from this future state being a reality – maybe five years from now – 2015?
What do you think – sooner or later? Post your comments below or through Twitter @NigelFenwick