Initial Idea Generation
Before any initial ideas could be created, an existing online retailer had to be chosen to focus on. As the brief states that the problem of 'social returners' needs to be minimised and prevented as much as possible, it was more appropriate to pick a large online retailer, as the outcome would target a larger number of people - therefore reducing the problem as much as possible.
It was found in the research stage that Amazon is the largest online platform for retail. Whilst focusing my ideas on their platform would target the biggest audience of people possible, I chose to pick another retailer, as have already developed the Amazon platform this year in the OUGD504 Design For Screen brief. In terms of UK retailers, the biggest online clothes-only retailer is ASOS, also being the highest ranked high street retailers in The UK RepTrak list. For this reason, I opted to focus on ASOS's platform and marketing.As almost all of my friends and peers use ASOS on a regular basis, it was much more appropriate for me to focus the idea generation stage on the 'young adults' target audience created, as I am able to receive feedback from both male and female consumers of this demographic. Whilst 16-24 is not the highest buying age group of clothes online, it is the second, being only 4% behind the 'top consumer' audience with a percentage of 69%.
The target audience chosen is therefore 'young adults', aged 16-24, that use ASOS. The two main outcomes required are a developed platform and marketing campaign. As the platform must work for all users and age groups, the resolution for the platform must be universal. However, for the marketing campaign, 'young adults' will be the main focus. Initial idea generation therefore focused on the two main outcomes. Ideas were informed completely from the research made, focusing on current retail technology, marketing strategies and resolutions to the 'serial returner' problem.
As my outcomes will be purely digital and online, to link entirely to my essay title, various physical aspects such as stock, print and binding did not need to be considered. Ideas focus much more on the audience ('young adults'), user experience, usability and functionality. Thumbnail drawings were made for each idea to visually highlight how each idea would work. Colour, images and typography will be focused on in the development stage, as I want to keep these ideas purely focused on resolving the problem, as opposed to aesthetics.
Platform Ideas
The main reason that 'serial returners' exist is because it is quite difficult to judge how an item of clothing will fit before buying online. Whilst sizing guides exist, not all are accurate, and some people order without checking individual items. For the platform ideas, I attempted to resolve the problem by essentially making the ASOS store a personalised assistant, whereby user data is input and used to assort the products only by sizes that fit them.
For the first two ideas, I put a focus on using new, and current, technology. The first idea was inspired by Amazon's 3D shoe size project, analysed in the research stage. For my idea, a 3D figure of the user would be made on-screen, built from uploaded photos and input data. Based on recorded clothing measurements, users would visually be able to see a fit of the clothes they want modelled on their body, before buying.
As for the second idea, a focus was put on using mobile augmented reality, whereby users can see items on themselves. This was inspired by the Converse app analysed in the research stage. Whilst this would be much easier to create, technologically, it would not resolve the issue of sizing, as the clothes would not be an accurate fit representation. It would however, aim to solve the problem of people sending items back that they don't like on them, rather than those that don't fit.
The next two ideas focus on solutions that are less technologically complex to create. Both would be personalised platforms that essentially choose your size in every item in the store.
In Idea 3, you would input various body measurements, such as height, chest size, average size and fit preference (there would be various clothing areas). These would be saved and used by data algorithms to assort the ASOS store for you, automatically picking the best size for you.
In Idea 4, instead of inputting your data, you enter a item that already fits you (already own) and it's size. ASOS would then analyse the data of this item and assort the store with items that match that type of fit.
The final platform idea focuses on restricting the way in which consumers order items. As many 'social returners' buy multiple sizes of the same item to try on and send back, this idea aims to put an end to this by limiting customers to buying just one size of an item. As free returns are essential to stay competitive online, it is not the main issue. Free returns would still be offered to customers, but only to swap one size for another.
Marketing Campaign Ideas
As 'young adults' are the biggest mobile shoppers online, it was appropriate to create marketing campaign ideas that are compatible on a mobile format. All these ideas were inspired and developed entirely from the marketing research made, and also new technology possibilities. As it was highlighted in the research stage that video advertising is far more successful than still photo advertising, the majority of ideas revolve around video marketing campaigns.
The first idea is a dynamic ad campaign that uses images of users from Facebook to make mockups of clothes on them, rather than on a model. This would utilise FB facial recognition data to swap the model's face with the targeted user. Model shapes and sizes would be picked depending on the user's pictures / data on the ASOS platform. The ads would be distributed on social media platforms, by would be only privately viewable to each individual user for privacy reasons.
As for Idea 2, inspiration was taken from the 'We Run Paris' campaign, analysed in the research stage. It would be a dynamic ad campaign that asks existing ASOS users about how their item fits (after ordering and receiving). A video with similar sized / fitting items would then be created, in a similar way that Nike was able to change the runner name and time in their video. This would be emailed out to users in conjunction with the new sizing platform. If users gave feedback suggesting items were too tight / baggy, the dynamic videos would suggest better sizes for them - it would become more intelligent as the campaign goes on.
The next set of ideas are video campaigns that aware people about the new Amazon sizing platform. Both would use the tag line 'Don't let size be an issue', but would have different approaches. Idea 3 would be more humorous, and most likely more engaging for a younger audience, by using short clips of things that don't fit in things. Some examples that come to mind are the new iPhone cable, extra large hot dogs in buns that are too small and crammed lifts.
The other idea would be much more serious. This may appeal to a older target audience; however, it would try to aware younger consumers about the effects of 'serial returners' and make them think again when ordering clothes online. The video would focus on facts and statistics due to 'social returners', and would be very punctual.
Both would end with a name for the new ASOS platform and sizing feature, to show that they are the first to be tackling the problem face on.
The final idea is a marketing strategy for existing ASOS. Once signed up to the new sizing platform and having received the user's data, videos with personalised clothing suggestions could be made and distributed onto the user's social media timeline. Clothes would target the user's style perference and would show the best suitable sizes.
Feedback & Prototype Solution
As a large variety of ideas to solve the 'social returner' problem were now made, I was able to gain some feedback by presenting them to a crit group of 'young adults' (the chosen target audience). After roughly explaining the problem of 'serial returners', how ideas link to my essay themes and the various ideas created I left the pieces of paper out on a table for people to look at. I asked the crit group to leave feedback on which ideas they thought would be the most successful in minimising the problems associated with 'social returners'. The main comments and ideas picked were used to finalise three main prototype solutions. These can be seen below.
Prototype 1
Inspired by Amazon's 3D shoe size project, analysed in the research stage, this prototype stems from 'Platform Idea 1'. The main aim is to allow consumers to create a 3D figure of themselves on ASOS, built from a variety of uploaded photos and input data. By 3D scanning all the clothes on ASOS, users would visually be able to try on the entire catalogue, online, before buying.
In the crit, many people commented that this would be the best possible solution to the 'serial returner' problem, as it would eliminate the issue of consumers not knowing how an item of clothing would fit on them before buying. The 3D system would have to be very detailed and complex in order for 3D sizings and fit visuals to be accurate.The main problem that was identified with this possible solution in the crit is that it would be a huge-scale task to take on for ASOS, and that they may not be willing to spend a huge amount of money on getting their items 3D scanned. Furthermore, it may be very difficult to make the 3D software work on mobile devices. This is extremely important, as 69% of ASOS' traffic comes from mobiles. Because the outcome would be so complex, technologically and financially, I chose not to develop this prototype forward.
Prototype 2
Platform Ideas 3, 4 and 5 were also highly voted in the crit group. The feedback given suggested that I combine either Idea 3 or 4 with Idea 5, as the platform would be much more effective with the two working together. The main argument for picking Idea 3 was that, with Idea 4, ASOS may not have an item of clothing on their database that the customer has at their home. This would make the sizing platform unaccessible to a lot of people; therefore, Idea 3 and 5 were combined.
This prototype is essentially a personalised platform that automatically chooses your size in ASOS item before buying. For this to work, the consumer would input various body measurements, such as height, chest size, average size and fit preference (there would be various requirements for different items). These would be saved and used by data algorithms to assort the ASOS store for you, automatically showing and selecting the best size for you. Whilst this would make shopping more convenient and easier for consumers, it would not necessarily stop the problem of 'social returners' ordering various sizes. Therefore, restrictions would be put on accounts, where users can only order one size per item. One piece of feedback given in the crit was that there needs to be a way in which users cannot order an item, then order it again in a different size. To prevent this, users would only be allowed to order items once until they have been delivered and kept. If an item does not fit, users can use the free returns service to swap it for another size.
This prototype would work effectively on desktops AND mobiles, which is crucial considering the target audience and fact that 69% of ASOS' traffic is from mobiles. The thumbnails seen in the idea sketches highlight how the platform would work. This is the platform idea that I am going to develop forward.
Prototype 3
The last prototype is essentially marketing idea 2; however, feedback suggested that I make use of social media, not just emails, as young people tend to check their Facebook page more often than their emails.
Inspiration for this solution was taken from the 'We Run Paris' campaign, analysed in the research stage. This marketing outcome would be a dynamic ad campaign that asks existing ASOS users about how their item fits (via email after ordering and receiving the item). A video with similar sized / fitting items would then be created, which can be customized to individual customers. This would work in a similar way to the Nike campaign, where they were able to change the runner name and time in their videos. The videos would be emailed out to users and would also appear privately on the user's social media feed (Facebook). If users gave feedback suggesting items were too tight / baggy, the dynamic videos would suggest better sizes for them - it would become more intelligent as the campaign goes on.
This marketing campaign would work in conjunction with the new sizing platform. As people thought that this would be much more useful and personal than the existing still ASOS adverts, I have chosen to develop this marketing campaign forward. Because of the identified target audience I am going to make outcomes in a mobile format.
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