Laura decides to get herself new outfits for her friend’s upcoming wedding this weekend. Since she doesn’t have enough time to go shopping, she decides to search online. She doesn’t have a specific design in mind, but a trendy dress that goes well with the weather seems like a nice idea. She uses the keyword ‘dress’ and scrolls down through the results.
‘This would be nice if sleeves were shorter.’
‘I like the pattern, but not so much the color…’
‘This fabric is too warm. I probably won’t wear it for too long if I buy it now.’
‘This one is a bit too cute for me.’
‘Trendy jacket dress? The design is good, but I don’t like the details much.’
Realizing that she won’t get anywhere by just searching, Laura goes on the online shops where she’s been interested in. None of the featured fashion items on the main page are in her best interests, so she browses by clicking on the ‘dress’ category and scrolls down. Too many dresses… will she ever find the perfect dress!? oh no..
Growth of Online Fashion Retail Business, but what about customer satisfaction?
Fashion is one of the industries with the most active online businesses. According to the global consulting firm McKinsey, it was forecasted that the world fashion market size in 2019 would increase to over 2.55 trillion USD and E-commerce market size to over 520 billion USD, and as it stands, the market is continuously increasing rapidly at 11% annually.
It’s true that with bigger market size, more opportunities have arisen for sales growth, but the online fashion industry still lacks the bullseye strategies to target consumers with high precision. From selecting items leading up to sales, most of the process is still being done by human’s ‘sense’ since the process is not yet automated or digitalized. The featured items on the main pages of online shopping malls are usually either from merchandiser’s picks or a list of items that made the most amount sale.
The biggest problem is, online shoppers are leaving since they cannot find satisfying products. Although Merchandiser’s picks do help, they’ll always be generalized recommendations, and hence they cannot reflect all of customer’s taste. Fashion is the industry where the decision to make the purchase is heavily influenced by one’s taste, and therefore more individualized services are needed to take sales conversions up a notch.
A successful case for increasing sales conversion through individualization strategy can be seen on Amazon. While the CVR(conversion rate) for other e-commerce sites remained on average at just 1.33%, Amazon’s was at a whopping 9.78%. This was achieved through aggregation and analysis of customer behaviour data, and using it to optimize customer experience for each person by predicting their preferences.
Personalization - The key to increase both consumer satisfaction and sales.
What if online fashion retail provides the contents based on one’s taste? Customers will be able to find the item they want much faster, resulting in increase of sales as well as better customer retention rate.
However, fashion is a field where information is conveyed through images not the texts. It’s general to refer to text information when buying products such as daily necessities or electronics. For fashion products however, consumers make the decision to purchase after checking out the details inside the images such as color, design and more. When uploading a fashion product, metadata composed with text is required together with an image.
Metadata by definition is ‘data that describes the other data’, i.e. it describes the fashion item’s attributes. Like in the case of Laura, she was able to get the search results with the keyword ‘dress’ because the metadata with the text ‘dress’ was uploaded with the item. The metadata can contain various tag information such as the item’s color, length, print pattern or style which can be used in searching products using keywords or filters.
However, it’s not easy to input tens of thousands of product’s tag value with details and consistently. Inputting these metadata needs to be done under clear classification standards, and this is only possible if manually performed by a trained merchandiser. Since this process takes too much time and if several people are involved in the process, inconsistent data could result from different classifying standards between each person.
The solution is simple. Use our OMNIOUS TAGGER that can tag much faster than human and precisely like experts.
Improve customer experience with using fast and accurately inputting OMNIOUS TAGGER.
OMNIOUS possesses AI(Artificial Intelligence) technology that can recognize fashion products inside images. OMNIOUS TAGGER uses a consistent standard to tag 13 different fashion attributes such as color, length, material, and style. It can tag over 200 thousand images a day with consistent tagging standards, and with high precision that’s in level with Merchandisers.
Tag data created by OMNIOUS TAGGER can be used in various ways like optimizing search keyword, enhancing filter function, personalized catalog service and more.
1) Search Keyword Optimization: Search fashion products with text from now on.
In the keyword ‘dress’, the only available information is its category(dress). OMNIOUS TAGGER not only tags the item’s category but also detailed attributes such as whole length, sleeve length, material and color that can be used as search keywords. If the search results return exactly the items they want, for example ‘striped shirt dress with knee length’, purchase conversion rate via searching will increase. What’s even better is, emotional keywords like ‘feminine style’, and ‘wedding guest style’ can also be used. We have a report showing that customers using the website’s searching function showed 80% increase in purchase conversion rate than customers who didn’t.
2) Improved product filter: Use various filter criteria to browse items closely aligned to your taste.
Take no more of unkind filters that only allowed options like ‘Highest sales’, ‘Highest Prices’ or ‘New Arrivals’. With the tag data from OMNIOUS TAGGER, you can narrow down your customer’s search more closely to their taste by providing additional options such as gender, age, style, color or textile. With our new system, you no longer need expert advice from merchandisers to provide effective product recommendations.
3) Check out product catalogs with data: see portfolio analysis on the dashboard at a. ingle glance.
OMNIOUS TAGGER’s clients are provided with catalog insight dashboard composed with data. See which products sold the most, see if there are any common tags in the high or low end of the sales category, see which item attributes were the most popular, and see many more super useful statistics on our data-driven portfolio analysis.
Start with OMNIOUS TAGGER now!
OMNIOUS TAGGER is provided in the form of an API. After going through a simple integration process, images can be put-in to extract various attribute information that is then automatically updated with your site’s listings, and added to the search filter options. OMNIOUS STUDIO is also available for private businesses who prefer using the product without going through the integration process.
Online fashion retail market will continue to grow in the future. If customer experience is improved, it’ll be possible for you to take the leading position in this ever-growing market. Break out from the old-fashioned method of displaying product information just through images, but try out the new filters and search features catered to improve customer experience. You will be surprised how much customer’s stay time and sales conversion rate improves. Use OMNIOUS TAGGER NOW and be a leader in this market.
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