3 Ways Computer Vision Elevates the Online Retail Experience
Today’s consumers are overwhelmed by virtually unlimited choices across multiple ecommerce channels for almost anything they want to buy - whether it's a new dress, a house, or flight. Computer vision (CV), a form of artificial intelligence (AI), helps smart retailers ensure the right product is discovered at the right time, reducing friction and creating a seamless experience to ultimately drive revenue.
In this post, I'll run through 3 ways CV AI is making the retail experience better by making it easier for shoppers to find what they want. Want even more examples and details around how CV AI is impacting retail along with real use cases and results? Download your full free guide to driving revenue with computer vision here!
1. Product Discovery Through Improved Tagging
Product discoverability starts with effective inventory management, which can be made more efficient through the use of CV AI. Automating your workflow with computer vision saves you and your team time and labor, as well as significantly impacting your bottom line.
Retailers lose countless hours hours fixing inconsistent, inaccurate product tags in their catalog trying to make their products easier to find. The problem often stems from suppliers, who rarely have a shared taxonomy for labeling retail products. Computer vision is helping many retailers solve this issue and boost efficiencies in their inventory management processes. How?
Attributes identified in product images are like a universal language—it doesn’t matter which supplier built the product or the source country. Computer vision automatically identifies these attributes and creates highly descriptive product tags.
Impact of automated product tagging:
- Reduced time to listing helps maximize product exposure
- Better product descriptions improves 3rd party search engine discoverability
- Enhanced onsite search capabilities results in more product views
2. Snap and Search Fuctionality
In this age of instant gratification, consumers expect to be able to purchase on the go. However, thanks to widespread adoption across the industry, mobile apps are no longer differentiators for retailers.
Mobile-enabled visual search (or ‘Snap and Search’) helps connect customers with precisely what they are looking for at the moment of inspiration. Customers simply upload photos via their mobile devices and are instantly returned your visually similar items.
Impact of snap and search functionality:
- Shorten path to purchase by offering customers exactly what they want, when they want it
- Connect offline inspiration to online purchases
- Enable high intent customers to make impulse purchases
3. Out of Stock Alternatives
Finding a product you like only to be told it’s currently unavailable is a frustrating experience. In the past retailers have tried to maintain buyer interest by implementing tactics such as in-stock email notification options. However, retailers are still losing millions of dollars thanks to these lost purchase opportunities.
Computer vision offers a significantly more effective way to handle out of stock scenarios by returning items that are visually similar to the unavailable product as an alternative to the customer, who is then able to complete their purchase quickly without looking at competing sources.
Impact of visually similar out of stock alternatives:
- Maintain competitive edge by proposing relevant alternatives
- Offer frictionless shopping experience - even when items are unavailable
- Reduce bounce rates and increase conversions
Computer vision's impact on retail is real and growing. Consumers today expect to be able to find what they want exactly when they want it, and CV AI enables any company with a retail experience to provide that and, ultimately, increase revenue.
相關推薦
3 Ways Computer Vision Elevates the Online Retail Experience
Today’s consumers are overwhelmed by virtually unlimited choices across multiple ecommerce channels for almost anything they want to buy - whether it's a n
3 Ways AI is Improving the Retail UX
Every retailer knows that delivering a satisfying, frictionless shopping experience is key, and consumer expectations have never been higher. According to
3 Ways AI Is Making the World More Inclusive & Accessible
At Clarifai, we believe in the importance of constantly improving AI to fuel the progress of humanity, and one of the most important elements of this is to
5 Ways Computer Vision can Increase E
From discounts to free shipping, businesses are always looking for ways to encourage their customers to buy more. Now, they can add computer vision to that
【立體匹配和深度估計 3】Computer Vision Toolkit (cvkit)
Computer Vision Toolkit (cvkit) 是釋出在 Middlebury Stereo Datasets 上的一套計算機視覺研究工具集。本文主要記錄它的安裝和使用方法。 文章目錄 1. cvkit 介紹 2. c
【Network architecture】Rethinking the Inception Architecture for Computer Vision(inception-v3)論文解析
傳統 tps 聚合 更遠 瓶頸 orm -o 分類 每一個 0. paper link inception-v3 1. Overview ??這篇文章很多“經驗”性的東西,因此會寫的比較細,把文章裏的一些話摘取出來,多學習一下,希望對以後自己設計網絡有幫助。 2. Four
《Inception V3-Rethinking the Inception Architecture for Computer Vision》論文筆記
1. 論文思想 在其它條件都滿足的(資料充足且足夠好)的情況下,增加模型的尺寸以及計算量會帶來實質上的優勢,但是可供計算的資源總是有限的,特別是在移動裝置上,並不能無節制的增加模型的尺寸。例如,在VggNet模型中使用的引數量是AlexNet引數量的三倍,實際取得的效果也是好於Ale
3 Ways Artificial Intelligence is Impacting the Art World
Picasso, Van Gogh, AI? Since artificial intelligence (AI) seeks to mimic human intelligence, it’s natural that AI developers would apply the technology to
3 Ways to Enhance the Customer Experience Using AI and Machine Learning
Digital transformation is atop the list of every marketing leader's initiatives. While there's a lot of hype around AI and machine learning, there seems to
Computer Vision: Keep a Sharp Eye on the Road
Deep learning is a method of machine learning. It allows an in-car AI to be trained to predict outputs based on a selected set of inputs. Hidden layers pla
How to Prove the ROI of Computer Vision Moderation
While other forms of AI are still in their infancy, one field of AI is already in practical use by businesses: computer vision. Computer vision (CV) has al
5 Ways To Remove In-Store Friction With Computer Vision
The retail landscape is rapidly changing as consumers expect more convenience and better service across the entire retail customer journey. Research shows
Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art
本文通過提供有關自動駕駛計算機視覺這一主題的最新調查。調查既包括最為相關的歷史資料,也包括識別、重建、運動估測、追蹤、場景理解以及端到端學習等當前最先進的專業主題。為了完成這一目標,首先通過分類學對每個方法進行分類,接著在 KITTI、ISPRS、MOT 和
網路模型 Inception V2/V3-Rethinking the Inception Architecture for Computer Vision
本文是對 GoogleNet 網路模型 Inception 架構的重思考和改進,Inception V3, 其中 Going deeper with convolutions 是 Inception V1, Batch Normalization 是 I
《Rethinking the Inception Architecture for Computer Vision》筆記
介紹 深度學習在計算機視覺方面取得了很大突破。在2014ILSVRC分類比賽中中,VGG和GoogLeNet取得了優異成績。卷積網路架構上的改進可以提升計算機視覺各類任務的效能。 VGG以很樸素的方式描述了特徵,但有很大的計算量。GoogLeNet
綜述自動駕駛中的計算機視覺Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art(下)
6. Semantic Segmentation Formulation Structured CNNs Conditional Random Fields Discussion 6.1 Semantic Instance Segmentati
綜述自動駕駛中的計算機視覺Computer Vision for Autonomous Vehicles: Problems, Datasets and State-of-the-Art(上)
17年CVPR上的一篇關於自動駕駛和計算機視覺的綜述,比較全面,大體整理一個提綱,重點關注比較新的研究成果,側重於深度學習方面的。 1. History of Autonomous Driving 自動駕駛的歷史 這一部分介紹了自動駕駛的專案和自
3 ways to define a JavaScript class
cts tel etime red pattern iat let lang ive 3 ways to define a JavaScript class September 29th, 2006. Tagged: JavaScript Introductio
3 Ways to Generate vCenter Support Bundle in vCenter Server Appliance
log1.Generate vCenter Support Bundle using Web Browsera.Log into any Windows machine on which you want to download the vCenter Support bundle.b. Open any w