DEV Community: neethu neethu

Intelligent Document Processing

neethu neethu — Tue, 03 Jan 2023 11:27:00 +0000

Let’s get real - most of us HATE paperwork. But documents are also the foundation of how our business gets done, from contracts to records to paper applications. Extracting and processing information from these documents involves operationally intensive processes. Or to put it simply, it’s a pain. Let’s get to the numbers involved:
80% of a company’s information resources exist as unstructured data.
9 in 10 employees waste up to 8 hours a week looking for data within documents
Companies spend 15% of their revenue on creating, managing, and distributing paper documents
And the results? Unplanned delays, errors, wasted time and even financial implications when documents are processed poorly.

Introducing: Intelligent Document Processing
Intelligent Document Processing by Blox.ai leverages AI with programmable automation. And what can you do with it?
Convert data from semi-structured and unstructured documents into usable, structured formats.
Enable faster and more accurate processing of documents across use cases (Listed at the end!) with organized data that is optimized for downstream processes.
How It Works
The Blox.ai Intelligent Document Processing solution uses Natural Language Processing (NLP), Computer Vision (CV), Optical Character Recognition (OCR) and machine learning tools to identify, label, and extract relevant data from any input document.
The extracted information is mapped into a structured format while the AI configures a model which can be applied to all similar document types.
The structured data is then matched, qualified, and reconciled against specified guidelines, thresholds, or other documents based on business needs.
The output is pushed to downstream systems automatically.
Blox.ai’s AI-on-AI layer enables real-time selection of the most relevant algorithm for a particular use case from the model library, leading to a more robust solution that is capable of handling diverse scenarios and edge cases.
Where You Can Use Intelligent Document Processing

According to IDC, 43% of knowledge workers say that paper-based workflows make their daily tasks less efficient, costlier, and less productive. With Blox.ai, enterprises have seen:
~ 90% accuracy in extracting key values from documents
85% decrease in time taken to organize data
50% reduction in resource costs
Maximize human potential in your business with Blox.ai

Process any document type through intelligent extraction, multi-way matching, and reconciliation with Blox.
Intelligent Document Processing: Optimize your document workflows through a combination of intelligent and programmable automation.
Read more about intelligent document processing blog

Personalized Search

neethu neethu — Thu, 21 Jul 2022 13:02:03 +0000

Vue.ai’s personalized search solution enhances product data to ensure greater catalogue coverage and more accurate results. Retailers saw an 80% increase in conversion rate for users interacting with Vue.ai.
Power search results to be accurate and relevant to every shopper

Vue.ai’s AI-powered personalized search solution uses rich product and shopper data to make search results accurate and personalized for every shopper.
Improve conversions and reduce bounce rate with personalized search results
Vue.ai capitalizes on the high purchase intent behind eCommerce searches, by personalizing results based on individual shopper preferences. The AI-powered personalized search solution also enhances product data to ensure greater catalog coverage and more accurate results. This tailored search experience reduces bounce rate and improves conversions for eCommerce retailers.

Virtual Dressing Room Experience Online

neethu neethu — Thu, 09 Dec 2021 14:28:15 +0000

One of the biggest victims of the pandemic has been the ubiquitous virtual dressing room in brick and mortar fashion stores. Strict hygiene requirements turned the shopping experience and the retail industry in 2020 on its head. But with the entry of the vaccine, brick and mortar stores are fast reopening in full swing in the US and UK. So what does this mean for shoppers who are likely to be uncomfortable about entering dressing rooms? How do eCommerce brands up their game? Can they offer a virtual dressing room for their online shoppers?
Closing the gap
The most glaring difference between physical and online shopping experiences is the inability for shoppers to determine fit. The problem of ‘touch and feel’ has been solved to an extent with product information and high quality photography. But the experience of actually checking fit as well as styling the product with other items from the store has been one of the biggest draws of the physical retail experience.
The Problem of Fit
Today, one of the top reasons for returns is that the product was not as described — or didn’t look like it did in the image.
Most female editorial models are 5 feet, 9 inches tall and quite slim. Whereas the average American woman is about 5 feet, 4 inches tall and veers between size 16 and 18. When consumers are shopping online and see these tall and thin models, one of two things happens. They may shop aspirationally, which often leads to returns because of fit problems and costs eCommerce retailers a lot in return shipping and restocking. Or, the consumer refrains from making the purchase. Had she seen the garment on a model of her size, she may have been convinced to buy it!
Case in point: The Good American does size variation well and has a more diverse range of models. Shoppers can see models of sizes 0, 8 and 16. Inclusivity has been the brand’s anchor from its inception — resulting in sales that crossed $1 million on its first day (the biggest denim launch in history!)
If a fashion eCommerce platform isn’t showcasing relatable models, it should consider the impact it could have on the bottom line.
Read more about Virtual dressing room

AI Powered Styling for Your Shoppers : Vue.ai’s Cross Product Recommendations

neethu neethu — Mon, 06 Dec 2021 14:44:05 +0000

Here’s a scenario for you: You’ve found the perfect “match” on Tinder, and want to make an impression on your first date. You want to start off by looking for a shirt and find one that you really like. So you click on it to look at its product detail page.
You start looking at the complete image and love everything that the model’s wearing — from the pants that work so well with that shirt, all the way down to the sneakers that look EXACTLY like the ones you’ve wanted for a while. You have no idea how to look for those sneakers — you don’t even know which brand they belong to! All you have is a vague description of the color and the style.
So you go through the painful process of clicking through innumerable pages and search results… without any luck! So after all that effort all that you’ve done, really, is waste lots of time without even buying that shirt. And don’t even get me started on the sneakers!
If only finding the right look was as easy as swiping right!
I’ve been there. And if your shoppers are anything like me, then you should know that it is extremely frustrating for them to see the products that they want, without being able to buy them.

Introducing Complete the Look By Vue.ai : Cross Product Recommendations for Fashion eCommerce

Here’s the good news. We’ve managed to solve this problem with our Complete the Look module which provides cross product recommendation engine, that can power not just your product detail pages but also your cart and checkout pages.
Complete the Look understands your shoppers’ behavioral patterns and visual affinities to products, and also the rules of fashion, to deliver 1:1 personalization (personalization engine). So your shoppers see curated outfits that are foolproof — in terms of style, color, pattern combinations. Complete the Look acts as your website’s AI-powered styling tool, to showcase curated looks that they’ll love, taking visual merchandising to the next level.

Understanding Shopper Behavior

We’ve noticed that while shoppers are inspired by the different looks offered as a part of the product images, they also want the individual elements making up the look to be “shoppable”.
On further observation, we realized some other aspects that are important to consider when targeting shoppers looking to buy ensembles:
Shoppers like to see accessories and other items of clothing that complement and complete a look, even if it’s not what the model is wearing. This is why cross product recommendations can significantly improve shopper engagement and have a direct impact on the basket size.
A little “visually similar” variety never hurt anybody. It is our understanding that it’s not just an item’s brand or price that shoppers fall in love with. More often than not, it’s also the visual merchandising that draws them. If a product within a particular look is sold out, they’re more likely to continue shopping on your site when you show them something that’s similar to products they like.
When in doubt, offer more choice. Shoppers want to see alternatives to the products showcased in a “look” even when all the original products are still available. This makes it easy for them to shop if something isn’t available in their size or preferred price range.
The versatility of products helps with decision-making. Shoppers like to see how versatile the product they are viewing really is. When you show them a product page that includes pairing suggestions in different colors — they’ll view more, click more, and buy more.
Minimizing navigation is key. While shoppers would like to gather different products within Complete the Look, they would also like to sift through them and add them all to their cart at once. This reduces the risk of the shopper abandoning your site during the course of their purchase journey.
Combining Behavioral Triggers With The Rules Of Fashion
As we developed an understanding of shopper behavior, we combined it with the rules of fashion to zero in on the parameters which would eventually allow our algorithms to curate ensembles without any manual intervention.
Visual affinity: This is a metric that is key to Complete the Look, and replicates the experience of having a personal stylist. We’ve developed a visual grammar by working closely with our in-house fashion and home stylists. This grammar allows the AI to pair the right top with the right bottom-wear, jewelry, and other accessories. This pairing is based on color temperature, the fit, the style, the patterns, the cuts, and much more. We approach it from a style perspective as opposed to just the attributes. So what you get in effect are formal ensembles for work, casual looks, 9 to 9 ensembles, evening wear ensembles and much more which are carefully curated by our artificial intelligence and computer vision engine.
Inter-product Correlation: This provides us with an understanding of how strongly two products are associated — whether they are usually bought together or independent of each other.
Price affinity: This allows us to group products that are termed similar in terms of their prices positioning within their categories.
For example, For example, a consumer who purchases expensive items in one category is likely to buy an expensive item in another category as well.
Brand affinity: This considers the shoppers’ preferred brands, and computes the similarity between two brand names to show relevant recommendations.

Different Use Cases For Complete the Look

Use Case I: Getting the Ensemble That Compliments the Product
The shopper can view the curated looks and ensembles on the Product Detail Page (PDP) of each item. If an item is not available, the Vue.ai engine proposes a similar item:
Use Case II: Recommend Complimentary Items
The product recommendation engine also suggests complementary items to shoppers, based on their price preferences:
Use Case III: Recommend Similar Items
The product recommendation engine also suggest items that are similar to the original products the model is wearing within the display image. So you not only get to shop the look, but also get to see alternatives.
Use Case IV: Get Other Looks
This feature relates to the assumption that users want to see an article in more than one look/styling.
Complete the Look Works, And The Numbers Prove It!
We put the feature to the test, going live with it across some of our fashion, furniture and lifestyle customers. We learned that while it works well on the product pages, it yields incredible results on the cart/checkout page. If we were to look at some of the initial results of how it has performed, we learned that it has led to a 1.5x increase in the average order value (AOV) , with the average order size (AOS) doubled across the board.
Considering that this was a completely new feature for our customers, we’d say these numbers are very encouraging. And with a GMV contribution of 25K USD to the revenue from a single widget, we’re ensuring these retailers are not leaving any money on the table. And with our algorithms only getting smarter, we can safely state that AI curated ensembles are the future of retail.

Virtual dressing room

neethu neethu — Mon, 22 Nov 2021 08:33:14 +0000

Grow eCommerce revenue with virtual dressing rooms
Dressing Room by VueModel allows shoppers to visualize and style products on relatable models of various shapes, sizes, ethnicities in real time.
Make your eCommerce site come alive with a virtual dressing room
Dressing Room by VueModel helps retailers deliver personalized, inclusive dressing room experiences in their eCommerce stores. Shoppers can mix & match looks, and visualize how they fit on models that most resemble them.
Virtual dressing room

Personalization Engine

neethu neethu — Mon, 22 Nov 2021 08:25:10 +0000

AI Powered Personalization Engine
Today’s consumer values a positive user experience as much as (if not more than) the cost of the products they’re purchasing. Naturally, they've come to expect personalized eCommerce experiences that place them, the customer, at the centre. These personalized experiences may well be a make or break factor. Personalization not only benefits the consumer through a more unique and relevent customer experience, but it also benefits companies by getting in front of the right customers, in the right places, at the right times, with the right experiences. The end result? Higher conversion, AOV, and greater customer retention.

So how do retailers achieve this? We've got the answers in this week's Your Retail Vue.
Step 1: Audience Segmentation
In order to be customer centric and deliver effective personalization, retailers need to identify which audience segments will bring them the greatest value. The more meaningful the segments, the more effective your campaigns and business strategies.
This is why top retailers are turning to A.I. to use customer data in ways that result in business impact. A.I. uses behavioral data to create audience segments that are in line with business outcomes. AI generated audience segments can be based on:

Behaviour - like discount shopper or high value shopper
Attribute preference - like cruelty free (beauty), kosher (grocery), bohemian chic (fashion)
Context - like owner of abandoned cart or one-time shopper What's more, retailers can also add custom segments like loyalty club members, offline promotion shoppers etc. Step 2: Dynamic Personalization Once audience segments have been identified and campaigns have been designed, A.I. can personalize the content within each campaign for every single shopper - and in real time! Dynamic personalization engine takes cognisance of the fact that every shopper is different. Their intentions are different, their preferences are different and their price affinities are different. AI-powered dynamic personalization engine takes into account their historical preferences and marries it with their actions in the current session to produce timely and relevant recommendations. Even if it's an anonymous shopper with no prior history, the A.I. can capture their behaviour in the current session to deliver the most relevant recommendations. And that results in greater conversions - and consequently - greater revenue. Step 3: A/B Test Did you know that retailers that run continuous A/B tests see 2X more growth than others? Constant A/B testing and optimization is key to determining the performance of any eCommerce strategy. A/B testing allows retailers to take decisions backed by data and not just gut-feel alone. What's more, A/B testing helps identify patterns and gain deep insights into shopper behavior. Data-led decision making is the key to sustained growth. VueX: A Single Platform That Can Power Every Strategy VueX is the AI-Powered Retail Personalization platform for eCommerce. With VueX, you can build, test and scale personalized shopper journeys that drive retail growth. Whether it's audience segmentation, dynamic personalization or A/B testing, VueX is a single tool that can power it all - and more! Vue.ai's personalization engine helps retailers grow revenue multi-fold with the power of A.I. that constantly learns and re-learns customer behavior as it relates to their business needs.

vue.ai's personalization engine offers retailers high revenue, brand development and multifold customers. our personalization tool understand each and every shoppers behaviour based on their historical data and live data. based on those datas we provide unique shopper journey to each and every customers. it helps them to get relevant product and experience from website. we offer different types of personalization on website

home page personalization
product page personalization
category page personalization
cart page personalization
email personalization our personalization engine features reduce shopping cart abandonment also

Personalization engine - https://vue.ai/solutions/personalization-engine/

Product recommendation engine

neethu neethu — Thu, 21 Oct 2021 12:53:24 +0000

Personalized product recommendation engine
Vue.ai’s product recommendation engine tracks website shoppers' behaviour based on their user behaviour. We tracked their historical and live data and based on that we provide product recommendations to them. Every shopper should delight in getting an individualized shopper experience. personalized recommendations that convert 120% better.

Drive growth with personalized product recommendations. Make every customer feel special with 1:1 curated & personalized recommendations that convert 120% better.A personalized experience at every touchpoint. Delight every shopper with truly individualized shopper experiences and grow your revenue.
Style Profiles
Build unique Style Profiles for each shopper based on their likes, affinities, and visual preferences.
Dynamic Personalization
Gauge shopper intent in real time with every click they make, to power relevant product discovery.
Recommendation Strategies
Deploy a variety of product recommendation engine strategies to improve shopper engagement and conversion.
AI-Powered Search and Sorting
Leverage the power of Image Recognition to serve individualized search results to every shopper.

https://vue.ai/products/product-recommendations/