Tag Archives for " retail technology "

Conversational AI – The next Step in E-commerce Evolution

Conversational AI - The next Step in E-commerce Evolution

There is no doubt that AI is a popular buzzword in the retail landscape and retailers are slowly recognizing its potential and are increasingly adopting at least one form of AI into their customer journeys or internal processes. By 2019, 40 percent of retailers will have developed a customer experience architecture supported by an AI. Retailers that choose not to incorporate an AI-backed solution into their business strategies will face consequences that can severely affect their bottom line.

Conversational AI can fundamentally transform the way consumers communicate and transact with brands. While this is true across all industries, retailers, in particular, can reap multiple benefits, depending upon their adoption of new technologies. To help retailers understand the importance of implementing Conversational commerce into their retail strategy, here are some aspects where it makes a real difference:

Meeting the customer where they are

Messaging is one of the popular means to interact with one another and that’s how they prefer to interact with brands, too. Conversational AI allows retailers to tap into the most immediate form of communication i.e. messaging and reach consumers in a very convenient manner at a higher scale which was not possible before.

Moreover, with Amazon Alexa, Google Home and now ubiquitous technology in the home and office, as well as with the growing familiarity towards similar technologies, people are shopping with voice-based assistants in greater numbers.

Increased Customer Interaction with Conversational AI

Technology is evolving at a rapid pace, and both web and apps which were once quite the rage among retailers are now tools that are causing friction between the customer and retailer. Conversational AI has the ability to add a new layer of interactivity to online shopping.

It further enables a richer, more complex customer engagement, featuring personalized shopping assistants and concierge bots answering questions, recommending items, and handling individual transactions. This helps to personalize the digital experience at each touch point of the customer journey.

Conversational Design is the New Personalized Web Design

Like the human language, conversational commerce is flat. This allows brands to engage in real relationship-based commerce not usually achievable through websites and apps. While it has the ability to handle a broad set of commands, without AI, it lacks the capacity to understand complex inquiries.

 The integration of AI breaks down these barriers and retailers can turn towards messaging solutions such as chatbots and program them to echo the brand voice as well as provide a more personalized and positive experience unique to each customer.


Conversational AI has the ability to change the way all brands conduct business. It connects them with their customers more organically and creates personalized experiences tailor-made for every individual. This will serve as the first universal interface, increasing the efficiency among retailers and brands as well as maximizing profits.

 

Related e-commerce articles:

Transforming the Retail Customer Experience with In-store Analytics
Online retailers have the advantage of tracking cookies and web analytics tools to calibrate different aspects of an online shopping[...]
AI is Redefining Experience in Customer Support Centres
Businesses need to understand the complexities of individual transactions and customer behavior over multiple touch points and channels, now more[...]
Speech Analytics vs Voice Analytics: What is the difference?
Speech Analytics vs Voice AnalyticsBusinesses today have access to more consumer data than ever before, especially through their customer support[...]
Conversational AI – The next Step in E-commerce Evolution
Conversational AI - The next Step in E-commerce EvolutionThere is no doubt that AI is a popular buzzword in the[...]
Conversational AI: Getting Started
Conversational AI: Getting StartedWith the increasing list of benefits and a growing demand for voice interfaces, the retail space is[...]
Voice-enabled chatbots vs Messenger bots: What you need to know
  There are two distinct ways in which a conversational interface works: text conversations and voice. Consumers interact with chatbots[...]
people looking at an ipad

User-generated Content: Playing a crucial role in e-commerce

User-generated Content: Playing a crucial role in e-commerce

Content is an extremely crucial part of any e-commerce business as it has the ability to drive a large amount of organic traffic onto a website. Businesses must be sensitive to providing the right content which provides the brand a wider range of audiences across the web for minimal cost.

One challenge that e-commerce brands face is the ability to create engaging content across all platforms. Moreover, the true challenge lies in creating engaging content as well as producing enough content.

Producing being the operative word, e-commerce brands have a distinct advantage wherein they don’t necessarily have to create or produce new content when sourcing user-generated content. They can leverage the content sourced from user-generated content (UGC) via various channels such as social media in many forms, such as messages, posts, videos, pictures, etc.

The rise of User Generated Content

Over the past decade, there has been an exponential rise in the amount of user-generated content on the internet and with the popularity of the various social media platforms out there, the growth comes as no surprise.

Customers have been talking about different products and brands for a long time now. With the ability to capture those conversations and interactions across the various social media and other marketing channels, e-commerce brands can avail the benefits without spending too much time attempting to produce newer content.

Why is UGC so effective?

One reason why UGC continues to have increased conversions is:  trust.

Multiple surveys showed that UGC plays an important role in a customer’s shopping journey. Some important findings being - 84% of people trusted online reviews as much as they trusted recommendations from their friends, and 74% of people said that positive reviews dramatically improved trust in a business.

Furthermore, almost 82% of consumers said that user-generated content (like reviews, for example) was extremely valuable in helping them make a purchase decision.

Sourcing UGC is not difficult, yet, deciding what needs to be done after, is important.

Incorporating Customer images in Product pages

Product pages benefit greatly from high-quality images. That being said, every brand going online is upgrading their images to better quality images. E-commerce brands can make their products stand out by skipping the usual images provided by the suppliers and manufacturers and instead, are turning towards customers.

Ex: Popular video streaming service Netflix utilizes UGC to promote fans’ posts about specific shows or movies on Instagram. UGC shows that other people are also getting excited about new shows and movies.

Instagram Netflix screenshot

This can be done if e-commerce brands do away with models, and start looking at their customers as models. Seeing real customers using and wearing products builds significant trust and generates interest in the product. Furthermore, it can also help deliver powerful messages during campaigns using the target audience as representatives for the brand.

Showcasing product benefits

Some brands have to come up with innovative ideas to use user-generated content. While brands selling tangible products such as fashion accessories, or home care products can easily benefit from using UGC easily, brands selling either a service or a software have to get creative.

When there are no tangible products that can be showcased, e-commerce brands can focus on the benefits to the customer and what they may experience using the service or product.

Example: Social media scheduling tool Buffer created #BufferCommunity to showcase photographs and personalities of its many users from all around the world. The aim for this campaign was to source UGC featuring exotic spaces to promote the freedom that Buffer provides.

Instagram Buffer community screenshot

Brands have to focus on how customers use their products and find ways to source UGC, and then insert that into various marketing campaigns - or reshare onto social media to boost engagement and brand awareness.

Including photos with product reviews

Reviews are the easiest UGC on the internet. E-commerce brands generate reviews without doing anything other than providing tremendous customer service and quality products.

To create a more lasting impact with reviews, e-commerce brands can opt for a review platform that enables users to add images as well as videos alongside their written reviews. E-commerce giants such as Amazon leverage this facility for their users.

Customers are more than happy to share their experiences, and that matters tremendously for brands. Many customers prefer to view the product reviews before choosing a particular product as it gives an authentic sense of how the product would appear on them.

The more customers share images alongside their reviews, the more value it brings to the e-commerce store.

Featured photo credit: Photo by rawpixel.com from Pexels

A Tour of CatalogIQ for Grocery

Kick-start eCommerce sales with awesome product data

E-commerce requires awesome product data to support successful search and conversion. Product data for the online grocery market is currently being created manually. Retailers are struggling to acquire the rich product data necessary to support their online needs. Brands are struggling to generate good data.

ContentIQ Add Product

IceCream Labs CatalogIQ is designed to automatically extract attributes from product images. Using either label mechanicals or actual product images of the packaging, CatalogIQ can extract text from the labels. From there, the artificial intelligence in CatalogIQ understands what the text is and inserts it into the appropriate product attribute. The AI can also determine which images are the hero image, and front, back and side images.

CatalogIQ Extracted Attributes

CatalogIQ identifies brand names, sub brands and variants, normalizing the brand to the appropriate text. titles are generated from various attributes to create an SEO-rich title to optimize search. Other key attributes include feature/benefits, ingredients and nutrition facts.

CatalogIQ extracting content from a product

Sample CatalogIQ extraction (front/rear)

How complete is your data?

ContentIQ Catalog List view

CatalogIQ can score the data to help the merchandising and ecommerce teams understand which product records have been enhanced.

  • Missing attributes
  • Accuracy of attributes (are all of the attributes congruent?)
  • How unique are the attributes?
  • Is your product record SEO optimized?
  • Do you have relevant search keywords?
  • How well does your product data match up to customer site searches?
catalog IQ demo screen

Support for Grocery merchandising teams

Grocery merchandising teams have the chore of uploading new catalogs from suppliers and manufacturers. Often this data arrives in the form of a spreadsheet. CatalogIQ can easily upload a new catalog file (in spreadsheet form) to quickly and easily complete the ingestion process.

ContentIQ Add Catalog screen

Support for Grocery and CPG Brands

Grocery retailer and channel partners expect high quality product data to list and sell your products online. Can you deliver the content?

CatalogIQ allows brand and product managers to auto-generate high quality product data directly from product label mechanicals and/or product images. If you're currently using manual processes to create product content and to check the accuracy of product data, then let CatalogIQ help you automate the creation process. You'll be able to complete the data creation process much faster than manual methods. CatalogIQ can also validate the content and ensure that it matches what is contained on all of the product labeling.

CatalogIQ Features

  • Quality product images including relevant Nutrition Facts
  • Accurate meta-data, including attributes like: allergens, sugar free, Kosher certified, Non-GMO and other facets
  • Complete, standardized and SEO enabled titles
  • SEO rich descriptions
  • Correct product categorization

As a merchandising manager with a large product catalog, you know the difficulties of reviewing your product data and ensuring that everything in the catalog is ready to publish live to customers. There is always the nagging concern that something is inaccurate or missing when you push the “publish” button. Every time that you receive new data from your suppliers, it’s a chore to process the data. You have a long checklist to complete before you can publish data to the live catalog. Processing this checklist can consume all of your time.

CatalogIQ Benefits

  • High quality product data
  • Improve product page discoverability 
  • Increase product sales
person using tablet

Tackling DNVBs for emerging brands and legacy retailers

Tackling DNVBs for emerging brands and legacy retailers

The recent years have seen the emergence of DNVBs or micro-brands; brands that focus on providing a niche product for a niche customer, which is changing the consumer brand landscape completely. These direct-to-consumer micro-brands or DNVBs, also known as v-commerce brands, are spearheading new approaches to retail. These brands have a distinct business model; combining the growth of an e-commerce company with the profit margins of a brand.

These brands control the entire experience - from sourcing and manufacturing to delivering product experiences online (website or social media platforms), thus enabling them to iterate product design and demand and connect with their customers in an authentic manner via micro-targeting.

So what can emerging brands and legacy retailers learn from the DNVBs that are disrupting and taking over the e-commerce environment?

Adopt a data-driven model

Standardized messaging is a big no for DNVB customers. High performing DNVBs invest heavily in collecting and measuring data to improve their communication with their customers. They leverage first, second and third party demographic, behavioral and psychographic to design bespoke digital advertising. This further enables them to understand the messaging that would resonate with the different segments in their target demographic.

Every touch point with a customer is devised to convince and convert. Legacy retailers and emerging brands must leverage data to intersect their demographic and strategically target potential customers.

Design strong product experiences

DNVBs offer customers a buying experience which is as memorable as the product. DNVBs create product experiences that are visual, descriptive and transparent (the product is represented in an image enabling the customer to visualize the product as part of their daily life). Furthermore, they also leverage UGC content and customer reviews to further represent the product ensuring that the customer is well briefed about the product before making a purchase. Emerging brands and legacy retailers must further focus on creating strong product experiences to drive revenue.

For example: For a home decor brand, besides how the product looks like, it is important for the brand to provide details about the materials used,  sourcing of the materials as well as the durability of the product. The product page must mention all these details along with the size, height, frame of the product. Pages that include lookbooks or UGC content further helps the customer to make a better choice.

Build tech with a human touch

DNVBs collect data on every transaction and interaction with customers and leverage this information to better understand their customers and how they behave online. The goal is driven to be relevant, highly personalized, efficient and convenient for the customers.

Traditional or emerging brands, while interacting with their customers, must ensure that their message is personalized. For ex: If the customer in the past has purchased organic, whole wheat pasta, the messaging they could receive could include organic tomatoes or organic arrabbiata sauce they could use for their pasta.

Take the brand experience offline

Digitally native brands understand the importance of brick and mortar and do not restrict themselves to being digital-only. DNVBs often expand to shops through partnerships with third-party retailers, pop-up stores or by creating their own physical locations. Moreover, these locations are heavily marketed by influencers, with strategic content as well as promotional offers. They ultimately expand from a digital-only space but without sacrificing their brand or customer experience.

Most e-commerce companies are heavily focused on distributing other brands' goods and competing with e-commerce giants like Amazon, Walmart, and Alibaba while DNVBs are paving the way for a new retail experience with technology, social sharing and being perceptive to the shifts in consumer buying behavior.


Consumers are increasingly demanding informative and convenient product experiences across every sales channel and with more DNVBs coming into the market, expanding their presence beyond digital channels to brick and mortar stores, it is imperative for traditional brands to take inspiration from the DNVBs and adapt their business models to the changing consumer trends. Brands that can not only meet these expectations but also deliver on it will be the most successful in the digital space.

Related e-commerce articles-

AI is Redefining Experience in Customer Support Centres
Businesses need to understand the complexities of individual transactions and customer behavior over multiple touch points and channels, now more[...]
Speech Analytics vs Voice Analytics: What is the difference?
Speech Analytics vs Voice AnalyticsBusinesses today have access to more consumer data than ever before, especially through their customer support[...]
Conversational AI – The next Step in E-commerce Evolution
Conversational AI - The next Step in E-commerce EvolutionThere is no doubt that AI is a popular buzzword in the[...]
Conversational AI: Getting Started
Conversational AI: Getting StartedWith the increasing list of benefits and a growing demand for voice interfaces, the retail space is[...]
Voice-enabled chatbots vs Messenger bots: What you need to know
  There are two distinct ways in which a conversational interface works: text conversations and voice. Consumers interact with chatbots[...]
AI Is The Best Present For Retailers This Holiday Shopping Season
Brands are undergoing massive digital transformations of their own in order to keep pace with the growing demands and expectations.[...]
person doing online shopping via mobile

The Rise of Digitally Native Vertical Brands (DNVBs)

The Rise of Digitally Native Vertical Brands (DNVBs)


In the past, brands that dominated supply chains, dominated the markets share in their category. P&G, Unilever are brands who owned their categories for the past few decades. With the shift towards digital, there was a rise in direct-to-consumer brands called Digitally Native Vertical Brands or DNVBs.

What is DNVB? A brand that is digitally native, vertically integrated company that sells its own products and controls its own distribution via the web maintaining a strong focus on customer experience. While the DNVB starts online, it often uses a brick-and-mortar strategy. This term was made popular by Andy Dunn, founder of a famous online-first brand, Bonobos.

DNVBs have been shaping a new Retail landscape in the US, building competitive advantages and differentiators enabling them to not only compete with well-established brick-and-mortar businesses but also leading e-commerce businesses making a huge impact on what consumers expect from brands. Some of the DNVBs include Blue Apron Inc., Casper, Dollar Shave Club, and Home Chef.

Let’s take a deeper look into three growth strategies of these brands that proved successful:

Personalization in products 

The product offerings in DNVBs are truly unique to each buyer, and these brands take time to craft experiences based on the specific user taking into account their needs, preferences, and behavior.
For instance, Blue Apron takes into account the preferences of the customer and with this information, provides custom meal options that would suit that customer’s need and likes, giving the customer a personalized brand experience.

Customized products require a lot of information and attention to details which requires a different supply chain that big e-commerce companies like Amazon are yet to provide. This provides DNVBs an edge within a cut-throat, competitive ecosystem.

Vertical integration

A brand that sells directly to customers combines multiple benefits - lower cost of online sales, better control of the whole supply chain from manufacturing to distribution.

A great example of vertical integration is Everlane, a web-only clothing brand that compares its own pricing to that of traditional retailers and is able to share with its customers its cost break down as they know their supply chain.

Tech roots

DNVBs are more like tech companies rather than retailers as they build their own retail technology to sell better. It further enables them to track customer interactions, manage inventory, offer store credit, gather feedback to improve data curation, etc.

This user-centric and data-centric approach of DNVBs emphasizes all the steps of the user journey, from pre-purchase to post-purchase experience. This helps meet customer experience and generate loyalty while still offering them a highly personalized experience depending on location, customer behavior, purchase history, etc.

Web-only brands have often become frequent acquisition targets, not only because of the products they sell, but also because of the talent and technology they bring to the traditional retail structures leading to  deals like Unilever’s one-billion-dollar for Dollar Shave Club. Another strategy that retail applies in order to avoid the downsides of an acquisition is to take part in the funding of startups of web-only brands such as Target and $170 million dollar series C led by Casper.

While all the retail companies are leaning towards technology to find new ways to innovate and change the customer experience, a factor that web-only brands or DNVBs heavily rely upon is to scale as well as the ability to attract and retain talents. This is something that traditional retail organizations are yet to tap into completely. 

The retail industry has never been as competitive as today, with three e-commerce giants Amazon, Walmart, and Alibaba taking the large chunk of the e-commerce revenue as well as the technological acceleration being this quick. Among all the retail players, a new category of business is on the rise, disrupting the industry.

Stay tuned to see what must traditional brands do, to keep pace and compete with DNVBs.

Related e-commerce articles:

AI is Redefining Experience in Customer Support Centres
Businesses need to understand the complexities of individual transactions and customer behavior over multiple touch points and channels, now more[...]
Speech Analytics vs Voice Analytics: What is the difference?
Speech Analytics vs Voice AnalyticsBusinesses today have access to more consumer data than ever before, especially through their customer support[...]
Conversational AI – The next Step in E-commerce Evolution
Conversational AI - The next Step in E-commerce EvolutionThere is no doubt that AI is a popular buzzword in the[...]
Conversational AI: Getting Started
Conversational AI: Getting StartedWith the increasing list of benefits and a growing demand for voice interfaces, the retail space is[...]
Voice-enabled chatbots vs Messenger bots: What you need to know
  There are two distinct ways in which a conversational interface works: text conversations and voice. Consumers interact with chatbots[...]
AI Is The Best Present For Retailers This Holiday Shopping Season
Brands are undergoing massive digital transformations of their own in order to keep pace with the growing demands and expectations.[...]
supermarket with fresh produce

AI and Automation are transforming the E-Grocery experience

AI and Automation are transforming the E-Grocery experience

The concept of e-grocery is not new, with existing e-commerce businesses like Walmart To Go, Amazon Fresh and Instacart, but with Amazon acquiring Whole Foods, all the players in the grocery retail industry have realized that grocery shopping is at the brink of transformation and are changing their strategies to accommodate and incorporate online shopping into their business goals. 

The focus is on providing solutions to enhance customer engagement, optimize inventory management and upgrade logistics for accurate and speedy delivery. To address these concerns, businesses are investing in technologies like artificial intelligence (AI), machine learning (ML), big data, internet of things (IoT), cloud computing, autonomous robots, virtual and augmented reality (VR/AR).

Challenges of e-grocery inventory management

The success of an e-grocery business essentially depends on inventory management. The fundamental problem that needs to be addressed is stocking: with grocers finding the right balance between understocking and overstocking. 

Overstocking uses up costly warehouse space and locks up capital which could be otherwise made available for resources. Products decay over time and with perishables, the decay is often quicker, in some cases, by the end of the day. Every wastage affects the business, increasing the costs and making it unproductive.

While on the other hand, understocking hinders the growth of the business. No grocer wants customers abandoning their shopping carts because of the inability to supply an item. While there are options to pre-order products that are not in stock, groceries are fast moving products that customers need on a regular basis. Grocers cannot list fruits, vegetables, cereals, soaps, detergents, and personal care items as out of stock. The demand for them is instant.

Optimizing inventory is crucial for the survival of the grocery industry. It’s no surprise that e-grocers are leaning towards innovative technologies to enhance and optimize their inventory management processes.

aisle with fresh fruits

Emerging trends in e-grocery

Big Data, AI and Machine Learning

E-grocery businesses generate a significant amount of data about purchasing patterns which can be useful to predict future trends. However, this data needs to be examined and categorized to make it efficient and useful. Here’s where data analytics and machine learning come in to help grocers extract relevant insights which help them make strategic business decisions.

Businesses are leveraging AI to predict operational failures and improve warehouse management. As machine learning models get smarter, the systems get more efficient over time.

Automation and use of robots

Besides inventory maintenance, the physical movement of the inventory is another challenge for the grocers as it requires a considerable amount of human labor. Technologies like automation and robotic systems are helping businesses by taking over these manual tasks.

The robotic systems are automating operations for customer orders and are also helping businesses to build space-saving warehouses and utilize the complete area efficiently without wastage. There are rails between aisles for robots to move around, stock and fetch products. Robotics and automation go hand in hand towards reducing the size of real estate investments.

Self-Drive logistics

Another challenge that e-grocers face is delivery of the products to the customers.

Groceries differ from regular e-commerce products such as shoes, or furniture items in two ways: the quick turn around time expected by the customer and the perishable nature of grocery items. As the order volume of the e-grocery business grows, the logistics system needs to scale along with it. This, in turn, increases the delivery cost that further affects the business.

Businesses are turning towards self-drive vehicles to deliver groceries to customers and with startups like AutoX with self-drive car deliveries and Marble with a sidewalk delivery robot coming in the market. As transport technology advances, self-driving automatons can become the next big thing to look out for.

The future of e-grocery

As online grocery businesses are adopting the latest technology to solve the supply chain, inventory management, and logistics problems, even small grocers are able to leverage these technologies to scale their businesses through automation and predictive analytics.

Moving grocery online has been a major problem with the high demand for operational excellence and the low margin of the products. This is a hard sell for many businesses, but with the advancements in AI, Machine Learning, Automation, Robotics, this is changing. This can be seen from the growth of e-grocery ventures that are emerging around the world.

Other e-commerce articles:

AI is Redefining Experience in Customer Support Centres
Businesses need to understand the complexities of individual transactions and customer behavior over multiple touch points and channels, now more[...]
Speech Analytics vs Voice Analytics: What is the difference?
Speech Analytics vs Voice AnalyticsBusinesses today have access to more consumer data than ever before, especially through their customer support[...]
Conversational AI – The next Step in E-commerce Evolution
Conversational AI - The next Step in E-commerce EvolutionThere is no doubt that AI is a popular buzzword in the[...]
Conversational AI: Getting Started
Conversational AI: Getting StartedWith the increasing list of benefits and a growing demand for voice interfaces, the retail space is[...]
Voice-enabled chatbots vs Messenger bots: What you need to know
  There are two distinct ways in which a conversational interface works: text conversations and voice. Consumers interact with chatbots[...]
AI Is The Best Present For Retailers This Holiday Shopping Season
Brands are undergoing massive digital transformations of their own in order to keep pace with the growing demands and expectations.[...]
Person taking a photo of a dish

AI in Images and Video: How can it benefit e-commerce?

AI in Images and Video: How can it benefit e-commerce?

With the growing popularity of image-based social media platforms like Instagram and Snapchat, there has been a significant rise in UGC (user-generated content) on the internet. Users upload photos not only of their lives but also of interactions with different products or brands they encounter online. Retailers and brands can leverage this information to engage and interact with users building brand awareness. However, with the increased use of UGC, it has become a challenge for them to track and categorize unstructured information. This challenge can be addressed using image recognition and computer vision.

Helping with Product Search

If a user while looking for a type of furniture is unable to use the right terms to describe the item in the search query, he/she could always depend on voice assistants such as Alexa, Siri or Google Home. However, the voice command is really just fulfilling a text query.

Instead, by taking a few pictures of the object and uploading it online using image search, the user can find what he/she is looking for. Using image-based AI, the search breaks down different elements of the image and enables the user to choose which aspects of the results are important.

couch in the living room

For instance, there is a beautiful couch in the living room but it is missing a coffee table. The user can take a picture of the couch and upload it as a search item. The image AI picks up on the couch and detects the elements such as color palette, wooden legs, etc. It then provides results of coffee tables that can match and complement these elements. Furthermore, based on its database, the AI can also recognize elements such as the brand, price range, etc. of the couch allowing the AI understand what type of budget the user may be willing to spend on furniture items. This goes beyond the simple search that people see today. 

Personalized experience on social media

Social media is empowered by AI, and brands and retailers can now detect and analyze every mention on the social media platforms using image recognition. They can also view how the brand is portrayed through the various images and videos shared on a daily basis. This further allows brands to interact with the users as well as collect and reshare their images helping the users to develop a personal connection with the brand.

Brands are also leveraging computer vision to provide a more targeted ad experience for users. For example, after browsing through an Instagram feed of a famous fashion celebrity, the user may get ads of fashion lookbooks featuring some of the pieces worn by that celebrity. These type of ads provide a subtle recognition for the user, which in turn helps brands build awareness and engagement.

AI in video content

For video content, brands and retailers can use AI to scan the video and index objects, scenes and audio sounds such as a dress from a popular brand or a painting from a famous artist or a song from a famous musician. Leveraging these elements, brands can then promote their products that can relate to these items such as bags that may match the dress in the video.

For video advertisements, brands can insert their products into a “placeholder” dynamically. Video producers can mark areas in their videos that can easily incorporate an inserted image and depending on the geography, language, and demographic segregation of the audience, AI can dynamically insert an ad into the video. This personalized approach enables a more local advertising experience for the users.


The e-commerce landscape is evolving with technological innovations changing the way people shop online. Images and videos are a largely untapped resource for retailers and brands to get insights from but with image recognition and computer vision gaining momentum, it is now possible. Giants like Amazon have also recognized its potential and have incorporated image-based search into their shopping experience. The applications for AI in images and videos are still limited but with deep learning, it is evolving and has the potential to change the shopping experience completely.

Other e-commerce articles:

AI is Redefining Experience in Customer Support Centres
Businesses need to understand the complexities of individual transactions and customer behavior over multiple touch points and channels, now more[...]
Speech Analytics vs Voice Analytics: What is the difference?
Speech Analytics vs Voice AnalyticsBusinesses today have access to more consumer data than ever before, especially through their customer support[...]
Conversational AI – The next Step in E-commerce Evolution
Conversational AI - The next Step in E-commerce EvolutionThere is no doubt that AI is a popular buzzword in the[...]
Conversational AI: Getting Started
Conversational AI: Getting StartedWith the increasing list of benefits and a growing demand for voice interfaces, the retail space is[...]
Voice-enabled chatbots vs Messenger bots: What you need to know
  There are two distinct ways in which a conversational interface works: text conversations and voice. Consumers interact with chatbots[...]
AI Is The Best Present For Retailers This Holiday Shopping Season
Brands are undergoing massive digital transformations of their own in order to keep pace with the growing demands and expectations.[...]
person using a tablet with a computer in the background

How AI helps to optimize e-commerce product content

How AI helps to optimize
e-commerce product content

With online sales growing faster and the e-commerce landscape changing with technological innovations, traditional retailers are increasingly investing in omnichannel strategies and doubling their efforts in order to meet consumer demands. An effective way to keep pace with e-commerce giants and stay relevant in the marketplace is to offer high-grade product discovery and selection. This requires providing detailed product content with product-specific attributes, along with semantic search.

The current product content problem

As more retail businesses are moving towards e-commerce, the need for quality information and powerful search platforms has become crucial in order to entice shoppers and help them make effective purchase decisions. However, this is a challenge as they are unable to easily deliver complete product content.

Retailers rely on the suppliers to provide all the coordinating images, videos, attributes, etc. for each of the products. Suppliers use various methods to provide content such as printed or digital catalogs or in different formats like Excel, PDF, etc., making it difficult for retailers to properly source and extract the right data required for the right product. In some cases, retailers even purchase content from third-party providers or online databases. However, the challenge here persists, as most of the time, content differs from suppliers to third-party providers and validation of the information becomes tedious.

Besides the price of a product, detailed product information along with superior quality-images, videos play an important role in a consumer’s buying decision. 

There are numerous technological challenges while extracting content from the product images - some including region segmentation, diverse product backgrounds, natural settings, typography and fonts, lighting conditions, and low-quality images. For instance, inconsistent product image sizes would limit the system to capture the product details completely from all the images.

Impact of poor quality data

Missing information and uncertainty are two leading factors for consumers to abandon their shopping journey. Consumers tend to leave their shopping journey when they sense that the product does not have clear or complete information. This could range from unclear product descriptions to missing or inaccurate product attributes such as size, materials used, ingredients, etc. or even product reviews.

While there is no definitive rule stating an optimal number of product images or videos or a recommended character limit for product information, the quality of product images and videos have a direct impact on the ability of the e-commerce business to generate sales. With complete and comprehensive product information (description along with attributes like size, or weight, etc.) and high-quality images and videos would enable shoppers with the information they may need to make a purchase decision.

Effective Extraction of Product Content

With IceCream Labs CatalogIQ, retailers can effectively address the problems they face while onboarding product content to their catalogs. Leveraging machine learning algorithms, Optical Character Recognition (OCR) systems, and Natural Language Processing (NLP) techniques, it can effectively extract the right information needed for the retailer to optimize their content as well as maintain their content health. Some of its capabilities include:

CatalogIQ extracting content from a product

Attribute Extraction: ​

Images would be clicked from all angles of the product and would be fed into the machine. Leveraging NLP techniques, brand attributes such as brand name, sub-brand, tagline, flavor, net weight/volume, and calorie information would be extracted.

Brand Name Detection (Logo detection): 

Leveraging OCR, the product image is scanned for text and the output is further sent to an NLP engine specifically to identify text logos (ex: for brand logos like Zara). If the text is not detected, image processing is further applied using the brand name parameters (ex: for brand logos like Nike)

Standard Certification Detection:

In this step, a preset database with standard food certification parameters is applied to detect and extract food certification labels such as “gluten-free”, “non-GMO”, “100% organic”. Here, the images are scanned using these parameters. This is similar to how the Brand Name detection functions.

nutritional label data extraction

Nutrition Facts Extraction:

Using OCR and region segmentation, nutritional facts text is extracted. This text is further corrected using a predefined vocabulary to streamline the content. A rule-based approach is then applied to the corrected text to extract nutritional values.

Product label images are a trusted source of product information for consumers. AI can ensure that the process would improve the quality of the information and maintain data consistency across all product pages. Retailers can further benefit from this as it would alleviate the burden of validating product data provided by various suppliers, online databases or third-party providers and can provide additional information that is critical for product discovery like brand or certification logo information.

The future of Product content

Applications leveraging AI and machine learning have projected tremendous potential for applying process automation to reduce data inconsistency and enhancing data quality and thereby, improving the product data extraction processes.


At IceCream Labs, we strive to address the challenges that businesses face in e-commerce using AI and machine learning. Are you ready to enhance your product content and take your e-commerce business to the next level? Reach out to us at sales@icecreamlabs.com for an AI-based solution for your business.


Related e-commerce articles - 

AI is Redefining Experience in Customer Support Centres
Businesses need to understand the complexities of individual transactions and customer behavior over multiple touch points and channels, now more[...]
Speech Analytics vs Voice Analytics: What is the difference?
Speech Analytics vs Voice AnalyticsBusinesses today have access to more consumer data than ever before, especially through their customer support[...]
Conversational AI – The next Step in E-commerce Evolution
Conversational AI - The next Step in E-commerce EvolutionThere is no doubt that AI is a popular buzzword in the[...]
Conversational AI: Getting Started
Conversational AI: Getting StartedWith the increasing list of benefits and a growing demand for voice interfaces, the retail space is[...]
Voice-enabled chatbots vs Messenger bots: What you need to know
  There are two distinct ways in which a conversational interface works: text conversations and voice. Consumers interact with chatbots[...]
AI Is The Best Present For Retailers This Holiday Shopping Season
Brands are undergoing massive digital transformations of their own in order to keep pace with the growing demands and expectations.[...]
woman taking photo food display

Online Shopping and Grocery – building consumer trust

Online Shopping and Grocery - building consumer trust

Online shopping has skyrocketed in the past few years. While it will continue to grow, majority of consumers still prefer to shop in-store - especially when it concerns grocery shopping. It’s no secret that the grocery industry has been the slowest major retail sector to join the e-commerce bandwagon.

As grocers are investing their resources to move their businesses online, there is competition among them to provide the best customer experience.

There have been a lot announcements made recently in this space. Retail giants like Walmart, announced the pilot of a new robotic back-end which would manage online orders in its super centers. Amazon added curbside grocery pickup for online orders as a Amazon Prime membership perk at Whole Foods. Whereas Target, rolled out same day delivery for groceries and other categories.

Consumers are concerned

While there is a lot of talk about omnichannel and online efforts, research suggests that people today still go to grocery stores.

According to a Gallup survey of 1,033 US adults, 84 percent said that they would never buy their groceries online. About 11 percent order groceries online for pickup or delivery twice in a month or lesser. While only 4 percent order once a week or more.

The survey highlights the fact that people still use the traditional means to purchase grocery. To ensure that the majority of the purchases are made online, it is imperative for the online retailers to provide an incentive to engage and help users purchase groceries online. The incentives could be in the form of timeline delivery of goods, competitive pricing, trusted & reliable products.    

The familiar feeling of a traditional store infrastructure cannot be replaced. Hence, the need of hour is to make the underlying technology for groceries feel human, comforting and intuitive.

lady buying apples at a store

Enabling technology for groceries 

By investing in technology and infrastructure, along with access to instant delivery channels, online grocers can build trust among consumers. 

Detailed product information 

Consumers have often been able to verify the quality of groceries such as fruits and vegetables with stores. When not physically present in the store, the consumer is unable to verify the quality of the products, thereby, increasing risk and uncertainty.

In an online platform, the product page must provide the right data of the particular product in terms of the images, the product description, the product specifications (size or weight/volume) along with the date it has been manufactured and the expiration date to be clearly mentioned.

This helps the consumer get the right information to make a decision. When consumers gain more knowledge about the product, and gain trust towards the platform, their uncertainty towards purchasing decreases. Furthermore, products that are from familiar brands also help reduce the perceived risk as the consumer already knows what to expect from a product that he/she is already familiar with.

Making reviews count

It is important to engage customers and community to rate the service of online retailers -   delivery of goods, the ease of ordering groceries through the platform, pricing, availability of groceries, etc.

Reviews are one way of building trust amongst existing users and new users alike to use the platform for their requirements. The more positive the reviews, the more users are likely to purchase through the online grocer.  

Instant Deliveries to instant gratification

Unlike appliances, groceries are mostly perishables and need to be consumed as early as possible. Sometimes, the need for groceries is almost instantaneous and requires delivery at the earliest. One way to make it readily available is strengthening the supply chain and the underlying technology to ensure instant delivery. 

Conclusion

While consumers today still prefer the traditional method of buying groceries, technology is fast catching up to cater to the needs and convenience of the consumer. There is tremendous scope for innovation and increase in grocery technology that can solve the problems for the retailers who want to move online and provide value to consumers. 


Related e-commerce articles

Transforming the Retail Customer Experience with In-store Analytics
Online retailers have the advantage of tracking cookies and web analytics tools to calibrate different aspects of an online shopping[...]
AI is Redefining Experience in Customer Support Centres
Businesses need to understand the complexities of individual transactions and customer behavior over multiple touch points and channels, now more[...]
Speech Analytics vs Voice Analytics: What is the difference?
Speech Analytics vs Voice AnalyticsBusinesses today have access to more consumer data than ever before, especially through their customer support[...]
Conversational AI – The next Step in E-commerce Evolution
Conversational AI - The next Step in E-commerce EvolutionThere is no doubt that AI is a popular buzzword in the[...]
Conversational AI: Getting Started
Conversational AI: Getting StartedWith the increasing list of benefits and a growing demand for voice interfaces, the retail space is[...]
Voice-enabled chatbots vs Messenger bots: What you need to know
  There are two distinct ways in which a conversational interface works: text conversations and voice. Consumers interact with chatbots[...]
Shop.Org event

IceCream Labs demonstrates Intelligent Data Mesh at Shop.Org

IceCream Labs demonstrates Intelligent Data Mesh at Shop.Org

Las Vegas - Shop.Org, the leading retail event hosted by the National Retail Federation (NRF) that has been bringing together top retailers across the country, was hosted last Thursday and Friday at  The Venetian in Vegas and brought in yet another excellent cohort of attending companies such as Walmart, Amazon, Best Buy, Target etc. The show’s headliner Serena Williams was on stage on Friday, discussing the challenge of being an entrepreneur, a new mom, and a world class athlete, all at the same time. She launched her new fashion line, in collaboration with Nike and HSN, in May.
IceCream Labs, being at the forefront of the retail AI space, was invited to host a booth in their Innovation Lab sector.

The NRF Innovation Lab consisted of 4 segments of the shopping experience, namely - Awareness, Consideration, Engagement, and Logistics & Loyalty. Each of the companies in these segments is focused on creating applications to improve the retail space with the help of  Facial Recognition, Data Analytics, Robotics and Augmented Reality. IceCream Labs was a part of the Awareness segment which showcased products that helped brands retailers entice new customers.

As part of our showcase, we released Intelligent Data Mesh (IDM) which is an AI-based platform that leverages machine learning for unparalleled eCommerce / digital merchandising for brands & retailers. The IDM enables retailers, brands, and suppliers to maximize the potential of digital commerce by bringing in the great experiences in traditional retail, resulting in immediate impacts to revenues and operations. By leveraging the vast amount of product and social data online, using machine learning, merchandising managers & e-commerce managers can now create experiences of dynamic discovery and visual merchandising online.

This release, we are proud to say, won the Innovation Award in the Awareness segment. The judges' panel including some big name VCs and top executives in the retail sector (Full list: https://shop.org/nrf-innovation-awards-exhibitors)

As a result of this award, we are going to be featured at the NRF Big Show in NYC in January 2019, and our CEO, Madhu Konety, will be a keynote speaker.

Read our blog for all things AI in ecommerce

AI is Redefining Experience in Customer Support Centres
Businesses need to understand the complexities of individual transactions and customer behavior over multiple touch points and channels, now more[...]
Speech Analytics vs Voice Analytics: What is the difference?
Speech Analytics vs Voice AnalyticsBusinesses today have access to more consumer data than ever before, especially through their customer support[...]
Conversational AI – The next Step in E-commerce Evolution
Conversational AI - The next Step in E-commerce EvolutionThere is no doubt that AI is a popular buzzword in the[...]
Conversational AI: Getting Started
Conversational AI: Getting StartedWith the increasing list of benefits and a growing demand for voice interfaces, the retail space is[...]
Voice-enabled chatbots vs Messenger bots: What you need to know
  There are two distinct ways in which a conversational interface works: text conversations and voice. Consumers interact with chatbots[...]
AI Is The Best Present For Retailers This Holiday Shopping Season
Brands are undergoing massive digital transformations of their own in order to keep pace with the growing demands and expectations.[...]