fbpx

Tag Archives for " Retail "

woman buying groceries from a stall

Revolutionizing grocery retail with artificial intelligence

Revolutionizing grocery retail with artificial intelligence

While there is a lot of chatter around artificial intelligence and the potential it has to transform retail, it has the capability to impact the most fundamental shopping experiences: the grocery store. Most retailers are moving towards building a better grocery store experience, with the rise of subscription meal kits and competition from pure-play grocery delivery services. With the abundance of customer data and product information available, grocers today are in a special position to apply machine learning and AI in other areas of the business as well.

The grocery industry has a heavy reliance on the movement of perishable goods and with supermarkets struggling to plan, promote and sell goods in a short period of time, it is not efficient. Furthermore, there is a lot of food wastage that happens in this industry - while some of that waste happens in consumers’ homes, a good amount is also lost in the supply chain - anywhere between the farm and the store shelf. And with the various options for when, where and how to buy groceries, grocers compete on prices that are most likely to be profitable.

While grocers are faced with these challenges, they have a fairly good idea of their customer base, who they are and what they want to buy at what price point. With the data available, there is a lot of opportunities utilizing the data in the right manner. This is where AI comes in. Using machine learning capabilities and analytics, more grocers are leaning towards adopting this technology to strengthen the relationship with customers, as well as address some of the biggest challenges they are faced with today.

Leveraging the abundance of customer data

The grocery industry was one of the first industries to collect shopper buying data through programs such as loyalty programs and in-store promotional offers. These methods helped grocers gather information about their key shopper demographic as well as brand preferences. This information is already leveraged to provide discounts and special promotions, the new technology can help enhance the relationship between the grocer and shopper even further.

AI helps grocers to provide a deeper understanding of context and intent by answering the questions behind customers' shopping decisions. It also enables the grocers to parse the customer data and automate the ability to offer targeted promotions to each customer.

Enhanced inventory management

AI can change the entire way of managing inventory. AI can help stock shelves with the right mix of products and ensure that the supply chain is aligned to avoid out of stock products using point-of-sale information and inventory visibility.

Machine learning can build on grocers' rich customer data and combine that with contextual data such as weather, climate, holidays and events - providing a more accurate forecast compared to traditional methods.

Reducing waste

With better inventory management and data analytics, AI can provide better visibility on produce and perishables. Automation can help stores dynamically re-adjust orders based on demand or automate product promotions for the items that are not performing well or selling fast, and helping stores to protect margins, and reducing the amount of food that goes into landfills.

As AI and machine learning advances, grocers should begin to position their systems for a seamless transition towards a highly automated future.


AI must integrate into the commerce platforms and connect across systems to maximize its effectiveness throughout the business. While AI is a valuable tool for customer service, the impact of it will come through its ability to reward loyalty, understand consumer behavior, ensure reduced wastage and increase revenue for the retailers.

Related e-commerce articles:

Simplifying the Data Consolidation Process with Machine Learning
What you will learn: This article discusses the application of AI and machine learning to help simplify the data aggregation[...]
Enhancing the customer experience beyond shopping
Enhancing the customer experience beyond shopping With consumers changing how they purchase and engage with a brand, retailers have leveraged[...]
Importance of AI in customer loyalty
The expectations of consumers today from their favourite brands has increased ten-fold, and with big companies such as Amazon providing[...]
What is GS1 Verified? – Everything you need to know
​Live from the GS1 Connect 2019 EventWith the GS1 Connect 2019 event happening this week in Denver, Colorado, we think[...]
DataPorts and Why they Matter
​Retailers today struggle with managing all of the product content necessary to publish and maintain their online product catalog. Assembling[...]
3 ways Grocery retailers can survive in the age of Amazon
3 ways retailers can survive in the age of AmazonRetail giants like Amazon’s ability to effectively address the ever-changing customer[...]

The growing importance of customer loyalty programs in grocery retail

The growing importance of loyalty programs in grocery retail

Grocery loyalty programs have been around for years, but with the changing landscape as well as customer shopping behavior, it is now more important than ever. The goal for loyalty programs is to be relevant and timely to shoppers and their preferences and to create a continuous dialogue between the customer and the brand or retailer.

The benefit retailers get utilizing loyalty programs is the access to customer data, shopping patterns and behavior with direct engagement with the shopper, elevating the communication and optimizing the offers to meet their needs. This ultimately leads to help drive sales for the retailers.

The current scenario

Customer loyalty programs build large customer databases and retailers can leverage this information to create more personalized and targeted promotions tailor-made for every customer. A successful loyalty program is a well-crafted blend of rewards and recognition features that change shopper behaviors. However, grocery loyalty programs are challenged not only by the economics of the industry but also the limited opportunities to differentiate the customer experiences for each customer.

However, compared to other industries, the grocery retail industry today still does not have a completely organized, leveraged and utilized customer data to deliver the optimum level of personalization and relevance to the customer, unlike in industries such as travel or banking.

Limited impact on shoppers

The grocery retail industry operates at small margins, which limit the rewards grocers can offer to the program members. Furthermore, compared to other retail loyalty programs, grocers depend on subsidizing their programs with discounts provided by the CPG manufacturers they are partnered with. Most loyalty programs have followed suit and use the same strategy, enabling shoppers to spread their loyalty across different brands.

Digital coupons - a primary feature of most grocery loyalty programs are offered by most of the retailers in an equal capacity. Another perk is the member pricing feature is an attractive way to entice shoppers into joining the program, but this feature too is replicated across all of the programs, limiting the impact these programs can create.

One feature of the grocery program that does create an opportunity cost and loyalty is reward points. Some shoppers even consolidate their shopping to a single brand in order to maximize the points earned and get a chance to get more discounts with every purchase. While most grocery programs prefer CPG subsidies, retailers should not limit the programs only to create more loyal customers. With e-commerce retail giants like Walmart and Amazon leaving no stones unturned to engage with shoppers, grocers need to double up on creating successful customer loyalty.

Looking ahead


Grocery retailers are facing several options today, they must decide among differing formats, both online and in-store, and seek the best combination of program features available to them.

A growing demographic - Millennials, in particular, seek immediate gratification, support, rewards, and recognition. Moreover, they do not invest a lot of time while planning grocery lists as they center their grocery visits around recipes more than replenishing a set stock. They are also far less price-sensitive in their menu planning as compared to previous generations. Additionally, as shoppers are increasingly opting for healthier lifestyles, produce as well as non-processed foods have become important aspects for grocers to drive retention and loyalty.

With the rising popularity of Walmart and Amazon among shoppers, grocers must foresee the future from both physical stores as well as digital capabilities. A well-managed loyalty program uses analytics and insights to enhance customer experience and elevate shopper journeys. Another major trend is the development of artificial intelligence. Leveraging AI, grocers can use unused retailer data and create additional value from it and tailor more relevant communication and improved personalized pricing and promotions.

Related e-commerce articles:

Enhancing the customer experience beyond shopping
Enhancing the customer experience beyond shopping With consumers changing how they purchase and engage with a brand, retailers have leveraged[...]
Importance of AI in customer loyalty
The expectations of consumers today from their favourite brands has increased ten-fold, and with big companies such as Amazon providing[...]
What is GS1 Verified? – Everything you need to know
​Live from the GS1 Connect 2019 EventWith the GS1 Connect 2019 event happening this week in Denver, Colorado, we think[...]
DataPorts and Why they Matter
​Retailers today struggle with managing all of the product content necessary to publish and maintain their online product catalog. Assembling[...]
3 ways Grocery retailers can survive in the age of Amazon
3 ways retailers can survive in the age of AmazonRetail giants like Amazon’s ability to effectively address the ever-changing customer[...]
The Impact of AI on Grocery Retail
The Impact of AI on Grocery RetailIn today’s age, grocery retailers no longer have to make guesses about what customers[...]
people shopping at a supermarket

An Evolving AI retail experience: Transforming the way consumers shop

An Evolving AI retail experience: Transforming the way consumers shop

The retail experience of a shopper is the latest area that AI and machine learning are causing disruption. Most retailers recognizing the potential of these technologies have started aligning them into their business goals. Two crucial aspects - data and computing power have changed in the past few years in the space of AI, which has opened up new opportunities for retailers today.

Computing power is easy to see, with the advent and rise of smartphones which have phenomenal computing power when compared to the bulky phones and computers used decades ago. Businesses today have unlimited computing access to train their AI algorithms. Furthermore, the data available today is extremely rich and scalable. AI systems that leverage learning techniques such as Machine learning thrive on large, rich data sets. When fed appropriately, these systems discover patterns and correlations that would be otherwise difficult with a human intervention. These machine learning approaches automate data analysis, enabling users to create models that can then be used to make useful predictions about other similar data.

Retail is a perfect fit for AI, here’s why -

The speed at which AI can be deployed depends on specific critical factors. The first is the ability to test and measure. Retail giants can effectively deploy AI and test and measure consumer response. They can also leverage AI to measure the effect on their entire supply chain.

There is some innovative and interesting robot technology taking place in retail such as Grocery giant partnering with Nuro.AI to deliver groceries to the customers’ doorsteps. But most significant changes will come from the deployment of AI rather than the use of physical robots or autonomous vehicles.

Here are 3 AI-based scenarios that will transform the retail experience -

Shopping habits

AI can detect underlying patterns in the shopping behavior of shoppers from the products that they buy and the method used to buy them. This could be a simple weekly purchase of groceries from the supermarket, the sporadic purchases of wine from the liquor store or the complex midnight icecream cravings from the local convenience store.

At a larger scale, analysis of the behavior of millions of consumers would enable supermarkets to predict the number of households that cook pasta every week. This would then inform the inventory management systems, and automatically optimize the stock of pasta. This information can also be shared with the suppliers, enabling more efficient inventory management and organized logistics.

Pricing dynamics

The pricing challenge for supermarkets involves applying the right price and the right promotion to the right product. Retail pricing optimization requires data analysis at a granular level for each customer, product and transaction. To be effective, many factors need to be considered such as the impact of sales due to the changing price over time, seasonality, weather and competitors’ promotions.

A well-defined machine learning program can factor in all variations, including details such as purchase histories and product preferences to develop deep insights and pricing tailored to maximize revenue and ultimately, profit.

Customer feedback

In the past, customer feedback was collected through forms and feedback cards that were filled out and placed in a suggestions box. The feedback had to be manually read and acted upon appropriately. With the rise of social media, the platforms were leveraged to express feedback publicly. Retailers subsequently engaged in social media scraping software to respond, resolve and engage with customers.

With the growing innovations, machine learning will play a larger role in this space. Machine learning and AI systems will be able to analyze unstructured data from multiple sources such as verbal comments or video content.  

The evolving retail experience

As a shopper moves through various stages in life, the circumstances and spending habits change. AI and machine learning models will adjust and be able to predict the needs of the consumer before the consumer even searches for a product.

This shift to predictive marketing would change the way shoppers purchase products, bringing in suggestions and recommendations that they would not have even considered. The possibilities would widen, all because of AI - for both consumers and retailers alike.

Related e-commerce articles:

Enhancing the customer experience beyond shopping
Enhancing the customer experience beyond shopping With consumers changing how they purchase and engage with a brand, retailers have leveraged[...]
Importance of AI in customer loyalty
The expectations of consumers today from their favourite brands has increased ten-fold, and with big companies such as Amazon providing[...]
What is GS1 Verified? – Everything you need to know
​Live from the GS1 Connect 2019 EventWith the GS1 Connect 2019 event happening this week in Denver, Colorado, we think[...]
DataPorts and Why they Matter
​Retailers today struggle with managing all of the product content necessary to publish and maintain their online product catalog. Assembling[...]
3 ways Grocery retailers can survive in the age of Amazon
3 ways retailers can survive in the age of AmazonRetail giants like Amazon’s ability to effectively address the ever-changing customer[...]
The Impact of AI on Grocery Retail
The Impact of AI on Grocery RetailIn today’s age, grocery retailers no longer have to make guesses about what customers[...]
grocery shopping for millennial shoppers

Millennial shoppers: How are they impacting grocery retail?

Millennial shoppers: How are they impacting the grocery retail landscape?

Millennial purchasing behavior greatly impacts the current retail landscape, and retailers, having realized this, are making Millennials their prime focus. Millennial shoppers are distinctly different from older generations as they are more racially diverse, more educated, and technologically-abled. Most of this demographic group are passing through the initial phase of their respective careers and are single or are starting their own families. Their grocery shopping habits are likely to change with time, but current differences from older generations could have implications for future food demand.

Millennials are price-sensitive but place preference for personalized offerings. However, they are ready to shell out money if the quality of the products is worth the amount. Furthermore, millennials are also fast in acclimatizing themselves to new technologies and are embracing newer grocery options such as online ordering/delivery and meal kits while navigating in-store and digital channels. They are demanding healthier and fresher food, including fruits and vegetables for at home preparations, but place a higher preference for convenience as compared to other generations.

Millennials Purchase More Prepared Foods

Millennial shoppers generally purchase a larger share of prepared foods such as pasta, sugar, and candies than the other generations. Prepared foods such as foods that are ready to heat and eat or just ready to eat such as canned soup, frozen pizza, sandwiches, pasta, salads, and rotisserie chicken. They also devote a part of their share of at home food preparation expenditures to grains, poultry, and red meat. The prepared foods require minimal preparation while grains and meats require cooking.

In comparison to GenX households, Millennials spend the least amount of money on food that requires at-home preparation. However, as income rises, there is a small positive effect on per capita at-home prepared food expenditure. While each preceding, older generation spends more on at-home food preparation than the younger generations and there is a larger gap between the Baby Boomers and Generation X.

Income governs food budgets

Income plays an important role for millennial shoppers. As income rises, expenditure shares for vegetables, fruits, red meats, and sugar increase while shares for poultry decreases as incomes rise. Millennial households generally allocate the lowest amount of their at-home food budgets to red meat and poultry. On average, expenditure for red meats decreases with the younger generation.

This health-conscious and nutritionally-aware generation is extremely mindful of what food they consume and the analysis of at-home grocery expenditure is important. The food purchasing behavior of Millennials not only determines their own dietary quality but also of their offsprings and the future generations. Grocery store shopping behaviors, however, are not permanent and may shift with time and millennial shoppers may find themselves in a position to swap frozen foods to a home-cooked meal in the near future.

Many studies have been focused on looking at how the largest living generation impacts food choices and selections in the grocery aisles. While they are aiming for healthier, fresher foods, they are also looking for more convenience. Trend lines and analysis are important to help fix the right building blocks and retailers to develop strategies and policies addressing the food industry issues.

Related e-commerce articles:

millennials sitting on the stairs with a laptop

Millennials: Capturing the largest spending demographic

Millennials: Capturing the largest spending demographic

Being the largest shopper segment, Millennials are currently a prime focus for all the retail businesses. This technology-driven and multichannel-hopping age group are on the threshold of creating pivotal disruptions in all segments. It is extremely critical for retailers to adapt their strategies to meet Millennials' needs. However, in order to do so, retailers must have a deep understanding of every millennial to get a better insight into them as shoppers.

Millennials today give utmost importance to experience over a material item. They seek a destination that allows them to make an outing of an otherwise boring and mundane task.  For instance, instead of going to a typical grocery store, they want a place that can not only provide fresh produce but also trials of different types of salsa or cheese. Wandering the aisles with a snack or a beverage in hand not only increases the time spent in the store but encourages them to add a few extra items in the shopping cart. So retailers must make an effort to transform their stores into the experience.

Personalization is key

Compared to the previous generations, millennial shoppers are far more comfortable sharing their data in order to receive personalized content that would be relevant to their individual needs. This makes it easier for retailers to tailor make product offers and run promotions increasing the likelihood of them making a purchase.
Furthermore, the retailer can also leverage omnichannel marketing to promote ads on social media to redirect the shoppers onto their platforms. 

Curated product offerings 

Retailers must also create curated product offerings that resonate with the needs of the millennial shoppers. Digitally-active millennials communicate, shop and do their tasks online, which creates a volume of valuable data that can be used by the retailers. This becomes increasingly important for brick-and-mortar retailers that compete with e-commerce giants such as Amazon who have endless online 'aisles' for users to shop right from their own homes.
These brick-and-mortar retailers need to leverage the data available and optimize their product offerings to boost store traffic and sales. 

Pricing the right way matters

While making a purchase, price is a key factor, but it is different from that of the previous generations. For example, Millennials are ready to splurge for luxury items such as organic fruits or vegetables or anti-aging creams but maintain a strict budget for other necessities like toothpaste or toothbrushes. If a retailer can leverage this information and price their products accordingly, the possibility of them purchasing products increase.
The best way for retailers to determine the pricing process includes analyzing which products Millennial shoppers are most likely to spend on heavily and which ones that they would not. Using past purchasing trends, retailers can collect the data needed to create a profitable pricing strategy.


Millennials have surpassed the previous generations with the most disposable income. Retailers need to focus on the three most important aspects - their product offerings, pricing and personalization based on a data-driven approach to create a Millennial-centric shopping experience. This would further help them to increase sales as well as loyal, avid shoppers.

Related e-commerce articles:

Enhancing the customer experience beyond shopping
Enhancing the customer experience beyond shopping With consumers changing how they purchase and engage with a brand, retailers have leveraged[...]
Importance of AI in customer loyalty
The expectations of consumers today from their favourite brands has increased ten-fold, and with big companies such as Amazon providing[...]
What is GS1 Verified? – Everything you need to know
​Live from the GS1 Connect 2019 EventWith the GS1 Connect 2019 event happening this week in Denver, Colorado, we think[...]
DataPorts and Why they Matter
​Retailers today struggle with managing all of the product content necessary to publish and maintain their online product catalog. Assembling[...]
3 ways Grocery retailers can survive in the age of Amazon
3 ways retailers can survive in the age of AmazonRetail giants like Amazon’s ability to effectively address the ever-changing customer[...]
The Impact of AI on Grocery Retail
The Impact of AI on Grocery RetailIn today’s age, grocery retailers no longer have to make guesses about what customers[...]
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-

Enhancing the customer experience beyond shopping
Enhancing the customer experience beyond shopping With consumers changing how they purchase and engage with a brand, retailers have leveraged[...]
Importance of AI in customer loyalty
The expectations of consumers today from their favourite brands has increased ten-fold, and with big companies such as Amazon providing[...]
What is GS1 Verified? – Everything you need to know
​Live from the GS1 Connect 2019 EventWith the GS1 Connect 2019 event happening this week in Denver, Colorado, we think[...]
DataPorts and Why they Matter
​Retailers today struggle with managing all of the product content necessary to publish and maintain their online product catalog. Assembling[...]
3 ways Grocery retailers can survive in the age of Amazon
3 ways retailers can survive in the age of AmazonRetail giants like Amazon’s ability to effectively address the ever-changing customer[...]
The Impact of AI on Grocery Retail
The Impact of AI on Grocery RetailIn today’s age, grocery retailers no longer have to make guesses about what customers[...]
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:

Enhancing the customer experience beyond shopping
Enhancing the customer experience beyond shopping With consumers changing how they purchase and engage with a brand, retailers have leveraged[...]
Importance of AI in customer loyalty
The expectations of consumers today from their favourite brands has increased ten-fold, and with big companies such as Amazon providing[...]
What is GS1 Verified? – Everything you need to know
​Live from the GS1 Connect 2019 EventWith the GS1 Connect 2019 event happening this week in Denver, Colorado, we think[...]
DataPorts and Why they Matter
​Retailers today struggle with managing all of the product content necessary to publish and maintain their online product catalog. Assembling[...]
3 ways Grocery retailers can survive in the age of Amazon
3 ways retailers can survive in the age of AmazonRetail giants like Amazon’s ability to effectively address the ever-changing customer[...]
The Impact of AI on Grocery Retail
The Impact of AI on Grocery RetailIn today’s age, grocery retailers no longer have to make guesses about what customers[...]
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 - 

Enhancing the customer experience beyond shopping
Enhancing the customer experience beyond shopping With consumers changing how they purchase and engage with a brand, retailers have leveraged[...]
Importance of AI in customer loyalty
The expectations of consumers today from their favourite brands has increased ten-fold, and with big companies such as Amazon providing[...]
What is GS1 Verified? – Everything you need to know
​Live from the GS1 Connect 2019 EventWith the GS1 Connect 2019 event happening this week in Denver, Colorado, we think[...]
DataPorts and Why they Matter
​Retailers today struggle with managing all of the product content necessary to publish and maintain their online product catalog. Assembling[...]
3 ways Grocery retailers can survive in the age of Amazon
3 ways retailers can survive in the age of AmazonRetail giants like Amazon’s ability to effectively address the ever-changing customer[...]
The Impact of AI on Grocery Retail
The Impact of AI on Grocery RetailIn today’s age, grocery retailers no longer have to make guesses about what customers[...]
man using phone with voice commands

Voice is changing the way consumers are shopping online

Voice is changing the way consumers are shopping online

It seems like, these days, you see an Amazon Alexa or a  Google Home everywhere. It’s not uncommon to see a person shout across the room to their voice device trying to turn the television on.

Amazon and Google have sold over 27 million voice command devices in the United States alone, and Apple’s Siri is available to more than 500 million users across the world. 

With the increased adoption of voice assistants, consumers are depending on them to do simple tasks like telling time, setting alarms or even making calls, so that they can focus their attention on some other tasks. However, it’s not just those simple tasks anymore, voice assistants are being increasingly used for online shopping, with users giving voice commands to the assistant about what products to purchase. Consumers are able to multitask without having to manually search different e-commerce portals and selecting products through each of their product categories, thereby, saving a lot of time.

Retailers, recognizing this trend, are slowly incorporating voice to further enhance the user experience. Incorporating voice in the shopping experience not only ups the convenience level of a shopper but also saves time lost in typing and searching for products. 21% of all Alexa and Home users have stated that they are shopping via their device today. Leveraging AI, voice recognizes language patterns such as dialects, intonations, and accents enabling them to converse with the user in a natural, conversational manner. The potential of turning the shopping world upside down is very high and the most immediate impact will be in the following areas:

Better searchability

SEO becomes beneficial for any retailer as it drives maximum traffic for e-commerce. However, there is a lot of difference between typing in search terms and using voice. Technology needs to evolve to differentiate voice commands from typewritten keywords. This will help to institute searchability and compatibility towards voice commands. Understanding the context is important as Voice is conversational. For example, auto-fill options must be provided for sentences or questions to understand the user intent.

With consumers increasingly moving towards voice search, e-commerce businesses must align their website and product pages to account for voice.

amazon echo dot

Ease of providing product reviews

The increase in voice searches eliminates having to browse through different categories and multiple pages. Furthermore, this has raised the importance of online reviews for products and services. The feedback loop between the retailer and the customer becomes more efficient and seamless.

For instance, imagine a customer ordered a pair of Nike Running shoes but never got around to filling out the review. The voice assistant would then ask questions like: “How would you rate your Nike Running shoes from one to five stars? Did it fit as you expected?” By answering these quick questions, the shopping experience can become increasingly personalized, providing better recommendations for the customer.

Online reviews will become increasingly important with almost 85% of voice-based customers trusting the recommendations provided by their assistants. These recommendations, in turn, are based on the top-reviewed products of that query making providing reviews more important than ever for retailers.

Shipment Tracking made easy

In the future, voice commands may not only be restricted to ordering products or proving reviews for them. Users may even get quick updates about their orders and their shipping status. There is a need for these complex processes to become more intuitive especially when consumers expect prompt responses. The retailer can enhance the shopping experience by connecting shipping operations with the voice app enabling users to get quick updates about their shipping status.

flat lay photography of coral Google Home Mini on black surface beside Apple AirPods

Although voice search and shopping is the next big thing, there are a number of challenges that are left unaddressed. The technology, in its current state, is yet to be equipped to handle complicated queries such as comparing different products. Many users still don't believe that the assistants can pick a product without choice, based on their query.

The consumer behavior is changing and as the popularity of using voice search grows, retailers must make decisions and act fast to cope with the change.

Related e-commerce articles

Enhancing the customer experience beyond shopping
Enhancing the customer experience beyond shopping With consumers changing how they purchase and engage with a brand, retailers have leveraged[...]
Importance of AI in customer loyalty
The expectations of consumers today from their favourite brands has increased ten-fold, and with big companies such as Amazon providing[...]
What is GS1 Verified? – Everything you need to know
​Live from the GS1 Connect 2019 EventWith the GS1 Connect 2019 event happening this week in Denver, Colorado, we think[...]
DataPorts and Why they Matter
​Retailers today struggle with managing all of the product content necessary to publish and maintain their online product catalog. Assembling[...]
3 ways Grocery retailers can survive in the age of Amazon
3 ways retailers can survive in the age of AmazonRetail giants like Amazon’s ability to effectively address the ever-changing customer[...]
The Impact of AI on Grocery Retail
The Impact of AI on Grocery RetailIn today’s age, grocery retailers no longer have to make guesses about what customers[...]
scattered photos of coffee

Types of product imagery that drive eCommerce sales

Types of product imagery that drive e-commerce sale

Touching and feeling a product has always been the sign of a savvy shopper. The softness of a fabric, the firmness of a fruit has been the cornerstone of the tactile experience of shopping and we have traditionally held in esteem, the men and women who are skilled at establishing quality just by their sense of touch. This age-old process, however, is eliminated in the increasingly digital world and Retailers are scrambling to innovate so as to provide the customers an experience that engages their other senses.

This is where good product content comes into play - a detailed product description paints an image which allows the customer to get to know what the product is, what it can do and what it potentially feels like. Labels, ingredients, and materials used to expand the connection we have with the product or similar products and the customer is given as many tools as possible to create the sensations needed to make that purchase.

And finally, product images connect the textual dots to let the customer see what the product would look like and give context to how the product appears visually.

Product imagery plays a pivotal role

Uncertainty and missing information are two of the top reasons why people decide not to buy a product online. Customers tend to leave their shopping journey when they feel the product doesn't have enough or clear information. This could range from product reviews and the materials used to the size specifications. However, product imagery takes the cake in being the primary driver of sales. Studies have shown, 92% of consumers are driven to a purchasing decision based on product imagery, may it be images or videos.

Therefore naturally, the quality of product images directly affects the ability to generate sales making it crucial for brands and retailers to use high-quality images and HD videos while showcasing their products.

So what exactly do shoppers want from a brand or retailer's product imagery?

Product angles

Customers generally like to view a  product from every angle. A study conducted by the Nielsen Norman Group found that consumers were better informed after viewing clear, high-quality product images. This helps them “see” and extrapolate on what the features could be.
The quantity of images also plays an important role. 

For example, for a floral dress, the imagery should reflect the color palette, the draping, and how it would look like from the front, sides and the back. This would bring the user’s attention to small features such as a button or a sleeve detailing.

Walmart - product page for floral dress with different product images

In the case of electronics, besides the ability to view the product from every angle, the images can also show the buttons or outlet sockets. This would come in handy for the user as he may not need to refer to the manual every single time, looking for a function.

Size matters 

If customers need a magnifying glass to view product images, there is something wrong. The imagery should be able to show enough details that the customers don't need to go to a store and look at the actual product in person. If the imagery shows the detailing from afar as well as when zoomed in, it would imitate feeling the texture of the product. Furthermore, the size of the image in the product catalog also plays a large role in piquing the interest of a shopper.

The VWO blog reported an A/B test comparing catalogs with smaller vs larger images. The results showed that larger product images led to a 9.46 percent in sales in comparison to smaller product images.

So when it comes to product imagery, size does matter.

Presentation

The battle does not end with putting up images of the product. How it is being shown also affects the shopper’s buying decision.

While some shoppers prefer to see the product image against a plain background, there are some that want to see the products used contextually. There is another set of shoppers who would like to see user-generated images from people who have purchased the product in the past.

When providing product images for millennial shoppers, in addition to quality sized images, social media tends plays a pivotal role. Millennials get attracted to products that are socially endorsed. This also gives shoppers an impetus to share their purchases online.

While shoppers have always valued brand shopping experiences above all, the rise of innovations integrating online and in-store is intriguing. VR technology and AI integration help shoppers get a better understanding of how to use the products. Shoppers also depend on VR to help product images or product labels come to life.

Piled up Polaroid photos


The fact that consumers want quality product imagery is not something new, but it is valuable to know what kind of imagery the target customers are looking for. This ensures that retailers and brands create product content that meets the needs of the customers inadvertently driving sales and an increase in customer base.

Other e-commerce articles:

Enhancing the customer experience beyond shopping
Enhancing the customer experience beyond shopping With consumers changing how they purchase and engage with a brand, retailers have leveraged[...]
Importance of AI in customer loyalty
The expectations of consumers today from their favourite brands has increased ten-fold, and with big companies such as Amazon providing[...]
What is GS1 Verified? – Everything you need to know
​Live from the GS1 Connect 2019 EventWith the GS1 Connect 2019 event happening this week in Denver, Colorado, we think[...]
DataPorts and Why they Matter
​Retailers today struggle with managing all of the product content necessary to publish and maintain their online product catalog. Assembling[...]
3 ways Grocery retailers can survive in the age of Amazon
3 ways retailers can survive in the age of AmazonRetail giants like Amazon’s ability to effectively address the ever-changing customer[...]
The Impact of AI on Grocery Retail
The Impact of AI on Grocery RetailIn today’s age, grocery retailers no longer have to make guesses about what customers[...]