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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

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E-commerce is moving towards social commerce – How to get it right

E-commerce is moving towards social commerce - How to get it right?

Social commerce is often described as the intersection between social media and e-commerce. While this holds value, there is a lot of traffic with no direction. There’s no doubt that social selling is a powerful and an increasingly influential sales tool.

According to recent BI Intelligence, the top 500 retailers earned an estimated $6.5 billion from social shopping in 2017, up 24% from 2016.

There are various forms that social commerce adorns, from group buying to social shopping; from mobile apps to retailers adding social features, or shopping integrated into social media. All of these forms have one thing in common - the use of social technology to replicate age-old buying models in the digital sphere.

Whether it is girls going shopping together in a store or asking a friend for advice on power tools, moving them to online would result in them having a social commerce experience. Taking another instance of bartering, here, instead of the traditional method of trading goods or services, shoppers are trading personal data such as buying habits and preferences for access to easy shopping portals.

There are social platforms like Pinterest, Snapchat and Instagram which have incorporated a “Buy now” button that can turn a static image into a product with a click. However, since the story came about how social platforms are using and monetizing user data, there was a certain amount of wariness among the users about sharing their data on these networks.

The key here is to find a model of social commerce that would work the world over. Some of the things to keep in mind -

  • Provide the shoppers the ability to earn credit for sharing their own data and of their social network.
  • Enable retailers to own the relationship with their customers while also providing access to insights and goodwill from happy customers. 
  • Provide every individual the ability to turn into an influencer. 
  • Star
    Using the existing social media networks as a channel to interact with the brand itself.
person using laptop that is showing a webpage of images

How to make it work

Say a user wants to purchase a mobile phone. The ideal route would be to go the website of the retailer of their choice (assuming if the retailer provides a social commerce experience). They can then choose the selection of the models of their favorite mobile phones.

They now post a picture of the phones on their social networks and ask friends to vote on which phone they think the user should buy.

By setting up this vote, the user can then earn shop credits. Their friends who voted for the products can also earn shop credits by that action. In this scenario, there is no prerequisite of having a large social media presence to be valuable for the business. This action inadvertently turns the user into a micro-influencer.

The information gathered during the voting helps the retailer sell more effectively. They learn which of the products is most appealing and have the potential to become hot sellers, and then accordingly manage stock or change how they display their products. They also gain access to an expanded audience. This eventually, helps them to build a relationship with their customers which can help them build brand loyalty.

Summary

Social channels have a major role to play. Besides influencing purchase decisions, social media is a larger part of the product discovery and research phase in the shopping journey.

The next few years will see social commerce expand its influence if it efficiently benefits the consumers and businesses. The world of commerce is on the verge of disruption, thanks to technological innovations, data collection, and social media. If social commerce is achieved correctly, the future of retailers and shoppers will widen.

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The Importance of m-commerce in e-commerce

The Importance of m-commerce in e-commerce

We have witnessed the advent of e-commerce and how it quickly became a part of all our lives. With over half of American consumers now doing most of their shopping online (51%), businesses find it crucial to have a web and mobile presence.

Approx. 1.2 billion people are in habit of using their smartphones to access the internet daily. Trinity Digital Marketing publication reports that in the US, nearly half of the population uses smartphones to connect to the internet

Mobile apps are the primary driver of digital media consumption, proving that creating a mobile-friendly website is imperative to ensure the success of the business.

However, creating a website is not the only goal for a business. It has to be an efficient platform that would allow customers to purchase their products. This is the key to increasing sales in tandem with growing the business’ digital footprint. Building a viable e-commerce site that is also optimized for mobile commerce (m-commerce), should be in forefront of the business strategy.

What is M-Commerce?

Simply put, mobile commerce or m-commerce is sales and commerce using wireless hand-held remote devices. These devices can be smartphones, phablets, or tablets. The main concept behind m-commerce is bringing a simple, accessible and user-friendly shopping experience to the consumers.

M-commerce is becoming increasingly popular and e-commerce companies and retailers are slowly moving away from strategies catering to creating awareness about their online stores and moving towards integrating m-commerce in their business strategy.  M-commerce can also be used as a method to enhance overall revenue and increase customer base.

Why is m-commerce important?

M-commerce is one of the major influencers that accelerate business growth. Here are some areas it plays an important role:

The positive impact of Increase in mobile sales

There is a steady increase in the number of mobile users. Now consumers surf the internet via their phones. This generates more than the traffic created with it on the web. The idea of purchasing something on the phone at a time and place of comfort, and having it delivered on the doorstep is a lucrative option for shoppers.

The mobile furthermore is a pocket-friendly device that is available 24/7 for any individual. Any necessity of shopping at any point in time can be satisfied with the mobile instead of hunting for a laptop or using a desktop. Overall, the increase in mobile sales creates a remarkable impact on online shopping which benefits the e-commerce sector.

Phones now have bigger screens - enhancing the shopping experience

Technology is constantly changing and enhancing, as is the competition. Bigger sized phones with larger screens have completely changed how people use mobile phones.

Online shopping is one of the major trends that are set by bigger screens. The comfort with large screens is recognized even with aged people as they can easily use the phone to view products or details easily without having to reach for their eyeglasses.

Innovations resulting in better business

There is a race to provide something new and exciting that the customers would use, ultimately enhancing the user experience. Due to this very race, many brands have started using various innovations as part of their marketing strategy enhancing the user experience.

Single Click Options
On e-commerce sites, buy buttons and checkout options are often the prominent features. With single clicks the site allows the user to complete the user journey fast and efficiently.

AI and Chatbots
Artificial Intelligence (AI) and chatbots are some of the latest technical integrations in the mobile phone for a better experience. AI voice assistants and chatbots bring in an ease of shopping. The tedious process of manually typing in product names, searches, address details can be eliminated - All of this, in the palm of the hand.

Capgemini's Unadkat stated that Artificial intelligence and chatbots will be a key area of focus for retailers in the coming years.​​​​​

Web pages and mobile apps are majorly used for online shopping

There are two main ways to reach the remote masses. One way is through mobile web pages, and the other through mobile apps. Both these methods have enhanced e-commerce experience for customers.

Mobile web pages
With a mobile web page, user data analysis becomes easy. Companies can understand and segregate the target customer and market. They can then, go ahead with the changes in the company portal.

Mobile Apps
Mobile apps are used widely by nearly all e-commerce dealers. They are considered more beneficial as the app customers are more loyal as they spare time and put in the effort to download the app. The chances of purchase from these users are very high.
Moreover, online retailers can avail the benefit of personalized communication with their users. Leveraging analytics and purchasing behavior, they can tailor make the promotions and send messages accordingly.

Push Notifications
Retailers use this feature to send updates to the customers for promotional offers. Many other such features have helped the online retailers get a greater grasp on customers.

Social Media Benefits

Social media networks such as Instagram, Facebook and Twitter have become a vital part of daily life. Every mobile app company has integrated social media features like share and like with their app and online portal. Mobile users prefer to keep everything from shopping to mobile apps handy. Within no time, they can share updates from online websites on social media.

Future of mobile commerce

More and more consumers are selecting mobiles as a medium to shop rather than laptops or desktops. M-commerce holds a lot of promise for the future.

Business Insider stated that 45% of e-commerce revenue will be coming from m-commerce, by the end of 2020.

While the e-commerce industry is expanding, mobile commerce is not far behind. The innovations will continue to drive the growth of m-commerce. Today, the tech innovations can be seen with the implementation of AR, VR, and wearables, but in the near future, m-commerce will drive innovation to reach new heights.

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Visual Search: AI tool for E-commerce

Visual Search: AI tool for E-commerce

AI has been empowering many of the world’s top technology solutions. Within e-commerce, AI is being used to make the industry increasingly customer-centric. This can be seen with sales forecasts, product recommendation engines, virtual personal assistants like Siri or Alexa, AI-powered chatbots, automated warehouses, etc.

The need for visual search in e-commerce


Large e-commerce companies offer catalogs with thousands of products and plenty of options. Customers, however, are becoming increasingly impatient during the buying process figuring out what they want to buy in the shortest possible time. This hence poses the question of how to make the search process short and seamless.

In an important use case, AI has enabled search engines to become smarter. This can be seen when using text as a search query, the search becomes more semantic and conversational. AI has also enabled enhanced voice search features. The latest popular feature being search via images.

A new way of search

E-commerce companies are investing largely in integrating all three search methods on their websites to make a more responsive search platform. With text and voice search being increasingly used for products such as electronics, visual search aids customers to find an easier alternative for fashion and lifestyle products which may be difficult to describe with words. For instance, when searching for outfits worn by celebrities, knowing the right keywords would provide the outfits that are indexed with those keywords. Most often than not, the right outfit is not found. With visual search combined with indexed images, the right outfit can be found in just a click!

Today, visual search has increased the level of engagement that customers have with e-commerce websites as well as offline retailers. Be it for searching a product page online or being provided with relevant product recommendations, smartphone apps are becoming more accurate and faster at predicting the customer needs.

Visual search has created new shopping experiences for online and offline retail stores. Customers can now scan images of their choice of products whether it is online or in a store. Providing relevant and accurate product results will ensure that users can shop from anywhere and at any time.

AI and visual search: The tech

Visual search is a very recent trend, and this has been possible only due to the recent advancement in this technology. Visual search is built using Deep Neural Networks, a subset of machine learning. This in fact built as a replica of the neural networks in the human brain.  To put it simply, Deep Neural Networks make machines intelligent to gather and categorize information in the form of text, images or videos like humans do, using their biological neural network.

For example, To make a machine understand a sofa using deep learning, it is first shown pictures of thousand sofas. The algorithm reads and extracts features that can collectively classify a sofa such as a backrest, armrest, cushions, etc. After this, if a new image of a sofa is shown, the machine would be able to now tell if the image has a sofa or not.

Furthermore, if a complete picture of a living room is shown, the machine can individually identify different objects that it has been trained via deep neural networks such as rocking chair, coffee table, rugs, side table, etc. This technology is very adaptive - it recognizes a user’s search pattern so as to provide accurate purchase predictions.

Deep learning technology, providing accurate results can ensure that users find exactly what are searching for, in a short search span. This helps enhance user experiences, which in turn, leads to an increase in conversion rates. Neural networks and deep learning provide the best solutions to problems being faced in image recognition, speech recognition, and natural language processing.

Visual search has become one of the most successful technological innovations in e-commerce and retail, in turn, boosting the effectiveness on a global scale.
With the tremendous emphasis on digitization and the rising economy, this holds a strong promise.

Today, companies are looking for product differentiation through tech and visual search advancements offer just what they are looking for.

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Personalization: The future of e-commerce

Personalization and recommendations: The future of e-commerce

Commerce has evolved over the span of 100 years. Over the century, it went from being driven by demographics in the 1890s - with retail catalogs offering a limited product selection to being driven by brands in 1990s - with stores and malls offering a rising product selection. With the advent of the world wide web, commerce was driven utility - with the rise of now e-commerce giants eBay and Amazon. In the 2010s, data began taking over as the driving trend.

The current trend

An indication of data-driven e-commerce are personalized e-commerce offering, curated product discovery and 24/7 recommendations. Many e-commerce and retail companies now have incorporated some level of personalization whilst engaging with their customers.

 The best examples can be seen with websites like Netflix - from the time a customer watches their first movie or show, Netflix’s algorithm starts working. They have been so successful at tracking customer preferences that they are spending almost 8 million dollars to keep up with the demand. They’re even using e-commerce personalization to affect the graphics for their shows.  Customers can get to see one of many different graphics of a show based on their preferences that Netflix knows about.

Another example on the other spectrum would be Subscription boxes like Stitch Fix, a personalized style service. Using the preferences provided by the user, Stitch Fix would deliver the best 5 items to suit them in the comfort of their own homes. Based on what customers keep and what they return, they personalize the clothes even further.

wooden box filled with condiments

Personalisation completely relies on data gathering to be effective, which depends on the customers as they have to be willing to trust and share their information with a brand. The brand can then, enhance their experience and engagement using this data. It becomes a win-win situation when carried out efficiently, the use of data will correlate positively with customer satisfaction.


While this is the current scenario of how companies are using some elements of personalization today, here are some predictions about how personalization will play a more substantial role in the near future.

The rise in Subscription services

Customers are slowly evolving from product purchases to subscribing. This is due to the rise in personalization - the leading factors driving the growth of subscription-based services. There is plenty of evidence suggesting that subscription services are the future of e-commerce or at least a big portion of it.   

Digital subscription services such as Netflix, Amazon Prime or even Spotify are now the driving our entertainment consumption, while retail subscription services like Birchbox, Dollar Shave Club and Stitch Fix have started becoming more and more popular among consumers.

We have already demonstrated with Netflix, how personalization is breaking ground, another example could be Spotify, with their paid subscribers rose from 0% in 2008 at its launch to 45% in 2017. In other words, if a service is available for free, yet its paid counterpart is providing a better and compelling experience, consumers will not hesitate to invest.

wooden box with bath supplies

Spotify uses personalization to effectively nurture its recommendation engine - which provides daily discoveries of music based on a user's preference of songs, artists, genres, etc. This has not only increased the app preference amongst users but also increased the exposure of new artists enlisting their albums & singles on the platform.

Automation to support omnichannel marketing

Automation and personalization largely go hand in hand.
In the next few years, automation will play a massive role especially with the growth of omnichannel marketing. A study conducted by The Harvard Business Review among 46,000 shoppers in the span of a year stated that only 7% of that group solely shopped online, 20% shopped solely in stores and a whopping 73% shopped using multiple channels.

Omnichannel marketing has challenges yet tremendous opportunities that companies will be able to leverage to utilize automation in the near future and the companies that would be able to leverage it would only be those that can efficiently utilize automation so as to offer personalization across all channels.

Personalised deals and pricing

Shoppers today not only differ on what they want to buy but also on what they would be willing to pay for. Traditionally, companies had to study different price ranges so they would pick on what would give them the most profit, even if this meant that they’d turn down potential customers.

This is now slowly changing. Personalisation is giving way for companies to charge individual shoppers. For instance, Orbitz used to charge Mac users more - based on the assumption that that demographic tended to have more spending power. Hence, it stood to reason that they were willing to pay more.

With the advent of AI and machine learning, companies in the future will easily be able to get into the granular details. This, in turn, will enable more people to get the products and services that they require at an accurate price point based on their past buying decisions. This approach will help e-commerce companies to build attractive bundles or tailor-made promotions for individuals.

AI and Machine Learning

Leveraging AI and machine learning, personalization can scale new heights by anticipating customer support needs before they even have them.

Furthermore, machine learning will also change the language that websites use based on the visitors it gets. In a scenario where a user needs help, machine learning would allow the site to find the best answers based on the information instead of the standard replies that most websites give now.

If the site knows that a returning shopper is looking for some products with respect to a previous purchase, they will be able to recommend the best products but also further provide them with relevant content that would help them make the purchase.

Looking ahead

E-commerce personalization is already here, so if retail or e-commerce businesses have not utilized it yet, they must start now. With more and more innovations coming in, the horizons are widening day by day. These predictions can ensure that your business is on the right path towards personalization.

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How can AI improve SEO for retailers?

How can AI improve SEO for retailers?

Drafting creative SEO strategies is a crucial point for retailers. Having rich data like clear images, or detailed product descriptions is imperative as the content is one of the main traffic drivers for e-commerce portals. Implementing the right product description strategies can impact and enhance site searches and increase sales.

Images play a pivotal role

Site searches and site data are directly related. This means that if the site contains poor data, the results received will be insufficient and may not meet visitor expectations. Consumers are more willing to engage with content that includes relevant images, and hence mapping images to rich attributes is important so that the relevant results appear on the website. This would show products that would better interest the customer.

This is especially important for e-commerce businesses because the product overview and its appearance play a very important role during a purchase. A research even shows that over 90% of consumers consider that the images play an important role during the purchase journey.

Automated descriptions are accurate descriptions

Many consumers when searching to find a specific product, often get irritated when the results show irrelevant products. For instance, while searching for a “little black dress”, maxi dresses in the results should not show up.

Search engines rank images against several factors. These include file name, the captions provided with the image, the alt tags, how the product is categorized, etc.

AI solutions based on image recognition have started to gain momentum. They help generate deeper and accurate attributes from product pictures in an automated manner.  These solutions are based upon recognizing the shape and size of objects. In terms of fashion, this can help in identifying clothing - the type of clothing (shirt, blouse, jumpsuit), the color, its fabric (denim, lace, cotton), the patterns (stripes, chevron, floral) and its shape (short sleeved, cowl neck, etc.)

The aim of this solution is to function in a similar manner to that of a human brain. The AI solutions can classify and extract very specific information from an image. From a product provided by a customer, the machine uses algorithms to recognize specific patterns and arrive at certain conclusions. It also utilizes patterns from previous experiences, as a way to learn by itself.

Homogenizing product attributes and categorization

Loading products onto the website along with each product categorization can be extremely time-consuming. If this is done manually, there is a chance that typing errors or duplicate entries in categorization may happen. These mistakes can highly affect SEO rankings, as Google factors in linguistic accuracy and classification.

Furthermore, the more specific and descriptive the product attributes are, the easier the task becomes to match long tail searches and provide relevant products to the users entering a search query.

woman looking at two different computer screens

Powerful and intuitive image recognition AI solutions help to avoid categorization mistakes and provide richer attributes. This makes online catalog management efficient and enables search engines to find appropriate products - ultimately, enhancing product discoverability with automated content.  


Leveraging AI and machine learning capabilities, CatalogIQ can help your e-commerce or retail business by strengthening your content and improve your search rankings.

Are you looking for boosting your e-commerce business? At Icecream Labs, we aim to provide solutions for your business problems. To know more on how AI can impact your business you can get in touch on LinkedIn, or mail us — sales@icecreamlabs.com

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What Can US Retailers Learn From Asian E-Commerce Companies?

What Can US Retailers Learn From Asian E-Commerce Companies?

There is stiff competition between Asian e-tailers and their American counterparts for the battle of global leadership. This is an extremely probable future as the e-commerce giants Alibaba and Amazon are already gaining momentum in India and Australia.

Nearly two-thirds of the US e-commerce industry is dominated by retailers such as Walmart, eBay, Best Buy and Amazon (that covers this space by over 40%), the local market is becoming more consolidated and less flexible. This is in comparison to the agile, data-driven, and fragmented Asian e-commerce industry.

Can the mature American retail market learn something from the comparatively young and rapidly growing Asian e-commerce market?

Modify selling strategies to Local markets

US-based brick and mortar stores and online retailers focus on domestic and English-speaking homogeneous markets. On the contrary, the nascent Asian e-tail market is constantly expanding beyond borders to markets with varying population sizes, purchasing powers and cultural backgrounds.

Here’s something to ponder upon — Amazon is the world’s third-largest retailer, it uses its universal selling strategy regardless of the market it scales up to, while its Asian competitor, Alibaba, the world’s sixth-largest retailer, acts on a different vision — “Act Local, Think Global”. This strategy works well in the rather fragmented Asian market and therefore, by extension, in the global market. Alibaba acts through local players or players that know the local market by offering a variety of affiliate programs.

For instance, Alibaba acquired a majority stake in Lazada, a major player in the South East Asian marketplace, an ideal platform for introducing Chinese vendors to non-Chinese buyers. Furthermore, another great example of Alibaba’s adjusting to local markets would be the expansion of Chinese marketplaces Taobao and Tmall in Russia. Alibaba’s strategy envisions adaptations to various local markets and finds ways of making the local systems reinforce each other.

person using smartphone

Cross-Border selling is the name of the game

Alibaba is not the only e-commerce company that wants to increase cross-border sales. Recently, South Korean retailer GS Retail made a $29 million equity investment in the U.S. e-tailer Thrive Market. US e-tailers are not far behind. Even in the US, retailers have begun to realize that buyers outside the English-speaking markets can also generate revenue. This trend could be seen when Walmart, one of the biggest retail chains in the US, acquired a majority stake in India’s largest online retailer, Flipkart, making the transaction “the world’s biggest purchase of an e-commerce company.”

To function in an unfamiliar environment, retailers need expertise, which in today’s market, only the Asian players have. They can soon be well equipped to battle American retail in the global market with optimized operations and the ability to cover different markets with subsidized prices.

Retailers who are tech-savvy, stay ahead

Innovation is a crucial element for businesses to compete in the market whether it wants to play internally, externally or globally. More and more businesses are opting for technology including AI and machine learning to gain an edge over the competition.

ML and AI are disrupting retail by enabling businesses to observe competitive prices and monitoring trends, helping them to react to changes and forecast demand and sales. This way, retailers can boost their revenue and can build data-driven strategies and make better business decisions. No algorithm can be useful if the data it processes is not of high quality. Trained on the data, can it recommend optimal pricing and forecast sales which directly affects the business performance.
The better the data is, the better the outcomes are.

Conclusion

Successful businesses will be those that recognize and adjust their strategies and offerings to that particular market. Moreover, building several channels of communication with customers and leveraging the marketplace as a way of accessing consumers as well as integrating innovations and data into their operations will further strengthen their success.

It’s a no-brainer — Data-driven companies are already dominating the market. The other retailers need to jump on the bandwagon if they want to stay competitive.


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Customer Loyalty Programs: Why Retailers Need Them

Customer Loyalty Programs: Why Retailers Need Them

We have already established that there is cutthroat competition present in the e-commerce and retail industries. This is forcing many brands to re-evaluate how they deliver value and stay relevant to customers. Retailers want to understand what drives their customers to visit their stores and make purchases, and how to reinforce those loyal behaviors.

Loyalty programs is one method to help achieve these goals like increased foot traffic, repeat visitors, build deeper engagement and reap a successful financial return on this loyalty investment. Customer loyalty programs are becoming increasingly popular and they offer a lot of benefits, to both the retailer as well as the customer.

Nielsen found that 84% of consumers are more likely to choose retailers that offer such a program, and 59% report that they’re available where they already shop.

Retailers need to capitalize on this interest in loyalty programs and create an active user base that eventually keeps them engaged with the brand for a long time.

What is a Customer Loyalty Program?

The idea is simple: The more you shop and spend, the more you receive in return. Nielsen describes them as “marketing programs that reward members with purchase incentives.”
With these programs, retailers can track and incentivize purchasing behavior and reward customers for their loyalty to their brand. This is a powerful customer retention tool as it motivates existing customers to continue engaging with the brand and therefore, spend more.

Different types of Customer Loyalty programs

Customer Loyalty programs come in different forms. Some retailers use only one type while some others create combinations of two.

Loyalty Points
This tactic can be seen especially in the grocery chains where customers get points for making purchases or perform certain actions such as providing some personal information.

Social Media
In this approach, retailers abandon the traditional approach to purchasing a product. They award certain points to their customers for social engagement with their brands such as sharing, liking or commenting on an ongoing campaign. Many brands even run contests and raffles that reward loyal fans with amazing prizes.

Paid Programs
Not every reward program is free. Some of these programs require their customers to pay a certain fee that could be a one-time payment or a recurring payment in order to enroll. Amazon Prime is a great example of this type of model.
Furthermore, these programs can also include partnerships with credit card companies who may provide special benefits and offers in exchange for reward points. Some of these benefits may include discounts, cash-backs, free shipping, access to exclusive shopping events, free services, upgrades.

Retailers may use these programs to modify buying behavior by incentivizing the action they want their customers to take. These programs also provide data to help retailers understand their customers more deeply. With this kind of data on purchasing behavior, it’s easier to segment, create personas, and gain insights to help guide new initiatives.

Role of AI in Customer Loyalty Programs

AI has found its way to many retail companies across different verticals and now have slowly made their way into loyalty and marketing programs as well.

Customers as well, to an extent have become familiar and comfortable with using these technologies. A research states that customers are increasingly willing to rely on algorithms and smart devices for enhanced and personalized retail experiences. This, in turn, fosters an expectation for convenient, low-friction shopping experiences with loyalty programs. AI and machine learning may help in streamlining customer experiences, but they are apt for managing and interpreting customer data captured by loyalty activities and customer interactions. A marketing strategy with an integrated AI and machine learning technology can create a single customer view dynamically, in real time. This can help brands and retailers with large footprints or multiple locations can understand their customers faster and predict trends and offers accordingly. Moreover, this helps them to stay ahead of the competition. Of course, enthusiasm for these technologies is at a high point, and there are many varied predictions about the impact AI will have on the world at large.

Summary

A research shows that retailers spend 5 to 10 times more to capture a new customer than to retain the currents ones. With Customer loyalty programs, engaging with the existing customers could cost less, and reap larger benefits in the future. Effective execution of these programs can increase the customer lifetime value and ROI. There is a huge chunk of consumers that modify their spending amounts in order to maximize points. Hence, program members are more likely to shop on a regular basis. Furthermore, they also activate word of mouth marketing as one customer’s experience with a brand can influence another’s choice or preference for a brand.

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Application of Artificial Intelligence to Extract Web Data

Application of Artificial Intelligence to Extract Web Data

The web is a giant storehouse where data is available in abundance. As on 2018, there are nearly 5 billion websites, according to a World Wide Web survey. The potential of what can be done with this data is massive but it is practically impossible to access this data manually. The main challenge that is being faced right now is navigating through this unstructured pile of information and extracting it. This takes a lot of time and effort especially scraping the data from the web. Here is the time when automation can play a pivotal role.

With the rapidly changing technological trends and advancements in AI, there is a way to use machines to extract information from a variety of sources on the web and train them to do it on their own.

Here is a quick example to make this simpler to understand — when we scan and skim through a document for a specific piece of information, we additionally look for alternative sources as well. This inadvertently adds to our knowledge on the topic. The AI system works in just that manner.

Automation is important for web data crawling

A major advantage of AI powered web crawlers are that they save cost of manpower and time put in manually. This even reduces the probability of human error. For simple web data crawling, it is a given that softwares can do this task faster and more accurately than humans. Once a data crawler machine is trained, it can efficiently extract from every single source.

This machine should be able to navigate through different pages and should collect the data from each of them. This is where things may get difficult as different websites use different navigation systems which results in complexity, hence the programmer, writing this code must have sound technical knowledge. He must deploy the code in such a manner that there should be minimal human interference once the machine is programmed.

The future of data extraction

With the ever growing need for data and the challenges associated with procuring it, AI can be the missing piece of the puzzle. The research behind this has tremendous potential with a positive glimpse into the future where intelligent machines with human sight can crawl web documents to give the missing pieces of information that we need to know.

The AI system can be a game changer in research tasks that require a lot of human labor. A system like this will not only reduce the time taken but also enable us to use the abundant information on the web.

Looking ahead, this new research is only a step towards creating the truly intelligent web crawler that would eventually be able to master a variety of tasks just like humans rather than being focused at just one process.

The application of AI and automation in web data crawling and scraping is extensive. Compared to humans, the consistency of the AI powered web data crawlers is unmatched. Furthermore, these machines do not require a lot of maintenance over long periods of time, which adds to its value. There is an immense amount of potential for improvements in web data crawling automation leveraging AI and therefore, the possibilities are endless.

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Blockchain — The Retail Advantage

Blockchain — The Retail Advantage

The retail landscape has changed over the last decade. With newer technological enhancements, more retailers are opting to incorporate the latest technology to stay ahead of the competition.

From drone deliveries to one hour deliveries, companies are increasingly investing in virtual assistants and AI to engage with customers and enhancing customer experience.

Blockchain is not far behind. With its satisfying results by effectively creating a complete virtual financial market, it is here to stay. It’s no surprise that blockchain is revolutionary technology. The retail industry has finally recognised the power blockchain holds.

Here’s how blockchain can play a crucial role in the future of retail:

Data Collection and Analysis

Data enhances the shopping experience for customers. Blockchain does that, by delivering an efficient way to collect and analyse the available information. Leveraging AI, Blockchain can gather and assess data in real time from different sources like consumers and retailers.

There is a lot of data now that is available from different locations. Unfortunately, the data that is available is fragmented. This makes it difficult to sift through and detect patterns that can let the retailer know which direction they have to take to enhance their customers’ experience and address their pain points. These become missed opportunities for retailers. Here, the blockchain technology can aptly address this problem and make it easier. A blockchain platform collects data from across the supply chain and leverages machine learning to structure the data. Blockchain can enhance the inventory tracking process, including reducing overstocking and under-stocking. Since blockchain uses a secure ledger format, the product data is more reliable and secure from tampering. Furthermore, it can reduce supply chain product waste.

blockchain-technology

Supply Chain Ledger

There are several ways that blockchain can help strengthen relationships. The entire supply chain is one major aspect retailers need to keep secure as it directly impacts the shopping experience for the customers. Using blockchain as a supply chain ledger can make a huge difference in all segments of retail. This especially can impact and enhance retailers that are involved in perishable goods.

Blockchain ensures that the supply chain and logistics is secure and authentic. This means that every record and form is being checked and time stamped in the supply chain. This ensures no tampering of data with everything being independently verified. Thus, there is greater control over product manufacturing location, process, and timing.

Furthermore, a blockchain supply chain model also enables retailers to control all aspects of transportation, storage, delivery, and presentation.

Payments and e-commerce

Blockchain is a trusted means of payments. The majority of retailers are integrating bitcoin and other cryptocurrencies as means of payment processing. The big advantage here is, compared to credit cards, the integration of cryptocurrencies is that it is cheaper and transparent to process transactions.

Blockchain allows for retailers to accept cryptocurrencies along with digital records which helps streamline refunds and return processes.

Besides, purchasing items that need a large amount of money such as cars or land property with cryptocurrency can track the ownership and verify resale of stolen goods.

e-commerce

Retailers must now realise that Blockchain is here to stay. While there are other developments happening in the industry, they need to keep an eye out for this technology.

The possibilities have only just begun.

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