Tag Archives for " Ecommerce "

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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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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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How important is catalog quality in e-commerce?

How important is catalog quality in e-commerce?

Lead nurturing is one of the most important aspects of E-commerce. A lot of retail brands so far have been investing their focus on lead acquisition investing in various sources via paid or organic means to lead potential customers to their landing pages. It is imperative for brands to pay attention to nurturing the lead until a conversion takes place. Here is when catalog quality plays an important role.

Catalog quality impacts the customer journey

A vital part of the process involves the catalog present on the e-commerce website. A weak catalog can cost customers and lose potential leads.  The customer journey from the time they land on the website, to the final checkout depends heavily on the catalog quality of the website, as it guides the customer through each step of the sales process. It is important that the customer does not leave at any stage of the conversion funnel. From the product list page to the payment page - lead nurturing can happen by an improved catalog quality.  

Some of the things to keep in mind - products must be properly classified on the landing page, product attributes must be well defined and images must be well represented. Furthermore, the information provided on the product page should be clear and unambiguous.

woman sitting on bed facing laptop
Content matters for catalog optimization

Catalog monitoring helps in tracking the catalog health ensuring product classification, data completeness, avoiding duplication and identifying errors in product information. Catalog optimization can help personalize a customer’s journey through the conversion funnel. This can be done by customizing product titles as per the customer’s search keywords as well as their descriptions, replacing missing titles and descriptions, enriching product information, and tags.

Catalogs are the focal point when a customer is making a buying decision. They take into consideration all the available details while choosing a product. If there is any discrepancy in the details, such as a missing feature can cost a potential lead, as the customer may abandon his journey.

Moreover, maintaining consistent catalog health can help improve conversion rates, by not missing out on qualified leads. Around 70% leads coming through any channel may not be all qualified leads, in spite of the credibility of its sources. Companies who invest in nurturing their leads can see a 450% increase in qualified leads and a 50% increase in sales.

Ultimately, a strong catalog quality can define a customer's experience on your site. This is what can impact a customer's revisit to your website. Building a good catalog helps towards building a strong relationship with a customer.

 

With CatalogIQ, we can help your e-commerce or retail business by strengthening your content using AI and machine learning.
Are you looking for boosting your eCommerce business? At Icecream Labs, we leverage AI and machine learning 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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Data Quality – How to measure for best results?

Data Quality - How to measure for best results?

There is a constant flow of data coming in to be extracted, and decisions have to be made. Ensuring that the data is accurate can become cumbersome if certain rules are not put in place. Data quality is a delicate balancing act juggling between accuracy and completeness. 

From an e-commerce perspective, Search Engine Algorithms need an understanding of the context behind each of the search terms that would inadvertently lead to better results and bag conversion rates. Attributes that are provided by the product content help search engines to understand the context as well as the intent of a consumer behind a  specific search term.

Many retail organizations manually add structured attributes using BPO companies or crowdsourcing firms like Amazon Mechanical Turk. Some large retail corporations engage their own associates to manually validate the quality of the data provided by their suppliers before the products are made available for customers.

How to effectively assess the data quality of product content?

A comprehensive yet concise data quality checklist helps in working towards analyzing the data. DAMA UK created an excellent guide on “data dimensions” that can be used to get a better picture of how data quality is determined.

There are 6 dimensions or steps that data quality can be determined from - 

  • Completeness - If the data coverage across required fields available
  • Uniqueness - When measured against other data sets, there is only one entry of its kind.
  • Accuracy - How well does the data reflect the real-world person or thing that is identified by it? 
  • check
    Timeliness - This could be previous sales, product launches or any information that is relied on over a period of time to be accurate.
  • check
    Validity - Does the data conform to the respective standards set for it?
  • check
    Consistency - How well does the data align with a preconceived pattern? 

In this article, we will measure data against 3 of these dimensions - 

Accuracy:

Improving data to produce the right information is the need of the hour. Accuracy states that the data is what it should be or it is a percentage measurement of how accurate the data is.

On using the search query - “floral cardigan” across 2-3 e-commerce sites, the search terms were classified individually wherein floral was classified as a pattern and cardigan as the clothing. This lead to incorrect results on the first page itself.

web page results for cardigans

Enhancing accuracy is a benefit to all, having more accurate attributes, as well as accurate values, enables search engines to produce better results. This eventually impacts and enhances the customer experience as well as bag conversions.

Completeness:

Completeness is the measure of whether data searched for exists or does not. It drives the attribute definition across all products as well as the coverage of attribute values across all available fields present in the product content.

For instance, if we have an attribute “pattern” for all products under product type skirts that contains 100k products, but pattern as an attribute is added only for 60k products, then “pattern” is only 60% filled in.

If we now perform a search for “striped cocktail dresses” at Macy’s, we could expect would look something like this  -

web page, cocktail dresses

However, these are the results that you get instead - 

web page, cocktail dresses

Investing efforts in encapsulating key data sets as well as attribute values while loading products from product content from suppliers would reap rewarding results. The completeness of key attributes and their values is very important. Missing data can cost a lot of potential customers.  

Consistency:

Consistency refers to data that requires to follow the same format for all the attributes in the product content which needs to match internal and external standards. Maintaining standard data formats across product types as well as attributes and values; keeping it in line with attribute names as well as the value label in accordance with external standards would help to show customers their desired products easily, without friction.

For instance, searching for “fruity perfumes for women” on Target results with these products and does not change even if another search query is given.  This gives the impression that the different scent attributes have not been cataloged.  Furthermore, the search query provides the same number of results despite the different search queries.

web page for perfumes
web page for perfumes

Values for scents provided on the product page are inconsistent and do not conform to external standards; although the “scents” may not be indexed for identification by the search engine.

There are certain attributes and values that would require consistency, which may be measured for reliability reasons. Measuring conformity against internal standards can be enhanced by ensuring the adherence to adding only valid labels that are verified and consistent with external standards. This would help to refer to the same product content available across retailers and define the list of standard attributes and their labels.


Conclusion

In conclusion, as more and more products along with the categories are being loaded onto platforms, attributes and their respective values are critical to understanding the customer’s purchase intent.

It is also essential to assess catalog data quality regularly so the three aspects of - consistency, completeness and accuracy - which help customers get better results and e-commerce portals can efficiently increase conversion rates.


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Disrupting the gifting industry with G-commerce

Disrupting the gifting industry with G-commerce

Gifting isn’t the same as it used to be. Thanks to last minute gifting. This has led to a massive change in the gifting industry, with Loop Commerce.

Loop Commerce is disrupting the $200 — $300 billion gifting market with their understanding of gifting commerce — changing the gift buying and receiving experience for customers. Loop Commerce have reasons to believe that all consumers have different mindsets while they shop and so the experience can’t be the same.

lady holding tablet, shopping on app

The platform takes care of virtual gifting by making all products easily giftable. Gift recipients can unbox their gifts virtually through a beautiful experience online. They can also exchange their gift with something else. One of the main issues retailers face is a decrease in the number of transactions per customer that results in lesser sales. Professor Dan Ariely, expert in Behavioral Economics works closely with Loopcommerce, a lot of studies on consumer psychology and behavioral economics confirm that gifting is an emotional process.

Loop Commerce data suggests that around 40% of the gifts are purchased on the day of the occasion or the day before, since a lot of people forget to buy gifts. Many retailers don’t take this last minute gifting habit into consideration , which leads to customer drop off. Some of the largest retailers are slowly adopting Loop’s solution. Implementing G-Commerce can help retailers increase customer satisfaction and double conversions.

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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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