Finding a perfect product (electronics or shoes) with, the correct attributions or quality is the customer’s challenge. With millions of browsers and limited shoppers, running a profitable business is the retailer’s challenge. In such a competitive world, with thousands of alternatives for every commodity. One of the simplest things these days is using ‘Google’ search for information(basically all kinds). Ever thought how easy it would be if finding data and ideas for your business were that easy.

If you haven’t, give it a shot!!!


Algolia serves as the platform for this thought. A hosted search engine capable of delivering real-time results from the first search. The API(Application Programming Interface) allows the implementation of the search within your website, mobile, and voice application.  The ‘speed’ and ‘relevance’ are the brightest highlights. With such a dense network, one of the expected con is a- server crash, but  Algolia has an interesting three-server architecture.  If one or even two servers go down, there’s always a third one ready and available. Trusted by brands like Slack, Decathlon, Coursera,  Amplitude, and more. It is higher in the cost range for data searches and documentation.


Window shoppers or browsers (even on online stores) are increasing steeply. Converting these window shoppers into actual buyers,remains as a difficulty.

Coveo is an information consolidating program. That provides quick information, which is, tailored according to the customer’s needs about relevant or searched products. Engaging customers in the advertised products is crucial for sales. This engagement comes with an effective response for customer queries and relevance or vital details about the product. This also happens to be one of the disadvantages of Coveo, the search results are at times not relevant and sorted. 

*Reviewers hold the opinion that Algolia meets the needs of their business better than Coveo( in certain aspects). But the general customer satisfaction is higher with Coveo when compared to Algolia. This makes the decision tricky, the features that the retailer requires are the deciding factor for opting, either of the two platforms.

3.Label Insight:

“Retailers: We Will Increase Your E-Commerce Sales. Guaranteed”. 

The confidence and assurance of the company is a great highlight. Label insight works closely with manufacturers and retailers to increase the transparency of foods and beverages. This serves as a factor for the increase in sales and growth of the company. They provide insights into these products. Which includes not only the general composition of the items but more. Example: if the product qualifies for a certain diet, allergens, environmental impacts, and other details. Most(that is,99%) of the customer queries are covered in their meta-data.


The uniqueness and emotional context(WHILE SHOPPING) of the customer is highly valued by the company. There are thousands of products to choose from, whilst both, online and offline shopping. Lily identifies intricate details about the product and also tries to replicate the in-store experience online. The concept of auto tag, adds valued attributes to the product. This makes the decision-making process easier for customers.    


 Many times customers have a predetermined product in their mind before visiting a site. The outfit may be worn by a public figure or an image found on Pinterest. The process ahead is delicate, finding the same or similar outfit. Syte allows the implementations of visual search on the website allowing shoppers to search for products using just an image. Myntra recently implemented the visual search. Syte currently caters to the needs of fashion, jewelry, and home decor brands.

6.True Fit:

Your True fit is quite easy to find with a few basic information, like- height, weight, the correct size can be found. The company combines each person’s unique body measurements profile and product profile to find the perfect fit. This profile will be saved for the future to remove the tedious process of re-entering all the data and to shop on the go. This feature is available for men, women, and kids. The personalized feature cuts short the process of finding the exact fit for various brands and also returning products(in case they aren’t the correct fit). Customers engagement is increased in the website and the time- reduction process gives it an edge over other shopping sites.


A product being visually appealing is important for a shopper. That is exactly what ViSenze does. Often the perfect product(a dress or shoes) cannot be described in text format, with visual search and image recognition technology the perfect product is a lot simpler to find. Having the in-store sales staff well equipped with details about a certain commodity or something similar is necessary, this promotes both engagement of the staff and an assured happy customer. Though the platform enables image recognition, video search is not a function of ViSenze.

Syte and ViSenze are competing sites, Syte has better coverage in more websites categories. Including Lifestyle, Home & Garden, E-commerce & Shopping, Finance, and 3 other categories. Whereas, ViSenze is leading in Sports, Computers Electronics & Technology and Business & Consumer Services. Syte has a larger customer base when compared to ViSenze. ViSenze entered the retail world in 2012 and Syte launched two(2) years later, that is, in 2014.                           

With image recognition and data science, the company helps retailers generate product, customer intelligence, and combine these with market insights, to power growth. Currently, retailers with businesses in fashion, beauty, grocery, electronics, and home and furniture. The AI enables a deep and personal understanding of each customer to make market strategies that help flourish.’s neural network for retail leverages image recognition and data science features to extract retail catalog data, analyze it with user behavior, and help retailers make better and faster decisions. Several reviews state that is best for small and medium businesses, not too costly, and an efficient system.

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