Tag: Popular searches


Automated home page product recommendations is key to e-commerce Merchandising

Posted on January 29, 2018 by


One of the most commonly executed tasks at any retail store (brick & mortar), is to merchandise the stock visible to consumers. The dictionary defines Merchandising as “the activity of promoting the sale of goods, especially by their presentation in retail outlets.” This is exactly why retailers do this religiously at their stores because the consumer psyche believes “what you see, is what you get”. The purpose of Merchandising is two fold

  1. For the window shoppers passing by the store often it creates a sign of freshness, helping them believe that there is more to see inside the store if they step in
  2. For retailers, this exercise also gives them a chance to promote items, collections, categories that they may want to drive sales or inventory turns, depending on their goals for the month

Retails mercnahdising products to attract visitors

This task of Merchandising requires the store to understand data – what products are new, best selling, trending by category, collection etc., it is more significant than just picking pretty looking products; and involves knowing which of these products meet the data requirements for the merchandising activity in mind.

This exact same user experience is expected by visitors even in the online world, but why do most online retailers have the same homepage for weeks together? Our data suggest that most visitors who have an interest in your online store are likely to visit the store more than 3 times before they purchase. Your store is just a click away and that is exactly why everyone loves online shopping: It’s convenient! It’s another channel for your customers to reach out to your store and they expect the same experience from your online store. But, online shopping is a lot harder on retailers because walking out of your store is also a click away.

The need for the art of  Merchandising is more important at your online store and should be executed with the same goals as your physical store. Keep it fresh and engaging, show something new every X days on your homepage. As a retailer, your core competency is to figure out the Merchanding plan for the week and leave it to tools like Tagalys or BlueFoot to execute this strategy in the easiest manner. You have to also understand that Merchandising tools like Tagalys and Bluefoot are geared to keeping the Merchandiser in mind. They are easy to use with visual & interactive tools that allow your online merchandising team to focus on Merchandising and the technical requirements also imposed by platforms like Magento, Shopify etc.,

At Tagalys, we help our customers with a suite of features that helps you merchandise your online storefront. Some of the most popular features used by our customers are homepage recommendations like – Personalized Recommendations, Bestsellers, New Arrivals & Trending that constantly change based on the data generated by your online store. The same strategy is used by leading online retailers like Amazon, Target, Walmart where they continuously change their home page, as first impressions are the best impressions. Our customers also use the Merchandising feature from Tagalys, to create product listing pages in less than 60 seconds, that is anchored to the home page. And with all these features, we also provide real-time analytics, so as a Merchandiser you can evaluate if the strategy is actually working.

Interested, then check out our 28 day free trial. Sign up now.

Posted in e-Commerce General, e-Commerce Product Listing pages, e-Commerce Product Recommendations
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Free eCommerce Site Search

Posted on March 21, 2017 by


Date: November 5th, 2017. This offer is no longer in effect as we reached the free quota.

In 2015, when Tagalys won the TechinAsia National Finals, one of the judges suggested: “Why not offer e-commerce Search for FREE? “. Back then, Tagalys was fully loaded, meaning we offered 1 packaged solution for all clients without the ability to break down our algorithm & features in parts. But each client’s needs are different and today the team has re-architectured Tagalys to offer Site Search free for any retailer with less than 5,000 monthly searches & 20,000 active products along with a few value-added features. Google used to offer free Site Search (not tailored for e-commerce), but they pulled the shutters. Interested – SIGNUP NOW

Value Additions in the PAID e-commerce site search plan

If your business has the budget to configure & continuously maintain indexes across SOLR, LUCENE, Elastic Search etc., for your e-commerce store. Save time & money. Get Tagalys. Listed below are the value-added features we offer you in our PAID plan with availability/SLAs that will meet, maybe exceed your internal requirements.

Trending & Localized results: Do not show only relevant results (Free plan). Show the products that have the highest probability of sale based on engagement data. 80% of your visitors will not scroll more than 3 pages of Search. Allow Tagalys to determine what products to display for each search query

Search Suggestions: Auto generate text suggestions and display the top X to your visitors that predictively change as they type. Interested – SIGN UP NOW

Suggestions - dresses

 

Multi-Store & Currency: No problem. Easily configurable with our integration kits.

Suggestions - Currency

Spell Check: Visitors make mistakes when they type. With fuzzy logic, these mistakes can be corrected on the go, providing frictionless site search experiences. Interested – SIGNUP NOW

auto correct

Synonyms: Unlimited Synonyms. Show your visitors the right products no matter what they call them. Cell phone vs. Mobile phone, Trouser vs. Pant.

Catalog updates: Update your search indexes LIVE via push integration mechanisms or choose the easy way out to synch your catalog once a day.

View comparison table

Magento search pricing compare

If Site Search is not configured in your e-commerce store, help us, help you. Interested – SIGNUP NOW

Posted in eCommerce Site Search
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Predictive Site Search suggestions for Magento e-Commerce

Posted on December 28, 2016 by


The starting point of any eCommerce Site Search experience, are search suggestions. There are a few shortcomings on the existing suggestions available at Magento, that make this an unwelcome experience for your visitors.

Predictive search suggestions

As most humans have experienced search with google, they invariably would be pleased with Google like suggestions. In other words, suggestions that autocomplete themselves with the user entered search query forming a subset of each suggestion.  Interested – Sign up now.

screenshot-2016-12-28-15-19-11

Popular searches

Before you allow your visitors to start the search experience, load up the most popular or trending searches that occurred in your e-commerce store. There is a high probability these popular searches will appeal to a vast majority of your visitors as they have been generated with the help of an analytics engine, based on search data from your e-commerce store. Typing is friction and by allowing visitors to click on the popular searches, saves them effort and provides the same end user experience – discovering products that they seek.  Interested – Sign up now.

Prioritized Search suggestions

Online visitors have high expectations as many of them might have also engaged with retail sites like Walmart, Amazon, Asos etc.,. Getting search suggestions wrong makes a retailer looks amateurish as visitors expect this as a bare minimum. A well-designed search suggestions product limits the suggestions between 5 and10 suggestions but this could vary by category. Here are a few examples

Ensure search suggestions have results

As simple as it sounds we have encountered many online stores that auto-generate suggestions but do not keep tabs on the potential results it will display or how inventory changes in time.  This is the first epic fail.

Ensure search suggestions have accurate results

Showing 5 to 10 search suggestions and leading visitors to a page where the search results have no connection with the suggestions that were clicked on, is 100% going to lead to bounce or a lost customer. We have encountered this issue at many brands that use the default suggestions on Magento, that generate suggestions but results are not accurate.  Interested – Sign up now.

Spell check

Visitors are humans and bound to make mistakes. Autocorrect what your visitors type into correct suggestions that ease the search experience and guide them into correct results. Interested – Sign up now.

Consider historical searches

In addition to generating search suggestions from available attribute and tag data within the product database, leveraging historical search data and also showcasing them in suggestions is likely to increase conversion rate. This is because historical search data is representative of what your visitors are asking from you and considering them in the right suggestions, is likely to convert visitors into customers.

Configurable or customizable

With all of the above working for you, having the ability to configure what suggestions to show and disable certain suggestions, give the retailer a chance to control consumer experience and promote business interests alongside customer needs.

Support currencies and languages

When your online store supports multiple languages and currencies, make sure suggestions support the same. Showing a visitor from Hong Kong suggestions and pricing based in USD, is bound to decrease visitor engagement. Tagalys ensures suggestions follow the same language and format enabled in your Magento store to support your global business.

At Tagalys we serve all of the above needs to further enhance visitor shopping experience at your Mageno powered eCommerce store. We love Magento and proud to associated with one of the fastest and largest platforms for eCommerce. While Magento focuses on their core competency, it allows products like Tagalys to add to their ecosystem to continue enhancing visitor experiences at Magento powered eCommerce sites.

SIGNUP NOW, join a free plan or a free trial to know whats best for you. 

Posted in eCommerce Site Search
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Extracting insights from search data in your eCommerce store

Posted on December 22, 2016 by


We recently shared a detailed post on the need for Search in eCommerce where we refer to the Search function as speaking to a sales person in a brick & mortar store. So lets continue with the same analogy here.

As a retail store owner, your in-store sales person (search), is interacting with visitors and getting to know their interest in products, colors, fabrics, specifications etc., every minute detail of interest is explicitly shared by your visitors during the search process. This is further fine tuned by the selection of filters to drill down and find that product that will convert them to a customer. This treasure trove of data (search queries & filters) should be used by your marketing and planning teams to improve the topline and bottom line of your business.

Topline impact

With access to search data and resulting visitor engagement details for these queries – impressions delivered, what was clicked, position of clicks, time spent, visitor segments etc., your team has data to understand what your customers seek. 19660747568_02f3186094_b

For example, if the top search query in New York City, is for “Kohler Faucets” and in San Diego is for a “Moen”, for the same data period across segments, it would be wise to promote products that match that query or specific products within that query in your SEO and SEM campaigns, geofenced to New York city and San Diego. This process of creating focussed marketing campaigns to target each customer segment is bound to deliver higher ROI for your digital marketing budgets. The only caveat is that you need “enough” data to make sense out of it.

Search data can also be used to decide what banners within the website, to guide visitors to a landing page with relevant results. Our advise on home page banner strategy is to dedicate 2/5 banners to Search data (historical data) and 3/5 banners to external trend data. Hence if your top site wide searches are “Faucets” and ” Moen”, create a landing page dedicated to these two keywords, that include products which received the most engagement for these keyword searches and maybe throw in an offer or incentive, to accelerate engagement, conversion and revenue generation.

Bottom Line Impact

Analyzing search queries gives you access to customer demand data. This can be used to better plan stock to ensure supply meets demand. For example, if your customers are seeking “Ruby rings” and only 5% of your stock in rings contain the Ruby stone and over 50% is Diamond rings, there is a good chance, you are going to be subject to low inventory turns. This is not good for your cash flow and will drive the “Discounting” act if you need to move the stock. Stocking products that are in demand could increase the probability that customers are less inclined to discounts as they need it NOW.

SIGNUP NOW, join a free plan or a free trial to know whats best for you. 

 

Posted in eCommerce Site Search
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How Amazon Site Search algorithms affected Flintobox in SEM

Posted on December 21, 2016 by


Want Amazon like Search experience in your online store?  Signup now and see your visitor engagement improve or read from one of our data analysts on the inside workings of Amazon Search.

Recently a fellow entrepreneur raised an issue on unfair acts by Amazon.in infringing on their trademark name “Flintobox”. The issue came alive because Amazon.in had bid for the keyword “Flintobox” on Google and given that it’s Amazon, there is no way a startup can outbid them. Also, legally no company is allowed to bid on a name that is trademarked by another entity. Below a screenshot of the dispute in question.

amazon-trademark-violation-2016-10-18

This has been rectified by Amazon, but it sure caused some heartburn for the Flintobox founders, a few folks at Amazon and many small businesses that feel threatened by such incidents.

amazon-response

It always confuses me when large, funded players are willing to outbid, underbid or even lose money to acquire your customer. This probably led to the founder sharing his woes across the social media where it was retweeted, shared and hence reached my timeline. My friends at Amazon, who speak highly of the company, insist that something like this must have been a mistake and not some personal agenda of any category manager to acquire customers by breaking the law. So, I personally spent some time trying to understand what could have happened, given that Amazon has been a very big influence in my life.

At Tagalys, one of the products we sell to our customers is personalized search as a service and we think the internal Amazon search tool, something that most visitors engage with, might be the cause to the above dispute. Here is our take on what could happened. We hope to hear your feedback as it will also help us improve what we live to build everyday.

Today (Dec 21st, 2016, 1358 hours) if you visit amazon.in and search for “Flintobox” you will still find search suggestions, even though Amazon.in does not carry any stock of the Flintobox products.

flintobox-search-amazon

Now everyone knows “Search” at Amazon is best in class, hence there is no way Amazon will show you Flintobox in search suggestions, if the engine knows products are – OUT OF STOCK. But if you click on any of the suggestions, it leads to a Search results page, that as expected, does not display any Flintobox products instead it lists Einstein box or Xplora box.

explorabox-jpg einsteinbox-results

This leads to two possible reasons, when sellers upload products onto Amazon.in, they upload details about the products including tags, search keywords, potentially even synonyms. We assume, that these products had the “Flintobox” keyword somewhere in the seller upload sheet.

Another reason, though highly unlikely, is that Amazon dynamically detects that products sold by FlintoBox, Einstein box, Xplora box are targeting the same customer segment. Hence even before a customer visits a “No results” page as Flintobox is not in stock, it redirects them to a page with products that will appeal to the same customer segment. Thereby ensuring engagement and potentially conversion.

But what does all this have to do with an ad created for “Flintobox” by Amazon on Google?

Every eCommerce Search or Site Search engine worth its salt, collects, groups and analyzes “Search” data and how visitors engage with the results across segments. Search is demand data directly from customers and visitors telling you what they want. There is also a high probability if X volume of visitors ask for something within your store, there are many more out there (Search engines like Google) who may want the same.

“Flintobox” as a keyword led to Search results and had engagement. It still continues to do so. For the category/subcategory, their search volume must have met certain minimum criteria and also led to engagement – views, add to carts, buys etc.,. We assume, Amazon has an inbuilt or uses a 3rd party keyword bidding tool for Search engines like Google etc.,, that studies keyword data, with engagement and dynamically creates a landing page (at a category or subcategory level) provided the real time bid requested by Google falls within the budget of Amazon. And since the dynamic page created for the advertisement is powered by Search keyword data, the keyword bidding tool has an active keyword, products to display and bid within budget and voila the landing page is created (This is a screenshot of the landing page reproduced from the blog posted by the Flintobox founder, hence products displayed may not not current)

flintobox_search_listing_on_amazon1

So what could have been done to have avoided this incident?

If the above assumptions are correct, then the Amazon seller services team should have more checks in place when sellers upload data. Google today will not allow you to bid for a search keyword that is trademarked by another entity and something similar within Amazon Seller services could have voided this incident from happening. Another way, although rudimentary is the compare the seller upload tags/keywords data with the Brand names stored within the Amazon database. This may not cover trademark infringements, but will definitely avoid Brand X showing in suggestions of results when Brand Y is what a visitor is searching for.

I feel this was not done on purpose, but sometimes a small mistake by a large company is enough to make a big impact in the ecosystem around them. While an apology may have been issued, it does not help with the loss in cash flow that many of the smaller companies rely to grow. Fortunately Flintobox survived to tell a story, many others may not.

SIGNUP NOW, join a free plan or a free trial to know whats best for you. 

Posted in eCommerce Site Search
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