Tag: ecommerce


Want to Open a Shopify Store? These Shopify Plug-ins are a Must Have

Posted on April 28, 2019 by


Shopify has single-handedly lifted ecommerce to a whole new level. By being affordable, easy to use and ready to deploy, Shopify has enabled even small retailers to take on the big guns. In addition to this, Shopify has also allowed retailers to add on applications to customize the platform in order to better meet the specific needs of each store.

In fact, Shopify has now reached a point where its app store is inundated with thousands of applications for wide range of needs. For aspiring as well as well-established online retailers, it is becoming increasingly difficult to find the right add-ons for their store in this clutter.

We understand the journey a retailer takes and have curated a list of apps which will help you get started and grow your business. The following apps have the highest ratings in their respective areas by the highest number of users.

 

Building your store – GemPages Page Builder

GemPages’ Page builder is a feature-packed store builder which lets you choose from thousands of stunning pre-built templates. You are not required to possess coding or design skills to make the most out of this app – you can easily build landing pages and product pages designed to convert visitors into customers. GemPages also allows you to integrate your store with Facebook Pixel and Google’ shopping catalog. With its easy-to-use features, GemPages can make it easy even for an absolute beginner to open a store on Shopify.

 

Inventory Management – Bulk Product Edit

Bulk Product Edit allows you to easily upload, update or remove hundreds of SKUs in a matter of a few minutes. You can simply upload a CSV or an excel sheet to the app and it will take care of populating your store with all the products. It also gives you the ability to schedule offers with the start and end date and undo multiple changes with a single click. As an added advantage, you can also upload the URL and meta descriptions for all your products in a few clicks. This ensures that all your pages are SEO-friendly and easily findable online. Since the hassle of inventory management is taken care of by BPE, you can save resources and time on an otherwise draining job.

 

Marketing your store – Kit

Kit recommends the right Facebook and Instagram marketing activities which are most likely to drive sales. With Kit, you can create dynamic ads, including retargeting ads to bring visitors back to your store. Since Kit is built with artificial intelligence, you are not required to have in-depth marketing and analytics knowledge to optimize your ads. The app works 24×7 to analyze your products, visitors and their interaction with your store to recommend your next marketing move to boost your sales. These features make Kit your cost-effective and personal marketing executive, who is always available to connect and brainstorm with.

 

Shipping and Tracking – Shippo

Shippo is a shipping and tracking app which provides you with discounted shipping rates for even large orders. Shippo allows you to connect with around 50 plus carriers from around the world and also provide your customers with accurate and transparent tracking information. In several instances, customers might love your products and offers and yet, not complete the purchase after taking a look at the shipping charges. With Shippo, you can get the best deals and ensure the timely delivery of your products to your customers.

 

Returns Management – AfterShip Return Center

AfterShip is a user friendly returns management system which makes it easy for your customers to return shipped products. With AfterShip, you can create custom returns policy, automated status notifications, all without your customers having to mail your store’s support desk. Allowing your customers to return products hassle-free can help build more customer-trust. With such a comprehensive solution, you can also save on the resources you would otherwise have to dedicate towards returns management.

Owning a successful ecommerce store isn’t determined only by providing your customers with what they need. In today’s competitive marketplace, it is necessary to go the extra mile and use novel methods to make a customer’s purchasing journey as effortless and enjoyable as possible.

 

At Tagalys we work to make this process easier, providing your online store with the ability to distinguish itself as the go-to store in any niche. Our solutions advance the visual merchandising capabilities of your store by understanding customer behavior and displaying products they are more likely to buy. To know more about our solutions, and how we can help you meet your merchandising objectives, please get in touch with us today!

Posted in e-Commerce General Site Reviews

The eCommerce marketer’s guide to using Tagalys

Posted on March 22, 2019 by


Marketing your ecommerce store can turn out to be quite a challenge. Right from understanding the ideal customer persona, identifying the right products to promote in your campaigns, bringing in traffic to your website, to ensuring that visitors have the shortest path to purchase on the website. A Marketer’s playbook can get quite complicated. 

Marketing in eCommerce

While there is no foolproof way to understand human behavior and deduce a perfect formula to crack the marketing for eCommerce code, using relevant data to drive your campaigns and other marketing decisions are the closest you can get to strike the perfect chord among visitors and/or customers.

To help you take those better data-driven marketing decisions, we have compiled 4 different ways that a Marketer can use Tagalys to enhance their online store’s marketing initiatives

Identifying the right products to promote in your Marketing Campaigns 

One of the key decisions an eCommerce store owner needs to make while setting up digital campaigns is to identify which SKU to promote. Tagalys analyzes every attribute assigned to each product to calculate a proprietary t-score, which is indicative of the popularity of a product within the store. Key metrics like the number of views, add to carts & purchases by segment etc. are factored in for the t-scoreThis will help in identifying the most popular / highest selling SKUs, which can then be used in your digital campaigns, ensuring the best possible click-through rate for your ads. This will also help in bringing in more traffic to your website, as compared to a non-data-driven SKU selected for the campaigns.

Ease of product sorting with Drag-&-Drop interface  

The t-score would give you the most popular product, but what if you wish to promote a seasonal product or put a few products on sale, and want it to be at the top or a specific position in your listing page? Tagalys makes it super easy for you to move around the products manually, with a simple drag-and-drop experience. So, whenever you feel the need for human intervention to override our data-driven algorithms, there is no need for coding to sort your products. Just drag and drop any product to any position that you wish. It’s as simple as that.

Create category pages for your eCommerce store in seconds 

Though this is something which would fall under the purview of the engineering team, generating category pages plays an equally important role in a Marketer’s playbook. Did you know that the number of listing pages in an online store is directly proportional to the probability of the store attracting organic search traffic? That’s how Amazon gets its vast amounts of trafficCreating listing pages on Magento or Shopify can be quite a tedious exercise, with each page taking 30 – 60 minutes, at a minimum. Plus, the customization options available are limited, i.e. creating a page for “Blue shirts” could be a tad easy, but creating a page for Blue shirts for weddings might be a bit more challenging, owing to the sheer amount of manual intervention it requires.  Now, with Tagalys’ proprietary listing page generator tool (which is also patent-pending), you can generate dynamic listing pages with automated SEO optimized content in a matter of seconds. You can literally create hundreds of search optimized pages in a day.

SEO friendly dynamic product and content refresh on category pages

SEO. One of the biggest challenges for an online store. Having to optimize each and every aspect to optimize your page for organic traffic can be a painstaking task with the sheer number of individual pages for an online store. With Tagalys, you can now add multiple SEO variables without any tech support – right from instantly modifying your page URLs to adding the relevant tags. Tagalys powered pages also have dynamic product sorting and content refresh, to keep the pages fresh and new at all times. This, in turn, helps your pages rank higher on SEO and Google searches, improving the discoverability of your pages through organic search.

There’s a lot more you can do with Tagalys as a Marketer. Sounds exciting and you would like to learn more? Book a Free Demo today with us today.

Posted in e-Commerce General

Amazon my mix – Personalized shopping feeds for ecommerce

Posted on July 19, 2017 by


In June 2017, Amazon.com made a quite launch of “My Mix”, a personalized shopping feed that curates “Interesting” products based on visitor interest.

My mix from amazon

Here is a company, that rules the market, commands your attention, for all purposes knows you will come back to Amazon tomorrow to check on on your next purchase. So why a personalized shopping feed?

Amazon, knows that tomorrow it will be fighting for visitor attention. Attention, not just from Walmart, Target, Alibaba etc., but from the millions of mobile applications that distract you in your shopping experience. Amazon, is fighting to keep you engaged at Amazon. Only then can the billions of dollars invested in R&D, supply chain, etc have any likelihood of influencing your purchasing decision.

What will start as a curation of “interesting products”, will tomorrow most likely be a curation of the entire store, to be delivered as a feed to you. Amazon understands, you the visitor are a busy person, engaging with the store usually on a mobile device.  The retailer knows what you want today or may want tomorrow. Given the data is available, Amazon is making the whole shopping process personalized. By this we mean, instead of you walking to the aisles or categories to find products, the aisles that are of personal interest, will come to you. All you have to do is walk into the store and the entire store will reorganize itself, to start showing you products of personal interest. This is personalization of e-commerce, where engagement data is used to predict shopper persona of what visitors are most likely going to buy.

Real time 1-1 visitor personalization always existed and with the lowered costs of computing power, it will be applied to across the product discovery journey in an e-commerce store. In the future, Amazon will ensure each shoppers product discovery channels will be 100% personalized, to ensure they get 100% of that shoppers attention. Lose attention, lose engagement, there will be no sale.

Why are we at Tagalys excited about My Mix? You will soon find out in a few more weeks. You can signup for Tagalys and get access to our full suite of product discovery solutions.

 

Posted in e-Commerce Personalization

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

Negotiating a Make vs. Buy when a retailer wants to build a Personalization engine for their eCommerce business

Posted on December 26, 2016 by


Ok. The title was a geared to help in SEO, but the points in this article are applicable to any Make vs. Buy decision when it comes to online retailers and buying technology.

As on online retailer, your goal is to try and ensure customers have great shopping experience. Some of the biggest challenges in retail is figuring out what to have in stock, inventory, pricing, supply chain, marketing and branding. That is the retail component. The online in retail is a channel and technology enables you to deliver a similar shopping experience in that channel. So should you build the online component or buy to enable shopping for customers who choose your digital channel? While there are many parts of the online channel like the platform, pricing tools, payment gateways, recommendations, site performance, Personalization etc., Lets go over some areas that will help you decide this make vs. buy decision.

What is you core competency?

The best way we have figured our core competency at Tagalys in make vs. buy decision, is asking ourselves if we had to sell out (not that we plan to), will that negotiation be hit if that component in technology was not part our our internal IP. So while the engine is always developed inhouse, we sometimes outsource aspects like the UI for our dashboard, charting, connectors etc., that we considered fairly commoditized So, as a retailer and you had to an offer to sell your company, how much will your offer reduce if you did not build the Personalization engine?

Do you have a different expectation for Personalization?

Personalization engines from Certona, Celebros, Tagalys etc., all run on different algorithms. Some tuned for speed, some tuned for increased personal relevance, some for both etc., If you were to build the same inhouse, are you trying to solve a different problem that cannot be already solved by existing players.

What is the 5 year return on investment?

If you choose to build and invest the money inhouse, will the ROI ((Revenue Generated/Monthly cost) * 60) be more that an external vendor. Lets assume you gather a great team and within a month build a product that generates equivalent revenue that one of these world class products. Will the cost to acquire the team, monthly salaries, churn (employees leaving and hiring new employees), server costs and adding new members to continue innovating be lower that the cost to buy the same over Period X

How long (pERIOD x) will it take to build a world class personalization engine?

When we define time to build, we are talking about the time from Day 0 when this engine can generate the same conversion rate of product views to impressions. That is how you measure if your engine is working at scale, by looking at this metric and not purely on the customer conversion rate. While we were liberal to assume it can be built in a month, truth is it absolutely cannot. With more resources time can reduce, but you need to also consider a learning curve and churn.

What is the opportunity cost of making inhouse?

This is the biggest variable that is not considered by retailers who choose to build inhouse. While cost is easy to assume assuming no churn and soft costs, it is almost impossible to quantify the revenue lost or left on the table during the period X when a retailer is building this product inhouse. And this lost revenue should also be multiplied by the internal rate of return (IRR) that is relevant to this company.

I have been fortunate to sit on the other side (Buyer) of the table in my previous avatar at Deloitte and my previous company, where I always negotiated to get the best value for my client and business. Hence it is important, to look at value through a Total Cost of Ownership lens vs. short term Cost/Price lens.

 

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

Posted in e-Commerce General

Image Search vs. Text Search in eCommerce

Posted on December 26, 2016 by


At Tagalys, we extract text data from the product catalog to start data enrichment, hence we are biased towards text-based tagging 🙂 But let us also share some of the advantages and disadvantages of the same so you can evaluate for yourself.

VERTICAL AGNOSTIC:

Tagalys can start working with an eCommerce company across any vertical and start showing improvements from day one. That is why we never hesitated to take on clients that sell apparel, shoes, accessories, jewelry, food and building material as long as they meet certain minimum requirements of scale. This is because, our engine relies on text data that is usually available in various parts of the product catalog and unlike image recognition we do not need any training data (vast sums), to reach a 90% accuracy in auto-generating tags.

DATA AVAILABILITY:

Image recognition products that are vertical focused extract tags from the image. The advantages are that if the engine is trained properly, it has the ability to extract fine details tags at scale with over a 90% accuracy. Hence an image of a dress can lead to extraction of externally visible tags tied to color, length, sleeve, neck, design etc., Text tagging engines like Tagalys rely on the content, hence if such details are missing they will not be considered in the analytics of visitor-product engagement. But this also means if Tagalys cannot find such tags, nor can your online visitors or search engines like Google that rely on text data to understand the product better. Hence it is in every retailer’s best interest to ensure all details about the product are clearly outlined in the product catalog to promote improved product discovery both in the website and also in search engines.

The second question is how much of an added benefit will the retailer have in terms of engagement/conversion/revenues by auto extracting tags from images? As mentioned below, costs for such a high accuracy image extraction engine are higher than text tagging, leading to higher prices for the customer.

COSTS:

As text-based tagging does not require vast sums of training data to get started, but on available data, our cost are much lower than image recognition companies.  The costs for an image recognition company are not only acquiring vast volumes of images to build a database but also the time it takes them to create this database as that impacts the NPV of cash on hand. As our costs are lower, these savings are passed on to you, the customer.

CORE COMPETENCY:

If a retailers problem statement is to improve personalization or showing the right products/content to the right visitors, then you need personalization engine like Tagalys, whose focus is to create data models that simulate the shopping persona of visitors. But if your problem statement is to auto extract tags from images as there is no content, then a visual recognition engine is what you need, provided it has been previously trained with millions of images in the same vertical.

APPLICATIONS:

A personalization engine like Tagalys can be applied to any channel where a visitor is likely to discover products. This could be a listing page, search results or a recommendations widgets.

Visual or image recognition engines, whose core competency is to identify the image and the metadata (tags) from the image is best applied in the Similar products recommendation widget. That being said, we recently worked with a jewelry retailer who switched from an Image Recognition to Tagalys recommendations and realized cost savings in monthly fees and higher revenues driven by better conversion from our recommendation engine.

Image recognition is also confined to verticals where there is enough data to improve the auto tag accuracy levels. If they need to be applied to any other features of eCommerce, then a personalization engine has to be built on top of the existing visual/image recognition engine.

ERROR TOLERANCE:

A combination of image recognition to extract the tags and human tagging might help reduce the error tolerance. Product catalog data that is a must-have for an e-commerce platform and is usually entered by humans. This task sometimes has errors or incomplete submissions, that can impact the pattern recognition algorithms in Tagalys. In over 90% of the cases, we find the data to be complete with some minute details missing by the data entry operator, but very seldom incorrect. This is also because incorrect data can negatively impact SERP score, as the content displayed on any listing page is based on the text data behind the product. Hence while we have seen good data from the catalog itself, adding an image based system to identify tags in verticals like fashion, can extract additional data that can be leveraged by Tagalys.

Try Tagalys for a 28-day free trial, to see the results, before you decide to spend 3X more on image recognition.  SIGNUP NOW

Posted in e-Commerce General eCommerce Site Search

Personalization for ecommerce – How did Tagalys start its journey?

Posted on December 26, 2016 by


Tagalys provides personalization of a service for ecommerce and our apis (using plugins) can be applied to personalize product discovery across channels like site search, recommendations and listing pages. Our founders did not wake up one morning and decide to build personalization as a service, it was built by accident.

In their previous avatar, Antony and Palani had conceptualized and built a social commerce platform as they saw a growing consumer need driven by the growth of eCommerce. The supply side of the platform consisted of a complex web of spiders crawling ecommerce sites for products and all public information about them. At its peak the platform covered over 3000 unique brands and over 8 million unique sku’s. The demand side consisted of consumers who were interested in online fashion and home décor shopping.

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Like most platforms, Monthly active users (MAU) was the primary metric of focus as that tied directly to their current and future revenue model. But how do you keep consumers engaged to ensure churn is minimal? How do you build an engaged community that will refer others to this platform?

Early metrics showed users spent over 9 minutes/session and the team was elated, but we also noticed the percentage of return visitors was not as expected. Post feedback with many users, we realized high session time is also an indicator that users being unable to find what they seek. Solving this problem was the advent of Tagalys. The founders first started by building their own analytics engine that collected visitor engagement data and also extracted meta data from products to  start extracting insights on why visitors might engage with certain products. The meta data also allowed to create data model or trend analysis to better understand the shopping persona of users. The first step was to start making sense of the data and apply the insights across search and listing pages, so products were sorted by what was most engaging site wide and not simply sorted by new arrivals etc., This logic helped increase engagement but still did not appeal to all users, as what maybe most engaging for user X might have no relation to user Y. The team then went onto analyze data at a user level and found out the high variances users have in preferences for the same category or subcategory of products. Thus the next steps was to  build a personalized view for each user for any page they engaged – Search results, Category pages, Recommendations. The end result was to showcase a unique set of products that match a user’s shopping persona and based on interaction with the assumed persona, to learn and continue improving the shopping persona to improve engagement.

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While founders were successful in delivery personalization at scale, as a business it failed. Failed due to unavailability of funds or maybe they were too early, but the learnings of this journey helped build the foundation of Personalization as a Service for eCommerce. When many of the users shared feedback on how such an experience was unavailable at regular eCommerce store, it got them thinking and made them pivot as they recognized the same need for eCommerce to help increase engagement, reduce their CAC and improve revenues.

Do share your feedback with us here or email us at cs at tagalys dot com

 

Posted in e-Commerce General e-Commerce Personalization

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

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

Personalization – Making your eCommerce store visitors feel LOVED has never been easier!

Posted on December 21, 2016 by


Signup now to improve your visitor engagement and save time reading the article. Or read and signup at the end.

The journeys that we find most memorable and wonderful are often the ones we take with people who make us feel truly special.

Winning your visitor’s heart on their journey to your e-commerce store is in fact not very different at all, when you make their journey a personal one that is close to their heart. Right from the time they enter to the time they register, to the golden moment they make a purchase, and even the stressful times when they abandon their cart or haven’t been in touch for a while.

In this article, we cover how your e-commerce visitors can enjoy a journey of a lifetime on your store when you personalize every aspect of it- one they remember for days, in fact even share with their friends and recommend to folks they care about.

But first, exactly what do we mean by personalization here? Is it simply just greeting folks by their name? Or showing them products that other people viewed after viewing a particular product. Luckily for e-commerce storeowners and customers, personalization has evolved into something way more powerful, predictive and well, personal than these techniques.

 The Advent of Personalization 2.0

Much like your favorite in-store sales personnel in the world, Jamal, today’s personalization tool is highly iterative, contextual, and real time. The engine is based on artificial intelligence, and thus, constantly learns and updates itself on each visitor based on their interactions as well as those of their counterparts, thus making each interaction more personal, more special, and more intimate than the last one. All this with no scope for human errors and that much more perfection and precision.

So, what are just some of the highly essential and relevant variables that are taken into account whilst personalizing a visitor’s journey?

Your Shopping Persona:

Everybody Loves Jamal!

Everybody Loves Jamal!

 Much like Jamal, who would notice your ensemble the minute you walk into the store to decide what kind of products to recommend to you, a robust engine tracks the journey of a visitor and extracts insights about their visitor based on how they interact with your store.

And just the way Jamal would recommend very different outfits to someone who wore a fun, blingy, high street outfit from Zara and someone else that wore an understated ensemble from Chanel, the engine would show distinct results for those who engage from an iPhone 7 (More premium, upscale products) looking for “Dresses”, as opposed to someone who is interested in “Dresses” using a regular smart phone (Products that would appeal to a price sensitive audience.)

Further diving into this concept, if a new visitor from Manhattan entered an e-commerce shoe store during peak winter she’d get very different results from a similar visitor from San Diego.

Explicit Surveys or Questionnaires

To understand the persona of your visitor, one way to get started is by incentivizing them to fill out out a survey before they start shopping. A great example of this is the beautiful wine site, Naked Wine, which woos its visitors to perfection by offering them 30 dollars to take a quick survey so they can create the perfect drinking persona!

Incase of a site that focuses on one particular category such as a smartphone which has a wide range in terms of pricing, a good idea could be to quickly ask for a budget range and then create a selection accordingly. Similarly, according to the category of the e-commerce site, similar variants can be made in terms of size, gender, and more.nakedwine-survey

Visitor interaction

Another way to understand your visitors shopping persona is my implicitly tracking their interests via a robust analytics engine. Much like once you go to your favorite brick and mortar store and Jamal your favourite sales personnel takes into account your personal tastes and preferences, the engine also partly bases its subsequent recommendations, listing pages, offers, etc next time you enter the store on your past behavior and actions. It remembers the ankle length boots that you added to cart but didn’t eventually buy. It also won’t forget that you spent a couple of minutes browsing that exquisite leather phone case but were pretty non-committal on it or that golden moment when you finally bought a black bomber jacket. (You badass, you!)

visitor product interaction

Visitor segmentation

And while the engine tries to understand your shopping interest and persona, it is also making a note of other people who might be similar to you in their shopping persona to start predicting what products that might interest you but are yet to be discovered by you.

shopper segmentation 

 

The objective of creating shopping personas is to ensure personal relevance in any interaction between your visitors and store. Improving personal relevance increases the conversion rate from a listing page (impressions) to a product page. More product views per visitor, increases the probability of sale conversion. Where can the actionable insights from a personalization engine be applied for an eCommerce store?

ONSITE ENGAGEMENT

Onsite channels in brick & mortar are similar to in-store sales, service, and promotions. Interactions that happen between visitors and your business within the walls of your store. In these eCommerce world, this is equivalent to

SITE SEARCH, LISTING PAGES, RECOMMENDATIONS WIDGETS, BANNERS & COUPONS

Over 90% of the interactions that lead your visitors to view products will happen across these channels. By extracting actionable insights from a personalization engine and applying it to these channels, each visitor will be catered a unique shopping experience engaging with products that are personally relevant to them or someone similar to them. We had discussed earlier about how the mobile first interaction by visitors has led to the attention economy. When visitor interaction with products in these channels becomes personally relevant, you keep your visitor engaged, allowing them to patiently discover products that appeal to them and finally convert to customers.

OFFSITE ENGAGEMENT

Offsite channels in brick and mortar would be similar to sending out direct mailers, promotional sms’s, etc. Basically anything outside the walls of the store to bring your visitors back to your store. In the eCommerce world these are equivalent to

MOBILE NOTIFICATIONS & EMAIL

Channels like mobile notifications and email. are the lowest cost to build re-enagement. Today, most online retailers send out mass notifications and email that reach every user in the store and may or may not be relevant to them. This spam like behavior has led to emails being confined to a separate tab in your inbox or users turning off notifications in mobile phones. This leads to low click through rates (CTR), reducing the visits generated back to the online store from these channels.

By considering the shopping personas generated by a personalization engine, retailers can not only save cost by sending notifications/email to the relevant users, but also increase CTR that leads to improved conversion rates & revenues.

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Posted in e-Commerce Personalization