END-TO-END CATALOG PRODUCT AUTOMATION

You will find all our news and informations about Product Catalog Management in this section. We cover all Product oriented artificial intelligence.

Product Catalog Management is Mash’n Learn core business

Our Product Catalog Management uses all the latest innovations on Text Mining. Text mining, also referred to as text data mining, roughly equivalent to text analytics, refers to the process of deriving high-quality information from text.

High-quality information is typically derived through the devising of patterns and trends through means such as statistical pattern learning. Text mining usually involves the process of structuring the input text*, deriving patterns within the structured data, and finally evaluation and interpretation of the output.

‘High quality’ in text mining usually refers to some combination of relevance, novelty, and interestingness. Typical text mining tasks include:

  • text categorization,
  • text clustering,
  • concept/entity extraction,
  • production of granular taxonomies,
  • sentiment analysis,
  • document summarization,
  • entity relation modeling (i.e., learning relations between named entities).

* usually parsing. This is used in addition of some derived linguistic features and the removal of others, and subsequent insertion into a database.

Product Description Generator for eCommerce

For 2 years, Mash’n Learn has been providing tools to generate Product Description Generator for eCommerce for each of your saleable items.
Product Description Generator

Installing our Product Description Generator

We offer e-commerce businesses the ability to write product descriptions at scale in a fraction of the time needed by a team of writers and at a fraction of the cost.

While writing product descriptions at scale offers obvious benefits, the proverbial white whale of e-commerce is personalizing product offers at scale. Having a well-written, one-size-fits-all product description generator puts you ahead of competitors that offer a set of nebulous specs in a table. But your best shot at converting shoppers comes from their feeling like you are catering specifically to them.

Getting fresh product descriptions will increase the number of pages indexed by Google and Bings. Since a massive number of well-written contents are made available to the web, your website authority is rising and your products keywords reach the first page of the search engines.

At Mash’n Learn, we fix your Catalog content with Machine Learning

From Natural Language Generation to Predictive Analysis, Mash’n Learn provides a complete tool suite for the large catalog retailers.

You can fill this form to have us to contact you

Get a call from us

Your Name (required)

Your Email (required)

Your Phone number (if you want us to call you)

Or you rather get a phone call, here are the numbers you can reach us with:
USA: (314) 399 82 87
UK: (203) 318 23 02
France: (01) 76 39 00 41
Belgium: (04) 268 03 33

The main struggle that eCommerce shops do face is around bad day-to-day management. Running an eCommerce shop is exactly like running a traditional retail business. You have to spend all available minutes of your day chasing customers and improving documentations.

Most of eCommerce starters think that they just have to wait for customers to order

To be plain profitable, an eCommerce shop has to be managed by 4 types of profiles: an online marketer, a product merchandiser, a supply manager and finally an integration manager. Those 4 functions are mandatory to get above the bar of 10k$ per month of revenues.

eCommerce Merchandising Automation

Reduce your workload by implementing eCommerce Merchandising Automation using Natural Language Generation. Our suite will hike your organic traffic.

eCommerce Merchandising Automation with Natural Language Generation

eCommerce Merchandising Automation will reduce your overhead

Connecting your product feed or item database will feed our bot with plenty of attributes and features. From those values, it will build and maintain your product descriptions.

eCommerce Merchandising Automation will increase your revenues

Getting fresh product descriptions will increase the number of pages indexed by Google and Bings. Since a massive number of well-written contents are made available to the web, your website authority is rising and your products keywords reach the first page of the search engines.

eCommerce Merchandising Automation will fasten your time-to-market

With IBM Alchemy Language, our bots can understand up to 17 languages. This means that we can build your entire catalog in German, French, Dutch, Spanish, Italian and obviously English.
The main bottleneck for an international deployment is the catalog merchandising part. Uploading your products usually take a long time while translating them makes it even slower. This is exactly the reason why a group of eCommerce and Affiliation experts like us invested in Catalog Merchandising Automation.

Mash’n Learn also provides those types of automation services to Media and Blogs.

At Mash’n Learn, we fix your Catalog content with Machine Learning

From Natural Language Generation to Predictive Analysis, Mash’n Learn provides a complete tool suite for the large catalog retailers.

You can fill this form to have us to contact you

Get a call from us

Your Name (required)

Your Email (required)

Your Phone number (if you want us to call you)

Or you rather get a phone call, here are the numbers you can reach us with:
USA: (314) 399 82 87
UK: (203) 318 23 02
France: (01) 76 39 00 41
Belgium: (04) 268 03 33

COLAS – Product Categorization and Integration through Machine Learning

Mash’n Learn has been taken along with BHI to improve the Product Categorization and Integration at COLAS, the Engineering company part of Bouygues group.

Catalog Categorization

Product Categorization though Machine Learning

Rationalizing the Product Catalog through categorization and complete integration can help any large organization to:

  1. Control the Costs
  2. Rationalize the Sourcing
  3. Share information inside the companies more efficiently
  4. Allow promotional testing of slow moving products

Thanks to the gain of productivity from the Machine Learning bits, the workload needed to analyse, sort and publish product data is heavily reduced. As soon as a catalog reaches 15 thousands products, the organization needs 4 fulltime equivalent employees just to maintain the data.

That workforce could be spared for value added tasks like negotiating and optimizing the supply chain.

At Mash’n Learn, we fix your Catalog content with Machine Learning

From Natural Language Generation to Predictive Analysis, Mash’n Learn provides a complete tool suite for the large catalog retailers.

You can fill this form to have us to contact you

Get a call from us

Your Name (required)

Your Email (required)

Your Phone number (if you want us to call you)

Or you rather get a phone call, here are the numbers you can reach us with:
USA: (314) 399 82 87
UK: (203) 318 23 02
France: (01) 76 39 00 41
Belgium: (04) 268 03 33

WooCommerce Product Categorization by Applying Machine Learning

At Mash’n Learn, all our features are built to reduce e-Commerce pain and by Research & Development. WooCommerce Product Categorization by Applying Machine Learning has been inspired by the great work of Sushant Shankar and Irving Lin from the Department of Computer Science at Stanford University.

WooCommerce Product Categorization

Our Lab developed a set of functions analysing Categories from our Product Feeds partners

The functions we built are analysing the hundreds of categories from stores in Home Design and Electronics and turning them into a well designed and simplified category tree. This is mostly important for Home pages as we recommend e-Commerce owner to limit their main parent categories to maximum 10.

3 categories can be featured from the home page and 7 others in the Menu links. Above 10, we highly recommend to think about splitting their catalog in multiple shop or subsection (e.g. splitting Home and Garden into 2 separate stores).

The rationalization of categories helps the user to have a greater experience browsing a store. If it takes multiple pages and levels to find the right product, your shop’s conversion rate will struggle.

At Mash’n Learn, our CEO‘s e-Commerce experience as well as our CSMO‘s Supply Chain & Lean Manufacturing years in this topic can give a boost to your company Sales growth.

The research that inspired our WooCommerce Product Categorization feature

Applying Machine Learning to Product Categorization. Irving Lin, Sushant Shankar. [pdf]

Small to medium sized businesses who sell products online spend a significant part of their time, money, and effort organizing the products they sell, understanding consumer behavior to better market their products, and determining which products to sell. We would like to use machine learning techniques to define product categories (e.g. ‘Electronics’) and potential subcategories (e.g., ‘Printers’).

This is useful for the case where a business has a list of new products that they want to sell and they want to automatically classify these products based on training data of the businesses’ other products and classifications. This will also be useful when there is a new product line that has not been previously introduced in the market before, or the products are more densely populated than the training data (for example, if a business just sells electronic equipment, we would want to come up with a more granular structure). For this algorithm to be used in industry, we have consulted with a few small-to-medium sized companies and find that we will need an accuracy range of 95% when we have enough prior training data and a dense set of categorizations.

At Mash’n Learn, we fix e-Commerce with Machine Learning

From Natural Language Generation to Predictive Analysis, Mash’n Learn provides a complete tool suite for the large catalog retailers.

You can fill this form to have us to contact you

Get a call from us

Your Name (required)

Your Email (required)

Your Phone number (if you want us to call you)

Or you rather get a phone call, here are the numbers you can reach us with:
USA: (314) 399 82 87
UK: (203) 318 23 02
France: (01) 76 39 00 41
Belgium: (04) 268 03 33

WooCommerce Natural Language Generation

Our WooCommerce Natural Language Generation plugin interact with our server in order to generate Products massive upload (up to 25 thousands products per night for a WooCommerce shop). These Product Descriptions are reworked until they’re fit for SEO and for readability.

WooCommerce Natural Language Generation

Lisa and Virginia, the WooCommerce Natural Language Generation bots

Our server uses the IBM Watson Alchemy Language API to create the keywords used by the bot to build additional texts to the product features. This way, our contest are not only about features but about the problems or the pain it solves.

e-Commerce Catalogs suffer from the same flaws than traditional commerce. Bad salesmen are trying hard to sell product features rather than selling the value it brings to the prospect. Our Machine Learning bot fixes it by emphasizing on non-product keywords so it become more relevant to final users searches.

Our bot also makes it possible to launch a 25k products catalog overnight. This can greatly help Marketing to test new markets before investing heavily in it. Most of our English and French speaking customers ask us to launch pop-up stores with German product contents.

Read our case study on Garden Orchid’s extended catalog

Check out our case study:
Case Study mashnlearn-casestudyphytesiauk_01

Do you have a large catalog of products? We sure can help you to reduce the overhead!

We can help you automating most of your e-Commerce maintenance tasks. We use WooCommerce Natural Language Generation and Artificial Intelligence to build operating bots. These bots are delivered to increase profit by reducing overhead costs of maintaining a catalog or sourcing of your products

You can fill this form to have us to contact you

Get a call from us

Your Name (required)

Your Email (required)

Your Phone number (if you want us to call you)

Or you rather get a phone call, here are the numbers you can reach us with:
USA: (314) 399 82 87
UK: (203) 318 23 02
France: (01) 76 39 00 41
Belgium: (04) 268 03 33

Artificial Intelligence matchup: Mash’n Learn seeks RankBrain

We are training our Mash’n Learn robot to find and meet Google RankBrain: All the e-Commerce Product descriptions are built towards RankBrain algorithm.

RankBrain Artificial Intelligence for SEO

What is RankBrain

RankBrain is an algorithm learning artificial intelligence system, the use of which by Google was confirmed on 26 October 2015. It helps Google to process search results and provide more relevant search results for users. In a 2015 interview, Google commented that RankBrain was the third most important factor in the ranking algorithm along with links and content.

If RankBrain sees a word or phrase it isn’t familiar with, the machine can make a guess as to what words or phrases might have a similar meaning and filter the result accordingly, making it more effective at handling never-before-seen search queries.

There are over 200 different ranking factors which make up the ranking algorithm, of which their exact functions in the Google algorithm are not fully disclosed. It seems that RankBrain interprets the user searches to find pages that may not have contained the exact words that were used in the user search query. When offline, RankBrain is given batches of past searches and learns by matching search results. Once RankBrain’s results are verified by Google’s team the system is updated and goes live again.

Mash’n Learn Catalog automation seeks RankBrain’s criterias

During our first 3 implementations, we managed to create up to 110 thousands of catalog products and integrate them in WooCommerce and Magento. We reached recently a peak of product descriptions generation at 27 thousands during 4 hours at night.

Since our latest releases, Mash’n Learn can fetch data directly from ERP (mainly SAP and JD Edwards) and publish it to advertising platforms as well as GS1 GDSN feeds. Our instances are running on Magento, DemandWare, WooCommerce, Amazon SellerCentral and Prestashop. We also have built integrations to fit built-in inhouse online platforms.

Read our case study on Garden Orchid’s extended catalog

Check out our case study:
Case Study mashnlearn-casestudyphytesiauk_01

We would be happy to explain our Mash’n Learn Catalog in Houston in December.

Do you have a large catalog of products? We sure can help you to reduce the overhead!

We can help you automating most of your e-Commerce maintenance tasks. We use Artificial Intelligence to build operating bots. These bots are delivered to increase profit by reducing overhead costs of maintaining a catalog or sourcing of your products

You can fill this form to have us to contact you

Get a call from us

Your Name (required)

Your Email (required)

Your Phone number (if you want us to call you)

Or you rather get a phone call, here are the numbers you can reach us with:
USA: (314) 399 82 87
UK: (203) 318 23 02
France: (01) 76 39 00 41
Belgium: (04) 268 03 33

WooCommerce Predictive Pricing by Machine Learning

At Mash’n Learn, we integrate Prezzu in our Catalog Automation Suite. Prezzu is a software solution that delivers Predictive Pricing by Machine Learning for online retailers – Pure player or not. We created the WooCommerce Predictive Pricing module based on it.

WooCommerce Predictive Pricing by Machine Learning

WooCommerce Predictive Pricing to raise your Gross Profit

Prezzu automatically adjusts prices on catalogs of hundreds of thousands of items, day after day. Prezzu goes beyond business rules by using predictive algorithms to generate prices maximizing turnover under margin constraints. Prezzu responds optimally to competition prices, cross effects among same-range products, the incidence of promotions and markdowns, and can generate optimal prices as a function of inventories.

Your sales data is a gold mine: Your historical sales data are a mine of information to anticipate the response of sales to a change in prices. Use them and improve your pricing performance.

Who is Prezzu for? Prezzu was designed for on-line retailers wishing to automate their pricing on the basis of a robust predictive solution. Prezzu is also for off-line retailers wishing to make the most of their data and emulate the technological innovations of e-commerce.

Set optimized prices and split test them. The reaction of quantities to a price change, combined with unit costs, determines the optimal prices that maximize the margin volume or sales. It also cab be used to move inventory at the best conditions within a set target date.

Measure the impact of promotions and all exogeonous effects. Prezzu assesses the impact of price markdowns (flash sale, special offers, etc.) and isolates the pure promotion effect from the impact of the price markdown itself.

At Mash’n Learn, we optimize your e-Commerce with Machine Learning

From Natural Language Generation to Predictive Analysis, Mash’n Learn provides a complete tool suite for the large catalog retailers. We can help your online pricing to reach towards perfection.

You can fill this form to have us to contact you

Get a call from us

Your Name (required)

Your Email (required)

Your Phone number (if you want us to call you)

Or you rather get a phone call, here are the numbers you can reach us with:
USA: (314) 399 82 87
UK: (203) 318 23 02
France: (01) 76 39 00 41
Belgium: (04) 268 03 33

Product description copywriting by a Bot

Our main App features product description copywriting by a Bot. Artificial Intelligence, with the help of IBM Watson, Yoast and Moz, has helped Mash’n Learn to produce one of the helping tool for all e-Commerce Merchants.

Product description copywriting is the main task for a Merchant

Whatever the industry and the platform, copywriting great contents for Google search engine is a complex and long task.

You can get Content Copywriters on the Market for a cheap cost, but you will still have to wait for quite a long time before they produce description for more than 100 products.

Most of the successful Merchants have more than ten thousands SKU references. We estimated with our Content provider that thirty thousands descriptions of 300+ words would take more than three months to produce.

Product descriptions on our prototype webshop

Casa Decoration has been used since 2015 by the development team to test research apps. This below image show a mattress that has been described by our Product description copywriting bot:
Product Description Copywriting

Contact us at Mash’n Learn for more info about Product description copywriting

We can help you automating most of your e-Commerce maintenance tasks. We use Artificial Intelligence to build operating bots. Those bots are delivered to increase profit by reducing overhead costs of maintaining a catalog or sourcing of your products

You can fill this form to have us to contact you

Get a call from us

Your Name (required)

Your Email (required)

Your Phone number (if you want us to call you)

Or you rather get a phone call, here are the numbers you can reach us with:
France: (01) 76 39 00 41
Belgium: (04) 268 03 33
USA: (314) 399 82 87
UK: (203) 318 23 02

Product description copywriting is using the latest Text Mining innovations

AlchemyAPI is a SaaS platform that enriches textual content through automated tagging, categorization, linguistic analysis, and semantic mining. Available as both a free online API and commercial subscription service, AlchemyAPI is used by online publishers, news aggregators, and contextual advertising firms world-wide to understand and monetize online content.

“Our sentiment engine provides the ability to identify opinions within vast quantities of data,” said Elliot Turner , CEO of AlchemyAPI. “Sentiment analysis is critical for organizations wishing to understand consumer trends and customer perceptions, and AlchemyAPI’s semantic technology provides best-of-breed capability.”

Built to power a variety of product and data-mining use cases, AlchemyAPI offers multiple modes of sentiment analysis functionality. Document-level, entity-level, and keyword-level sentiment mining is provided–in addition to support for advanced features such as negation handling, sentiment amplifiers / diminishers, slang, and typos. “AlchemyAPI has been specifically tuned to understand user-generated, short-form social media content as well as editorialized text”.

Phytesia UK - Catalog Machine Learning

Case: Catalog Machine Learning in UK

This case is about Catalog Machine Learning in the Home & Garden business. The benefits of the Machine Learning Product Listing Advertising are described in this document.

About Phytesia

With approximately 500k € in annual online revenue, 10 employees, one breeding lab, 3 distribution platforms and 3 transit points, Phytesia is the leading producer and distributor of hardy orchids in Europe.

eCommerce Merchandising Facts

  • Due to the significant range of orchids accessories, it creates inventory risk;
  • To update the (enriched) content of the extensive product catalog is very labor intensive;
  • How to find the right keywords in an ever changing online market becomes challenging;
  • Despite all efforts, current site traffic continues to be flat and too low..

Project and Objectives for Mash’n Learn

UK and Germany are the top markets for flowers purchasing in Europe. Though they are very large, they are also difficult to enter. Prospect visitors expect a large choice of products as well as high informational quality content. Besides this, they won’t visit a web site unless it’s visible on either Google, Bing or Yahoo preferably on the first page.

Phytesia had grown in recent years, mainly through an aggressive commercial policy towards wholesalers, which resulted in a significant increase in the number of products to manage. Each product had a different set of logistics, requiring Phytesia to reorganize its network and processes. At first, a half time staff was dedicated to enrich content data as well as organizing PPC ads and weekly newsletters.

However, Phytesia’s competitive advantage comes from having the best array of rare orchids. The complexity of Phytesia lies in the fact that its brand is relatively unknown and most of the gardening hobbyists only do know about tulips, roses and begonias. Therefore, Phytesia decided to request LR Physicshelp in order to build an innovative and highly reliable aggregated website (i.e. pumper site), which should enforce the local UK identity and also should be able to present as many orchids growing products as possible.

Day-to-Day

Phytesia’s daily marketing tasks are mostly about gathering and analysing consumer behaviour data on its website by using Google Analytics. Until recently, all products showing traffic traction were closely looked at. Every day, a copywriter spent some hours to improve the current product content. The remaining part of the time was spent on publishing the targeted product into Social networks and implement PPC campaigns to aim for better site traffic and related purchase conversion.

In addition, Phytesia had to provide product information to hundreds of retailers. The Demand Planning process includes collecting information from these field operations, including promotions, assortments and seasonality to define a demand plan which converts dynamically into a production and corresponding distribution plan.

Today Phytesia manages this process with the Mash’n Learn MLPLA (Machine Learning Product Listing Advertising), which is capable of identifying, analyzing and enriching product content based on gathered information over the internet. To manage the keyword analysis, MLPLA uses the latest IBM Watson built in technologies.
The set of APIs are analysing users feeling about the product keywords and then mining the web and Phytesia’s library for text. The goal is to make sure all key products are ranking as high as possible on Google search engine.

 

Results and Benefits of a Catalog Machine Learning

  • Mash’n Learn was able to identify the  top keywords based on Product information;
  • The MLPLA tool set  based on machine learning technology translates keywords data into usable quality information product content;
  • Phytesia brought its UK organic daily visits from 20 to 300, tripled the sales revenues and introduced 26 orchids accessories and bundles;
  • All Phytesia products reached page one of Google and reached twice the top 10 Home & Garden sales on Amazon UK;
  • The Product content management workload was reduced from 1.5 to .5 FTE, creating the opportunity for the Marketing staff to focus on A/B testing and new advertising opportunities;
  • A significant improvement on the conversion rate were realised as the content quality reached up to 10/10 on Google Adwords. Therefore more and more qualified organic traffic caused a doubling of the conversion rate which resulted in revenue increases up to 450% in the UK only;

MLPLA software is used for managing Product information and to provide content to wholesalers. Online direct sales are having an indirect effect on wholesale as Gardening retailers request for Phytesia product is now rising as it outbids the biggest Home and Garden retail chains in the UK. Since growth is tangible, MLPLA proved to be a fundamental tool to support decision-making at the strategic, tactical and operational levels, all with the same base data.

MLPLA is a turnkey software that can easily be implemented within a maximum of 10 days depending on the company’s eCommerce and / or ERP environment. The MLPLA’s ‘Pop Up’ functionality can also create an instant store from scratch on a WooCommerce (WordPress backbone) instance.

About Mash’n Learn

Mash’n Learn is a Tool Suite based on catalog machine learning designed and developed by LR Physics with Stephan Pire’s Supply Chain and eCommerce experience. The ML Tool Suite uses all the latest science on Catalog Machine Learning and is taking advantage on the R&D capabilities of LR Physics. Managing over more than 15 websites for his holding and for his clients, Stephan Pire has identified all the repetitive tasks that could be optimized by a powerful Machine Learning set of algorithm.

The innovative and advanced technologies enable you to daily brass thousands of extensive Product data and automate your end-to-end marketing processes. Mash’n Learn’s solutions span key marketing platforms areas such as Google PLA, Amazon Seller Central, Facebook Products and Pinterest integration.

Since April 2016, Mash’n Learn gained the trust of various online retailers with whom we’re partnering today in order to get more qualified traffic and related sales revenue. The catalog machine learning Tool Suite also includes Artificial Intelligence integration for Supply Chain Demand Management, Sourcing and ERP Product Catalog.

For any additional information, please visit our website at www.mashnlearn.com and click on “About Us” for a list of our offices in Belgium, France, USA and UK. Or you can fill up this form:

Get a call from us

Your Name (required)

Your Email (required)

Your Phone number (if you want us to call you)

Powered by themekiller.com anime4online.com animextoon.com apk4phone.com