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Lisa Mashn is a Natural Language Generation bot

Lisa Mashn is a Natural Language Generation bot. More specifically, she’s 3 types of bots into one: Maintenance bot, Chat bot and Twitter bot. Her job is to manage the end-to-end operations of Gamers Paradise, a French speaking Gaming webshop.

Gamers Paradise Natural Language Generation bot

Our NLG bots deal with English, French, German, Dutch and Spanish. We can also add 17 languages to this/

Natural Language Generation bot managing eCommerce websites

In my 10 years experience with eCommerce owners and wannabees, 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.

At Mash’n Learn, we are building robots whose Artificial Intelligence (or more specifically Machine Learning) is dedicated to achieve daily tasks a human can do.

The first results are more than satisfying since we managed to build robots that can produce and maintain thousands of Product Descriptions overnight by using the latest Natural Language Generation techniques.

Natural Language Generation backend

Lisa’s back end may look ugly at first sight…

The code behind the Lisa bot may look ugly, but it becomes beautiful when you realize that it can generate months of hard work in only just a few hours. The use of IBM Watson‘s capabilities at the pace of light is helping each bot to reach up to 25 thousands pages of content in only 5 hours. So fast it has to run between midnight and 5AM to avoid creating a burden on the websites performance.

From creating to categorizing

Lisa will create the Product descriptions, will manage the product categorization, the changes in pricing, the seasonal promotions, the new offers from the manufacturers and merchants and will tweet them and pin them on Social Networks.

All those operational tasks within the organisation such as overhead dedicated to merchandising and communication, which usually takes resources hundreds of hours, are reduced to almost nothing. If you are a starter, you can avoid hiring backoffice people. If you’re running a large organisation, you can shift your staff to more value added tasks instead.

Obviously, this cannot happen without a precise organisation and we use Automated Insights Wordsmith to do so. This Natural Language Generation tool has the best user interface so far on the Market. In a couple of hours, our clients can manage the building of text structures without any pain.

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.

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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)

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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

Why your robot should rewrite fresh Product Descriptions every week?

While our Mash’n Learn clients clearly understand the great value of having one of our Natural Language Generation robots to create their product descriptions, they usually wonder why we suggest to have those contents frequently updated.

Mash’n Learn’s Natural Language Generation robots fresh Product Descriptions frequently

fresh Product Descriptions

We discussed this with my SEO colleagues the potential need for fresh contents and we came up with the following observations:

Fresh Product Descriptions are good for Google/Bings/Yahoo SEO ranking

MOZ states that Google ranks based on frequency of content changes (The age of a webpage or domain isn’t the only freshness factor. Search engines can score regularly updated content for freshness differently from content that doesn’t change. In this case, the amount of change on your webpage plays a role.). Their full article for your own understanding here: https://moz.com/blog/google-fresh-factor-new.

MOZ fresh product descriptions

Fresh Product Descriptions are good for temporary Promotional contents

We can adapt the NLG template each time there is a promo or a related product we want to temporary push.

Last year, we rewrote all 40 thousands product descriptions for Conforama between Christmas and the January sales. It resulted into a hike in the conversion rate as the promotional code were directly visibles in the top description.

Fresh Product Descriptions are helping A/B testing

We can rapidly test during a short period multiple type of descriptions and their effect on Sales. We aim to raise the conversion rate.

Also, we are also using Prezzu as Pricing predictive pricing to increase our clients Gross Margin. Finding the fair pricing is a constant struggle and our Catalog automation tools help to ease that.

Fresh Content creates spikes in organic traffic

At Mash’n Learn, we fix your e-Commerce 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

Natural Language Generation for Media

Media Natural Language Generation is a growing feature. From finance to sports, from politics to millions of individualized stories, our partner Wordsmith is revolutionizing media. Companies like The Associated Press are expanding output by orders of magnitude and freeing up staff time, all while decreasing errors.
Media Natural Language Generation

Media Natural Language Generation is an essential component of our Retail suite

How does Media Natural Language Generation works? The 4implementation steps are similar to the eCommerce Mash’n Learn process:

1. Establish the automated content strategy

Depending on your goals, we have to build up to 4 different types of published contents: for email Marketing, for Twitter/Facebook, for a printed Journal/Magazine or for Product features.

2. Structuring Data and Contents

Create a Data Warehousing gathering all texts produced for similar contents. Depending on the targeted quality, this process can take a while. The more source content we use, the more human the automated generated articles will be.

3. Build the outputs

From all the content templates, we build a significant number of generated scenarios that will be tested during 2 weeks until all stakeholders agree on the result.
Automated Insights Wordsmith

4. Integrate with all interfaces

Our skills at Mash’n Learn are Data Mining and Integration with information systems and publishing tools (HTML, eCommerce platforms, Adobe suite, Social Media). We will your Natural Language Generation robot to be quickly ready to be autonomous.

Media Natural Language Generation: we can help

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

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

For a Media Natural Language Generation project, this is an Alpha implementation planning that target going live within two weeks (assuming all resources are available):
Media Natural Language Generation planning

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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

What is Natural Language Generation?

At Mash’n Learn, our biggest challenge is to produce 300+ words description for thousands of catalog products. We achieve this using the Research & Development we invest on Natural Language Generation.

Natural Language Generation

Natural Language Generation: the Quora definition

Natural language generation (NLG) is the natural language processing task of generating natural language from a machine representation system such as a knowledge base or a logical form. Psycholinguists prefer the term language production when such formal representations are interpreted as models for mental representations.

It could be said an NLG system is like a translator that converts a computer based representation into a natural language representation. However, the methods to produce the final language are different from those of a compiler due to the inherent expressivity of natural languages. NLG has existed for a long time but commercial NLG technology has only recently become widely available.

Check out how we use it for e-Commerce

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.

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

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

Mash’n Learn Catalog Automation in Houston Dec 8-11 2016

Along with the Belgian Economic Mission to Texas, Mash’n Learn will be showcasing its Product Tool Suite for any e-Commerce Catalog Automation in Houston Dec 8-11 2016. We will show how retailer can integrate and enhance their large catalog in a extremely short timeframe thanks to IBM Watson’s Artificial Intelligence.

How to massively produce and maintain Product content on your e-Commerce

Mash'n Learn features on Catalog Automation in Houston

Mash’n Learn Catalog Automation in Houston for its first US roadshow

Now that the proof-of-concept implementations had a good success in France, we’re ready to start building real large catalogs in USA.

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 Automation 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

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