Natural Language Generation Software For Product Description Copy Writing(old)4

NATURAL LANGUAGE GENERATION (NLG) AI

What sets Writesof apart from other natural language generation software?  With our artificial intelligence systems, text generation is performance driven.  Messages are constructed based on user behavior.  Keywords are positioned by search visibility and engagement.  Our NLG technology works by adapting to changes in search visibility, audience engagement, and competitor environments.   Text output can be customized by user or audience attributes, and can adapt to changes in performance data.  Each natural language system that we build is unique, writing with a particular style (voice).

based on performance.  Messages are tuned by user behavior and .  systems are unlike anything else used in computational linguistics.  Each Writesof machine (NLG persona) that we deploy is in competition with every other Writesof machine in our arsenal.  Machines compete against other machines, and also compete indirectly against human writers and peripheral marketing objectives.  Unfortunately, due to certain legal obligations, we are not at liberty to disclose details of our AI with clients.  But essentially our natural language generation software is built on proprietary AI that “learns” and improves by analyzing measurable features of message performance, for example, user engagement, market visibility, and competitor metrics.

Each NLG machine, or “writer persona” that we deploy is constantly evaluating the quality of what it writes, learning and adapting to changes in audience engagement and competitive environments.  Collectively, NLG personas share performance information with one another,  also serving as performance benchmarks among various intersections of topics and audiences.  Personas can be customized and trained by one or more human writers or, in certain cases, they can be autonomously trained by other well established personas, along with user engagement data.   Each persona is either established with a specific “voice” (writing style), for example, a brand, or is built to be adaptable to alter its writing voice by analyzing audience engagement metrics.  Message performance is always determined by human oversight.  For example, message performance can be goal-oriented, rule-based, with restrictions, limitations, and risk-reward features controlled by human managers.  Human oversight of a persona’s writing voice is typically built around a set of audience characteristics, some of which are configured by human understanding, while others may be built on data analytics, typically a combination of both.

Personas can be cloned and reconfigured to target different audience segments or to make adjustments to content subject and topic features.  NLG personas semi-autonomously learn voice and writing style by modeling linguistic characteristics from sources of author and brand content.  Most crucial to our NLG AI capability is our proprietary data, to include retail consumer data and product message analytics data.  Our big data is like fuel that accelerates machine learning and computational linguistics processing, empowering our Writesof NLG personas to produce higher value content for online retailers, product manufacturers, B2B merchants, and long assortment consumer product brands.

NATURAL LANGUAGE GENERATION AI

What sets us apart from other natural language generation software?  Our NLG is built to integrate seamlessly with e-commerce systems and data.  Our AI utilizes a treasure trove of e-retail data and customer data.  Like other NLG systems, we employ advanced computational linguistics algorithms and natural language processing tools.  We use proprietary e-retail data and customer engagement data that  that reinforce our AI and machine learning.  And we use content engagement analytics t systems and data are trained  are trained to write product copy.  with AI and machine learning developed specifically for h NLG system, which we call NLG “personas”, to write high performing product copy with a distinct generative writing style.  A persona creates content by first performing deep analysis on relationships between word usage and customer behavior.  Millions of computations occur before a single word is written. Each generated message is self-monitored, word for word, for ROI and conversion metrics.  This and other customer data utilized in machine learning processes that help train and improve decision confidence, with every edit.  In most use cases, the client will already have tons of product pages, which means, at first, most of these can be used as static benchmarks for ROI, conversion rate,

Tbig data, and Our AI is powered by proprietary e-commerce data that helps our trainNLG make well-informed decisionscan create dozens of unique product descriptions, ads, and marketing notifications, for every product that you sell.  Similar to other automated personalization marketing software,  Writesof uses proprietary algorithms, machine learning, and data sets, each designed to interact with online customers.  The system interprets and evaluates customer data and linguistics data,  analyzing how each customer interacts and engages with each message.  This enables Writesof to deliver one of the most advanced natural langauge systems, one that has been formally trained to write good copy.  If you sell physical products online, you have a competitive duty to present them, in a personalized manner, to online customers.  Customers want to be convinced on the value of your products’ physical attributes, intangible qualities, use benefits, and quality assurance in a manner that makes the click “Buy” with a winning smile on their face.  Customers feel that they deserve special treatment and good copy, as well as informative content, are message drivers that help give customers a sense that they got a good deal.  Strategically worded messaging encourages customers to buy and makes them feel like they got a good deal.  Good information helps overcome objections.  And hitting the right tone on messaging makes them smile during checkout.   to buy and  that highlights physical attributes, qualitative features, customer benefitscopy about physical products.  online merchants, product brands, and manufacturers.  If you, and manufacturers  customers interacts with the messa of the generated text that it generates.  ustomer behavior analytics, to quantifiably match-make our messaging with predicted user intent.  Customer data, paricularly behavior and demographic data, when full value is extracted, translate to quality and performance scores for your landing pages and push messages.  Writesof harnesses the power of this data to train our natural language generation systems how to adapt to user intent, with respect to campaign settings.  We use machine learning and predictive decision models to perform measured edits of each narrative, rewarding our system with new expermiments when high-value edits are made and restricting or rolling back edits when poor edits are made.  As quality goes up, A/B testing of new and unique messages is broadened.  When quality goes down, messages either revert to the original benchmark or some other higher performing version.

Tbig data, and Our AI is powered by proprietary e-commerce data that helps our trainNLG make well-informed decisionscan create dozens of unique product descriptions, ads, and marketing notifications, for every product that you sell.  Similar to other automated personalization marketing software,  Writesof uses proprietary algorithms, machine learning, and data sets, each designed to interact with online customers.  The system interprets and evaluates customer data and linguistics data,  analyzing how each customer interacts and engages with each message.  This enables Writesof to deliver one of the most advanced natural langauge systems, one that has been formally trained to write good copy.  If you sell physical products online, you have a competitive duty to present them, in a personalized manner, to online customers.  Customers want to be convinced on the value of your products’ physical attributes, intangible qualities, use benefits, and quality assurance in a manner that makes the click “Buy” with a winning smile on their face.  Customers feel that they deserve special treatment and good copy, as well as informative content, are message drivers that help give customers a sense that they got a good deal.  Strategically worded messaging encourages customers to buy and makes them feel like they got a good deal.  Good information helps overcome objections.  And hitting the right tone on messaging makes them smile during checkout.   to buy and  that highlights physical attributes, qualitative features, customer benefitscopy about physical products.  online merchants, product brands, and manufacturers.  If you, and manufacturers  customers interacts with the messa of the generated text that it generates.  ustomer behavior analytics, to quantifiably match-make our messaging with predicted user intent.  Customer data, paricularly behavior and demographic data, when full value is extracted, translate to quality and performance scores for your landing pages and push messages.  Writesof harnesses the power of this data to train our natural language generation systems how to adapt to user intent, with respect to campaign settings.  We use machine learning and predictive decision models to perform measured edits of each narrative, rewarding our system with new expermiments when high-value edits are made and restricting or rolling back edits when poor edits are made.  As quality goes up, A/B testing of new and unique messages is broadened.  When quality goes down, messages either revert to the original benchmark or some other higher performing version.

toward the benchmark    Writesof harnesses the power of this data your landing pages and push notifications are working.   suchcustomer behavior analyticsombined with ,  , millions of powered by proprietary data on millions of unique products, transaction data and customer behavior data.  We use this data in conjuction with our online retail AI and machine learning customer profiles.  Our lexicons were developed in-house, from millions of live product descriptions.  We are capable of extracting and analyzing product information and messaging assoicated with any category or class of product.  as well as lexicons built from Online Retail  that no other natural language generation company has the ability to access.  We also maintain large libraries of product information and classified lexicons that help train our AI specifically to describe physical products.   retrieved from a of product information and data signals that accelerate machine-learning-driven decision algorithms.  Our NLG is the first available technology that can automatically develop “author personas”, or virtual machines that autonomously model their respective writing styles after human authors.  The system can actually predict how an author would write about a subject or topic that she has never written before.  Each NLG persona can learn how to interact with different people by assigning it with simple goal-oriented objectives, such as increasing time-on-page or conversion metrics.

Writesof’s mission is to empower writers to focus more on the interactive aspects of writing, such as angles, tone, and personalization, delegating the elemental and analytics-based writing workflow to Writesof.

NATURAL LANGUAGE GENERATION AI

trains and improve decision confidence  processing text and analytics data, then automatically editing higher performing messages that The content that a persona creates is directly tied to a relatively finite depth and breadth of a “learned” brand voice, with a distinct writing style.  Writesof’s Pessage Message Analytics platform,  to write top-performing product copy.  We refer to our NLG systems as “personas”.  And yes, we give them names – sorry.  personas as a “persona”G “personas”  Second, each persona “learns” to write content in a specified brand voice by analyzing quality-validated source text from selected authors, domains, and brand websites.  Third, Writesof’s natural language generation seldom writes the same thing twice.  Each narrative that a persona generates is quantifiably unique.  Finally, Writesof uses the most sophisticated product message analytics platform in our field.  Most NLG software is focused on data-reporting narratives such as business reports, sports stories, and financial articles.  Online retail and product merchandising requires an immensely different set of data and analytics tools to achieve high quality content, particularly so for long form content.  Product assortments with a combined one-million-word online content footprint are nearly impossible to manage internally without some form of natural language generation technology, template-based listing generators at minimum.   But in today’s competitive e-commerce landscape, personalization is a critical component of your competitive market position.  Online merchants with fewer than 500 channel-wide product pages, those that primarily use prescribed brand content, are at a far greater advantage with personalization initiatives.    rely primarily on content spinning or pre-authored brand content, do not face this level of challenge.     finance, and online retail data and only produces unique, high ROI product descriptions, push messages, and ad copy.

.  For example, one NLG persona might be modeled after a large retail website having 150,000 product listings authored by over 100 internal and third-party or brand writers.  Writesof’s message analytics platform can even, with a high degree of accuracy, classify which narratives are most likely to belong to a particular author.  We use this same text analytics technology to teach each unique persona how to predict what an author might write, if given access to certain types of linguistic data, for example subject and topic attributes, or user response goals.

subject and topic information.  has published copy from a total of 25 authors.  Another  while a different persona is modeled after two in-house product copywriters.

Writesof’s proprietary e-retail and campaign data, as well as user and behavior profile data.  data and esigned just to write product copy.   were developed as artificial intelligence that analyzes the behavior of individual consumers  for for the online consumer.  Each NLG system operates as independent computational writers, which we call “virtual personas”.  Powered by our proprietary online retail data and machinehow to write by “learning” from one or more human writers.  For example, Writesof can analyze every word of text published on a luxury retailer’s website and, in a short period of time, can predict how the writer(s) would describe and sell every product in a new collection launch.

capable of learning how to write by analyzing large quantities of topic and subject-level copy.  writing at the same level as writers with a ssimilar-style authors.   Each NLG “pand communicates directly with Writesof’s Product Message Analytics platform, proprietary data and analytics systems. Writesof’s Product Message Analytics platform is a computational powerhouse, capable of calculating granular-to-aggregate values for every word published, in every channel where customer engagement happens.

., comprised of big data, natural language processing tools, and our machine learning platform.  All of our these systems were developed to process Writesof-developed computations specifically for online retail data and linguistics data.

from other  has a unique “NLG Persona”, a writing style similar to the human writers that “taught” them how to write.  Each virtual machine learns to write in a particular style, and within a narrow scope of subjects and topics, based on the author text that it analyzes and interprets.  A    related subjects and topics by analyzing after. have developed human-like writing capabilities ththat a human copywriter has, create dozens of variable product descriptions, ads, and marketing notifications, for every product that you sell.  Similar to other automated personalization marketing software,  Writesof’s proprietary algorithms and data sets, , each designed to interact with online customers.  Systems interpret and evaluate customer and linguistic data,  analyzing how each customer interacts and engages with each message.  The specific types and the breadth of data that we process  that  enables Writesof to deliver one of the most advanced natural langauge systems, machine personas that have each been uniquely trained to write good copy for any brand, any product.  If your company sells a large assortment of products online and have hard-working people that understand your content systems and data, and our team of engineers, data scientists, and e-commerce experts would like to hear from you.  are ready to  competitive advantage in personalized product messaging looks like.  Sho  your channelsyou have a competitive duty to present them, in a personalized manner, to online customers.

Product Description Generation

Writesof’s Automated Copywriting platform, which we call “AC”, is developed specifically for online product marketing. systems are great for descriptive writing, they but have struggled with dynamic personalization and persuasive messaging. , typically measurable attributes and events. structured data and text templates into narratives that describe measurable attributes and events. that Your marketing team wants machines that write copy. just don’t know it yet. Our machines are naturally tuned to echo brand voice and human writing styles, each focused on unique campaign goals and audience segments. Empower your writers to shift focus to creative branding, message tuning, and personalization segments, rather than spending ROI-critical time on keyword placement, audience analytics, and ad experimentation.

Market Driven Message Valuation

Your marketing team wants machines that write copy, they just don’t know it yet. Our machines are naturally tuned to echo brand voice and human writing styles, each focused on unique campaign goals and audience segments. Empower your writers to shift focus to creative branding, message tuning, and personalization segments, rather than spending ROI-critical time on keyword placement, audience analytics, and ad experimentation.

Personalized Natural Language Generation

More content equates to improved keyword placement, better search visibility, opportunities for improved engagement, as well as opportunities for testing and analysis.  Consumer brands, manufacturers, and online merchants that invest in personalized marketing automation will be among the best positioned for growth and profitability.  Companies that lag behind in this technology may still survive, but especially for companies with longer SKU lists, they will be at a significant disadvantage compared to competitors who are focused on automated their personalized selling strategy.

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