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Automatic text generation saves Retresco customers time and resources. Especially in e-commerce, natural language generation (NLG) can be an important key to the efficient creation of product descriptions. Suppliers of products from such diverse sectors as fashion, office supplies, bicycle accessories or consumer electronics already rely on rtr textengine in their content strategy.
However, the possibilities for the use of automatic text generation are far from exhausted. Our ideas will show you how you can achieve your marketing goals quickly and effectively with the creative application of textengine.io.
Above a certain size, an online offering must drive a diversified strategy in order to be successful. Your own website is no longer sufficient; satellite pages of the brand and a presence on different channels ensure sustainable growth.
The use of automatic text generation is crucial in order to successfully stage offers and generate the desired reach. NLG software is able to generate different, variant-rich, unique texts on the basis of a text model – this results in the significant saving of resources, especially for online shops.
The implementation with textengine.io is that simple:
Automatic text generation does not “just happen”. Unique texts are created in textengine.io on the basis of templates and conditions that are defined in advance. The operation of the tool is as simple as MS Word – the user does not need to have programming knowledge or linguistic expertise.
Once the input has been completed, you as an online retailer can create unique text for not only your own website with the self-service platform, but also the product detail pages on important sales channels such as Amazon and eBay – without significant additional effort.
Individual formulations and formatting of texts per channel is possible with textengine.io, as well as the automatic translation of content at native-language level into the most important European languages. The content from textengine.io reaches a shop system or platform thanks to a stable and high-performance API.
If statements change or if tailor-made messages are to supplement a text, the adjustments are made intuitively and quickly. Read more about this in the following ideas.
In e-commerce, the price is one of the most important factors in the customer’s purchasing decision. Discounts and price campaigns for large portions of the product range are therefore among the most effective measures to boost sales in the intense competition of online retailing.
In addition to proven measures such as crossed-out prices, a disrupter on the product image or the banner in the header area of the website, sales-campaign-related text blocks on product detail pages can supplement the mix of measures.
The implementation with textengine.io is that simple:
Communicate the individual price advantage in the context of a special offer directly in the product text – and lead the customer deeper into the conversion funnel.
The individualised addition to a product description could then look something like this:
“Only on Black Friday 2019 and only with us: Secure the Samsung Galaxy S10 on 2 December for an incredible EUR 499.90 and save a whopping 20% compared to the RRP.”
Let textengine.io automatically fill the basic structure of the statement with the respective data about the campaign period, campaign price and savings and thus create individual text elements for a scalable quantity of articles.
By the way: the discount information is perfectly suited for generation in the meta description. The communication of concrete prices can give the click rate from the search results a considerable boost.
The aim of every online shop is to retain customers and optimally monetise expensive traffic. Cross-selling and upselling are therefore important keys to sustainable economic success in e-commerce.
Automatic text generation can make a simple contribution – without the need for graphic or IT resources. Simply formulate an additional statement to the text model in textengine.io and insert the new text into the website as a product description.
The implementation with textengine.io is that simple:
As soon as a new product or series of products comes into the shop – on a fashion website, for example, this can be a new, seasonal collection – individual text elements supplement relevant descriptions of the existing products with references to the new articles.
For example:
“Are you interested in football shoes like the Adidas Predator X? Get to know the brand-new Adidas Nemeziz 19+ in our shop! For real soccer pros at our introductory price of 129,90 EUR.”
The same applies to products for which the customer needs accessories or which offer more possibilities in higher-priced versions. If there are additional offers linked to an article in the data set, textengine.io automatically generates conversion-strong statements.
A particularly innovative and creative example for the use of NLG is the linking of an offer with current weather data. In this way, the implementation of weather forecasts on a portal for short holidays is conceivable. If the offer for a Mediterranean destination contains a text for a 14-day forecast, for example, this could be the decisive factor for spontaneous decision-makers to book.
Classic product descriptions can also be decorated by weather data. If a product can only be used under certain temperature conditions, the corresponding information can be found automatically in text form on the website:
“Today, temperatures throughout Germany exceed the 30°C mark. You don’t want to wait until it cools down? Our high-performance SuperGlu Plus is also suitable for use at extreme temperatures. Don’t let the heat keep you away from DIY and buy now.”
The implementation with textengine.io is that simple:
Templates and conditions in textengine.io are the basis for individual texts – structured data fill the templates with life. This applies not only to your own data, but also to information from free OpenData projects such as the offer of the German Weather Service.
The combination of textengine.io and external tools such as MS Excel, Google Sheet, MS Flow or Zapier automates such processes efficiently. The combination of several interfaces creates a workflow that creates real added value: the provider personalises his or her content to a high degree, while the website visitor receives additional information.
Google Analytics is one of the most important tools in the digital world. Understanding the data of the analysis tool is a prerequisite for online business models of any kind to create a basis for strategic and operational decisions.
Marketing managers who regularly produce reports know how much explanation is needed for some Analytics KPIs – especially if the counterpart does not work with terms such as bounce rate,conversionor landing pageon a daily basis.
Natural language generation uses the data from Google Analytics to automatically create one-time or recurring reports and thus helps to better understand and classify information for interested parties and decision-makers at all levels.
The implementation with textengine.io is that simple:
The setup of automated textual reporting is simple: in step 1, the data from Analytics is transferred to a Google Sheet, the settings for which can be found in the Google service. Using automation tools such as Zapier and MS Flow, the Google Sheet connects to textengine.io.
Here, the tool generates reports from text templates which the user has previously defined according to his or her wishes. Depending on which Analytics KPIs are to be additionally written, the user quickly and easily completes the statements with his own text modules. The result is a finished report which can be created for specific periods of time and sent automatically.