Posted by Owen Matson, Ph.D. on February 28
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marketscale_B2B marketing_data_analytics.pngIt’s one thing to have data; it’s quite another to be able to use it effectively.  In the era of big data, the work of turning increasingly massive amount of information into “news you can use” represents an increasing challenge. 

 More often than not, data is difficult to interpret. Not to mention that the data science skills required for this type of analysis are still very hard to find and notably expensive. For end users who are just interested in knowing what happened and what action to take next, graphs and charts are not particularly helpful.

Now, a technology called Natural Language Generation could mean big changes for the world of B2B marketing, promising to help professionals to get more use from high volumes of data.

True data storytelling, enabled by advanced natural language generation (NLG), offers a better way to translate numbers into user-friendly stories. By automatically turning sensor data into meaningful and insightful narratives that people can read and easily understand, advanced NLG makes the required data analysis and communication possible. Explaining this data in natural language—as opposed to code—provides B2B marketers with actionable information that, ultimately, makes their job easier.

 A large part of advanced NLG is driven by a process known as narrative analytics, an approach to analysis that is driven by specific communication goals versus the typical bottoms-up approach to data analysis. With narrative analytics, the desired narrative determines the type of analysis that needs to be performed and the data required for that analysis. The result is a natural language explanation users read and immediately understand.


What is Natural Language Generation?

Natural language generation (NLG) is a technology for turning raw data into finished product descriptions. It’s an automatic process for writing copy at scale that reads as though each description was typed by hand.


NLG allows one writer to scale his or her work across an unlimited amount of data. A user configures a template, inputs data, and the NLG engine does the rest, writing about the underlying data with the insights and style that the user would apply. Don’t let the word “template” fool you: NLG technology produces narratives that not only read well individually, but are fully unique and distinct from all others in the same narrative batch. As a bonus, they are distinct from the basic manufacturer bullet points that many online retailers use for product descriptions, so NLG-generated copy can help with SEO.


The process is far faster manual writing – after a few hours of configuration time, an NLG platform can generate individual descriptions instantly. This speed allows for unprecedented scale; if the data is available, the right NLG can produce thousands or even millions of unique pieces of content.


B2B industries represent an especially fitting arena for NLG because of the sheer volume of data available about both products and clients. And since communicating about specific products or to specific clients can be expensive, automation via NLG can add incredible value.


How Data Storytelling Can Impact Industries

Consider the ways in which advanced NLG can be applied to industries such as agriculture, logistics, retail, insurance, and utilities. In medicine, narrative analytics promises to bring new precision and efficiency to the work of reviewing lengthy patient medical records.  For farmers, rather than being forced to interpret the circles on a heat map or some other visualization, they’ll receive an email with simple, easy-to-understand natural language instructions outlining the day’s planting instructions. For logistics vendors, it would mean sending a personalized route recommendation to a driver’s mobile device so he doesn’t have to decipher a new map while on the road. Likewise, retailers could deliver personalized weekly inventory reports to individual storefront managers with shelf-stocking guidelines and other instructions tailored to the specific buying habits of that particular store’s customers.


For utility companies, there are numerous, valuable ways to leverage personal usage data to better engage and serve customers. Would you value your relationship with these companies more if they provided personalized communications based on your behavioral data? Your monthly premium statement would include insight into your driving style and (hopefully) a refund because of your safe driving habits. Likewise, your utility usage update isn’t just a bill anymore, but rather a personalized letter with advice on what temperature to set your thermostat to optimize your energy efficiency and save money. These are just a few ways that combining data with advanced NLG can help companies to not only improve operational efficiency but also enhance engagement with their customer base.

MarketScale has begun to adopt narrative analytics to process marketing data into accessible, user-friendly information.  To learn more about the ways in which MarketScale can help your business develop a content strategy supported by the latest tools in data analysis, feel free contact us:

Also feel free to take a look at our marketing technology playbook.

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