AI is helping marketers treat people like individuals
Posted: 23 August 2017 | By Jeff McDowell
While advancements in big data analytics have done a good job at helping marketers target mass markets and people of like interests, they fall short of understanding a person’s unique interests and going that extra mile of treating people like individuals. While there is no argument that people have overlapping interests, there is a false assumption that just because a person falls into a certain category (i.e. adult male, outdoor enthusiast) that all people within that category can be addressed in the exact same way.
A person will express hundreds of different interests that extend beyond any given category; this is what makes a person unique. Big data approaches don’t treat people like individuals. Instead, they tend to bucket people into broad categories. Big data needs many data points to evaluate whether an interest is statistically significant. If you or your chosen ad network/content distributor has little information on a possible customer, how can you target them with content or products that satisfy their unique individual interests?
Understanding of individual interests unlocks the true potential of personalization. Only through that higher level of personalization, or individualization, will marketers be able to increase engagement in their brand, generating higher levels of sales and customer satisfaction.
Through the use of artificial intelligence and knowledge representation, Primal provides marketers with the tools they need to understand the unique interests of every individual, to engage with them on their terms, and at scale.
Taking on the challenge of individualization by teaching machines to understand interests
Primal is an innovator in AI and knowledge representation, with over 140 international patent filings (over 50 granted), more than 10-years of R&D and over $20-million invested.
The main difference between Primal and more conventional approaches to machine intelligence involves our use of semantic synthesis, as opposed to big data analysis. Conventional big data analytics derive representations of interests from existing data. In stark contrast, Primal’s AI automates the processes by which humans create meaning, known formally as semantic representations. We call our process semantic synthesis.
Primal’s AI understands interests in much the same way that people understand interests, using an iterative process of inference and evaluation against observational data. Interests are then assembled on-demand into machine-readable formal semantic representations known as interest graphs, requiring only simple indicators of user interests.
Adding Primal’s intelligence to your marketing and advertising organization
Primal’s intelligence may be added directly to the marketing services and tools you know and love, such as Hootsuite, Twitter, Oracle Bluekai and Slack. Primal supports rapid development and pain free integration. Our cloud-based solution requires no software to install, or expensive data scientists to operate. All the consumer data you require is generated by Primal.
Primal uses a 3-step process (Sense – Think – Act) to deliver the right information to the right audience:
Step 1 – Sense – Sense: Natural language processing (NLP) is used to sense an individual’s interests based on their online interactions. For example, if an individual clicks on a link to an article, Primal captures signals of their interest as entities and keywords extracted from the article. This sensing works with any textual object, from the sparsest search queries and tweets, to the most expansive websites. Primal’s sensing capabilities are web-scale: virtually every source of public information is within reach. Primal’s APIs may also be extended to incorporate proprietary sources of information, such as corporate information repositories and knowledge-bases.
Step 2 – Think – Think: Primal’s core intellectual property is applied at the level of thinking, generating formal semantic representations of interests, known as interest graphs.
For each signal of interest, Primal creates a semantic representation using constructive rules and probabilistic inference. These semantic representations are then evaluated against the content landscape (including your competitors), highlighting the information that is most likely to interest the target audience.
This thinking process works in real-time, across all the signals of interest associated with the target audience, to construct a rich and valuable representation of their interests: their interest graph.
Step 3 – Act – Act: Primal’s actions are facilitated with a software agent framework for creating personal intelligent assistants. These intelligent assistants process the information contained in the interest graphs to deliver useful tasks, such as recommending content items to audiences, sending emails, interacting in social media, and responding to customer support requests. Actions may also be performed to distill Primal’s consumer interests’ data into reports and visualizations, giving customers valuable insights into the needs and motivations of their audiences.
Artificial intelligence is the next frontier in digital marketing and advertising
The job of a social media or advertising manager isn’t easy. Even companies with the narrowest of product offerings have customers with varying interests and varying needs. When it’s your job to keep thousands or even millions of customers and followers in social media engaged with your brand on a daily basis, you need all the help you can get. And while there are literally hundreds of marketing technology companies out there all with the promise that they’ll help you target your customers better, they are all at the mercy of big data’s shortcomings.
Primal’s precise understanding of interests leads to world-beating levels of audience engagement. Based on a study of engagement rates on Twitter, Primal’s intelligent assistants outperformed the top brands in the world by over 5-times! This lift in engagement was measured across both media targeting and advertising.
Based on a study of engagement rates on Twitter, Primal’s intelligent assistants outperformed the top brands in the world by over 5-times!
In addition to the dramatic benefits in engagement, Primal has a unique advantage in privacy as well. Unlike big data approaches, Primal doesn’t require analyses of large scale data, or creepy surveillance techniques. This maintains trust and goodwill, and avoids the considerable risks of data governance and regulations.
Whether the job to be done is curating new content matched to the individual interests of your social media followers, or the targeting of advertising to the best possible audience, Primal’s Intelligent Assistants are the perfect solution to achieve accuracy and scale while maintaining or even decreasing costs.
Jeff McDowell is the Chief Commercial Officer at Primal. Through the use of AI and knowledge representation, Primal provides marketers with the tools they need to understand the unique interests of every individual, to engage with them on their terms, and at scale. This was originally published in A Case for Investing in AI an Access-AI Ebook.