Using data to fuel and optimize a legacy marketing strategy into an intent marketing strategy is a priority for many Marketing and Sales organizations in the B2B industry.
The capturing and synthesizing of insights from buyer intent signals emitted on the web is possible because of key technology enablers such as artificial intelligence (AI), machine learning, automated marketing platforms, and intent data providers.
In an article on DMNews.com, Kayla Matthews explores five robust opportunities for B2B organizations to succeed at “intent marketing,” or “any marketing that concentrates on a what a prospect tells marketers, ether directly or indirectly, they need or want at a given point in time.”
Five Ways to Succeed at Intent Marketing
- Video ad targeting is a key tactic to leverage the power of intent data. Marketing spend allocated to video advertising can really get some mileage; even B2B prospects scroll through their phones and engage with ads.
Marketers can even target ads on YouTube videos to prospects who have been identified and segmented based on purchase intent signals they’ve emitted.
- Increased data volume is both a boon and a potential trap for data-hungry marketing organizations. Though today’s unprecedented amounts of data about user intent, behavior, purchase history and much more are powering B2B Marketing and Sales operations, they still require careful attention and thorough governance. With great amounts of data come great privacy, security, and compliance requirements.
Competitive marketing technology stacks contain tools and software that enable the collection and analysis of such huge quantities and disparate types of data, and they allow marketers and sales reps to execute personalization tactics to engage the right audiences at the right time, using various approaches and channels.
- AI introduces many possibilities and capabilities to the modern marketing function. AI-powered programs and analytics capture buyer intent signals from amidst the din of all web traffic; natural language processing engines parse keywords, searches, research behavior, and content consumption; and machine learning algorithms are able to learn from the data insights to make better and better predictions about outcomes and buyer journeys and intent.
Indeed, Aberdeen research shows that augmenting your marketing operations with AI improves performance and return on marketing investment.
Additionally, the increasing ease-of-use and user-friendliness of business intelligence and data analytics programs means even your least tech-savvy marketers can make some sense of insights that used to need a data scientist to discover and interpret.
- Account-based marketing (ABM) has replaced the marketing strategies of the past, and it’s not even what you’d call nascent any longer. ABM lets marketers focus their efforts on intelligently segmented categories of prospects and treat those engagements as they would interactions with established accounts – not just prospects.
Intent data is the key to successful ABM. It informs the segmentation of prospects who have emitted purchase intent signals, and the machine learning algorithms can use their historical predictions to refine and improve each subsequent prediction.
- Intent-based content marketing is possible only with verified and accurate intent data. Throwing spaghetti at the wall to see what sticks doesn’t do it anymore; B2B marketers must consider buyer intent when strategizing and creating content.
When content matches a user’s intent, it will perform better, resonate more, and engage the user much more than content that doesn’t address their needs or stage of the buyer’s journey. A prospect conducts active research when they have a problem to solve – use your content to address the problem they’ve expressed intent to solve.
As cutting-edge, artificially intelligent marketing stacks improve, content-based marketing will become more effective at helping prospects find the solutions they seek than any marketing they’ve (or we’ve!) known.
