Many enterprise marketers share a common worry. It’s not that they have too little intent data, but about their struggle to turn that data into useful and actionable insights. There’s a lot of intent data out there, but the real challenge is figuring out how to make sense of it and use it effectively to achieve concrete outcomes.
Intent Data Explained
Buyer intent data is a collection of signals that helps marketing and sales teams understand when potential customers are actively looking for or interested in a solution. By combining these signals, teams gain valuable insights about organizations that may be seeking more information during their buying journey.
For example, if an account is consuming content on “HR software”, downloading the content asset or watching the virtual event is an early indicator that this organization may want to learn more about HR software. As a result, savvy marketers can engage this account by delivering relevant marketing content and advertising. As this prospect moves from research to inquiry about a specific solution, the sales team can understand the key points and messaging they need to engage and influence the buying journey.
Intent data plays a critical role in creating effective account-based marketing strategies by providing valuable insights into target accounts, enabling marketers to tailor their marketing efforts, and allowing them to maximize their return on investment.
Yet, those Marketers who struggle to rationalize significant amounts of data across various sources and silos won’t see its full impact. The sheer quantity of intent data makes it difficult to separate the true signals from the noise. Marketers increasingly need a single and comprehensive source for intent to identify opportunities, personalize content, and improve the performance of their campaigns.
A Better Approach to Intent Data
Enter ML Insights, Madison Logic’s combined dataset that empowers marketers to effortlessly identify in-market accounts, reach the key personas across the buying committee, and determine the content that drives engagement. What sets us apart is our global reach and unique combination of proprietary and third-party intent data that measures the research and engagement trends of millions of companies around the world to dynamically predict and prioritize accounts most likely to convert. This higher level of accuracy and predictability gives marketers more visibility into in-market accounts and the content and messaging that will engage them the most.
Let’s take a closer look at how quality intent data fuels the three components that make demand generation programs a success.
1. Target and Prioritize the Right Accounts and Personas
According to Gartner, the typical buying group for a complex B2B solution involves six to 10 decision-makers, each armed with four or five pieces of information they’ve gathered independently and must reconcile with the group. Data is key to understanding not only the accounts actively in-market, but the people within these trending accounts who are researching and engaging with relevant content and messaging.
ML Insights unifies three key sources of intelligence to identify the accounts and buyers within them demonstrating the highest propensity to purchase:
- Historical Performance: Madison Logic’s proprietary data consisting of 245M monthly multi-channel engagement signals gathered over 18 years offers unique insights into the buying centers actively engaging with content and advertising relevant to a solution.
- Install Base: Technographic data highlights an account’s investment in complementary or competitive hardware and software applications.
- B2B Research: Measures the monthly Content consumption events to provide visibility into the accounts consuming content and advertising relevant to a specific solution.
By combining this data with first-party customer data from their CRM and MAP, marketers can significantly enhance targeting efficiency by focusing their efforts on the accounts aiming to purchase a solution. This enables marketers to accelerate deal velocity by influencing the buyers with significant involvement in the decision-making process.
2. Personalize Campaign Strategy
Personalization was once a nice touch but has now become a marketing standard as buyers increasingly expect more personalized experiences. In fact, research shows that 80% of consumers are more likely to make a purchase with brands that offer personalized experiences. Designing personalized experiences that live up to buyer expectations requires addressing both their business and emotional needs. To do this, marketers need to leverage data to choose the content and messaging that uniquely meets buying committees with the information needed to convert.
Data also enables marketers to differentiate their offerings through target market expansion and competitive displacement campaigns built on comprehensive market intelligence. By understanding the topics that buyers are searching for, marketers can identify emerging trends, uncover unmet needs, and develop innovative strategies to persuade buyers to buyers to make a change.
With a better understanding of their specific needs and behaviors, marketers can surround the entire buying committee with a multi-channel, full-funnel ABM strategy to stay engaged with key decision-makers. Since Gartner research shows the average software buyer spends just two minutes on a seller’s website but spends hours a day online, a persistent presence builds trust and ensures your solution stays top-of-mind.
3. Optimize Campaigns in Real-Time
Acquiring intent data to complement first-party data helps marketers better validate an account’s readiness to buy, provides an accurate picture of an account’s engagement with sales teams, and improves the performance of nurture campaigns. Marketers can also leverage data to uncover each account’s most effective channels, content, and advertising to optimize ABM strategy and maximize impact and ROI. By measuring success based on real-time pipeline impact, marketers can determine optimization opportunities faster based on multi-channel engagement.
In order to successfully convert potential buyers according to their needs, sales teams need comprehensive and predictive information about the accounts. Engagement data from ML Insights equips them with account activity and historical data from similar accounts with shared characteristics. Based on enhanced account data, sales will have an accurate picture of an account before they first reach out.
The Next Level of Intent Data
Now, more than ever, marketers need ways to work smarter, not harder. The most efficient way to maximize marketing investments and campaign performance is to leverage more accurate and predictable intent data.
Marketers leveraging ML Insights in multi-channel ABM see 32% lift in engagement, 28% faster sales cycle, and 17% increase in pipeline. What’s more, all clients gain access to ML Insights and its intent data as a value-added component of their existing media investment—a service no other platform provides.
Start building your pipeline today using intent data. Contact us to learn more about how Madison Logic helps the world’s fastest-growing companies leverage data to drive pipeline impact and boost marketing efficiency.
