Don’t Miss Buyer Intent Signals: Adopt AI for B2B Marketing

Many B2B Marketing and Sales organizations have already implemented some level of AI to optimize their activities, including personalization of the buyer’s journey. But according to a blog post by Nida Chughtai, 2019 is the year AI for B2B marketing and sales will explode. In a Mintigo blog post, Chughtai explores the ubiquity of AI, the winning power of human + artificial intelligence, and the potential for B2B organizations to use data to drive revenue, particularly by using AI to decipher buyer intent signals.

She projects organizations will prioritize development of strategies for selling more products and services, new product development, expansion to new markets, maximizing average deal sizes, and improving customer retention rates. These goals will be attained by augmenting strategic operations and human intelligence with AI.

B2B Marketing and Sales outfits rely on actionable insights to drive revenue; they must have deep understanding of their ideal customer profiles (ICP), their marketspaces, brand perceptions, buyer’s journey, purchase histories, and more, to be able to ultimately close deals.

Augmenting operations and human intelligence with AI enables B2B organizations to more accurately and quickly unlock, and even predict, the best business decisions. And timely, data-driven decisions about which accounts or prospects to target — and when, with which message, and with which kind of message! — is the key to taking a buyer intent signal all the way to a converted, satisfied client.

Chughtai said, “By applying AI in both your business strategy as well as your automated processes, you’ll be able to reach your revenue goals faster and with a much higher success rate.”

Augment Marketing Activities with AI

In her post, Chughtai lays out five benefits of applying AI and machine learning to a B2B marketing strategy, and they include better targeting of accounts, guided market expansion, accurate and fast automation of marketing processes, higher quality lead scoring and prioritization, and improved, more relevant personalization.

Lead scoring is crucial when determining which accounts to target. Effort, time, and resources are saved by identifying which leads are most likely to respond and enter your funnel, and which leads aren’t ready for engagement or don’t need your solution or services. In other words, using AI to score leads and accounts helps to accurately and quickly prioritize prospects emitting legitimate buyer intent signals, determine which prospects to nurture, and disqualify and filter out “the pure crappy ones,” according to Chughtai.

Personalization is a topic that should be on every B2B marketer’s radar in 2019. In fact, a lack of personalization is a contributing factor to low conversion rates of website visitors.

As such, it is imperative to augment personalization activities with data about the buyer’s journey that is collected via third-party APIs or a third-party partner who specializes in operationalizing intent data.

Data relating to the buyer’s journey is vast, and the smartest human brains can neither compute nor contextualize countless volumes of buyer intent signals. AI, however, can easily contextualize active research conducted by target accounts, provide actionable insights to marketing, and then augment its own predictive capabilities with what it has learned about the buyer’s journey.

Chughtai posits that incorporating AI into business processes in real time can speed up marketing returns on investments.

Given the speed at which AI improves and automates business-critical marketing programs, decision making, and intent data crunching, B2B Marketing and Sales organizations who have not yet augmented their activities with AI and machine learning should do so — before your competitors’ AI prioritizes your clients’ buyer intent signals and turns your past wins into real-time losses.