Never Miss Buyer Intent signals by Adopting AI for B2B Marketing
Many of the B2B sales organizations have already implemented some level of AI, with the main intention to optimize their activities. Mainly personalization of the buyer's journey.
2019 is supposed to be the year where AI for B2B will begin to see a lot of popularity and this will lead to a massive explosion in marketing and sales. It is also known that AI will not be autonomous as the winning power of HUMAN + AI will be only show potential for B2B organizations to use data to drive revenue.
B2B marketing and sales rely on actionable insights to drive revenue. A marketing team needs to have several keep players to get the optimal results. For example, the marketing analyst or team must have deep understanding of their ideal customer profiles, their marketspaces, brand perception, best derived buyers journey, purchase histories, visibility of products and more, to be able to ultimately close deals. Especially in a more complex industry like hotel supplies, you must know the chefs trends, aim differently for each specific cuisine type, understand the buying trend of those who buy locally and find a good enough reason to convert them into online customers ( as B2B e-commerce is still growing in Kuwait)
Augmenting operations and human intelligence with AI enables B2B organizations to do more, while the data curated is more accurate and quickly unlocked. AI can also help predict through various algorithms and data collected, this is slowly being considered for 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 buyers intent signal all the way to converting to a sale, with a satisfied client.
Applying AI in both your business strategy as well as your automated processes, you will be able to reach your revenue goals faster, with a much higher success rate.
5 Benefits of applying AI and Machine Learning to a B2B marketing Strategy.
- Better Targeting of Accounts
- Guided market expansion
- Accurate and fast automation of marketing processes
- higher quality of lead generation and prioritization through lead scores
- improved, more relevant and personalized data
Lead scoring is crucial when determining which accounts to target. Effort, time and resources are saved by identifying which leads are most likely to response and enter your pool, and which leads aren't ready for engagement or don't need your solution or services. It's a constant argument i have with my company after every exhibition. They feel the necessity to buy contact lists of the attendees, but i strongly recommend that they try to fulfill at least 30% of the visitors contacts acquired and converted them to sales before buying a contact list and complicating the work process. In other words, using AI to score leads helps to accurately and quickly prioritize prospects emitting legitimate buyer intent signals, determine which prospects to nurture, and disqualify and filter out "the waste of time ones"
Personalization is a topic that should be on every B2B marketer's radar. In fact, a lock of personalization is a contributing factor to low conversion rates of website visitors.
Data relating to the buyers journey is vast, and the smartest human brains cant compute nor contextualize countless volumes of buyer intent signals. However, AI 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.
Given the speed at which AI is evolving, improving and automating 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 the competitors AI prioritizes your clients buyer intent signals and turns your past wins into real-time losses.