Artificial Intelligence has often been associated with doomsday ramifications from science fiction, but in recent years, it has become more integrated and applicable to our daily living. In that regard, it is one of the most impactful technological advancements today, and it is transforming every aspect of people’s lives - from turning homes into smart living with the help of Alexa to easing your mobile experience with Apple’s Siri, and even spurring innovation in every sphere of the business landscape.
On that note, AI has helped B2B marketing in more ways than one as it helps provide a more in-depth understanding of customers and prospects due to the machine’s ability to extract any information. Not to mention, with the help of AI, it has helped customers from around the world elevate the experience of purchasing online - anytime, anywhere.
For that reason, we’re here to give you the rundown on how AI can improve your B2B sales.
What is B2B Marketing and How Does AI Make it Easier?
Business-to-business marketing refers to the techniques and best practices used by companies to market their production of goods to general business operations and for resale to other consumers like a retailer or a wholesale seller. This includes raw materials, finished parts, services, or consultations that other businesses need to operate.
It is comparatively more challenging than business-to-customer (B2C) because marketing your company to other businesses means fewer customers, limited data, complex transactions, and sometimes even derivative demand. That is why they have adopted data-driven marketing, wherein strategies are built on insights on behavior collected through consumer interactions and engagements.
In retrospect, AI and machine learning are used as a supporting tool that allows various industries to track troves of data far more efficiently and quickly than a person could, which is beneficial for businesses to streamline their decision-making process. On that note, AI can help improve B2B in the following:
- Predict potential customers
- Discriminate between buyers and viewers
- Identify special trends and choices
- Personalize various online campaigns
- Improve lead generation
- Smart decision-making
- Increase efficiency
- Drive more sales and revenue
AI and Machine Learning Can Gather More Data to Enhance Target Market Strategies
AI has the uncanny ability to gather any information efficiently and promptly - from site heat maps, company descriptions on any given search engine results, down to the minute detail of a product data. These sources help build the AI’s algorithm and construct a pattern that can easily be identified by AI, allowing B2B marketing to make a better customer-centric approach.
Not to mention, AI and machine learning can also analyze firmographic data, which focuses on the characteristics of the audience’s organizations, size, location, and industry. This includes look-alike modeling studies wherein the profile of a target audience and pens down keynotes on their characteristics, allowing you to have better filtration on your ads. This is one part of the data pipeline that we have built, by gaining a better understanding of your ideal target profile we can start creating smarter campaigns and forms of engagement in order for your sales and marketing team to win. In some instances, we only need 50 examples of your best customers for us to start modelling.
This type of targeting only exist because of the recent explosion in research and adoption of machine learning libraries and algos. Being in the heart of the AI boom (Montreal) we are surrounded by a great ecosystem of innovators and thought leaders that continuously push the boundaries of what is possible.
Finally, it can touch on technographic data to let AI have more abundant information on the target audience’s behavior and characteristics when making purchases, which is crucial for businesses as it can help them redirect sales. For example, our models look at aspects such as: Information on the person, the company, their technology choices, their growth, their engagement data (This includes stats such as: open rate, reply rate, interested response rate, click through rate) in order to inform the prospecting activities. This gives small teams the ability to scale their targeting ideas in an ever evolving way.
If you’re looking for an AI assistant for sales, get in touch with us today to see how we can help.
