Artificial intelligence (AI) has been the darling of film directors and sci-fi writers for years. He has often acted and will continue to act as a sinister force posing an existential threat to humanity.
But the truth is, AI has already been put to useful use in all kinds of applications and industries, including B2B marketing.
Although AI and machine learning (ML) are two terms that are sometimes used interchangeably, they are not the same thing. It covers multiple fields such as AI, image processing, cognitive science, neural networks and more.
Its aim is to make machines and systems “intelligent” by giving them the ability to acquire and apply human-like knowledge.
ML is a subset of artificial intelligence, it aims to enable a machine to learn from the external environment through sensors and other data input sources. The focus is on the classification and clustering of data.
ML is used to increase the accuracy of the target, while Artificial Intelligence is used to increase the probability of success.
B2B marketing professionals with good marketing automation software already take advantage of multi-touch attribution features.
This way, they know when, where and how the customer or potential customer clicked on the ad, subscribed to the email, filled out a form to download a piece of content (e.g. an e-book), watched a video, and finally made the purchase.
Michael Trapani, who leads the Watson marketing team at IBM, said, “The reality today is, after all, that customers design their own journeys, work things out on their own terms, and for these reasons the process is largely beyond the control of marketing professionals.” says. “There are multiple paths between channels that a customer can navigate. Artificial Intelligence creates the ability to sort these customer journeys by multiple variables. ”
AI can process billions of events such as clicks, engagements and location updates at blazing speeds, allowing marketers to identify the factors that have the most impact on customer journeys. It gives its customers the ability to identify which travel routes are the fastest and easiest.
AI is also capable of detecting anomalies and their hot spots in real time.
It can alert marketers to issues such as lower-than-expected prices or clicking buttons that don't work properly, and suggest corrective actions to take.
This way, they can predict what will happen while a published campaign is still running, so marketing professionals don't have to wait until the end of the campaign to make adjustments.
Marketing professionals can use all this information to create a better experience for their customers as they develop campaign performance metrics.
For example, they can sort customer journey paths by the most profitable and use this information to increase their return on investment.
“The rankings and recommendations provided by AI enable marketers not only to create a better experience for their customers, but also to prioritize, focus, and invest in what works,” Trapani said. says.
A Possible Solution to Some Big Problems
AI and ML have the potential to help solve B2B marketers' biggest problems. “Our B2B marketing customers are often looking for more efficient lead generation and sales productivity, two things that are trending in the wrong direction for many companies,” said Neil Michel, vice president of Accenture Interactive . We saw a 12% drop.” says.
Michel says ML is all about insight and gives B2B marketers new ways to handle increasingly complex purchasing processes that are fundamentally shifting to digital and are being significantly informed by social channels. “Cold calling is dead, so B2B marketers need to be smarter and more effective about who they reach out to and when,” he says.
“If marketing professionals or their sales counterparts can't interact with a real understanding of a customer's situation and needs, their process is getting nowhere,” he says.
The AI and ML benefits can be particularly pronounced for B2B marketing professionals in the social channels that Michel mentions.
Yuval Ben-Itzhak, CEO of Socialbaker, the artificial intelligence-powered social media marketing platform used by B2B marketers at institutions like ING Bank and Orange Telecom, said the combined power of AI and ML can automate low-level, repetitive tasks, reducing the workload of marketers by at least 30 percent. It envisions streamlining business and freeing them up to focus on higher-value activities that fuel their business growth.
Ben-Itzhak, “For example, at Socialbakers today, tasks such as lead scoring, ad rating, data processing, and anomaly detection are already handled by ML.” says. “Taking advantage of these technologies can save incredible time and money, and this trend will only grow in the future.” he adds.
Michel says AI helps marketing professionals engage in B2B-related efforts more meaningfully because decades of training model have developed three key skills that mimic human abilities: perceive, understand, and act. “For example, Google Alerts may be set for key potential candidates or competitors, but it takes time to understand and interpret industry news in a way that results in marketing strategies.” says. “AI helps us do that.”
Nate Skinner, VP of product marketing for Pardot, Salesforce said: “As a result, AI and ML have a better way of understanding the expectations of B2B organizations, delivering a tailored customer experience, creating pipelines (for example, contact list-leads) and closing deals faster . they will be able to help them get a job, ” he says.
By leveraging features like AI-powered campaign insights and behavior scoring, marketers can move away from rules-based scoring models and examine what really drives campaign engagement.
Skinner says it enhances AI-based abilities to distinguish between successful and unsuccessful campaigns and identify which leads are most likely to become customers.
They can further improve marketing performance by pairing AI with predictive lead scoring and automatic event capture to prioritize the best leads and automatically capture things like contact information .
Siddharth Taparia, VP of co-marketing at SAP , a provider of marketing transformation, business software and technology solutions, says the use of AI and ML in marketing is still evolving. New technologies are helping marketers automate out-of-date approaches to important tasks like data collection, lead scoring and personalization.
Taparia says, “in terms of customization, these innovations have greatly improved the markers' ability to identify, locate and microtarget the right customers and prospects at the right time, rather than the old "do something pray" mentality. “When we personalize campaigns, data collection becomes easier and more effective because people are more willing to opt for something they find relevant and worth their time.”
He adds that AI and ML have the same kinds of positive effects on B2B marketers' ability to effectively nurture their customers with relevant, personalized information and experiences throughout their purchasing journey.
Applying the AI story to C-Suite executives
Note: C-Suite executives is used to refer to the CEO's team of “Chiefs”. CRO, CFO, CMO… it goes on and on.
Josh Mueller, global head of marketing at business data, analytics and integration services provider Dun & Bradstreet, says two of the biggest benefits it brings to B2B organizations are significant increases in internal efficiency and better ROI on current marketing spend.
“AI and ML should be considered additional resources to contribute to the marketing team,” Mueller says. “They can step in and help speed up processes, prevent churn and generate analytics in times that might be impossible for humans.”
He adds that when coupled with the right master data strategy, AI and ML enable marketers to pull together all the different interactions that individual and corporate customer accounts have with a brand, and then make smart decisions about what content and experiences to serve.
Experts say that like all B2B marketing technologies, AI and ML are not the end for marketing professionals, but a tool to lead them to results.
In the B2B world, products are often complex, as are the decision-making processes involved in a purchase. While long-term relationships between buyer and seller are common in B2B, B2B buyers are often more demanding than consumers. For all these reasons, personal relationships play a huge role in B2B sales.
Marketing's job is to find the customers most likely to be buyers, nurture them with relevant, personalized content and experiences at every stage of the buying journey, and continue to provide the necessary support to sales as they become leads. Pete Sena, CEO of digital demand consultancy Digital Surgeons, said, “The integration of any new tool needs to be important not just to your marketing team, but to your entire company.” says.
“While technology is key to driving stronger results, it cannot happen without education and consensus on how each tool works and the value it adds to the organization, so AI and ML must be a focus for B2B marketing professionals,” Sena says. Our future lies in machine learning and artificial intelligence,” he adds. “It's not just something we can dismiss as 'nice', it's a 'must have' for any B2B organization.”
Accelerating B2B Marketing
Jan Haderka, chief technology officer at open source content management systems provider Magnolia, says AI technologies will play an increasingly transformative role in reshaping B2B marketing in three key areas.
These;
1. Image tagging: Marketing professionals already use high-performance APIs (application interfaces) to help eliminate the need for image tagging, but AI allows them to automate and diversify and augment tasks such as content tag mining to perform detection analysis.
2. Audience segmentation: Here is where AI has the greatest potential to play a truly transformative role. Audience is a time-intensive manual process that AI can automate and deploy with a higher level of granularity. B2B marketers will be able to build sophisticated segmentation engines that go beyond demographics/firmography and dynamically adapt when calculating common customer behaviors such as page zapping.
3. Enhanced testing: By integrating AI into continuous testing processes, they will be able to quickly identify sub-breakdown areas and use analytics to automatically adjust the experience.
Isn't it time to adapt ML and AI to your business?
For example, transferring your budget to some non-important events (only to attend) and useless digital advertising campaigns for only 1 year can create a springboard for your company and your own success.
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