Personalization has long been the industry standard in B2B. Moreover, according to a recent study by Salesforce, 62% of B2B buyers expect vendors to personalize their offers based on their needs. In comparison to B2C, the sales process is longer and more complex, the services are more complex, and B2B buyers are more ‘rational’ and long-term than consumers. According to one study by 6sense, B2B buyers refrain from engaging sellers directly until they're approximately 70% through their buying process. The decision-making process is increasingly long and complex and features many key interests. Indeed, a recent study showed younger customers actively shun businesses that lack some form of personalized experience, with 49% of Gen Z left less likely to purchase after an impersonal interaction. There is a generational gap regarding personalization.
Millennial buyers aged 25-44 are increasingly in decision-making roles and are expected to make up 75% of business buying teams in 2024. These buyers are digitally motivated and self-guided in their solution research process. To meet and exceed evolving customer expectations, brands must use data and analytics to better understand their customers and harness the power of AI to create authentic interactions and the hyper-personalized experience that customers now expect. Not only is personalization expected, especially by younger generations of buyers, but it’s also a dealbreaker for buyers who anticipate personalized and targeted communication.
Although there is a general consensus that personalization is preferable, nay, required, for B2B buyers, there still exist two schools of thought regarding ‘relevance’. As Brennan et al. summarized in their 2014 paper “Improving relevance in B2B research”, there exist two ‘camps’ within the marketing discipline: “the camp that considers practitioner relevance to be a sine qua non and the camp that considers relevance to be, at best, a distraction from serious research and, at worst, a threat to the quality of academic research.” Although this distinction was first elucidated in 2011, there have been a score of articles in recent months decrying personalization in favor of relevance, with titles like, “Relevancy Beats Personalization for B2B Outreach and Marketing”. Given that the academic B2B community cannot be clear about the role of relevance in their research, it’s
Personalization, which could be more elaborately termed ‘building personal relationships and sculpting individualized purchasing experiences’, is a key to B2B sales, and in 2024, the significance has never been more pronounced.
Marketers are aware of their customer desires, and data shows that most marketers believe personalization helps advance customer relationships, while a stunning 92% believe their prospects or customers expect a personalized experience. The State of the Connected Consumer report found that 64% of customers expect tailored engagement based on past interactions, but 52% say companies are generally impersonal. The report also found that 71% of customers expect companies to communicate with them in real-time.
Seventy-three percent of B2B customers expect companies to understand their unique needs and expectations according to Salesforce, and in an increasingly competitive inbox environment, personalized and targeted communication is more important than ever, and first-name personalization is the lowest echelon of personalization. Despite the simplicity of this type of customizable experience, research indicates that using personalization in an email body may lead to a 28.57% increase in click-throughs.
Even if you don’t use Spotify and Netflix regularly, you can probably still appreciate that personalization is essential to a modern customer experience; all the content available on the most popular entertainment websites is pushed according to your watch history, and generic experiences fall flat compared to those. According to Deloitte analysis, Amazon and Netflix achieved high customer conversion rates and customer retention, which translates into increased revenue.
The Deloitte report “Hyper-personalizing the customer experience using data, analytics, and AI” features a diagram indicating how the personalization maturity curve will unfold. It shows how, when personalization moves beyond rules-based segmentation, behavioral recommendations, and omni-channel optimization, predictive personalization will allow for anticipatory analysis, and allow for engagement of each customer separately.
They evidently envision this as a major change in the way that personalization is actioned in sales spaces, as they speak about hyper-personalization in no uncertain terms, and how
“This segment-of-one approach allows you to optimize whom you target with key messages and offers through the most relevant and appropriate channels,” and they envision it as “a holistic marketing strategy that fundamentally changes the way organizations interact with customers and should be treated as an evolving and maturing practice that’s embedded throughout the customer journey and part of every marketing campaign.”
Although many consumers have come to expect personalization, many can also be put off by hyper-personalization. Sixty-nine percent of consumers appreciate personalization as long as it is based on data they have explicitly shared with a business. To the average user, personalization has become synonymous with the ever-present third-party cookie; requesting access to reams of specific data in order to optimize for you can feel as much an infringement on one's personal liberties as it is an optimization of it. There’s a lot to lose. A Gartner study found that brands risk losing 38% of their existing customer base because of poor personalization efforts, and 76% of consumers get frustrated when they can’t find a personalized experience with a brand. As Alex Elliott noted pithily, “Personalization without relevance is just creepy.”
One theory-based research paper from 2023 noted the widening gap between theory and praxis in B2B marketing: Ojanvisu’s paper suggests different epistemic underpinnings of B2B marketing, and in the course of the paper, surmises how “B2B scholars are urged to think beyond their subspecialized silos and acknowledge how the business environment and the various strands of B2B marketing congruently shape B2B marketing relevance, while also embracing research methods that bring them closer to business practice.” In other words, B2B marketing theory is a far cry from reality.
To be relevant, your team needs to ensure they’re delivering relevant engagement to prospects who are in the market. In this way, relevancy also implies lead qualification, as attempting to pitch to a prospect not in the market is the epitome of irrelevant, despite their other personal qualities.
To be more relevant, your team can use data-driven insights and analytics to understand customer behavior, preferences, and real-time needs. In turn, teams can adopt dynamic segmentation and utilize behavioral triggers and real-time data to create dynamic customer segments and campaigns that target certain events in the app. Moreover, then using the situational data, including location or time, can allow contextual messaging, before A/B testing to reiterate the success of the relevant messaging.
With the development of various AI hyper-personalization, the right cloud-based technologies are also important, including embracing an omnichannel strategy. Deploying cloud applications with effective database management capabilities that offer contextual relevant data, constant availability, real-time access, global access, and scalability. In turn, you can harness insights surrounding all manner of relevancy metrics, including geolocation, firmographic information, buyer persona, buyer status, and more, all of which allows for further relevance.
But as Mohan Muthoo noted very aptly, although we talk a lot about personalization being less important than relevance, we should turn our attention to the “relevance of the personalization.”
Whilst a relevant email might have you placed in the right situation with appropriate timing, for example in front of a currently-hiring manager, and a personalized email might segue from an untethered observation into a pitch, a combination of relevant insight with personalized observation is ideal. To analyze whether the insight is relevant or just personalized, consider the email from the POV of the prospect: if it would annoy you, it might the prospect too. Especially with the new rules of outbound impending – the threshold for being seen in a prospect’s inbox is much higher than in ZIRP days, long-past.
The LinkedIn B2B Benchmark report supports these findings. Given the top two priorities of B2B companies involve “Improving B2B measurement tools and relying on data and insights to demonstrate effectiveness”, and then “Creating relevant and useful thought leadership and content for customers”, brands are turning their attention to how they can leverage data, and how they can deliver relevant content to their customers, and undoubtedly the two are also going hand-in-hand.
Now, what Deloitte counts as hyper-personalization might well be merely a crossover of relevance and personalization. This newest mode of interacting with customers also has the added benefit of accomplishing every CMO desire by “Driving business growth through re-imagined platform and service design”, “Employing new marketing strategies and tools to drive growth and reduce costs”, “creating and ensuring a consistent, personalized, and memorable brand experience across all media through a deeper understanding of customer needs and relevant touch points, and finally, “making more data-driven decisions”. In this vision, the CX is improved, revenue maximized, and cost reduced. A host of interactive technologies are set to be ushered onto the scene.
These mechanisms seek to gather relevancy and personalizing proxies. Data-driven content generation, in-moment customer journeys, and next-best-action engines serve to offer the most personalized and relevant experience. To preferentially value relevance over personalization would be to involve oneself in an unnecessary semantic discussion. Hyper-personalization would include relevance by definition, at least by Deloitte’s definition, as they write that “with cost-consciousness still top of mind, it’s more important than ever to spend budgets wisely, optimizing your marketing approach to target customers with relevant and contextualized offers.” At the heart of it, they conclude that “When the relevant data is gathered, implementing a method of targeting customers with the correct content can be achieved through technology.”
With Burger King’s recent announcement of their dynamic pricing strategy, it’s never been a more perfect time for both hyper-personalization and hyper-relevance to continue to optimize customer experience, and in so doing, reduce operational costs.
Super Benji leverages advanced AI to send hyper-personalized and contextually relevant emails and messages, ensuring your team connects with prospects in the most impactful way possible.
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