What is B2Me commerce?

The cornerstone of building authentic, meaningful, memorable, and lasting relationships with customers is personalization. Research by McKinsey has found that:

• Personalized marketing matters more than ever, with COVID-19 and the surge in digital behaviors raising the bar. During the pandemic, 75% of consumers switched to a new store, product, or buying method.
• 71% of customers expect companies to deliver personalized interactions, and 76% of customers get frustrated when this does not happen.
• Personalization drives performance and better customer outcomes. Fast-growing brands drive 40% more of their revenue from personalized marketing vs. slow-growing competitors.

Clearly, the top priority for B2B brands should be to personalize the end-to-end customer journey and enable various customer segments — e.g. C-suite, IT, R&D, HR, Ops, and so on — to get the answers and advice they need, when they want it.

Yet, if customers clearly want a personalized experience, and brands want to use content to make this happen, why isn’t this always the case? That is, despite their significant investments and dedicated efforts, why are some brands unable to personalize the customer journey and create the authentic, robust customer relationships that are so essential for success and growth? Surprisingly, it is because their existing tools and technologies will not let them.

Ideally, brands want to engage each customer on a 1:1 basis, and usher them along the customer journey. In other words, they want to deliver personalized marketing at scale. But practically, they struggle to do this because they don’t know who each customer is, or what they’re doing. So, brands are obliged to do the next best thing: create an inventory of (hopefully relevant) content such as articles, guides, whitepapers, webinars, datasheets, case studies, and so on, and deploy them across various touchpoints on their website.

The idea is that customers will self-select the content they want. The problem, however, is that many customers are not willing to do this — especially early in the customer journey, when the relationship is new and not “sticky.” As marketing executive and Forbes Council member Caroline Tien-Spalding points out:

Therefore, something else is needed that would enable brands to stop hoping and start knowing what content is going to resonate with different types of customers. This something else is AI and ML, and it unlocks the power of personalized marketing — which is the gateway to B2Me.

B2Me commerce is arguably not so much an evolution of B2B, as it is a recollection that behind every “B” are several “HBs”: human beings. Research by Gartner has found that the typical buying group for a complex B2B solution involves six to 10 decision-makers. And while each of these decision-makers share a common goal — getting the best solution for their organization — they have different perspectives and paradigms. For example, those in IT and InfoSec focus on data security and compliance. Those in operations focus on logistics and implementation. Those in human resources focus on workforce management and culture. And those in the C-suite focus on cost, ROI, and strategy. And of course, there is often considerable overlap.

B2Me embraces this complex reality and creates a landscape for customers that is hyper-personalized, convenient, seamless, and integrated across devices and platforms — similar to what B2C customers expect today. As David Michela, VP Digital Solutions at Horizontal Digital, observes:

AI and ML (which technically is a type of AI where systems are designed to perform a singular objective) makes B2Me possible by automating personalized marketing at scale. It is driven by real-time business intelligence (gleaning data to know what a specific customer is actually interested in) vs. only predictive analytics (analyzing historical data to guess what groups of customers are hopefully interested in).

Here are some of the key ways AI and ML are enabling B2Me, while also helping brands get closer to their customers than ever before:

• Analyzing the behavior of customers on a website — what they do, when they do it, how long they do it for, whether they have done it before, and so on — and automatically placing them into pre-built audience segments.
• Identifying when the behavior of customers does not conform with pre-built audience segments, and automatically creating new ones.
• Automatically delivering specific content recommendations to customers in each segment, and at the optimal time in their respective customer journey. For example, customers who are fairly early in the journey can be prompted to watch a webinar or download an ebook that promises to clarify and inform their preliminary research process. Alternatively, customers much further along the journey who are ready to make a decision can be prompted with testimonials, case studies, and other kinds of social proof to help them confidently move forward into a transaction.
• Running automated split A/B tests to measure the performance of various pieces of content (e.g. ebooks, whitepapers, etc.), in order to accurately measure which are delivering the most value and ROI — and which need to be re-invented or retired.
• Automatically identifying what an image or video portrays, then tagging them accordingly. In addition to breaking down content silos, this frees up marketers to focus their time and effort on higher-value tasks and priorities.

Earlier, we noted that B2Me is about helping brands get closer to customers than ever before. However, this does not mean that brands must ask customers to reveal personally identifying information (PII) — which is not something many consumers will do; especially early in the relationship. Instead, brands can capture a range of rich, actionable intelligence through non-PII interaction data, such as:

• Visit details (e.g. time, day, location, traffic source).
• Campaign source (e.g. messaging or targeting used in an acquisition campaign that brought customers to a website).
• Onsite behavior (e.g. pages visited, clicks, content accessed, galleries viewed) clicked on, content consumed, galleries viewed, etc.

All of this data can be used to drive automated personalized marketing, but in a way that is not perceived by customers as invasive or aggressive. Customers will feel that the relationship is collaborative — not creepy.

B2B marketing is highly sophisticated, and sales cycles are often lengthy. According to a report from CSO Insights, 75% of B2B sales take at least four months to close, and more than 46% take seven months or longer. Yet despite this inherent complexity, brands must not lose sight of the fundamental truth that sales and long-term loyalty are not driven on tactics: they are deeply rooted in authentic customer relationships. This means AI and ML-driven personalization is essential rather than optional, and the only scalable and sustainable way to make the leap from B2B to B2Me.

For additional insights, dive into additional content within the Sitecore Knowledge Center, featuring thought leadership content on personalized marketing (B2Me), marketing automation through AI and ML, and more.

We also invite you to learn more about Sitecore’s headless, API-first e-commerce platform Sitecore OrderCloud®, which supports a wide range of composable commerce strategies and AI/ML-driven personalized marketing. With a robust developer portal including comprehensive API documentation, cloud-native architecture, and an extensive B2B2X e-commerce data model, Sitecore OrderCloud® is an e-commerce platform built to scale, which supports a wide range of composable commerce strategies with brands through continuously evolving digital transformation.