How B2B sellers drive greater ROI with personalized modular content

No surprise, business-to-business (B2B) decision-makers want their buying experiences to mirror the ones they enjoy with consumer brands. They expect companies to understand their unique pain points and credibly make real-time product and service recommendations to address those needs. Some sellers responded with digital experiences that more or less aligned with buyer’s job titles, industries and company size but fell short of substantive connections and sustainable results. Purpose-built content, sellers realized, can’t be produced or meaningfully personalized at scale using current approaches. One-size-fits-all collateral isn’t proving to be a long-term match.

Market-savvy B2B sellers took that challenge to heart. They shifted their focus from creating generic, static content with a limited shelf life—and hoping for the best—to crafting personalized content modules that can be dynamically tailored in real time to connect with decision-makers across the buying funnel. They’re investing in content management, data and analytics platforms, as well as changing how content is created, all to drive personalized experiences across the funnel, leading to improved engagement and conversion rates.

We asked a popular artificial intelligence (AI)-powered chatbot to explain modular content. Its definition came close to how we see the industry describe it:

“Modular content refers to a content strategy that involves breaking down larger pieces of content into smaller, reusable and self-contained modules. Each module can be used individually or combined with other modules to create different content pieces or variations of a larger piece of content. This approach allows for greater flexibility and agility in content creation and publishing, as well as easier maintenance and updating of content.”

Because chatbots also learn industry mistakes, the “breaking down larger pieces” language can be misunderstood as a jigsaw puzzle with pieces that can only be assembled in one way. Lego blocks are the better metaphor, as they follow a particular structure but allow for endless possibilities of putting them together. This paradigm shift has led to an evolved role for both creative and content production agencies.

Content modularization maturity is measured across six key dimensions, typically included as part of an overarching go-to-market transformation.

Content strategy today loosely connects with the brand strategy. In a data-driven, insights-based ecosystem, we recommend the content strategy correlates the content being created with the objectives and goals in the brand strategy. Additionally, the content strategy should articulate how and where modules will be used in marketing, sales and service initiatives and define the data that will be used to deliver operational insights. It also should identify the channels where content will be used and adapted for specific channels. The strategy specifies the different types of:

• Content to be created, from headers and body copy to subject lines, calls to action, icons, pictures and videos
• Modules to be developed, such as promotional, cross-sell or up-sell offers or product and service details that can be used interchangeably and in combination with other related content
• Templates to be used to create flexibility within a framework, whether for an email, landing page, social media post or mobile app

The content strategy also should account for ensuring a consistent brand voice and quantifying and qualifying what good looks like. Analytics gauge the program’s overall return on investment, spot content gaps to patch and track performance of individual content components and modules. Adapting the strategy based on real-world metrics keeps content relevant and fresh and sets a foundation for growth.

The technology stack needed to support personalized modular content campaigns can vary significantly from traditional B2B campaigns. Beyond more advanced automation and data integration and orchestration capabilities, they depend on robust tools to glean and analyze customer insights to guide the creation of content modules that can be assembled, personalized and distributed at scale. Most of these foundational tools already are available within the ecosystem. What we generally find missing is the appropriate integrations and configuration on how the tools are being used.

“Content” as a term is interpreted differently in every organization, so roles and responsibilities are defined accordingly. Our view of content is any asset that is leveraged to communicate with the customer in any channel. Hence, content can be text, images, video or webpages. It also can include promotional offers and alerts via email or push notifications. Scripts used in customer service channels or physical flyers also are content.

Depending on your organization’s data assets, content modules are crafted to address the role-based interests, preferences and unique pain points of individual decision-makers or identified buyer personas in targeted industries and organizations. AI tools use machine learning algorithms to analyze customer data and behavior profiles to predict what content will be the most relevant and engaging to these audience segments at a given time, across myriad channels and devices. AI also can, for example:

• Automate content component and module creation, compiling material from existing articles, case studies, white papers and announcements and packaging them per predefined rules and templates
• Deliver modular content tailored for segment-preferred channels, such as email, the company’s websites, portals and social media
• Create unique email subject lines or custom landing pages with personalized calls to action, based on the recipient’s role or prior engagement, to increase conversions
• Re-engage with buyers who seem to be stuck in the decision-making process by directing them to new or follow-up content with additional context around the product or service they’re considering
• Retarget prospects with relevant display ads and social media posts leveraging content modules they have interacted with in the past in another owned channel
• Uncover additional insights and patterns, based on how customers previously engaged with content, that can help refine the personalization strategy and the AI model to sustain optimal performance

• A wealth manager uses tables and charts set up as modular content to talk about portfolio performance and risks during an in-person meeting with a client. The same modules can be leveraged on the website or through email channels to communicate similar messages or cross-sell other products.
• A technology company can set up product drawings as modular content that can used both in user manuals and guides for customer service reps.
• Last-minute offers for a hotel chain can be set up with business rules so the same modular content can be used as mobile push alerts and banner ads on partner sites.

As with traditional personalized campaigns, modular content is published across multiple digital and nondigital channels—for example, email, ads, websites, print, kiosks and social media. As opposed to promoting the same content across each of these channels equally, personalized modular content can be used more strategically. Data, not hunches, guides decisions on where to place collateral so that it reaches the audience most likely to interact with and act on it.

In other B2B scenarios, this same insight can help get modular content in front of influencers. Raising awareness of your product and service bona fides among third parties such as consultants, industry analysts and trade media reporters often translates into coverage that helps build credibility with in-market prospects.

To foster internal collaboration and information sharing, organizations are removing marketing-sales silos and investing in shared content repositories and data analytics platforms. This framework allows B2B suppliers to better coordinate how their teams respond to opportunities, based on prior content interactions, the revenue impact and where they are in the funnel. Next-best-action recommendations help teams decide, for example, if a one-to-one interaction or automated message triggered by the rep or a marketing colleague is most likely to move the needle.

We expect to see more fluidity as digital technology enables greater customer reach and B2B sellers become more fluent in adopting build-it-once-apply-it-multiple-times scenarios. A B2B supplier, for example, may opt for a sales-led approach for the top end of its customer base but adopt a marketing-led approach for the small and midsize business segment. Whatever the choice, the experience should be transparent for decision-makers.

With modular content, process and governance become even more central. The operating model lays out a leadership mandate for the change and new expectations from the departments that will do the work. For analytics teams, it defines how data will be collected, consolidated and analyzed to segment customers and how insights will be used to shape content and channel decisions. At a more tactical level, the operating model sets standards and procedures for how content will be created and compiled in a component library. It puts a structure in place to oversee and accelerate workflows against an editorial calendar.

The program can be led in-house or by an outside agency, depending on the company’s expertise and resources. In either case, collaboration tools, incentives and expected behaviors will need to be realigned to ensure effective collaboration. Reusing existing content or creating content modules that can be recontextualized, for example, might be counterintuitive or differ from how the current operating model is set up.

As B2B sellers become more proficient in delivering seamless omnichannel experiences, they must be equally committed to continuous improvement and optimization. The buyer journey remains the critical path to follow, albeit a frequently nonlinear one. Not only do individual buyer journeys reveal market-based insights companies can use to deepen their customer and industry knowledge, but they also yield data to evaluate and fine-tune content modules for greater impact and reach. Delivering consistently engaging and personally relevant collateral helps organizations efficiently and cost-effectively raise brand and product awareness, build trust and close deals—including conquest wins. A bonus: Personalized support content delivered after the sale can minimize the risk of churn and translate into repeat and referral business.