Marketing

Integrated marketing technology stacks pave the way for personalized B2B customer journeys

By Srihari Sarangan, Pete Mehr, and Ashutosh Mehndiratta

May 9, 2023 | Article | 11-minute read

Integrated marketing technology stacks pave the way for personalized B2B customer journeys


Cloud-based marketing technology solutions fueled by customer data captured and integrated across the buying funnel are a foundational component of delivering personalized customer experiences. However, across business-to-business (B2B) industries, existing martech platforms, data flows and operating models aren’t ready to consistently deliver personalized and integrated sales, marketing and service experiences. This limits the ability of companies to provide orchestrated and preference-driven customer experiences.

 

A big challenge is data silos. Customer data is captured at various spots along the buying funnel but stored in separate data ecosystems. This disconnected data is frequently due to the absence of a system of record and unified customer profiles built from the earliest possible phase in customers’ buyer journeys. Companies often fail to leverage both identifiable and unidentified prospect data because they lack a cohesive platform, system integrations and metadata management and processes to bring this data together. These capabilities are necessary to guide prospects through a personalized, preference-driven buyer journey from initial awareness stages through conversion.

 

The business impact of technology and data connectivity limitations manifest in several ways. One key limitation is that organizations are unable to track prospects through their entire journey. As a result, customer-oriented funnel flow optimization analytics cannot be robustly set up. Another limitation is that channel data is siloed, making synergies across channels difficult to quantify. Lastly, marketing and sales representative data is often disconnected, so delivering a seamless customer experience across digital and in-person channels is challenging. Establishing, building and deploying an appropriate martech stack to deliver personalized customer experiences is crucial.

 

In our experience, the most successful B2B organizations establish and integrate a range of technology tools and platforms to take control of their customer and external data, and to enable personalized and targeted marketing and sales capabilities. A thoughtful approach to building, integrating and deploying a martech stack comprised of an appropriate mix of off-the-shelf and in-house platforms, allows the delivery of personalized, multi-touchpoint customer journeys. The following comprehensive representation of the elements in a typical martech stack shows the specific groups (and types) of systems, as well as the information flows which make this vision a reality.

FIGURE 1: A martech stack helps B2B organizations manage and enable data-driven orchestrated decision-making and deliver personalized customer journeys



First, it’s important to integrate data ingestion capabilities from multiple sources, including customer experience channels and partners. Robust extract, transform and load and external-facing platforms and services from market leaders such as Informatica are frequently deployed to make this possible.

 

Integrated customer and company data flows into organizational stores and mastering capabilities powered by master data management tools for warehousing. This mix of software-as-a-service and organizational cloud-based capabilities enables accurate and deduplicated company and customer lookups. It establishes a clear baseline for robust and accurate marketing and sales impact analytics.

 

Customer data management and enhancement capabilities centrally enrich, uniquify and prepare to activate customer profiles. This data uses first-party data as its foundation, augmenting it with second-party partner data and third-party profile enhancement information data. This is combined with gleaned and interpreted prospect and customer preferences as well as stated consent. Market-standard tools and platforms, such as customer data and data management platforms, coupled with robust processes and data flows from external sources such as LiveRamp and Acxiom and trust management tools such as OneTrust enable this key ecosystem component. The comprehensive picture of prospects and customers enabled by this set of components drives all marketing planning, experience decisioning and the adherence to regulatory and individual privacy expectations.

 

Once a robust set of data platforms and profile management capabilities are in place, organizations can benefit from understanding the impact of their marketing and sales efforts in a granular way, at an individual or segment level for customers and products, with the deployment of a well-designed analytics, measurement and reporting strategy. This is typically enabled by analytics and taxonomy tools and business intelligence platforms operating on owned and unified data platforms.

 

These insights can be supercharged through advanced analytics capabilities, including modeling and data science tools and journey orchestration platforms. These respectively automate interpretation and decisions and subsequent marketing and sales operations. A blend of models and insights yields an overall understanding of customer and prospect behaviors in the context of their needs. This knowledge equips organizations to use predicted future behaviors to create more tailored content and channel touchpoints or experiences, specific to customer segments. These are delivered through experience orchestration and automation platforms. A robust set of data science tools also enables good targeting and segmentation at the front end of strategic planning efforts.

 

The experiences delivered to prospects and customers comprise content, making content management capabilities paramount to any organization’s success. This can grant a company the ability to market in a consistent voice, suited to all its prospects and customers, in the channel of their choice, and across stages of their journey. There is great potential to leverage content and asset management systems, along with clear guidelines and processes for content creation, approval, categorization and tagging, re-use and effectiveness measurement.

 

Finally, execution and delivery tools and platforms ensure that the content and experiences are delivered consistently across owned and paid channels, partner capabilities and via in-person high-touch opportunities and events. The capture of execution data across these platforms closes the loop and enables the virtuous cycle of data insights flowing to planning and strategy.

Optimize account-based marketing (ABM) with centralized customer data



There is justifiably a strong reliance on ABM platforms, supported by external partners or operated by organizations, to manage the complex task of delivering advertising and messaging via third-party sites to customers and leads. However, we commonly see disconnected experience planning and distribution via these platforms, inconsistent landing pages on business websites and a limited ability to associate ABM workflows with overall sales and marketing journeys. To supercharge ABM impact, many organizations are starting to unify and centralize customer data with in-house systems of record, including solutions with 360-degree customer views, customer relationship management (CRM) systems and customer data platforms (CDP). Enabling these martech and data connections requires robust internal processes to operate a balanced set of marketer-friendly technologies and well-established omnichannel analytics, so organizations don’t fly blind. These systems track various attributes about customer behaviors that can be used to better understand individual needs and account dynamics. 

Data analytics takes center stage and enables personalized customer journeys



The importance of analytics cannot be overstated. Without connected data, organizations are unable to tie conversion outcomes back to the channels, content or campaigns that drove them. Comprehensive analytics insights require robust data capture and management, across channels and customer journey phases, as well as the systems that enable interpretation of the interconnected impact of omnichannel marketing and sales activities on engagement and conversion. This key capability can drive a better understanding of the impact of content used across customer segments and for different journey stages.

 

These analytic insights and data drive advanced modeling algorithms to enable cohesive delivery of sales and marketing journeys, as an evolution of disconnected, cadence-based execution across marketing automation tools, partner-driven media and sales channels. Prospects progress first-in, first-out through the marketing funnel, and organizations drive personalized messaging while prioritizing high-value prospect journeys through targeted marketing. In addition, a cohesive martech stack enables analytics and inference so marketing teams focus on the channels individual customers prefer, delivering timely content that resonates. Prospects more efficiently convert into top customers, and marketing return on investment improves.

Connect first- and third-party data earlier in the decision-maker journey



Many forward-thinking B2B organizations already are utilizing third-party and external data sources from providers such as Dun & Bradstreet and Bombora to build prospect and profile management capabilities. By incorporating CDPs with their CRM systems, they’re able to effectively connect near-real-time digital signals and intent to first-party and third-party data earlier in the funnel. This allows comparison of prospect behavior with that of buyers to identify segments and patterns. When combined with third-party data enrichment services, the result is insights and prioritized, actionable lists of prospects.

 

Additional understanding is beneficial at every stage of the journey, from prospecting to onboarding and retention. Another key step in maturing martech stacks is establishing robust analytics to support automated triggers recognition and power artificial intelligence-based (AI) algorithms. This functionality allows for better reporting and the ability to highlight insights. All this requires capturing data across channels and campaigns and utilizing a content taxonomy to measure the impact of specific messaging and creative. Data science and analytics teams must have robust tools to understand influence conversion pathways. This step is key before B2B firms can effectively cater to differentiated customer preferences.

AI helps tailor B2B decision-maker experiences



Another trend in the maturation of the martech stack is the deployment of configurable ABM platforms with strong B2B connectivity and third-party data signal identification such as Demandbase and 6sense. The use of ABM platforms and managed marketing automation tools such as Salesforce and Marketo help organizations cater and react to customer actions and expectations at every stage of the journey. These tools allow for greater control and the delivery of sequenced, personalized messaging to prospects and customers. They leverage insights from enriched data and unified profiles as well as predictive algorithms.

 

In-house AI algorithms are being built to help identify patterns in customer behaviors and actions. They can prompt specific marketing steps with identified prospects, in preferred channels and using appropriate content, to drive desired outcomes. Deploying AI requires tools to orchestrate timely delivery of omnichannel messaging that advances customers along their journeys. This technology-powered personalization improves the likelihood of conversion and enhances customer experiences.

 

B2B organizations are building increasingly crisper customer segmentation and establishing holistic customer journeys from the top down. From heuristic beginnings, this segmentation can be continuously refined through captured data and identified signal analysis. This can power automated and targeted marketing through paid media and lets firms drive qualified traffic to their owned channels, supplemented with search engine optimization tactics. Using test-and-learn experimentation tools to refine and optimize the content on landing pages drives these benefits.

 

Another key technology-driven capability is the automated and timely recognition and routing of high-value prospects and hand raisers. Using web analytics and CDP triggers, sales teams can prioritize high-touch follow-up with active prospects, augmented by retargeting via media and recognition and consistency of delivered experiences on owned channels such as the company’s website.

Charting a course for martech success



The first step B2B firms need to take is to establish a segmentation strategy aligned with a martech strategy. Understanding prospects based on their behaviors, and buyers, based on comprehensive analyses of prior conversion and performance outcomes, is critical. This should form the basis of classification and decisioning about the customer journey the organization wants to provide. Thereafter, by designing an effective martech stack to deliver the experiences and then measure their performance, organizations can continuously refine programs and sharpen core tactics. This task may seem daunting, but it can be thought of systematically as decision-makers move through the prospect, conversion and onboarding stages—and then to the retention and ongoing growth phase.

 

During prospecting, unifying and segmenting customer data with upstream, self-identified and third-party-sourced customer information is important for establishing an analytics pathway from the funnel entry point onward. Organizations thereafter need to prioritize building robust capabilities, using technology and an appropriate operating model, to deliver personalized content and messaging based on decision-makers’ interests, responsiveness and likelihood to convert. These capabilities can take many forms, but they have a common theme. Better data management with a CRM and a CDP, as well as the establishment of a reporting platform or data layer, enables robust analytics and drives AI-powered recommendation and prioritization algorithms. This can automate omnichannel messaging and salesperson-led communication.

 

As prospects move through the sales funnel, continuous data gathering and analytics improve the algorithms and the actions taken across the prospect pool in a virtuous feedback loop. Flexible and scalable content management capabilities enable orchestrated messaging across channels and ensure a consistent voice and theme. This overall set of capabilities crafts personalized journeys through experiences specific to B2B decision-makers while maximizing the potential for conversion and revenue growth. Happy customers also make for strong referrals. Tactics to capitalize on this influence product and service reviews and favorable user-generated content that discusses features and benefits.

Sustain growth and profitability over the long term



Continuing to engage customers and drive increased product adoption also is critical to sustain and grow future revenue streams. This requires a mindset shift in account management, supported with robust ABM capabilities and algorithm- or AI-supported automation tools that adapt content and generate and disseminate messaging. Finally, the concept of a robust data feedback loop from outcomes across all channels to achieve results through personalization is gaining traction. Gathering these insights enables decisioning and planning. It helps drive content selection, modification and personalization to reach prospects and customers in the right channel, based on where they are in their respective journeys.

Cloud-based marketing technology solutions fueled by customer data captured and integrated from across the buying funnel are a foundational component of delivering personalized customer experiences. However, across business-to-business (B2B) industries, existing martech platforms, data flows and operating models aren’t ready to consistently deliver personalized and integrated sales, marketing and service experiences. This limits the ability of companies to provide orchestrated and preference-driven customer experiences.

 

A big challenge is data silos. Customer data is captured at various spots along the buying funnel but stored in separate data ecosystems. This disconnected data is frequently due to the absence of a system of record and unified customer profiles built from the earliest possible phase in customers’ buyer journeys. Companies often fail to leverage both identifiable and unidentified prospect data because they lack a cohesive platform, system integrations and metadata management and processes to bring this data together. These capabilities are necessary to guide prospects through a personalized, preference-driven buyer journey from initial awareness stages through conversion.

 

The business impact of technology and data connectivity limitations manifest in several ways. One key limitation is that organizations are unable to track prospects through their entire journey. As a result, customer-oriented funnel flow optimization analytics cannot be robustly set up. Another limitation is that channel data is siloed, making synergies across channels difficult to quantify. Lastly, marketing and sales representative data is often disconnected, so delivering a seamless customer experience across digital and in-person channels is challenging. Establishing, building and deploying an appropriate martech stack to deliver personalized customer experiences is crucial.

 

In our experience, the most successful B2B organizations establish and integrate a range of technology tools and platforms to take control of their customer and external data, and to enable personalized and targeted marketing and sales capabilities. A thoughtful approach to building, integrating and deploying a martech stack comprised of an appropriate mix of off-the-shelf and in-house platforms, allows the delivery of personalized, multi-touchpoint customer journeys. The following comprehensive representation of the elements in a typical martech stack shows the specific groups (and types) of systems, as well as the information flows which make this vision a reality.

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