Seamless customer architecture

From “One-for-All” to “All-for-One”

Historically, marketers sought to implement a single, wide-ranging technology solution (e.g., marketing clouds) to solve their challenges. But over the last few years, marketers have rapidly begun migrating to best-of-breed technology stacks. According to Gartner, 64% of enterprise marketers now prefer best-of-breed over all-in-one solutions — an almost perfectly inverted ratio from 10 years ago.

This is primarily due to two reasons:

1. There is growing marketer disillusionment with all-in-one solutions, which have been cobbled together through years of M&A activity and rarely come close to fulfilling the capabilities or outcomes they promise.
2. Today’s marketers have increasingly complex needs due to the expansive activity modern marketing requires: more channels, more data, more use cases — all of which are poorly handled by older, all-in-one technology platforms.

Instead, as new use cases and challenges arise, marketers want to choose a piece of technology that is fit for purpose. Often, this means working with a smaller, emergent vendor with particular expertise suited to a marketer’s specific business and problem. Companies realize significant benefits on the back of this trend: eliminating technology redundancy in their stacks, reducing unnecessary spend, unlocking net-new capabilities from niche providers, and seeing significantly better customer relationships.

In practice, this means an enterprise marketing technology leader will now choose an independent SMS vendor, like Attentive, and pair it with a provider like Braze for push notifications while remaining committed to Salesforce Marketing Cloud for email. The same leader might opt for Looker over Tableau, leverage Google Analytics for ad performance while using Amplitude for mobile analytics, and implement MetaRouter over Segment for tag management.

In parallel, this marketing technology leader will have an engineering counterpart that will make major architectural decisions to solve half of the “customer management challenge.” She might choose Snowflake for data warehousing and pair it with Fivetran, Databricks, and dbt, to ensure consistent data flows and support collaborative data science work.

While procurement might have complaints, the above scenario unlocks significant incremental capabilities for the business, providing opportunities that would not be available if they had stayed within one martech ecosystem. It also presents new challenges.

Which “Breeds” Are We Talking About, Anyway?

Before we dive into these challenges — and how to solve them — it’s essential to define the new category landscape for martech. We use the term “best-of-breed” above, but what are the breeds in question? Despite some confusion, there is an emerging consensus as to which categories comprise a modern marketing stack.

In our experience, the typical best-of-breed marketing technology stack consists of 8 categories:

• ELT (extract, load, and transform) tools to stream data into a data warehouse via pre-built data connectors.
• Leading vendors include Fivetran, Talend.
• Data cleansing tools to transform data within a data warehouse.
• Leading vendors include dbt, Airflow.
• Data warehouses to act as the central repository of data.
• Leading vendors include Snowflake, Redshift, BigQuery, Azure.
• Tracking tools (i.e., tag managers) to manage and deploy tags (tracking pixels) on a website.
• Leading vendors include Segment, mParticle, MetaRouter, Rudder Stack.
• Web analytics tools to track and analyze web activity.
• Leading vendors include Google Analytics, Amplitude.
• End channels to communicate with audiences, e.g., SMS, direct mail, email, push, social, ad channels, customer service, etc.
• Leading vendors include Twilio, Optimizely, SendGrid, Zendesk, Facebook.
• Data science tools for statistical analysis of data via programming languages.
• Leading vendors include Databricks, DataRobot.
• Business intelligence tools for data analysis and visualization.
• Leading vendors include Looker, Tableau, PowerBI.

This classification helps guide the digital transformation — or evolution — for many of the most progressive companies with whom we work.

These vendor types represent a modern “reference architecture” for customer engagement, providing all of the capabilities a business would want to deliver a best-in-class customer experience. Well, almost.

As companies shift towards this new reference architecture, they see firsthand what happens when disconnected technologies hinder customer relationships.

The Challenge: Connecting

The entire marketing stack mentioned above aims at one objective: maintaining excellent customer relationships. Each of these best-of-breed tools has a “superpower” that it provides in service of that objective.  

Technology teams need to connect these siloed systems to harness their superpowers, an integration process that is fraught with challenges.

Consider the diagram below:

Here, we see the eight categories of tools, connected in a way that’s typical for an enterprise. As technologists implement these solutions, we can observe that the flow of customer data between them becomes more complicated. This complexity leads to:

• Data Gaps
• Disconnected Customer Profiles
• Broken Connections
• Duplicative Flows
• Data Latency & Scale
• Compliance Failure
• Maintenance Burden

It also creates a tremendous burden on the marketing team:

• Tech Cost: money that could go toward media or content that flows straight to the bottom line is wasted on duplicative and sub-optimal functionality (e.g., each channel has its journey builder).
• Effort and Agility: since customer experiences are maintained across many systems, changing tools or adding new end channels is more time-consuming, expensive, and risky.
• Customer Experience: customers have disjointed experiences and offers since it is impossible to perfectly coordinate end channels without unified orchestration, leading to churn and missed opportunities.
• Reporting: analytics and reporting are significantly more challenging, as conversion and engagement data often live in siloed tools with different identifiers.
• Results: validating attribution is impossible, and experimentation can’t be adequately controlled, leading to false certainty.

Notice just how many connections a modern marketing architecture requires. The obstacles to integration don’t just come from the sheer number of connections, but also the nature of the data they must pass.

So what’s the answer? How do we unify these systems? Through a Smart Hub.

The Smart Hub: Your Martech Nucleus

A smart hub centralizes customer data from disparate “best-of-breed” solutions. It amplifies their power through seamless orchestration so marketers can unlock the true potential of their best-of-breed solutions.

The smart hub acts as the central node ingesting all relevant data sources and orchestrating actions across channels while maintaining a consistent customer profile through a seamless workflow. In essence, it becomes the nucleus around which all other marketing technologies revolve.

The Key Competencies of the Smart Hub

Data Ingestion and Customer Profile Management

A smart hub creates and maintains a customer profile based on numerous identifiers (e.g., email, phone number, name, web cookie). As new identifiers surface in a customer’s profile (e.g., device ID), they are seamlessly joined together, ultimately defining how to stitch all customer behaviors and characteristics.

Data Centralization

Centralization fuels transparent segmentation, downstream orchestration to end channels, and experimentation.

Orchestration

This includes a range of actions, such as syncing a contact list to a customer service tool or triggering a personalized message to an email-service tool. Since all customer data is centralized, dynamic personalization is seamless based on customer events and characteristics across channels.

Experimentation

The ability to launch experiments and seamlessly integrate learnings is essential for any enterprise to continue refining its content for acquisition, retention, and reactivation. Within a smart hub, experimentation is easy to manage by splitting segments into test and control groups and maintaining those groupings across downstream end channels, giving a unified view across touchpoints. All end channel and downstream engagement data feed into the smart hub for reporting and further segmentation.

Centralizing data from best-of-breed tools within a smart hub powers seamless orchestration, producing personalized, relevant, and consistent messaging to customers throughout their lifecycle. As specialized martech solutions and mile-high marketing stacks grow, companies looking for real digital transformation turn to smart hubs to manage their best-of-breed tools, unlocking all of these tools’ capabilities.

The Smart Hub’s Value Drivers

The value of building a seamless customer architecture with a smart hub spans a variety of dimensions.

Revenue Growth & Spend Efficiency

A smart hub can lead to revenue growth and spend efficiency through many avenues, but the two primary drivers are campaign optimization and leveraging net new channels. Campaign optimization produces personalized content to customers at the right time. Net new channels allow marketers to meet their customers wherever they are.

Combining these avenues facilitates coordinated, personalized, cross-channel messages that reach customers at the right time in the right place to drive conversions and improve customer-acquisition costs.

Relationship Growth & Better Customer Engagement

Relevant and personalized content builds a strong relationship with customers. Customers that build strong relationships with brands become compelling brand advocates. These customers will spend more time with the company’s products — using a subscription service (e.g., cooking with a Blue Apron kit or riding a Peloton bike), browsing the company website (e.g., Allbirds’ shoes), or engaging with content (e.g., responding to a TripAdvisor blog).

Cost Reduction via Tech Stack Consolidation

Since a smart hub can act as the brain for marketers’ tools by managing audience creation, orchestration, and dynamic content, robust end channels are unnecessary. Companies can replace legacy “do-it-all” end channels with less expensive, a la carte end channels. A leaner tech stack will reduce technology costs, FTE hours, and agency costs associated with supporting those tools.

Increased Workflow Productivity & Expedited Time to Value

A smart hub reduces manual workflows, reducing the steps needed to launch a campaign. Marketers can launch a campaign without waiting for IT or data engineering to pull data assets and stitch them together.

Reduce Personal Pain

Workflow problems — such as manual journey creation and no single tool to run campaign orchestration — are solved with the integration of a smart hub. Marketing teams can be confident in their ability to streamline superior customer experiences throughout a customer’s lifecycle.  

The integration of a smart hub will help marketers drive better customer experience and grow strong customer relationships. Not only will customers benefit from thoughtful, personalized, and timely content that a smart hub can provide, martech and IT professionals will benefit from consolidated technology stacks and seamless end-to-end marketing processes.

Conclusion

The introduction of a smart hub is an essential shift in the fractured martech ecosystem of endlessly proliferating solutions. Marketers feel an enormous amount of pain, trying to wrangle data and streamline their workflows across so many tools.

A smart hub doesn’t replace best-of-breed technologies and point solutions. A smart hub centralizes and amplifies each solution’s capabilities by allowing marketers to build a modular but seamless stack built to manage customer experiences and help marketers get back to providing a more human customer experience.