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How to Set up an Outbound Marketing Tech Stack: A Comprehensive Step-by-Step Blueprint

Davis

January 6, 2024
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How to Set up an Outbound Marketing Tech Stack: A Comprehensive Step-by-Step Blueprint

Setting up an Outbound Marketing Tech Stack
Setting up an Outbound Marketing Tech Stack

Outbound marketing technology stacks have evolved from being a nice-to-have to mission-critical infrastructure for modern B2B and DTC organisations aiming to drive scale efficiently. Tech-driven outbound capabilities like personalised, automated multi-channel campaigns and triggered cross-channel messaging help break through the noise to connect with audiences on an individual level across the entire customer journey. 

However, with an overwhelming choice of martech solutions out there ranging from niche bots to elaborate customer data platforms, constructing a cohesive stack that aligns to your strategies and resources is akin to solving a complex puzzle. 

In this definitive guide, we will provide a step-by-step blueprint to plan, architect and implement a best-in-class outbound marketing technology stack tailored to your organisation’s maturity, budgets and business objectives. 

  • Chapter 1 will cover the key mindset shifts and design principles to anchor your tech stack strategy. 
  • Chapter 2 provides the technical building blocks required to establish a scalable data foundation.
  • Chapter 3 maps execution channels for multi-channel activation.
  • Chapter 4 explores comprehensive automation and orchestration to streamline outbound operations,
  • and Chapter 5 focuses on intelligence capabilities that allow your stack to continually optimise through built-in feedback loops and machine learning.

Let’s get started!

Chapter 1: Adopting an Outbound Marketing Technology Mindset

Outbound Marketing Technology Mindset

Before diving into the specific stack components, embracing an outbound technology philosophy across stakeholders from marketing to the C-suite is vital for alignment, strategic prioritisation and change management required to drive adoption success:

Growth Mindset

View your tech stack as an adaptive organism that evolves with business needs rather than a static expense. Continually evaluate both emerging and existing solutions to enable next-generation strategies across the customer journey. Outbound strategies should also progress from broad targeting to fully personalised lifecycle campaigns.

Fail Fast Culture

The best enterprise marketing stacks support continual testing and experimentation of content, offers, channel mix and segmentation parameters through embedded analytics and simple UIs. By taking an agile, fail fast approach, you double down on what works while quickly eliminating low-ROI initiatives across owned, earned and paid channels. 

Unified Data Standards

Centralised, accessible and structured customer data is the lifeblood of orchestration, personalization and automation across an outbound stack. Establishing unified protocols, schemas, tagging standards, metadata hierarchies and quality KPIs cross-departmentally prevents downstream issues from disjointed, incomplete or messy data.  

Omni-outbound-channel Mindset

While omnichannel typically refers to consistent inbound experiences, adopting this mindset for outbound messaging ensures coordinated timing, complementary content and unified brand+voice across all channels based on customer preferences rather than internal siloes. 

Automation First

An automation-first approach applies to both campaign execution and back-end workflow operations. The ultimate goal is leveraging technology to efficiently scale high-value, strategic initiatives while eliminating redundant and repetitive manual marketing tasks through intelligent automation capabilities.   

With the foundations firmly established through the right organisational mindsets and principles, let’s explore the technical building blocks. 

Chapter 2: Constructing a Scalable Data Foundation

Scalable Data Foundation
Scalable Data Foundation

The foremost consideration for building any marketing technology stack is assembling flexible and high-performance data infrastructure. Without reliable, easily accessible unified customer data that serves as a single source of truth, you severely limit orchestration, automation and personalization potential across outbound and inbound channels.

Robust data infrastructure provides the centralised nervous system that senses and responds to customer behaviours and preferences across their journey in real time through interconnected execution channels and engagement systems. Let’s explore the core components:

Customer Data Platform (CDP)

The foundation for managing reliable first-party data leveraged across your stack starts with an enterprise customer data platform (CDP). Leading options like Adobe Real-Time CDP, Tealium, Segment, ActionIQ and Blueconic serve as the customer data hub - capturing data from databases, apps, websites, payments systems and more. 

CDPs resolve identities to form unified customer profiles by applying data quality protocols. Accessible via APIs, this enriched dataset fuels downstream personalization. Consider the below CDP capabilities tailored to your martech maturity stage:

Identity Resolution

As customers engage with brands across locations, devices and communication modes, a CDP should capture those interactions then use algorithmic identity resolution to connect the dots between engagement breadcrumbs to assemble a unified profile. Techniques ranging from deterministic (exact username matching) to probabilistic (inferring user 123 on web is likely user A on mobile given location data overlaps) fuel personalised outbound triggers.

Integrations

With data living across CRMs, web analytics tools, marketing automation platforms, support ticketing systems and more, having 300+ pre-built data source connectors minimises IT involvement required for piping datasets into a CDP. Reduced dependency on engineering resources accelerates time-to-value. Track core events like email clicks, site actions, transaction data types in a single platform.

Predictive Modelling

Applied machine learning for tasks like propensity scoring allows predicting the likelihood of prospects to convert or customers to churn based on statistical models trained on behavioural datasets. This enables targeting high-propensity accounts with tailored nurture campaigns and optimising customer retention programs with preemptive outreach to at-risk subscribers. Auto-detecting predictive attributes that most influence outcomes surfaces insights.

Audience Activation

To operationalize data-driven outbound activations, dragging and dropping audience segments from the unified dataset within your CDP into integrated execution channels is key. This allows triggering email nurtures when contacts exhibit key traits, building lookalike models of high LTV customers for targeted ads and even exporting lists to offline channels.

Orchestration

Streamlining customer journey mapping across channels both digital and physical is enabled by orchestration engines within modern CDPs. This entails visually modelling multi-step sequences customers move through and then tracking engagement events at an account level across email, web, mobile etc to inform next best actions and personalise path scenarios. Multiple paths can be defined for testing and optimization.

Data Pipeline (ELT/ ETL/Reverse ETL)

With reliable data centralised in your CDP, specialist extract, load and transform (ELT) tools like Fivetran actually allow movement of datasets to downstream execution channels while altering formats suitable for each platform. This is the connectivity tissue enabling a frictionless flow of data across all stack systems.  

Robust ELT connectors and pre-built workflows eliminate complex coding requirements for business users while still providing advanced data modelling, standardisation, scheduling and stream processing of large datasets. Consider functionality around: 

  • Cloud migrations: Future-proofing through pure cloud-based architecture
  • Scalability: Channels leverage cloud data warehouses (next section) for immense scale without incremental costs
  • Built-in transformations: Intuitive drag-and-drop data shaping and modelling 
  • Advanced scheduling: Dataflow automation ensures seamless interoperability between systems 

Data Warehouse Environment

A performant, secure and stable cloud data warehouse environment like Snowflake, BigQuery or Amazon Redshift provides the storage, processing and analytics layer for the stack - enabling both high-volume data migrations from the ELT alongside real-time unified insights. 

This is where cross-functional teams can access clean, transformed datasets through business intelligence tools or SQL clients for everything from flexible reporting, ad hoc queries and data discovery to complex data modelling, machine learning model training and multi-touch attribution analysis.

With best-in-class commercial and open source charting, dashboarding and notebook interfaces like Tableau, Looker, Metabase and Jupyter available, leveraging the granular engagement data within the cloud DWH unlocks unlimited analysis use cases without Ops or data eng bandwidth constraints. 

By aligning stakeholders around customer data as a strategic asset through every layer outlined - from collection (CDP) to cloud transformations (ELT) to flexible consumption (DWH) -  you construct an extensible platform to operationalize data-driven customer experiences powered by unified intelligence.

This core data infrastructure offers the roots and trunk for growing additional branches (execution channels), foliage (orchestration) and fruit (measurement) of your enterprise marketing technology tree.

Chapter 3: Mapping Required Activation Channels

How to Map Activation Channels
How to Map Activation Channels

Now with scalable data piping established, the second step involves mapping required outbound activation channels based on strategies, budgets and in-house skill sets. Options fall into 5 core categories:

  • Email 
  • Advertising 
  • Social engagement  
  • Direct mail
  • Conversational 

Here we'll cover considerations for core execution platforms and solutions within each channel to assess against business objectives around budget, staffing and priority.

With scalable data infrastructure cemented through your customer data platform, data pipelines and cloud data warehouse, the next step is deciding which outbound engagement channels should be enabled based on strategies, budgets and existing in-house skills. 

Email remains the versatile workhorse channel that can support both top-of-funnel lead nurturing campaigns as well as tailored lifecycle communications. To power personalised email at scale, leading enterprise ESPs like MailChimp, Klaviyo and Customer.io tightly integrate with underlying CDPs to trigger real-time behavioural messages and allow drag-and-drop customer segment export for groups like high-value customers, contract renewers and product adopters. Capabilities around deliverability optimisation, multi-variant testing and rich analytics into recipient engagement at an individual message level also enable continual optimisation of email targeting and content. 

Beyond email, orchestrating paid and organic social media activations in a unified manner is vital for diversified reach and engagement - especially for consumer facing brands. Multi-channel platforms like Sprinkler, Socialbakers and Sprout Social connect directly to digital ad accounts while empowering persona-based content strategies tailored to channels like Facebook, Instagram and LinkedIn. CDP integrations also facilitate activating unified audience segments for relevant social messaging. Monitoring channel contribution and influencer attribution provides optimisation insights.  

For transaction-oriented businesses, catalogue-based direct mail still provides an invaluable physical touchpoint when coordinated as part of an omni-channel customer journey. Solutions like PFL and Printi merge variable print content with digital mail production workflows to enable personalised packaging and mailers powered by real-time data feeds of customer attributes from unified profiles within your CDP.

And with the prolific usage of messaging and voice channels, conversational engagement layers like chatbots and two-way outbound messaging over platforms like WhatsApp, Facebook Messenger and SMS allow expanding reach through AI-powered experiences thanks to CDP profile data connectivity. 

Chapter 4: Enable Seamless Orchestration Between Channels

Seamless Orchestration Between Channels

With key channels mapped to activation technologies, seamlessly orchestrating journeys across those touchpoints is enabled through customer journey orchestration and workflow automation tools. 

Multi-step journey orchestration platforms like Sailthru and Adobe Campaign allow both marketers and customer success teams to visually map tailored inbound and outbound paths a customer moves through. This covers exposures across email, mobile push, web experiences, chatbots and more. Platforms leverage underlying profile data to then actively manage engagement flows at scale for cohorts – from triggering messages to optimising paths based on aggregated success metrics.

On the sales side, CRM workflow automation platforms like Microsoft Dynamics and HubSpot empower account managers and reps to configure rules-based lead nurturing workflows specific to their team priorities. This includes lead routing and assignment, triggering automated email and SMS tasks based on profile attributes and behaviours tracked across your unified dataset, configuring notifications and more based on the ideal cadence. CRMs naturally serve as the interface layer for all sales staff interfacing directly with prospects and customers. 

Finally, behind the scenes marketing operations workflow tools like Introhive streamline all back-end processes across disparate stack systems - everything from data standardisation, automation of repetitive reporting, integrating external applications via API, conditional notification logic and workflows tailored to common cross-functional sequences. Drag-and-drop build environments even allow business users to model workflows spanning data transformation, normalisation, movement across systems and conditional branching without engineering support.

Chapter 5: Enable Continuous Optimisation and Intelligence

Continuous Optimisation and Intelligence
Continuous Optimisation and Intelligence

With the ability to activate unified audiences at scale across orchestrated outbound channels, the final element involves using engagement data, machine learning and experimentation capabilities to ensure your messaging strikes the right chord over time.

Unified analytics solutions like Amplitude, Mixpanel and Fullstory automatically consolidate all interaction and behavioural data across each stack component through pre-built connectors. This delivers engagement visibility ranging from email campaign performance to website behaviour funnels and even cross-channel customer journey analytics. Marketing and CX teams can then uncover optimisation opportunities through cohort reports, retention and churn analytics, funnel analytics and other derived insights only possible thanks to the underlying centralised dataset.

Layered on top, enable continuous multivariate testing of audiences, offers, content and channel prioritisation through dedicated experimentation platforms like Optimizely. With direct access to customer profile data from your CDP, campaigns can be adapted to micro-segments to drive relevance. Tooling also supports champion vs challenger campaign testing methods using engagement and revenue goal metrics to double down on what resonates.

And finally - as customers interact with various brand touchpoints across devices and communication platforms - leveraging the evolving identity graph within your CDP ties together behavioural breadcrumbs at an individual level. This fuels personalisation engines while resolving anonymous users over time via inference matching based on heuristics like email patterns.

Conclusion and Next Steps

We hope that this comprehensive guide has provided a structured approach and actionable blueprint to help demystify the process of implementing a best-in-class marketing technology stack tailored to your organisation’s specific outbound engagement and orchestration requirements. 

With the exponential growth in martech solutions however, executing an ambitious stack transformation requires thoroughly vetting capabilities across dozens of complex platforms and tools. It demands deep technical expertise around integrating APIs, debugging data flows, ensuring interoperability between components old and new. 

That’s why over a hundred forward-thinking enterprises have chosen to partner with Devhaus as their trusted martech stack advisor and implementation catalyst.

With a proven track record architecting and executing tailored stack roadmaps aligned to your budget, resources and use cases, Devhaus serves as your martech stack implementation partner across every step explored in this guide:

  • Clarifying engagement strategies and requirements
  • Auditing existing infrastructure and gaps 
  • Vetting and aligning vendor capabilities or building custom if required
  • Leading solution integration with future extensibility  
  • Providing adoption coaching and optimisation support post-launch

As a Singapore-based digital transformation consultancy, Devhaus can help your organisation benefit from up to 70% in government subsidy funding through Enterprise Singapore's Enterprise Development Grant specifically aimed at enabling impact-driven automation. 

If you see automation technology like marketing stacks as key to bolstering efficiency, agility and revenue contribution across your regional or global organisation, set up a consultation with our architects today by filling up our enquiry form.

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