Building a Marketing Technology Stack 2023

Marketing technology stack framework

Marketing technology stack or otherwise called Martech Stack is a new term in the last few years in Marketing and technology space. The biggest budget in business are moving from traditional technologies to specific marketing technology as an investment in marketing, could have a direct impact on the business. And also the high expectation from the consumer side to business needs a personalised and smooth experience across every touch points in their journey. Thus the reason the amount of focus on this space is increasing. Let me use E-commerce as an example industry to go through sample problems and solutions as everyone knows this space 🙂

Marketing technology stack framework

Why did you need to have a vision for your Marketing Technology Stack? 

Building a marketing stack or customizing the existing stack comes with a lot of new feature at the same cost of complex problems as well. However, all of this could be avoided if we plan things properly in advance.

A Non Visible Problem: Efficiency on Time and Resource

Life wasn’t that much easy for marketers before 10 years as it is now 🙂 There weren’t a lot of marketing technologies (MarTech) and Advertising technologies (AdTech) tools available to make their job easier. Especially data-driven marketing channel managers are lucky that they enjoy the most part of this automation innovation.

In Social Advertising, One of the simplest example that helped marketers to scale the campaigns is testing different variations & bulk ads creation, tools like Nanigans or Smartly made easy the creation of 10,000+ creative variation in few minutes.

Imagine before a couple of years, we used to sit late at night or waking up earlier to make sure, we pause/resume the non-performing campaign or launching a new campaign. Now the advanced AdTech tools made our job easier our to set up the end TARGET GOAL (any CPA) and then the system AUTOMATICALLY pause/resume/scale the best creatives based on the TARGET GOAL among the 10,000+ ads we created before.

“For every action, there is an equal and opposite reaction” Correct?

So when things are simple, it’s easy to manage and control, but when you have multiple systems, It comes with complexities on the initial stage if you don’t architect well.

In analytics, The most famous issues analyst face in the first stage of every tool they use is discrepancies in data between different tools. For example, the way Google Analytics attributes the source traffic of purchase transaction is different from your CRM backend system or even another analytics tool. (Attribution: First Click, Last Click, View through, etc)

Or the simplest example is date(or currency) difference between tools because of the default time zone you set up on the initial stage.

All these tools act accordingly based on how we set up them, so we are the one who responsible for it.

An Unexpected Problem: Cost Savings and Simplicity (when people overuse it)

In terms of cost savings, most of the tools nowadays try to provide multiple features which in some cases overlaps what we have already with other tools and this is not easily avoidable as there are some unique features available in that tool. In straightforward look, it may not be a big problem but once we are in the stage of too many tools with us, we start to think 🤔 which tools we should be using for what. This is all creates unnecessary confusions in people mind.

Just think why Steve Jobs wear the same dress every day and his designs are simple to the core… People become over using everything, then they forget about what’s the initial objective we planned for.

Example: In a typical E-Commerce, Marketers use analytics like Google analytics for website dominantly, and use analytics like Localytics or Amplitude for mobile apps even though Google analytics has a basic mobile analytics option as well. Yes, people need mobile messaging option which Google Analytics doesn’t have. And people use tool Like Appsflyer to do mobile app attribution whereas Localytics still can provide the basic attribution (or say tracking link creation) but yes not to the level of Appsflyer. And there are complexity keep on going. Not easy to understand on the initial stage.

But knowing upfront about all of these overlaps and integration issues between different tools can allow us to save our cost and make our job easier. So let’s see in depth what are the factors we need to consider…

The List of Factors need to consider when architecting Marketing Technology Stack

  1. What’s your base CRM environment?
  2. Integration with your analytics tools
  3. Integration with you paid advertisement management tools
  4. Integration with your Tag Management Solutions
  5. Integration with your Personalization systems
  6. Integration with your Marketing automation systems (Email, Push Messaging, InApp)
  7. Whether you are looking for basic features or cutting-edge features which is not used by 80% of the companies currently
  8. Whether your stack has a budget?
  9. Whether your stack is Google or Adobe or NonGoogle or NonAdobe?
  10. Implementation of those tracking
  11. Support

List of blocks in the Marketing Technology Stack

I believe in looking at the strategy or implementation of tools or even running a survey of users should be taken from marketing funnel perspective as each funnel or say stage in the journey of the user is different and need special attention. No best way to structure marketing things than the funnel structure. so let’s look at those blocks in this structure.

Content Creation

As a base, everybody would have a Content management system (CMS) or even tools like HubSpot to create simple landing pages for promotion. Selecting the right content creation makes a lot of people job easier. Selecting a very complex and advanced tool for simple landing page creation can

  • Always make the marketing team depend on IT
  • By having a simple drag and drop tools makes the marketing team create pages in few secs and get the job done
  • Not just that, the new landing page and CMS tool has a lot of advanced features like A/B testing, personalization, automatic lead collection to CRM systems

I will be writing soon a round-up of comparing different landing page and CMS tools which are helpful for marketers especially.

The industry well known CMS is WordPress as it makes people job easier to create anything faster. For landing pages, there are tons of tools available, neil patel guide on this very elaborative. 

 Blog Content (CMS)Landing Page toolsDynamic Paid Creatives

Awareness & Acquisition:

Once the content is ready to be read or promoted, we need to look for either organic or paid ways to get exposure (awareness). Having proper tools helps to do our job efficiently, creatively and scale

  • A tool that helps us to research about content (it should be before content production, but let’s put it here as it helps other stages in the funnel as well)


 Content OptimizationSEO optimizationReferral & Other tools


 SearchDisplayPaid SocialAdditional Networks
PurposeThe purpose is how to manage all these channels in scale (like a few thousand ads creation, spending a few thousand, automated rules, etc)

The whole stack of double-click solution has many features for every business. Whether you are a marketer or publisher or agency, each of them gets its own advantage from their solution.

(2) Will be sharing here a detailed article on choosing the right paid ads management tool as it considered as a big topic to write separately.

Awareness & Acquisition:

Once the user has been acquired into our own media platforms. Own media platforms are social media, email database, mobile app, SMS, etc . we are able to reach them to engage about promotion, newsletter and need to retain them with us.

Previously we used to work silo like someone sending bulk SMS notifications, some sending email, some contacting on social media posting based on their strategy. but imagine you are sending a 10% to a user called John via SMS and simultaneously sending another email to the same John with 15% discount. Does it look correct or confusing?

 Small ScaleMedium levelEnterprise level ToolAdditional Networks
PurposeThe purpose is how to manage all these channels in scale (like a few thousand ads creation, spending a few thousand, automated rules, etc)
ToolsGoogle optimizeGoogle optimize 360   VWO Insider Evergage   Dynamic Yield  

Check this guide for detailed comparison of website optimization tool

 Small ScaleMedium levelEnterprise level ToolAdditional Networks
PurposeThe purpose is how to manage all these channels in scale (like a few thousand ads creation, spending a few thousand, automated rules, etc)
ToolsGoogle optimizeGoogle optimize 360   VWO Insider Evergage   Dynamic Yield  

Check this guide for detailed comparison of website optimization tool

Analytics – Business Intelligence(BI) – Machine Learning(ML):

Tracking: First foremost of important thing in digital activity is tracking. As we all know “the one measurable is easy to make actions” so if we can track and tie the information from first touch point to end touch point, we will be king of our data!

Analytics: We have data on contents we created, a user who exposed to It, engaged with it.. what, when they engage, whether they convert or not, where they drop off blah blah. so having proper analytics tools to track each stages going to provide answers for our curiosity.

DataSync & BI: Once all this data is tracked, we need to act on whether audience segmentation, data sync between different tools, sending further communication to this audience, and dashboard to monitor and find insights

Data Warehouse: It is very hard to have one analytics that has everything. Web analytics can have its own but may not have what’s happening on the advertising side or even offline transactions data. So we need a data warehouse to store data from different analytics and other tools.

Machine Learning: Once we find insights with current data, we may want to go next level of predicting what could be the feature. So there needs a proper infrastructure to run all these predictions. Once the predictions are ready, we may want to automate the next set of actions

Reporting Automation: Sometimes you want to automate the data transfer between different tools, for example: automating the transfer of Facebook ads data into google sheet or tableau or even big query is not a simple thing. So the stack we build needs to consider all this factor. If we build the stack where it can natively has a feature to transfer this data, that’s the best scenario. If we not, we need to build custom solutions to make this happen.

Web AnalyticsMobile App AnalyticsBI ToolsDataWarehouseMachine Learning Environments
PurposeThe purpose is how to manage all this channels in scale (like few thousand ads creation, spending few thousand, automated rules, etc)

Would like to continue expanding and adding details as much as need to keep it useful, please comment if there is anything need to be added or modified.