Are your customers asking for a DXP instead of a CMS? Are your developers struggling to build personalized digital experiences with Drupal?
Efficiently managing digital content has become commodity by using giants such as Drupal. Making that content and customer experience personal and consistent across all digital touchpoints can still be challenging. However, with ever rising customer expectations, it's becoming more important. No wonder that Gartner has replaced the CMS quadrant by a DXP quadrant.
Not sure what a DXP really is about? This blog can help you.
In this post, I will explain how you can build your own DXP for Drupal using Open Source components.
- Not just a bucket of products
- Not just a website or an app
- Not a tool
- Not a one-way communication vehicle
- Not standalone
- Not IT nor Marketing system
- NOt a monolithic system
So now we have that out of the way. A DXP is not a single product. You can maybe compare it to the word website. It can mean anything as long as it is digital. A website meant that you had a place where you represented yourselves or shared information. A DXP is a place where your customers come to solve questions they have, in a digital form. There is a lot of research on this topic, but I'll leave it to you, the reader, to dig in a bit deeper. I imagine you would get overloaded if you would google "what is a website" as well :-)
Drupal is also moving forward with its content management capabilities and the video below shows how a content editor would work with Drupal to create rich landing pages. That said, Drupal is still missing many other capabilities that needs to be augmented with tools in the same ecosystem to become a DXP building solution.
Creating great editorial experiences
This video demonstrates how you can create great editorial experiences using Dropsolid Rocketship & Layout Builder.
Management capabilities of a DXP
In terms of Management capabilities it is fairly easy to create registration, login & password management, roles & permissions but also to create group communities together so they can exchange information. It is a lot harder to keep a customer profile or to move towards voice and immersive elements using Drupal out of the box.
Platform capabilities of a DXP
In terms of Platform capabilities Drupal makes it very easy to do custom development because of its years of community building on drupal.org. This also makes custom integrations very easy but it is a lot harder or near impossible to build neural networks in Drupal or with customer data that interacts with a Drupal application. Not only because of Drupal but also because how the web works and the many caching layers such as a CDN or Varnish are in between an interaction of the end user and Drupal.
Another important benefit of Drupal is its API-First approach to allow frameworks such as Vue, React, Angular or others to create multi-channel experiences in a headless/decoupled or hybrid way.
Experience Capabilities of a DXP
In terms of Experience capabilities, it is also lacking when it comes to detecting intention or introducing personalisation and A/B testing. On the plus side, Drupal has a very powerful Search API extension which can be used to index the site and query structured data. However, to personalise this search or to boost information based on AI feedback loops it becomes a lot harder.
What are we missing?
- Customer Data Platform
- Personalisation
- Consent management
If we trim it down to practical capabilities we are missing a tool in our toolset for the above 3 cases. In the video below I'm demoing how this can be solved by utilizing the power of Apache Unomi. Next to that we can augment our toolset towards marketing automation with Mautic.
Drupal Personalization
This video demonstrates Dropsolid website Personalization for Drupal based on Apache Unomi.
Optimize!
The ultimate goal is to increase conversions. The optimizations you do within the DXP are ultimately to drive conversions so that you can connect with your end user through marketing campaigns, powered by manual or automated actions. In the image here we see that in Google Analytics we segment the data in the different intention groups that were detected by the AI. We can then detect if certain intention groups have a higher conversion rate than others and start to change the content to influence these numbers over time. We can also add A/B testing and measure the result within the goals that were set in Google Analytics.
How can you do this yourselves?
Need help? Happy to assist you.