At Creative CX, we believe that successful experimentation starts with a deep understanding of the problem.
Too often, businesses rush into testing ideas without spending enough time clarifying what is really happening in the customer journey.
They end up wasting time and valuable resources trying to solve non-existent problems and then wonder why they have very low win-rates and are struggling to make an impact.
This is why triangulating data sources is essential. No single method tells the whole story.
A complete and reliable picture emerges only when multiple perspectives and research methods come together.
Tools like Contentsquare play a vital role in this, as part of a broader research-led approach.
Why We Take a Problem-first Approach
Our approach always includes a number of research and analysis methodologies, the quant and the qual, to identify the biggest well-understood customer problems across the entire end-to-end user journey, spanning multiple channels.
And then we conduct collaborative ideation sessions with client teams to generate many different potential solutions and executions to each problem statement that can move into A/B Testing.
By embedding this overall problem-first approach across the business, this results in a greater percentage of ideas being evidence-informed, leading to higher win-rates and greater impact for the business.
The key to all of this is in the quality of the insights and this is where tools like Contentsquare come in, as they help us uncover the behavioural side of the story by providing multiple ways to view customer activity.
These platforms offer different perspectives on journeys, micro-behaviours and interaction patterns, each revealing clues about what customers are doing, where friction occurs and how various segments behave.
Actually, the differences in how segments behave lead to amazing personalisation opportunities – but that’s for another article.
This triangulated approach gives us a much deeper and more accurate view of the customer journey.
By combining quantitative and qualitative sources, we can better understand where problems appear and why they happen.
Once the root causes are understood, behavioural analytics tools again help us quantify the scale of the problem, which is critical for prioritisation.
And now with the recent AI enhancements this is even easier to do.
The Analysis Bottleneck
Two of the biggest blockers to value in many experimentation programmes sit at opposite ends of the workflow.
Upstream, teams often struggle during the opportunity discovery phase, where identifying and understanding the right problems can be slow, inconsistent or overly reliant on manual investigation.
Downstream, analysis becomes a second major bottleneck, with teams spending significant time deciphering experiment results and stitching together data to understand what actually happened.
Contentsquare’s growing AI capabilities help to remove much of this friction.
Automated insights, intelligent reporting and seamless integrations across data sources all contribute to a faster and clearer picture of what is happening.
Instead of spending weeks interpreting results, teams can move quickly to action, learning and iteration.
An example of this is with the ContentSquare session recordings analysis, which, before the latest AI capabilities, would take teams a considerable amount of time and effort to complete.
Now this gold mine of insights is so much more accessible.
These AI features are becoming increasingly powerful.
By connecting with other data sources, the platform can surface richer insights without requiring teams to dig through multiple dashboards.
This creates more user-friendly access to insight and enables agentic workflows that guide teams toward the most meaningful problems, opportunities and next steps.
Importantly, these agentic workflows can operate in an always-on state.
They can trigger activities based on real behaviour or emerging patterns, prompting teams to investigate issues, explore opportunities or validate changes as soon as they appear.
This means insights move closer to real time, and teams are supported with proactive nudges rather than relying solely on scheduled reporting cycles.
In addition to this, the really exciting area that we’re moving towards is automated direct intervention within the user journey to solve customer problems in real time. Which is one big step beyond just having the insights.
AI does not replace human judgement, but it makes it far easier for teams to focus their time where it matters most: understanding, prioritising and acting.
Even automated workflows require humans to design and orchestrate.
Recognition of Our Approach
Our work with Contentsquare has been recognised recently, with Creative CX named EMEA Solutions Partner of the Year.
We are proud of this achievement because it reflects our commitment to combining the right technology with a research-led, problem-first approach to experimentation.
It is also a testament to the strength of our partnership and the results we have been able to deliver together for our clients.
Our Perspective
At CCX, we see behavioural analytics tools as powerful enablers within a broader triangulated research framework.
They help us understand what is happening at scale and from multiple angles, while qualitative methods help us understand why.
When combined, these perspectives allow us to create clearer, more accurate and more actionable problem statements.
With the right approach and the right technology, experimentation becomes more than a process.
It becomes a powerful driver of growth, grounded in a confident understanding of customer behaviour and the impact of the problems that need to be solved.
