Customer
Behaviour
Timeline: 4 weeks +
Investment: £24,000+
All projects fully scoped beforehand.
Go beyond the numbers. 173tech combines machine learning with deep analytical expertise to uncover the ‘why’ and turn insights into impact.
overview
Our Three
Big Goals
There comes a time when you can no longer run your business off educated guesses and market research. When you need firm answers on not just what is happening with customers but how you should affect it.173tech build bespoke data solutions for growing businesses.
Uncover
The 'Why'
People are complex! 173tech provide deeper analysis on what is really driving customer behaviour.
Just like we did for…
Where we applied customer value to app usage to discover winning features.
Predict &
Influence
173tech can implement predictive models to anticipate key customer actions proactively.
Just like we did for…
Where we modelled different signs of churn and applied them automatically.
Dynamic
Segmentation
173tech can automate the segment and cohorting of customers at scale, enabling personalisation at scale.
Just like we did for…
Where we were able to segment million of users to allow for easy intervention.
Creating Value
Fragmented customer data sits across multiple sources and departments.
Integrate data from various platforms to create a unified view of the customer journey.
Customer actions are distinct from their value, behaviours and feedback.
Overlapping different data points gives you a holistic picture on your customers.
You are constantly reacting to what customers have done sometimes weeks later.
Predictive analytics can give you early warning signs on key moments like churn.
DATA WE INTEGRATE
Secrets From
Your Sources
WHAT WE DELIVER
Dashboards
& Beyond
We surface data models in rich, user-friendly dashboards, accurate predictions and through deep-dive analysis.
DATA WE INTEGRATE
Not Mystic ,
Just Modelled
Our aim at 173tech is to get you started with predictive analytics in just a few months. We build scaleable and adaptive models that stand the test of time.
We start off with a few sessions aimed at understanding your business model and current infrastructure to identify the gaps where data can make a difference. We map out your customer journey, different touchpoints, data volumes and KPIs.
Your Team: Project Stakeholders (business & technical)
Your Time: Two lots of 45 minute sessions typically
Key Outcomes: Information gathered feeds directly into our recommendations
From here we will start an exploratory data analysis, most often focusing on the lifetime value of your customers. This analysis aims to input directly into your business decisions and highlight critical areas for growth. It also serves as the basis for us to then leverage machine learning to enact more complex models – allowing us to automate the process of this analysis.
Your Team: Project Stakeholders (business)
Your Time: We will walk you through the analysis and then reconvene for feedback/further questions.
Key Outcomes: In-depth analysis on customer behaviour.
Building a machine learning model, such as churn prediction, involves several key steps. First, we gather and clean customer data, next, we explore the data to identify patterns and select relevant features. Then, we split the dataset into training and testing sets and choose an appropriate model. From here we now need to see how the model performs so we can train and refine it.
Your Team: Project Stakeholders (Business)
Your Time: We will present you with the initial results of the model and compare
Key Outcomes: Data models – not yet productionised.
Training a machine learning model, involves selecting an appropriate algorithm and feeding it structured data to learn patterns. The dataset is split into training and validation sets to prevent overfitting. During training, the model adjusts its parameters to minimise error using techniques like gradient descent. We will then refine the parameters of the model such as adjusting learning rates or tree depths, helps improve performance. Once the model achieves satisfactory results, we are ready to activate it.
Your Team: Project Stakeholders (Business)
Your Time: Minimal
Key Outcomes: Data models – ready to activate!
Activating a machine learning model, involves integrating it into a real-world system for making live predictions. The trained model is loaded into a production environment, often exposed via an API or embedded within business software. Incoming customer data is pre-processed to match the model’s training format before being fed into the model for inference. The predictions are then used to trigger actions, if our model was for churn risk – this might be personalised retention offers for high-value customers. Continuous monitoring ensures accuracy, and feedback loops help refine the model over time to adapt to changing patterns.
Your Team: Project Stakeholders (Business)
Your Time: Feedback is really key to refining the model’s results.
Key Outcomes: Activated data models in the tolls your team is using.
IMPACT
Returning Your Investment
Pricing will depend on the amount of data sources and end goal. We will always give you a full time/cost upfront.
Get In Touch
Our friendly team are always on hand to answer questions, troubleshoot problems and point you in the right direction.
