Customer experience 
Why real insight into customer experience is valuable
Many companies send on ‘ NPS ‘ or ‘ Customer Experience ‘ and that’s a good start. But do you really want to know what your Customer Experience is all about? Does a better customer experience also ensure higher conversion? And what are the most important touch points for the customer? Where is the experience most affected? We believe in quantifying behavior. Understand the drivers of customer experience and quantify how much a 1% increase in customer experience affects your company’s sales. Our team quantifies your customer journey using advanced statistical methods and gives you the ‘ buttons ‘ to improve your customer Experience.
How we help you better serve your customer (yet)
Step 1: Understanding the purpose and Context
We help you to make the scope and the goal concrete. Then we can clarify what the drivers in the customer journey are when it comes to: customer satisfaction, retention, NPS, CES and financial results. To do this, a number of sessions with the GROWTH model (from our sister organisation PEBex) are made clear what the goals are.
Step 2: Understanding your current customer journeys and the challenges therein
A clear understanding of the context is essential. Which journeys are already worked out? How do you tackle CX management in your organisation? Which data sources can best be used for driver analysis?
Step 3: Inventory of existing data sources
A: With CX and data teams discuss which data is available
In between step A, the development and construction of the conceptual analysis model is started. Here we start completely blank to make it clear, together with the various stakeholders within the organisation, the CX team, it, BI and the data team, what data and data sources are, how we can unlock them and where enrichment is still needed.
B: Development Research Model
Based on this inventory, a conceptual smart data research model will be developed. Includes an overview of the variables and sources included in the model. At this stage, the statistical hypotheses will be compiled. It will also be necessary to determine whether we have sufficient data to analyse them. In addition, legal agreements are drawn up that are necessary to obtain the required dates for the model, so that we can act as a processor.
C: Identify “grey spots” in the data
Finally, we verify that the collected data from the different data sources are complete, and can be linked together. Where the data may and may be used in the investigation and what data may be missing. Of course, we think about how these gaps can be filled. [/blue-row]
Step 4: Statistical modeling CX Model.
During step 4 we will link the data from different data barons through data wrangling. The data from the different data sources are linked at the lowest possible level (customer-). For this, all data will be merged, adapted and transformed into a format in the R programming language, so that all analyses can be carried out on them.
Step 5: Analyzing the data
With Structural Equation Modelling and Machine Learning we can interpret the results. We build one PLS-SEM (Partial Least squares Structural Equation modeling) model, to examine all hypotheses simultaneously and to take into account the interrelationships.
Step 6: Create insight into the drivers of Customer Experience
Based on the analyses, we will achieve concrete improvement points and insight in the detail level. All results and findings obtained from statistical analyses are visualised and made available in presentations, dashboards and reports. Our focus is on identifying improvements that have the most impact and add value. Like finding the main drivers and touch points for the customer experience and NPS. But we also provide insight into the impact that an increase in customer satisfaction has on the (financial) results. We offer you the possibility to create a business case in which the return on your targeted investment in specific Customer Experience touch points can be demonstrably made. Besides pointing drivers and touch points with a big impact on the results, we also focus on identifying the drivers and touch points that are less important. So that time and budget are only spent on the things that really matter.
Step 7: Improve on the basis of the findings
The findings will show which touch points (or drivers) have the most impact on the Customer Experience. The added value is that you are now back from multiple touch points to a top 3. You know where to invest and which points really have the most impact on the CX. The best approach in our experience is to concretely zoom in on a particular touch point at this step and make it negotiable in the (working) group in which way the experience can be improved. This step will have to be done in cooperation with the team, with our specialists in an advisory role, because change works best from within. Then, after working as a team on a plan of action and the necessary measures have been taken, the next measurement will show whether the score has gone up by the measures taken (and thus the CX).
Step 8: Continuous evaluation and steering
We believe in an integrated approach in which constant measurement, analysis and improvement result in better results. One-time measurement and throwing findings ‘ over the fence ‘ leads to nothing. Just tracking the Customer Experience Index and permanent evaluation of the results are important. Organizations often already have an approach to measuring CX that we like to join. By making monthly measurements it is clear at any time whether the chosen change strategy and practical adjustments have the intended effect. Monthly insight gives you the chance to assess whether the chosen route will produce the desired result and where to adjust the course is needed.